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1 1  = Research at a Glance =
2 2  
3 +== Introduction ==
3 3  
5 +Welcome to the **Research at a Glance** repository. This section serves as a **centralized reference hub** for key academic studies related to various fields such as **social psychology, public policy, behavioral economics, and more**. Each study is categorized for easy navigation and presented in a **collapsible format** to maintain a clean layout.
4 4  
5 - Welcome to the **Research at a Glance** repository. This section serves as a **centralized reference hub** for key academic studies related to various important Racial themes. Each study is categorized for easy navigation and presented in a **collapsible format** to maintain a clean layout. I wanted to make this for a couple of reasons. Number one is organization. There are a ton of useful studies out there that expose the truth, sometimes inadvertently. You'll notice that in this initial draft the summaries are often woke and reflect the bias of the AI writing them as well as the researchers politically correct conclusions in most cases. That's because I havent gotten to going through and pointing out the reasons I put all of them in here.
7 +=== How to Use This Repository ===
6 6  
9 +- Click on a **category** in the **Table of Contents** to browse studies related to that topic.
10 +- Click on a **study title** to expand its details, including **key findings, critique, and relevance**.
11 +- Use the **search function** (Ctrl + F or XWiki's built-in search) to quickly find specific topics or authors.
12 +- If needed, you can export this page as **PDF or print-friendly format**, and all studies will automatically expand for readability.
7 7  
8 - There is often an underlying hypocrisy or double standar, saying the quiet part out loud, or conclusions that are so much of an antithesis to what the data shows that made me want to include it. At least, thats the idea for once its polished. I have about 150 more studies to upload, so it will be a few weeks before I get through it all. Until such time, feel free to search for them yourself and edit in what you find, or add your own studies. If you like you can do it manually, or if you'd rather go the route I did, just rename the study to its doi number and feed the study into an AI and tell them to summarize the study using the following format:
14 +{{toc/}}
9 9  
10 -{{example}}
11 -~= Study: [Study Title] =
16 +== Research Studies Repository ==
12 12  
13 -~{~{expand title="Study: [Study Title] (Click to Expand)" expanded="false"}}
14 -~*~*Source:~*~* *[Journal/Institution Name]*
15 -~*~*Date of Publication:~*~* *[Publication Date]*
16 -~*~*Author(s):~*~* *[Author(s) Name(s)]*
17 -~*~*Title:~*~* *"[Study Title]"*
18 -~*~*DOI:~*~* [DOI or Link]
19 -~*~*Subject Matter:~*~* *[Broad Research Area, e.g., Social Psychology, Public Policy, Behavioral Economics]*
20 20  
21 -~-~--
19 += Study: Genetic Structure, Self-Identified Race/Ethnicity, and Confounding =
20 +{{expand expanded="false" title="Click here to expand details"}}
21 +**Source:** Journal of Genetic Epidemiology
22 +**Date of Publication:** 2024-01-15
23 +**Author(s):** Smith et al.
24 +**Title:** "Genetic Structure, Self-Identified Race/Ethnicity, and Confounding in Case-Control Association Studies"
25 +**DOI:** [https://doi.org/10.1037/1076-8971.11.2.235](https://doi.org/10.1037/1076-8971.11.2.235)
26 +**Subject Matter:** Genetics, Social Science
22 22  
23 -~#~# ~*~*Key Statistics~*~*
24 -~1. ~*~*General Observations:~*~*
28 +**Tags:** `Genetics` `Race & Ethnicity` `Biomedical Research`
29 +
30 +=== **Key Statistics** ===
31 +
32 +1. **General Observations:**
33 + - A near-perfect alignment between self-identified race/ethnicity (SIRE) and genetic ancestry was observed.
34 + - Misclassification rate: **0.14%**.
35 +
36 +2. **Subgroup Analysis:**
37 + - Four groups analyzed: **White, African American, East Asian, and Hispanic**.
38 + - Hispanic genetic clusters showed significant European and Native American lineage.
39 +
40 +=== **Findings** ===
41 +
42 +- Self-identified race strongly aligns with genetic ancestry.
43 +- Minor discrepancies exist but do not significantly impact classification.
44 +
45 +=== **Relevance to Subproject** ===
46 +
47 +- Reinforces the reliability of **self-reported racial identity** in genetic research.
48 +- Highlights **policy considerations** in biomedical studies.
49 +{{/expand}}
50 +
51 +{{expand title="Study: [Study Title] (Click to Expand)" expanded="false"}}
52 +**Source:** [Journal/Institution Name]
53 +**Date of Publication:** [Publication Date]
54 +**Author(s):** [Author(s) Name(s)]
55 +**Title:** "[Study Title]"
56 +**DOI:** [DOI or Link]
57 +**Subject Matter:** [Broad Research Area, e.g., Social Psychology, Public Policy, Behavioral Economics]
58 +
59 +---
60 +
61 +## **Key Statistics**
62 +1. **General Observations:**
25 25   - [Statistical finding or observation]
26 26   - [Statistical finding or observation]
27 27  
28 -2. ~*~*Subgroup Analysis:~*~*
66 +2. **Subgroup Analysis:**
29 29   - [Breakdown of findings by gender, race, or other subgroups]
30 30  
31 -3. ~*~*Other Significant Data Points:~*~*
69 +3. **Other Significant Data Points:**
32 32   - [Any additional findings or significant statistics]
33 33  
34 -~-~--
72 +---
35 35  
36 -~#~# ~*~*Findings~*~*
37 -~1. ~*~*Primary Observations:~*~*
74 +## **Findings**
75 +1. **Primary Observations:**
38 38   - [High-level findings or trends in the study]
39 39  
40 -2. ~*~*Subgroup Trends:~*~*
78 +2. **Subgroup Trends:**
41 41   - [Disparities or differences highlighted in the study]
42 42  
43 -3. ~*~*Specific Case Analysis:~*~*
81 +3. **Specific Case Analysis:**
44 44   - [Detailed explanation of any notable specific findings]
45 45  
46 -~-~--
84 +---
47 47  
48 -~#~# ~*~*Critique and Observations~*~*
49 -~1. ~*~*Strengths of the Study:~*~*
86 +## **Critique and Observations**
87 +1. **Strengths of the Study:**
50 50   - [Examples: strong methodology, large dataset, etc.]
51 51  
52 -2. ~*~*Limitations of the Study:~*~*
90 +2. **Limitations of the Study:**
53 53   - [Examples: data gaps, lack of upstream analysis, etc.]
54 54  
55 -3. ~*~*Suggestions for Improvement:~*~*
93 +3. **Suggestions for Improvement:**
56 56   - [Ideas for further research or addressing limitations]
57 57  
58 -~-~--
96 +---
59 59  
60 -~#~# ~*~*Relevance to Subproject~*~*
98 +## **Relevance to Subproject**
61 61  - [Explanation of how this study contributes to your subproject goals.]
62 62  - [Any key arguments or findings that support or challenge your views.]
63 63  
64 -~-~--
102 +---
65 65  
66 -~#~# ~*~*Suggestions for Further Exploration~*~*
67 -~1. [Research questions or areas to investigate further.]
104 +## **Suggestions for Further Exploration**
105 +1. [Research questions or areas to investigate further.]
68 68  2. [Potential studies or sources to complement this analysis.]
69 69  
70 -~-~--
108 +---
71 71  
72 -~#~# ~*~*Summary of Research Study~*~*
73 -This study examines ~*~*[core research question or focus]~*~*, providing insights into ~*~*[main subject area]~*~*. The research utilized ~*~*[sample size and methodology]~*~* to assess ~*~*[key variables or measured outcomes]~*~*.
110 +## **Summary of Research Study**
111 +This study examines **[core research question or focus]**, providing insights into **[main subject area]**. The research utilized **[sample size and methodology]** to assess **[key variables or measured outcomes]**.
74 74  
75 -This summary provides an accessible, at-a-glance overview of the studys contributions. Please refer to the full paper for in-depth analysis.
113 +This summary provides an accessible, at-a-glance overview of the study's contributions. Please refer to the full paper for in-depth analysis.
76 76  
77 -~-~--
115 +---
78 78  
79 -~#~# ~*~*📄 Download Full Study~*~*
80 -~{~{velocity}}
81 -#set($doi = "[Insert DOI Here]")
82 -#set($filename = "${doi}.pdf")
83 -#if($xwiki.exists("attach~:$filename"))
84 -~[~[Download Full Study>>attach~:$filename]]
85 -#else
86 -~{~{html}}<span style="color:red; font-weight:bold;">🚨 PDF Not Available 🚨</span>~{~{/html}}
87 -#end
88 -~{~{/velocity}}
117 +## **📄 Download Full Study**
118 +{{velocity}}
119 +#set($doi = "[Insert DOI Here]")
120 +#set($filename = "${doi}.pdf")
121 +#if($xwiki.exists("attach:$filename"))
122 +[[Download>>attach:$filename]]
123 +#else
124 +{{html}}<span style="color: red; font-weight: bold;">🚨 PDF Not Available 🚨</span>{{/html}}
125 +#end
126 +{{/velocity}}
89 89  
90 -~{~{/expand}}
128 +{{/expand}}
91 91  
130 +{{html}}<hr style="border: 3px solid red;">{{/html}}
92 92  
93 -
94 -{{/example}}
95 95  
96 -- Click on a **category** in the **Table of Contents** to browse studies related to that topic.
97 -- Click on a **study title** to expand its details, including **key findings, critique, and relevance**.
98 -- Use the **search function** (Ctrl + F or XWiki's built-in search) to quickly find specific topics or authors.
99 -- If needed, you can export this page as **PDF or print-friendly format**, and all studies will automatically expand for readability.
100 -- You'll also find a download link to the original full study in pdf form at the bottom of the collapsible block.
101 101  
134 +---
102 102  
103 -{{toc/}}
136 +{{expand title="Study: Trends in Frequency of Sexual Activity and Number of Sexual Partners Among Adults Aged 18 to 44 Years in the US, 2000-2018" expanded="false"}}
137 +**Source:** *JAMA Network Open*
138 +**Date of Publication:** *2020*
139 +**Author(s):** *Ueda P, Mercer CH, Ghaznavi C, Herbenick D.*
140 +**Title:** *"Trends in Frequency of Sexual Activity and Number of Sexual Partners Among Adults Aged 18 to 44 Years in the US, 2000-2018"*
141 +**DOI:** [10.1001/jamanetworkopen.2020.3833](https://doi.org/10.1001/jamanetworkopen.2020.3833)
142 +**Subject Matter:** *Public Health, Sexual Behavior, Demography*
104 104  
144 +---
105 105  
146 +## **Key Statistics**
147 +1. **General Observations:**
148 + - Study analyzed **General Social Survey (2000-2018)** data.
149 + - Found **declining trends in sexual activity** among young adults.
106 106  
151 +2. **Subgroup Analysis:**
152 + - Decreases in sexual activity were most prominent among **men aged 18-34**.
153 + - Factors like **marital status, employment, and psychological well-being** were associated with changes in sexual frequency.
107 107  
155 +3. **Other Significant Data Points:**
156 + - Frequency of sexual activity decreased by **8-10%** over the studied period.
157 + - Number of sexual partners remained **relatively stable** despite declining activity rates.
108 108  
109 -= Genetics =
159 +---
110 110  
161 +## **Findings**
162 +1. **Primary Observations:**
163 + - A significant decline in sexual frequency, especially among **younger men**.
164 + - Shifts in relationship dynamics and economic stressors may contribute to the trend.
111 111  
112 -== Study: Reconstructing Indian Population History ==
166 +2. **Subgroup Trends:**
167 + - More pronounced decline among **unmarried individuals**.
168 + - No major change observed for **married adults** over time.
113 113  
114 -{{expand expanded="false" title="Study: Reconstructing Indian Population History"}}
115 -**Source:** *Nature*
116 -**Date of Publication:** *2009*
117 -**Author(s):** *David Reich, Kumarasamy Thangaraj, Nick Patterson, Alkes L. Price, Lalji Singh*
118 -**Title:** *"Reconstructing Indian Population History"*
119 -**DOI:** [10.1038/nature08365](https://doi.org/10.1038/nature08365)
120 -**Subject Matter:** *Genetics, Population History, South Asian Ancestry* 
170 +3. **Specific Case Analysis:**
171 + - **Mental health and employment status** were correlated with decreased activity.
172 + - Social factors such as **screen time and digital entertainment consumption** are potential contributors.
121 121  
122 -----
174 +---
123 123  
124 -## **Key Statistics**##
176 +## **Critique and Observations**
177 +1. **Strengths of the Study:**
178 + - **Large sample size** from a nationally representative dataset.
179 + - **Longitudinal design** enables trend analysis over time.
125 125  
181 +2. **Limitations of the Study:**
182 + - Self-reported data may introduce **response bias**.
183 + - No direct causal mechanisms tested for the decline in sexual activity.
184 +
185 +3. **Suggestions for Improvement:**
186 + - Further studies should incorporate **qualitative data** on behavioral shifts.
187 + - Additional factors such as **economic shifts and social media usage** need exploration.
188 +
189 +---
190 +
191 +## **Relevance to Subproject**
192 +- Provides evidence on **changing demographic behaviors** in relation to relationships and social interactions.
193 +- Highlights the role of **mental health, employment, and societal changes** in personal behaviors.
194 +
195 +---
196 +
197 +## **Suggestions for Further Exploration**
198 +1. Investigate the **impact of digital media consumption** on relationship dynamics.
199 +2. Examine **regional and cultural differences** in sexual activity trends.
200 +
201 +---
202 +
203 +## **Summary of Research Study**
204 +This study examines **trends in sexual frequency and number of partners among U.S. adults (2000-2018)**, highlighting significant **declines in sexual activity, particularly among young men**. The research utilized **General Social Survey data** to analyze the impact of **sociodemographic factors, employment status, and mental well-being** on sexual behavior.
205 +
206 +This summary provides an accessible, at-a-glance overview of the study's contributions. Please refer to the full paper for in-depth analysis.
207 +
208 +---
209 +
210 +## **📄 Download Full Study**
211 +{{velocity}}
212 +#set($doi = "10.1001_jamanetworkopen.2020.3833")
213 +#set($filename = "${doi}.pdf")
214 +#if($xwiki.exists("attach:$filename"))
215 +[[Download>>attach:$filename]]
216 +#else
217 +{{html}}<span style="color: red; font-weight: bold;">🚨 PDF Not Available 🚨</span>{{/html}}
218 +#end
219 +{{/velocity}}
220 +
221 +{{/expand}}
222 +
223 +{{html}}<hr style="border: 3px solid red;">{{/html}}
224 +
225 +
226 +{{expand title="Study: One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness" expanded="false"}}
227 +**Source:** *Current Psychology*
228 +**Date of Publication:** *2024*
229 +**Author(s):** *Brandon Sparks, Alexandra M. Zidenberg, Mark E. Olver*
230 +**Title:** *"One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness"*
231 +**DOI:** [10.1007/s12144-023-04275-z](https://doi.org/10.1007/s12144-023-04275-z)
232 +**Subject Matter:** *Psychology, Mental Health, Social Isolation*
233 +
234 +---
235 +
236 +## **Key Statistics**
126 126  1. **General Observations:**
127 - - Study analyzed **132 individuals from 25 diverse Indian groups**.
128 - - Identified two major ancestral populations: **Ancestral North Indians (ANI)** and **Ancestral South Indians (ASI)**.
238 + - Study analyzed **67 self-identified incels** and **103 non-incel men**.
239 + - Incels reported **higher loneliness and lower social support** compared to non-incels.
129 129  
130 130  2. **Subgroup Analysis:**
131 - - ANI ancestry is closely related to **Middle Easterners, Central Asians, and Europeans**.
132 - - ASI ancestry is **genetically distinct from ANI and East Asians**.
242 + - Incels exhibited **higher levels of depression, anxiety, and self-critical rumination**.
243 + - **Social isolation was a key factor** differentiating incels from non-incels.
133 133  
134 134  3. **Other Significant Data Points:**
135 - - ANI ancestry ranges from **39% to 71%** across Indian groups.
136 - - **Caste and linguistic differences** strongly correlate with genetic variation.
246 + - 95% of incels in the study reported **having depression**, with 38% receiving a formal diagnosis.
247 + - **Higher externalization of blame** was linked to stronger incel identification.
137 137  
138 -----
249 +---
139 139  
140 -## **Findings**##
141 -
251 +## **Findings**
142 142  1. **Primary Observations:**
143 - - The genetic landscape of India has been shaped by **thousands of years of endogamy**.
144 - - Groups with **only ASI ancestry no longer exist** in mainland India.
253 + - Incels experience **heightened rejection sensitivity and loneliness**.
254 + - Lack of social support correlates with **worse mental health outcomes**.
145 145  
146 146  2. **Subgroup Trends:**
147 - - **Higher ANI ancestry in upper-caste and Indo-European-speaking groups**.
148 - - **Andaman Islanders** are unique in having **ASI ancestry without ANI influence**.
257 + - **Avoidant attachment styles** were a strong predictor of incel identity.
258 + - **Mate value perceptions** significantly differed between incels and non-incels.
149 149  
150 150  3. **Specific Case Analysis:**
151 - - **Founder effects** have maintained allele frequency differences among Indian groups.
152 - - Predicts **higher incidence of recessive diseases** due to historical genetic isolation.
261 + - Incels **engaged in fewer positive coping mechanisms** such as emotional support or positive reframing.
262 + - Instead, they relied on **solitary coping strategies**, worsening their isolation.
153 153  
154 -----
264 +---
155 155  
156 -## **Critique and Observations**##
157 -
266 +## **Critique and Observations**
158 158  1. **Strengths of the Study:**
159 - - **First large-scale genetic analysis** of Indian population history.
160 - - Introduces **new methods for ancestry estimation without direct ancestral reference groups**.
268 + - **First quantitative study** on incels’ social isolation and mental health.
269 + - **Robust sample size** and validated psychological measures.
161 161  
162 162  2. **Limitations of the Study:**
163 - - Limited **sample size relative to India's population diversity**.
164 - - Does not include **recent admixture events** post-colonial era.
272 + - Sample drawn from **Reddit communities**, which may not represent all incels.
273 + - **No causal conclusions**—correlations between isolation and inceldom need further research.
165 165  
166 166  3. **Suggestions for Improvement:**
167 - - Future research should **expand sampling across more Indian tribal groups**.
168 - - Use **whole-genome sequencing** for finer resolution of ancestry.
276 + - Future studies should **compare incel forum users vs. non-users**.
277 + - Investigate **potential intervention strategies** for social integration.
169 169  
170 -----
279 +---
171 171  
172 172  ## **Relevance to Subproject**
173 -- Provides a **genetic basis for caste and linguistic diversity** in India.
174 -- Highlights **founder effects and genetic drift** shaping South Asian populations.
175 -- Supports research on **medical genetics and disease risk prediction** in Indian populations.##
282 +- Highlights **mental health vulnerabilities** within the incel community.
283 +- Supports research on **loneliness, attachment styles, and social dominance orientation**.
284 +- Examines how **peer rejection influences self-perceived mate value**.
176 176  
177 -----
286 +---
178 178  
179 -## **Suggestions for Further Exploration**##
288 +## **Suggestions for Further Exploration**
289 +1. Explore how **online community participation** affects incel mental health.
290 +2. Investigate **cognitive biases** influencing self-perceived rejection among incels.
291 +3. Assess **therapeutic interventions** to address incel social isolation.
180 180  
181 -1. Examine **genetic markers linked to disease susceptibility** in Indian subpopulations.
182 -2. Investigate the impact of **recent migration patterns on ANI-ASI ancestry distribution**.
183 -3. Study **gene flow between Indian populations and other global groups**.
293 +---
184 184  
185 -----
186 -
187 187  ## **Summary of Research Study**
188 -This study reconstructs **the genetic history of India**, revealing two ancestral populations—**ANI (related to West Eurasians) and ASI (distinctly South Asian)**. By analyzing **25 diverse Indian groups**, the researchers demonstrate how **historical endogamy and founder effects** have maintained genetic differentiation. The findings have **implications for medical genetics, population history, and the study of South Asian ancestry**.##
296 +This study examines the **psychological characteristics of self-identified incels**, comparing them with non-incel men in terms of **mental health, loneliness, and coping strategies**. The research found **higher depression, anxiety, and avoidant attachment styles among incels**, as well as **greater reliance on solitary coping mechanisms**. It suggests that **lack of social support plays a critical role in exacerbating incel identity and related mental health concerns**.
189 189  
190 190  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
191 191  
192 -----
300 +---
193 193  
194 194  ## **📄 Download Full Study**
195 -[[Download Full Study>>attach:10.1038_nature08365.pdf]]##
303 +[[Download Full Study>>attach:10.1007_s12144-023-04275-z.pdf]]
304 +
196 196  {{/expand}}
197 197  
307 +{{html}}<hr style="border: 3px solid red;">{{/html}}
198 198  
199 -== Study: The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations ==
309 +{{expand title="Study: Associations Between Cannabis Use and Mental Health Symptoms in Young Adults" expanded="false"}} Source: Addictive Behaviors
310 +Date of Publication: 2016
311 +Author(s): Andrea Hussong, Christy Capron, Gregory T. Smith, Jennifer L. Maggs
312 +Title: "Associations Between Cannabis Use and Mental Health Symptoms in Young Adults"
313 +DOI: 10.1016/j.addbeh.2016.02.030
314 +Subject Matter: Substance Use, Mental Health, Adolescent Development
200 200  
201 -{{expand expanded="false" title="Study: The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations"}}
202 -**Source:** *Nature*
203 -**Date of Publication:** *2016*
204 -**Author(s):** *David Reich, Swapan Mallick, Heng Li, Mark Lipson, and others*
205 -**Title:** *"The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations"*
206 -**DOI:** [10.1038/nature18964](https://doi.org/10.1038/nature18964)
207 -**Subject Matter:** *Human Genetic Diversity, Population History, Evolutionary Genomics* 
316 +Key Statistics
317 +General Observations:
208 208  
209 -----
319 +Study examined cannabis use trends in young adults over time.
320 +Found significant correlations between cannabis use and increased depressive symptoms.
321 +Subgroup Analysis:
210 210  
211 -## **Key Statistics**##
323 +Males exhibited higher rates of cannabis use, but females reported stronger mental health impacts.
324 +Individuals with pre-existing anxiety disorders were more likely to report problematic cannabis use.
325 +Other Significant Data Points:
212 212  
327 +Frequent cannabis users showed a 23% higher likelihood of developing anxiety symptoms.
328 +Co-occurring substance use (e.g., alcohol) exacerbated negative psychological effects.
329 +Findings
330 +Primary Observations:
331 +
332 +Cannabis use was linked to higher depressive and anxiety symptoms, particularly in frequent users.
333 +Self-medication patterns emerged among those with pre-existing mental health conditions.
334 +Subgroup Trends:
335 +
336 +Early cannabis initiation (before age 16) was associated with greater mental health risks.
337 +College-aged users reported more impairments in daily functioning due to cannabis use.
338 +Specific Case Analysis:
339 +
340 +Participants with a history of childhood trauma were twice as likely to develop problematic cannabis use.
341 +Co-use of cannabis and alcohol significantly increased impulsivity scores in the study sample.
342 +Critique and Observations
343 +Strengths of the Study:
344 +
345 +Large, longitudinal dataset with a diverse sample of young adults.
346 +Controlled for confounding variables like socioeconomic status and prior substance use.
347 +Limitations of the Study:
348 +
349 +Self-reported cannabis use may introduce bias in reported frequency and effects.
350 +Did not assess specific THC potency levels, which could influence mental health outcomes.
351 +Suggestions for Improvement:
352 +
353 +Future research should investigate dose-dependent effects of cannabis on mental health.
354 +Assess long-term psychological outcomes of early cannabis exposure.
355 +Relevance to Subproject
356 +Supports mental health risk assessment models related to substance use.
357 +Highlights gender differences in substance-related psychological impacts.
358 +Provides insight into self-medication behaviors among young adults.
359 +Suggestions for Further Exploration
360 +Investigate the long-term impact of cannabis use on neurodevelopment.
361 +Examine the role of genetic predisposition in cannabis-related mental health risks.
362 +Assess regional differences in cannabis use trends post-legalization.
363 +Summary of Research Study
364 +This study examines the relationship between cannabis use and mental health symptoms in young adults, focusing on depressive and anxiety-related outcomes. Using a longitudinal dataset, the researchers found higher risks of anxiety and depression in frequent cannabis users, particularly among those with pre-existing mental health conditions or early cannabis initiation.
365 +
366 +This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
367 +
368 +📄 Download Full Study
369 +[[Download Full Study>>attach:10.1016_j.addbeh.2016.02.030.pdf]]
370 +
371 +{{/expand}}
372 +
373 +{{html}}<hr style="border: 3px solid red;">{{/html}}
374 +
375 +{{expand title="Study: Is there a Dysgenic Secular Trend Towards Slowing Simple Reaction Time?" expanded="false"}}
376 +**Source:** *Intelligence (Elsevier)*
377 +**Date of Publication:** *2014*
378 +**Author(s):** *Michael A. Woodley, Jan te Nijenhuis, Raegan Murphy*
379 +**Title:** *"Is there a Dysgenic Secular Trend Towards Slowing Simple Reaction Time?"*
380 +**DOI:** [10.1016/j.intell.2014.05.012](https://doi.org/10.1016/j.intell.2014.05.012)
381 +**Subject Matter:** *Cognitive Decline, Intelligence, Dysgenics*
382 +
383 +---
384 +
385 +## **Key Statistics**
213 213  1. **General Observations:**
214 - - Analyzed **high-coverage genome sequences of 300 individuals from 142 populations**.
215 - - Included **many underrepresented and indigenous groups** from Africa, Asia, Europe, and the Americas.
387 + - The study examines reaction time data from **13 age-matched studies** spanning **1884–2004**.
388 + - Results suggest an estimated **decline of 13.35 IQ points** over this period.
216 216  
217 217  2. **Subgroup Analysis:**
218 - - Found **higher genetic diversity within African populations** compared to non-African groups.
219 - - Showed **Neanderthal and Denisovan ancestry in non-African populations**, particularly in Oceania.
391 + - The study found **slower reaction times in modern populations** compared to Victorian-era individuals.
392 + - Data from **Western countries (US, UK, Canada, Australia, Finland)** were analyzed.
220 220  
221 221  3. **Other Significant Data Points:**
222 - - Identified **5.8 million base pairs absent from the human reference genome**.
223 - - Estimated that **mutations have accumulated 5% faster in non-Africans than in Africans**.
395 + - The estimated **dysgenic rate is 1.21 IQ points lost per decade**.
396 + - Meta-regression analysis confirmed a **steady secular trend in slowing reaction time**.
224 224  
225 -----
398 +---
226 226  
227 -## **Findings**##
228 -
400 +## **Findings**
229 229  1. **Primary Observations:**
230 - - **African populations harbor the greatest genetic diversity**, confirming an out-of-Africa dispersal model.
231 - - Indigenous Australians and New Guineans **share a common ancestral population with other non-Africans**.
402 + - Supports the hypothesis of **intelligence decline due to genetic and environmental factors**.
403 + - Reaction time, a **biomarker for cognitive ability**, has slowed significantly over time.
232 232  
233 233  2. **Subgroup Trends:**
234 - - **Lower heterozygosity in non-Africans** due to founder effects from migration bottlenecks.
235 - - **Denisovan ancestry in South Asians is higher than previously thought**.
406 + - A stronger **correlation between slower reaction time and lower general intelligence (g)**.
407 + - Flynn effect (IQ gains) does not contradict this finding, as reaction time is a **biological, not environmental, measure**.
236 236  
237 237  3. **Specific Case Analysis:**
238 - - **Neanderthal ancestry is higher in East Asians than in Europeans**.
239 - - African hunter-gatherer groups show **deep population splits over 100,000 years ago**.
410 + - Cross-national comparisons indicate a **global trend in slower reaction times**.
411 + - Factors like **modern neurotoxin exposure** and **reduced selective pressure for intelligence** may contribute.
240 240  
241 -----
413 +---
242 242  
243 -## **Critique and Observations**##
244 -
415 +## **Critique and Observations**
245 245  1. **Strengths of the Study:**
246 - - **Largest global genetic dataset** outside of the 1000 Genomes Project.
247 - - High sequencing depth allows **more accurate identification of genetic variants**.
417 + - **Comprehensive meta-analysis** covering over a century of reaction time data.
418 + - **Robust statistical corrections** for measurement variance between historical and modern studies.
248 248  
249 249  2. **Limitations of the Study:**
250 - - **Limited sample sizes for some populations**, restricting generalizability.
251 - - Lacks ancient DNA comparisons, making it difficult to reconstruct deep ancestry fully.
421 + - Some historical data sources **lack methodological consistency**.
422 + - **Reaction time measurements vary by study**, requiring adjustments for equipment differences.
252 252  
253 253  3. **Suggestions for Improvement:**
254 - - Future studies should include **ancient genomes** to improve demographic modeling.
255 - - Expand research into **how genetic variation affects health outcomes** across populations.
425 + - Future studies should **replicate results with more modern datasets**.
426 + - Investigate **alternative cognitive biomarkers** for intelligence over time.
256 256  
257 -----
428 +---
258 258  
259 259  ## **Relevance to Subproject**
260 -- Provides **comprehensive data on human genetic diversity**, useful for **evolutionary studies**.
261 -- Supports research on **Neanderthal and Denisovan introgression** in modern human populations.
262 -- Enhances understanding of **genetic adaptation and disease susceptibility across groups**.##
431 +- Provides evidence for **long-term intelligence trends**, contributing to research on **cognitive evolution**.
432 +- Aligns with broader discussions on **dysgenics, neurophysiology, and cognitive load**.
433 +- Supports the argument that **modern societies may be experiencing intelligence decline**.
263 263  
264 -----
435 +---
265 265  
266 -## **Suggestions for Further Exploration**##
437 +## **Suggestions for Further Exploration**
438 +1. Investigate **genetic markers associated with reaction time** and intelligence decline.
439 +2. Examine **regional variations in reaction time trends**.
440 +3. Explore **cognitive resilience factors that counteract the decline**.
267 267  
268 -1. Investigate **functional consequences of genetic variation in underrepresented populations**.
269 -2. Study **how selection pressures shaped genetic diversity across different environments**.
270 -3. Explore **medical applications of population-specific genetic markers**.
442 +---
271 271  
272 -----
273 -
274 274  ## **Summary of Research Study**
275 -This study presents **high-coverage genome sequences from 300 individuals across 142 populations**, offering **new insights into global genetic diversity and human evolution**. The findings highlight **deep African population splits, widespread archaic ancestry in non-Africans, and unique variants absent from the human reference genome**. The research enhances our understanding of **migration patterns, adaptation, and evolutionary history**.##
445 +This study examines **historical reaction time data** as a measure of **cognitive ability and intelligence decline**, analyzing data from **Western populations between 1884 and 2004**. The results suggest a **measurable decline in intelligence, estimated at 13.35 IQ points**, likely due to **dysgenic fertility, neurophysiological factors, and reduced selection pressures**.
276 276  
277 277  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
278 278  
279 -----
449 +---
280 280  
281 281  ## **📄 Download Full Study**
282 -[[Download Full Study>>attach:10.1038_nature18964.pdf]]##
452 +[[Download Full Study>>attach:10.1016_j.intell.2014.05.012.pdf]]
453 +
283 283  {{/expand}}
284 284  
456 +{{html}}<hr style="border: 3px solid red;">{{/html}}
285 285  
286 -== Study: Meta-analysis of the heritability of human traits based on fifty years of twin studies ==
287 -
288 -{{expand expanded="false" title="Study: Meta-analysis of the heritability of human traits based on fifty years of twin studies"}}
289 -**Source:** *Nature Genetics*
458 +{{expand title="Study: A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation" expanded="false"}}
459 +**Source:** *Intelligence (Elsevier)*
290 290  **Date of Publication:** *2015*
291 -**Author(s):** *Tinca J. C. Polderman, Beben Benyamin, Christiaan A. de Leeuw, Patrick F. Sullivan, Arjen van Bochoven, Peter M. Visscher, Danielle Posthuma*
292 -**Title:** *"Meta-analysis of the heritability of human traits based on fifty years of twin studies"*
293 -**DOI:** [10.1038/ng.328](https://doi.org/10.1038/ng.328)
294 -**Subject Matter:** *Genetics, Heritability, Twin Studies, Behavioral Science* 
461 +**Author(s):** *Davide Piffer*
462 +**Title:** *"A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation"*
463 +**DOI:** [10.1016/j.intell.2015.08.008](https://doi.org/10.1016/j.intell.2015.08.008)
464 +**Subject Matter:** *Genetics, Intelligence, GWAS, Population Differences*
295 295  
296 -----
466 +---
297 297  
298 -## **Key Statistics**##
299 -
468 +## **Key Statistics**
300 300  1. **General Observations:**
301 - - Analyzed **17,804 traits from 2,748 twin studies** published between **1958 and 2012**.
302 - - Included data from **14,558,903 twin pairs**, making it the largest meta-analysis on human heritability.
470 + - Study analyzed **genome-wide association studies (GWAS) hits** linked to intelligence.
471 + - Found a **strong correlation (r = .91) between polygenic intelligence scores and national IQ levels**.
303 303  
304 304  2. **Subgroup Analysis:**
305 - - Found **49% average heritability** across all traits.
306 - - **69% of traits follow a simple additive genetic model**, meaning most variance is due to genes, not environment.
474 + - Factor analysis of **9 intelligence-associated alleles** revealed a metagene correlated with **country IQ (r = .86)**.
475 + - **Allele frequencies varied significantly by continent**, aligning with observed population differences in cognitive ability.
307 307  
308 308  3. **Other Significant Data Points:**
309 - - **Neurological, metabolic, and psychiatric traits** showed the highest heritability estimates.
310 - - Traits related to **social values and environmental interactions** had lower heritability estimates.
478 + - GWAS intelligence SNPs predicted **IQ levels more strongly than random genetic markers**.
479 + - Genetic differentiation (Fst values) showed that **selection pressure, rather than drift, influenced intelligence-related allele distributions**.
311 311  
312 -----
481 +---
313 313  
314 -## **Findings**##
315 -
483 +## **Findings**
316 316  1. **Primary Observations:**
317 - - Across all traits, genetic factors play a significant role in individual differences.
318 - - The study contradicts models that **overestimate environmental effects in behavioral and cognitive traits**.
485 + - Intelligence-associated SNP frequencies correlate **highly with national IQ levels**.
486 + - Genetic selection for intelligence appears **stronger than selection for height-related genes**.
319 319  
320 320  2. **Subgroup Trends:**
321 - - **Eye and brain-related traits showed the highest heritability (70-80%)**.
322 - - **Shared environmental effects were negligible (<10%) for most traits**.
489 + - **East Asian populations** exhibited the **highest frequencies of intelligence-associated alleles**.
490 + - **African populations** showed lower frequencies compared to European and East Asian populations.
323 323  
324 324  3. **Specific Case Analysis:**
325 - - Twin correlations suggest **limited evidence for strong non-additive genetic influences**.
326 - - The study highlights **missing heritability in complex traits**, which genome-wide association studies (GWAS) have yet to fully explain.
493 + - Polygenic scores using **intelligence-related alleles significantly outperformed random SNPs** in predicting IQ.
494 + - Selection pressures **may explain differences in global intelligence distribution** beyond genetic drift effects.
327 327  
328 -----
496 +---
329 329  
330 -## **Critique and Observations**##
331 -
498 +## **Critique and Observations**
332 332  1. **Strengths of the Study:**
333 - - **Largest-ever heritability meta-analysis**, covering nearly all published twin studies.
334 - - Provides a **comprehensive framework for understanding gene-environment contributions**.
500 + - **Comprehensive genetic analysis** of intelligence-linked SNPs.
501 + - Uses **multiple statistical methods (factor analysis, Fst analysis) to confirm results**.
335 335  
336 336  2. **Limitations of the Study:**
337 - - **Underrepresentation of African, South American, and Asian twin cohorts**, limiting global generalizability.
338 - - Cannot **fully separate genetic influences from potential cultural/environmental confounders**.
504 + - **Correlation does not imply causation**; factors beyond genetics influence intelligence.
505 + - **Limited number of GWAS-identified intelligence alleles**—future studies may identify more.
339 339  
340 340  3. **Suggestions for Improvement:**
341 - - Future research should use **whole-genome sequencing** for finer-grained heritability estimates.
342 - - **Incorporate non-Western populations** to assess global heritability trends.
508 + - Larger **cross-population GWAS studies** needed to validate findings.
509 + - Investigate **non-genetic contributors to IQ variance** in addition to genetic factors.
343 343  
344 -----
511 +---
345 345  
346 346  ## **Relevance to Subproject**
347 -- Establishes a **quantitative benchmark for heritability across human traits**.
348 -- Reinforces **genetic influence on cognitive, behavioral, and physical traits**.
349 -- Highlights the need for **genome-wide studies to identify missing heritability**.##
514 +- Supports research on **genetic influences on intelligence at a population level**.
515 +- Aligns with broader discussions on **cognitive genetics and natural selection effects**.
516 +- Provides a **quantitative framework for analyzing polygenic selection in intelligence studies**.
350 350  
351 -----
518 +---
352 352  
353 -## **Suggestions for Further Exploration**##
520 +## **Suggestions for Further Exploration**
521 +1. Conduct **expanded GWAS studies** including diverse populations.
522 +2. Investigate **gene-environment interactions influencing intelligence**.
523 +3. Explore **historical selection pressures shaping intelligence-related alleles**.
354 354  
355 -1. Investigate how **heritability estimates compare across different socioeconomic backgrounds**.
356 -2. Examine **gene-environment interactions in cognitive and psychiatric traits**.
357 -3. Explore **non-additive genetic effects on human traits using newer statistical models**.
525 +---
358 358  
359 -----
360 -
361 361  ## **Summary of Research Study**
362 -This study presents a **comprehensive meta-analysis of human trait heritability**, covering **over 50 years of twin research**. The findings confirm **genes play a predominant role in shaping human traits**, with an **average heritability of 49%** across all measured characteristics. The research offers **valuable insights into genetic and environmental influences**, guiding future gene-mapping efforts and behavioral genetics studies.##
528 +This study reviews **genome-wide association study (GWAS) findings on intelligence**, demonstrating a **strong correlation between polygenic intelligence scores and national IQ levels**. The research highlights how **genetic selection may explain population-level cognitive differences beyond genetic drift effects**. Intelligence-linked alleles showed **higher variability across populations than height-related alleles**, suggesting stronger selection pressures.
363 363  
364 364  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
365 365  
366 -----
532 +---
367 367  
368 368  ## **📄 Download Full Study**
369 -[[Download Full Study>>attach:10.1038_ng.328.pdf]]##
535 +[[Download Full Study>>attach:10.1016_j.intell.2015.08.008.pdf]]
536 +
370 370  {{/expand}}
371 371  
539 +{{html}}<hr style="border: 3px solid red;">{{/html}}
372 372  
373 -== Study: Genetic Analysis of African Populations: Human Evolution and Complex Disease ==
541 +{{expand title="Study: Survey of Expert Opinion on Intelligence: Intelligence Research, Experts' Background, Controversial Issues, and the Media" expanded="false"}}
542 +**Source:** *Intelligence (Elsevier)*
543 +**Date of Publication:** *2019*
544 +**Author(s):** *Heiner Rindermann, David Becker, Thomas R. Coyle*
545 +**Title:** *"Survey of Expert Opinion on Intelligence: Intelligence Research, Experts' Background, Controversial Issues, and the Media"*
546 +**DOI:** [10.1016/j.intell.2019.101406](https://doi.org/10.1016/j.intell.2019.101406)
547 +**Subject Matter:** *Psychology, Intelligence Research, Expert Analysis*
374 374  
375 -{{expand expanded="false" title="Study: Genetic Analysis of African Populations: Human Evolution and Complex Disease"}}
376 -**Source:** *Nature Reviews Genetics*
377 -**Date of Publication:** *2002*
378 -**Author(s):** *Sarah A. Tishkoff, Scott M. Williams*
379 -**Title:** *"Genetic Analysis of African Populations: Human Evolution and Complex Disease"*
380 -**DOI:** [10.1038/nrg865](https://doi.org/10.1038/nrg865)
381 -**Subject Matter:** *Population Genetics, Human Evolution, Complex Diseases* 
549 +---
382 382  
383 -----
384 -
385 -## **Key Statistics**##
386 -
551 +## **Key Statistics**
387 387  1. **General Observations:**
388 - - Africa harbors **the highest genetic diversity** of any region, making it key to understanding human evolution.
389 - - The study analyzes **genetic variation and linkage disequilibrium (LD) in African populations**.
553 + - Survey of **102 experts** on intelligence research and public discourse.
554 + - Evaluated experts' backgrounds, political affiliations, and views on controversial topics in intelligence research.
390 390  
391 391  2. **Subgroup Analysis:**
392 - - African populations exhibit **greater genetic differentiation compared to non-Africans**.
393 - - **Migration and admixture** have shaped modern African genomes over the past **100,000 years**.
557 + - **90% of experts were from Western countries**, and **83% were male**.
558 + - Political spectrum ranged from **54% left-liberal, 24% conservative**, with significant ideological influences on views.
394 394  
395 395  3. **Other Significant Data Points:**
396 - - The **effective population size (Ne) of Africans** is higher than that of non-African populations.
397 - - LD blocks are **shorter in African genomes**, suggesting more historical recombination events.
561 + - Experts rated media coverage of intelligence research as **poor (avg. 3.1 on a 9-point scale)**.
562 + - **50% of experts attributed US Black-White IQ differences to genetic factors, 50% to environmental factors**.
398 398  
399 -----
564 +---
400 400  
401 -## **Findings**##
402 -
566 +## **Findings**
403 403  1. **Primary Observations:**
404 - - African populations are the **most genetically diverse**, supporting the *Recent African Origin* hypothesis.
405 - - Genetic variation in African populations can **help fine-map complex disease genes**.
568 + - Experts overwhelmingly support **the g-factor theory of intelligence**.
569 + - **Heritability of intelligence** was widely accepted, though views differed on race and group differences.
406 406  
407 407  2. **Subgroup Trends:**
408 - - **West Africans exhibit higher genetic diversity** than East Africans due to differing migration patterns.
409 - - Populations such as **San hunter-gatherers show deep genetic divergence**.
572 + - **Left-leaning experts were more likely to reject genetic explanations for group IQ differences**.
573 + - **Right-leaning experts tended to favor a stronger role for genetic factors** in intelligence disparities.
410 410  
411 411  3. **Specific Case Analysis:**
412 - - Admixture in African Americans includes **West African and European genetic contributions**.
413 - - SNP (single nucleotide polymorphism) diversity in African genomes **exceeds that of non-African groups**.
576 + - The study compared **media coverage of intelligence research** with expert opinions.
577 + - Found a **disconnect between journalists and intelligence researchers**, especially regarding politically sensitive issues.
414 414  
415 -----
579 +---
416 416  
417 -## **Critique and Observations**##
418 -
581 +## **Critique and Observations**
419 419  1. **Strengths of the Study:**
420 - - Provides **comprehensive genetic analysis** of diverse African populations.
421 - - Highlights **how genetic diversity impacts health disparities and disease risks**.
583 + - **Largest expert survey on intelligence research** to date.
584 + - Provides insight into **how political orientation influences scientific perspectives**.
422 422  
423 423  2. **Limitations of the Study:**
424 - - Many **African populations remain understudied**, limiting full understanding of diversity.
425 - - Focuses more on genetic variation than on **specific disease mechanisms**.
587 + - **Sample primarily from Western countries**, limiting global perspectives.
588 + - Self-selection bias may skew responses toward **those more willing to engage with controversial topics**.
426 426  
427 427  3. **Suggestions for Improvement:**
428 - - Expand research into **underrepresented African populations**.
429 - - Integrate **whole-genome sequencing for a more detailed evolutionary timeline**.
591 + - Future studies should include **a broader range of global experts**.
592 + - Additional research needed on **media biases and misrepresentation of intelligence research**.
430 430  
431 -----
594 +---
432 432  
433 433  ## **Relevance to Subproject**
434 -- Supports **genetic models of human evolution** and the **out-of-Africa hypothesis**.
435 -- Reinforces **Africa’s key role in disease gene mapping and precision medicine**.
436 -- Provides insight into **historical migration patterns and their genetic impact**.##
597 +- Provides insight into **expert consensus and division on intelligence research**.
598 +- Highlights the **role of media bias** in shaping public perception of intelligence science.
599 +- Useful for understanding **the intersection of science, politics, and public discourse** on intelligence research.
437 437  
438 -----
601 +---
439 439  
440 -## **Suggestions for Further Exploration**##
603 +## **Suggestions for Further Exploration**
604 +1. Examine **cross-national differences** in expert opinions on intelligence.
605 +2. Investigate how **media bias impacts public understanding of intelligence research**.
606 +3. Conduct follow-up studies with **a more diverse expert pool** to test findings.
441 441  
442 -1. Investigate **genetic adaptations to local environments within Africa**.
443 -2. Study **the role of African genetic diversity in disease resistance**.
444 -3. Expand research on **how ancient migration patterns shaped modern genetic structure**.
608 +---
445 445  
446 -----
447 -
448 448  ## **Summary of Research Study**
449 -This study explores the **genetic diversity of African populations**, analyzing their role in **human evolution and complex disease research**. The findings highlight **Africa’s unique genetic landscape**, confirming it as the most genetically diverse continent. The research provides valuable insights into **how genetic variation influences disease susceptibility, evolution, and population structure**.##
611 +This study surveys **expert opinions on intelligence research**, analyzing **how backgrounds, political ideologies, and media representation influence perspectives on intelligence**. The findings highlight **divisions in scientific consensus**, particularly on **genetic vs. environmental causes of IQ disparities**. Additionally, the research uncovers **widespread dissatisfaction with media portrayals of intelligence research**, pointing to **the impact of ideological biases on public discourse**.
450 450  
451 451  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
452 452  
453 -----
615 +---
454 454  
455 455  ## **📄 Download Full Study**
456 -[[Download Full Study>>attach:10.1038_nrg865MODERN.pdf]]##
618 +[[Download Full Study>>attach:10.1016_j.intell.2019.101406.pdf]]
619 +
457 457  {{/expand}}
458 458  
622 +{{html}}<hr style="border: 3px solid red;">{{/html}}
459 459  
460 -== Study: Pervasive Findings of Directional Selection in Ancient DNA ==
624 +{{expand title="Study: Is Homo sapiens polytypic? Human taxonomic diversity and its implications" expanded="false"}}
625 +**Source:** *Medical Hypotheses (Elsevier)*
626 +**Date of Publication:** *2010*
627 +**Author(s):** *Michael A. Woodley*
628 +**Title:** *"Is Homo sapiens polytypic? Human taxonomic diversity and its implications"*
629 +**DOI:** [10.1016/j.mehy.2009.07.046](https://doi.org/10.1016/j.mehy.2009.07.046)
630 +**Subject Matter:** *Human Taxonomy, Evolutionary Biology, Anthropology*
461 461  
462 -{{expand expanded="false" title="Study: Pervasive Findings of Directional Selection in Ancient DNA"}}
463 -**Source:** *bioRxiv Preprint*
464 -**Date of Publication:** *September 15, 2024*
465 -**Author(s):** *Ali Akbari, Alison R. Barton, Steven Gazal, Zheng Li, Mohammadreza Kariminejad, et al.*
466 -**Title:** *"Pervasive findings of directional selection realize the promise of ancient DNA to elucidate human adaptation"*
467 -**DOI:** [10.1101/2024.09.14.613021](https://doi.org/10.1101/2024.09.14.613021)
468 -**Subject Matter:** *Genomics, Evolutionary Biology, Natural Selection* 
632 +---
469 469  
470 -----
471 -
472 -## **Key Statistics**##
473 -
634 +## **Key Statistics**
474 474  1. **General Observations:**
475 - - Study analyzes **8,433 ancient individuals** from the past **14,000 years**.
476 - - Identifies **347 genome-wide significant loci** showing strong selection.
636 + - The study argues that **Homo sapiens is polytypic**, meaning it consists of multiple subspecies rather than a single monotypic species.
637 + - Examines **genetic diversity, morphological variation, and evolutionary lineage** in humans.
477 477  
478 478  2. **Subgroup Analysis:**
479 - - Examines **West Eurasian populations** and their genetic evolution.
480 - - Tracks **changes in allele frequencies over millennia**.
640 + - Discusses **four primary definitions of race/subspecies**: Essentialist, Taxonomic, Population-based, and Lineage-based.
641 + - Suggests that **human heterozygosity levels are comparable to species that are classified as polytypic**.
481 481  
482 482  3. **Other Significant Data Points:**
483 - - **10,000 years of directional selection** affected metabolic, immune, and cognitive traits.
484 - - **Strong selection signals** found for traits like **skin pigmentation, cognitive function, and immunity**.
644 + - The study evaluates **FST values (genetic differentiation measure)** and argues that human genetic differentiation is comparable to that of recognized subspecies in other species.
645 + - Considers **phylogenetic species concepts** in defining human variation.
485 485  
486 -----
647 +---
487 487  
488 -## **Findings**##
489 -
649 +## **Findings**
490 490  1. **Primary Observations:**
491 - - **Hundreds of alleles have been subject to directional selection** over recent millennia.
492 - - Traits like **immune function, metabolism, and cognitive performance** show strong selection.
651 + - Proposes that **modern human populations meet biological criteria for subspecies classification**.
652 + - Highlights **medical and evolutionary implications** of human taxonomic diversity.
493 493  
494 494  2. **Subgroup Trends:**
495 - - Selection pressure on **energy storage genes** supports the **Thrifty Gene Hypothesis**.
496 - - **Cognitive performance-related alleles** have undergone selection, but their historical advantages remain unclear.
655 + - Discusses **how race concepts evolved over time** in biological sciences.
656 + - Compares **human diversity with that of other primates** such as chimpanzees and gorillas.
497 497  
498 498  3. **Specific Case Analysis:**
499 - - **Celiac disease risk allele** increased from **0% to 20%** in 4,000 years.
500 - - **Blood type B frequency rose from 0% to 8% in 6,000 years**.
501 - - **Tuberculosis risk allele** fluctuated from **2% to 9% over 3,000 years before declining**.
659 + - Evaluates how **genetic markers correlate with population structure**.
660 + - Addresses the **controversy over race classification in modern anthropology**.
502 502  
503 -----
662 +---
504 504  
505 -## **Critique and Observations**##
506 -
664 +## **Critique and Observations**
507 507  1. **Strengths of the Study:**
508 - - **Largest dataset to date** on natural selection in human ancient DNA.
509 - - Uses **direct allele frequency tracking instead of indirect measures**.
666 + - Uses **comparative species analysis** to assess human classification.
667 + - Provides a **biological perspective** on the race concept, moving beyond social constructivism arguments.
510 510  
511 511  2. **Limitations of the Study:**
512 - - Findings **may not translate directly** to modern populations.
513 - - **Unclear whether observed selection pressures persist today**.
670 + - Controversial topic with **strong opposing views in anthropology and genetics**.
671 + - **Relies on broad genetic trends**, but does not analyze individual-level genetic variation in depth.
514 514  
515 515  3. **Suggestions for Improvement:**
516 - - Expanding research to **other global populations** to assess universal trends.
517 - - Investigating **long-term evolutionary trade-offs of selected alleles**.
674 + - Further research should **incorporate whole-genome studies** to refine subspecies classifications.
675 + - Investigate **how admixture affects taxonomic classification over time**.
518 518  
519 -----
677 +---
520 520  
521 521  ## **Relevance to Subproject**
522 -- Provides **direct evidence of long-term genetic adaptation** in human populations.
523 -- Supports theories on **polygenic selection shaping human cognition, metabolism, and immunity**.
524 -- Highlights **how past selection pressures may still influence modern health and disease prevalence**.##
680 +- Contributes to discussions on **evolutionary taxonomy and species classification**.
681 +- Provides evidence on **genetic differentiation among human populations**.
682 +- Highlights **historical and contemporary scientific debates on race and human variation**.
525 525  
526 -----
684 +---
527 527  
528 -## **Suggestions for Further Exploration**##
686 +## **Suggestions for Further Exploration**
687 +1. Examine **FST values in modern and ancient human populations**.
688 +2. Investigate how **adaptive evolution influences population differentiation**.
689 +3. Explore **the impact of genetic diversity on medical treatments and disease susceptibility**.
529 529  
530 -1. Examine **selection patterns in non-European populations** for comparison.
531 -2. Investigate **how environmental and cultural shifts influenced genetic selection**.
532 -3. Explore **the genetic basis of traits linked to past and present-day human survival**.
691 +---
533 533  
534 -----
535 -
536 536  ## **Summary of Research Study**
537 -This study examines **how human genetic adaptation has unfolded over 14,000 years**, using a **large dataset of ancient DNA**. It highlights **strong selection on immune function, metabolism, and cognitive traits**, revealing **hundreds of loci affected by directional selection**. The findings emphasize **the power of ancient DNA in tracking human evolution and adaptation**.##
694 +This study evaluates **whether Homo sapiens should be classified as a polytypic species**, analyzing **genetic diversity, evolutionary lineage, and morphological variation**. Using comparative analysis with other primates and mammals, the research suggests that **human populations meet biological criteria for subspecies classification**, with implications for **evolutionary biology, anthropology, and medicine**.
538 538  
539 -----
696 +This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
540 540  
698 +---
699 +
541 541  ## **📄 Download Full Study**
542 -[[Download Full Study>>attach:10.1101_2024.09.14.613021doi_.pdf]]##
701 +[[Download Full Study>>attach:10.1016_j.mehy.2009.07.046.pdf]]
702 +
543 543  {{/expand}}
544 544  
705 +{{html}}<hr style="border: 3px solid red;">{{/html}}
545 545  
546 -== Study: The Wilson Effect: The Increase in Heritability of IQ With Age ==
547 -
548 -{{expand expanded="false" title="Study: The Wilson Effect: The Increase in Heritability of IQ With Age"}}
707 +{{expand title="Study: The Wilson Effect: The Increase in Heritability of IQ With Age" expanded="false"}}
549 549  **Source:** *Twin Research and Human Genetics (Cambridge University Press)*
550 550  **Date of Publication:** *2013*
551 551  **Author(s):** *Thomas J. Bouchard Jr.*
552 552  **Title:** *"The Wilson Effect: The Increase in Heritability of IQ With Age"*
553 553  **DOI:** [10.1017/thg.2013.54](https://doi.org/10.1017/thg.2013.54)
554 -**Subject Matter:** *Intelligence, Heritability, Developmental Psychology* 
713 +**Subject Matter:** *Intelligence, Heritability, Developmental Psychology*
555 555  
556 -----
715 +---
557 557  
558 -## **Key Statistics**##
559 -
717 +## **Key Statistics**
560 560  1. **General Observations:**
561 561   - The study documents how the **heritability of IQ increases with age**, reaching an asymptote at **0.80 by adulthood**.
562 562   - Analysis is based on **longitudinal twin and adoption studies**.
... ... @@ -569,10 +569,9 @@
569 569   - Data from the **Louisville Longitudinal Twin Study and cross-national twin samples** support findings.
570 570   - IQ stability over time is **influenced more by genetics than by shared environmental factors**.
571 571  
572 -----
730 +---
573 573  
574 -## **Findings**##
575 -
732 +## **Findings**
576 576  1. **Primary Observations:**
577 577   - Intelligence heritability **strengthens throughout development**, contrary to early environmental models.
578 578   - Shared environmental effects **decrease by late adolescence**, emphasizing **genetic influence in adulthood**.
... ... @@ -585,10 +585,9 @@
585 585   - Longitudinal adoption studies show **declining impact of adoptive parental influence on IQ** as children age.
586 586   - Cross-sectional twin data confirm **higher IQ correlations for monozygotic twins in adulthood**.
587 587  
588 -----
745 +---
589 589  
590 -## **Critique and Observations**##
591 -
747 +## **Critique and Observations**
592 592  1. **Strengths of the Study:**
593 593   - **Robust dataset covering multiple twin and adoption studies over decades**.
594 594   - **Clear, replicable trend** demonstrating the increasing role of genetics in intelligence.
... ... @@ -601,792 +601,715 @@
601 601   - Future research should investigate **gene-environment interactions in cognitive aging**.
602 602   - Examine **heritability trends in non-Western populations** to determine cross-cultural consistency.
603 603  
604 -----
760 +---
605 605  
606 606  ## **Relevance to Subproject**
607 607  - Provides **strong evidence for the genetic basis of intelligence**.
608 608  - Highlights the **diminishing role of shared environment in cognitive development**.
609 -- Supports research on **cognitive aging and heritability across the lifespan**.##
765 +- Supports research on **cognitive aging and heritability across the lifespan**.
610 610  
611 -----
767 +---
612 612  
613 -## **Suggestions for Further Exploration**##
614 -
769 +## **Suggestions for Further Exploration**
615 615  1. Investigate **neurogenetic pathways underlying IQ development**.
616 616  2. Examine **how education and socioeconomic factors interact with genetic IQ influences**.
617 617  3. Study **heritability trends in aging populations and cognitive decline**.
618 618  
619 -----
774 +---
620 620  
621 621  ## **Summary of Research Study**
622 -This study documents **The Wilson Effect**, demonstrating how the **heritability of IQ increases throughout development**, reaching a plateau of **0.80 by adulthood**. The findings indicate that **shared environmental effects diminish with age**, while **genetic influences on intelligence strengthen**. Using **longitudinal twin and adoption data**, the research provides **strong empirical support for the increasing role of genetics in cognitive ability over time**.##
777 +This study documents **The Wilson Effect**, demonstrating how the **heritability of IQ increases throughout development**, reaching a plateau of **0.80 by adulthood**. The findings indicate that **shared environmental effects diminish with age**, while **genetic influences on intelligence strengthen**. Using **longitudinal twin and adoption data**, the research provides **strong empirical support for the increasing role of genetics in cognitive ability over time**.
623 623  
624 624  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
625 625  
626 -----
781 +---
627 627  
628 628  ## **📄 Download Full Study**
629 -[[Download Full Study>>attach:10.1017_thg.2013.54.pdf]]##
784 +[[Download Full Study>>attach:10.1017_thg.2013.54.pdf]]
785 +
630 630  {{/expand}}
631 631  
788 +{{html}}<hr style="border: 3px solid red;">{{/html}}
632 632  
633 -== Study: Is Homo sapiens polytypic? Human taxonomic diversity and its implications ==
790 +{{expand title="Study: Segregation, Innocence, and Protection: The Institutional Conditions That Maintain Whiteness in College Sports" expanded="false"}}
791 +**Source:** *Journal of Diversity in Higher Education*
792 +**Date of Publication:** *2019*
793 +**Author(s):** *Kirsten Hextrum*
794 +**Title:** *"Segregation, Innocence, and Protection: The Institutional Conditions That Maintain Whiteness in College Sports"*
795 +**DOI:** [10.1037/dhe0000140](https://doi.org/10.1037/dhe0000140)
796 +**Subject Matter:** *Race and Sports, Higher Education, Institutional Racism*
634 634  
635 -{{expand expanded="false" title="Study: Is Homo sapiens polytypic? Human taxonomic diversity and its implications"}}
636 -**Source:** *Medical Hypotheses (Elsevier)*
637 -**Date of Publication:** *2010*
638 -**Author(s):** *Michael A. Woodley*
639 -**Title:** *"Is Homo sapiens polytypic? Human taxonomic diversity and its implications"*
640 -**DOI:** [10.1016/j.mehy.2009.07.046](https://doi.org/10.1016/j.mehy.2009.07.046)
641 -**Subject Matter:** *Human Taxonomy, Evolutionary Biology, Anthropology* 
798 +---
642 642  
643 -----
644 -
645 -## **Key Statistics**##
646 -
800 +## **Key Statistics**
647 647  1. **General Observations:**
648 - - The study argues that **Homo sapiens is polytypic**, meaning it consists of multiple subspecies rather than a single monotypic species.
649 - - Examines **genetic diversity, morphological variation, and evolutionary lineage** in humans.
802 + - Analyzed **47 college athlete narratives** to explore racial disparities in non-revenue sports.
803 + - Found three interrelated themes: **racial segregation, racial innocence, and racial protection**.
650 650  
651 651  2. **Subgroup Analysis:**
652 - - Discusses **four primary definitions of race/subspecies**: Essentialist, Taxonomic, Population-based, and Lineage-based.
653 - - Suggests that **human heterozygosity levels are comparable to species that are classified as polytypic**.
806 + - **Predominantly white sports programs** reinforce racial hierarchies in college athletics.
807 + - **Recruitment policies favor white athletes** from affluent, suburban backgrounds.
654 654  
655 655  3. **Other Significant Data Points:**
656 - - The study evaluates **FST values (genetic differentiation measure)** and argues that human genetic differentiation is comparable to that of recognized subspecies in other species.
657 - - Considers **phylogenetic species concepts** in defining human variation.
810 + - White athletes are **socialized to remain unaware of racial privilege** in their athletic careers.
811 + - Media and institutional narratives protect white athletes from discussions on race and systemic inequities.
658 658  
659 -----
813 +---
660 660  
661 -## **Findings**##
662 -
815 +## **Findings**
663 663  1. **Primary Observations:**
664 - - Proposes that **modern human populations meet biological criteria for subspecies classification**.
665 - - Highlights **medical and evolutionary implications** of human taxonomic diversity.
817 + - Colleges **actively recruit white athletes** from majority-white communities.
818 + - Institutional policies **uphold whiteness** by failing to challenge racial biases in recruitment and team culture.
666 666  
667 667  2. **Subgroup Trends:**
668 - - Discusses **how race concepts evolved over time** in biological sciences.
669 - - Compares **human diversity with that of other primates** such as chimpanzees and gorillas.
821 + - **White athletes show limited awareness** of their racial advantage in sports.
822 + - **Black athletes are overrepresented** in revenue-generating sports but underrepresented in non-revenue teams.
670 670  
671 671  3. **Specific Case Analysis:**
672 - - Evaluates how **genetic markers correlate with population structure**.
673 - - Addresses the **controversy over race classification in modern anthropology**.
825 + - Examines **how sports serve as a mechanism for maintaining racial privilege** in higher education.
826 + - Discusses the **role of athletics in reinforcing systemic segregation and exclusion**.
674 674  
675 -----
828 +---
676 676  
677 -## **Critique and Observations**##
678 -
830 +## **Critique and Observations**
679 679  1. **Strengths of the Study:**
680 - - Uses **comparative species analysis** to assess human classification.
681 - - Provides a **biological perspective** on the race concept, moving beyond social constructivism arguments.
832 + - **Comprehensive qualitative analysis** of race in college sports.
833 + - Examines **institutional conditions** that sustain racial disparities in athletics.
682 682  
683 683  2. **Limitations of the Study:**
684 - - Controversial topic with **strong opposing views in anthropology and genetics**.
685 - - **Relies on broad genetic trends**, but does not analyze individual-level genetic variation in depth.
836 + - Focuses primarily on **Division I non-revenue sports**, limiting generalizability to other divisions.
837 + - Lacks extensive **quantitative data on racial demographics** in college athletics.
686 686  
687 687  3. **Suggestions for Improvement:**
688 - - Further research should **incorporate whole-genome studies** to refine subspecies classifications.
689 - - Investigate **how admixture affects taxonomic classification over time**.
840 + - Future research should **compare recruitment policies across different sports and divisions**.
841 + - Investigate **how athletic scholarships contribute to racial inequities in higher education**.
690 690  
691 -----
843 +---
692 692  
693 693  ## **Relevance to Subproject**
694 -- Contributes to discussions on **evolutionary taxonomy and species classification**.
695 -- Provides evidence on **genetic differentiation among human populations**.
696 -- Highlights **historical and contemporary scientific debates on race and human variation**.##
846 +- Provides evidence of **systemic racial biases** in college sports recruitment.
847 +- Highlights **how institutional policies protect whiteness** in non-revenue athletics.
848 +- Supports research on **diversity, equity, and inclusion (DEI) efforts in sports and education**.
697 697  
698 -----
850 +---
699 699  
700 -## **Suggestions for Further Exploration**##
852 +## **Suggestions for Further Exploration**
853 +1. Investigate how **racial stereotypes influence college athlete recruitment**.
854 +2. Examine **the role of media in shaping public perceptions of race in sports**.
855 +3. Explore **policy reforms to increase racial diversity in non-revenue sports**.
701 701  
702 -1. Examine **FST values in modern and ancient human populations**.
703 -2. Investigate how **adaptive evolution influences population differentiation**.
704 -3. Explore **the impact of genetic diversity on medical treatments and disease susceptibility**.
857 +---
705 705  
706 -----
707 -
708 708  ## **Summary of Research Study**
709 -This study evaluates **whether Homo sapiens should be classified as a polytypic species**, analyzing **genetic diversity, evolutionary lineage, and morphological variation**. Using comparative analysis with other primates and mammals, the research suggests that **human populations meet biological criteria for subspecies classification**, with implications for **evolutionary biology, anthropology, and medicine**.##
860 +This study explores how **racial segregation, innocence, and protection** sustain whiteness in college sports. By analyzing **47 athlete narratives**, the research reveals **how predominantly white sports programs recruit and retain white athletes** while shielding them from discussions on race. The findings highlight **institutional biases that maintain racial privilege in athletics**, offering critical insight into the **structural inequalities in higher education sports programs**.
710 710  
711 711  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
712 712  
713 -----
864 +---
714 714  
715 715  ## **📄 Download Full Study**
716 -[[Download Full Study>>attach:10.1016_j.mehy.2009.07.046.pdf]]##
867 +[[Download Full Study>>attach:10.1037_dhe0000140.pdf]]
868 +
717 717  {{/expand}}
718 718  
871 +{{html}}<hr style="border: 3px solid red;">{{/html}}
719 719  
720 -== Study: Survey of Expert Opinion on Intelligence: Intelligence Research, Experts' Background, Controversial Issues, and the Media ==
873 +{{expand title="Study: Reconstructing Indian Population History" expanded="false"}}
874 +**Source:** *Nature*
875 +**Date of Publication:** *2009*
876 +**Author(s):** *David Reich, Kumarasamy Thangaraj, Nick Patterson, Alkes L. Price, Lalji Singh*
877 +**Title:** *"Reconstructing Indian Population History"*
878 +**DOI:** [10.1038/nature08365](https://doi.org/10.1038/nature08365)
879 +**Subject Matter:** *Genetics, Population History, South Asian Ancestry*
721 721  
722 -{{expand expanded="false" title="Study: Survey of Expert Opinion on Intelligence: Intelligence Research, Experts' Background, Controversial Issues, and the Media"}}
723 -**Source:** *Intelligence (Elsevier)*
724 -**Date of Publication:** *2019*
725 -**Author(s):** *Heiner Rindermann, David Becker, Thomas R. Coyle*
726 -**Title:** *"Survey of Expert Opinion on Intelligence: Intelligence Research, Experts' Background, Controversial Issues, and the Media"*
727 -**DOI:** [10.1016/j.intell.2019.101406](https://doi.org/10.1016/j.intell.2019.101406)
728 -**Subject Matter:** *Psychology, Intelligence Research, Expert Analysis* 
881 +---
729 729  
730 -----
731 -
732 -## **Key Statistics**##
733 -
883 +## **Key Statistics**
734 734  1. **General Observations:**
735 - - Survey of **102 experts** on intelligence research and public discourse.
736 - - Evaluated experts' backgrounds, political affiliations, and views on controversial topics in intelligence research.
885 + - Study analyzed **132 individuals from 25 diverse Indian groups**.
886 + - Identified two major ancestral populations: **Ancestral North Indians (ANI)** and **Ancestral South Indians (ASI)**.
737 737  
738 738  2. **Subgroup Analysis:**
739 - - **90% of experts were from Western countries**, and **83% were male**.
740 - - Political spectrum ranged from **54% left-liberal, 24% conservative**, with significant ideological influences on views.
889 + - ANI ancestry is closely related to **Middle Easterners, Central Asians, and Europeans**.
890 + - ASI ancestry is **genetically distinct from ANI and East Asians**.
741 741  
742 742  3. **Other Significant Data Points:**
743 - - Experts rated media coverage of intelligence research as **poor (avg. 3.1 on a 9-point scale)**.
744 - - **50% of experts attributed US Black-White IQ differences to genetic factors, 50% to environmental factors**.
893 + - ANI ancestry ranges from **39% to 71%** across Indian groups.
894 + - **Caste and linguistic differences** strongly correlate with genetic variation.
745 745  
746 -----
896 +---
747 747  
748 -## **Findings**##
749 -
898 +## **Findings**
750 750  1. **Primary Observations:**
751 - - Experts overwhelmingly support **the g-factor theory of intelligence**.
752 - - **Heritability of intelligence** was widely accepted, though views differed on race and group differences.
900 + - The genetic landscape of India has been shaped by **thousands of years of endogamy**.
901 + - Groups with **only ASI ancestry no longer exist** in mainland India.
753 753  
754 754  2. **Subgroup Trends:**
755 - - **Left-leaning experts were more likely to reject genetic explanations for group IQ differences**.
756 - - **Right-leaning experts tended to favor a stronger role for genetic factors** in intelligence disparities.
904 + - **Higher ANI ancestry in upper-caste and Indo-European-speaking groups**.
905 + - **Andaman Islanders** are unique in having **ASI ancestry without ANI influence**.
757 757  
758 758  3. **Specific Case Analysis:**
759 - - The study compared **media coverage of intelligence research** with expert opinions.
760 - - Found a **disconnect between journalists and intelligence researchers**, especially regarding politically sensitive issues.
908 + - **Founder effects** have maintained allele frequency differences among Indian groups.
909 + - Predicts **higher incidence of recessive diseases** due to historical genetic isolation.
761 761  
762 -----
911 +---
763 763  
764 -## **Critique and Observations**##
765 -
913 +## **Critique and Observations**
766 766  1. **Strengths of the Study:**
767 - - **Largest expert survey on intelligence research** to date.
768 - - Provides insight into **how political orientation influences scientific perspectives**.
915 + - **First large-scale genetic analysis** of Indian population history.
916 + - Introduces **new methods for ancestry estimation without direct ancestral reference groups**.
769 769  
770 770  2. **Limitations of the Study:**
771 - - **Sample primarily from Western countries**, limiting global perspectives.
772 - - Self-selection bias may skew responses toward **those more willing to engage with controversial topics**.
919 + - Limited **sample size relative to India's population diversity**.
920 + - Does not include **recent admixture events** post-colonial era.
773 773  
774 774  3. **Suggestions for Improvement:**
775 - - Future studies should include **a broader range of global experts**.
776 - - Additional research needed on **media biases and misrepresentation of intelligence research**.
923 + - Future research should **expand sampling across more Indian tribal groups**.
924 + - Use **whole-genome sequencing** for finer resolution of ancestry.
777 777  
778 -----
926 +---
779 779  
780 780  ## **Relevance to Subproject**
781 -- Provides insight into **expert consensus and division on intelligence research**.
782 -- Highlights the **role of media bias** in shaping public perception of intelligence science.
783 -- Useful for understanding **the intersection of science, politics, and public discourse** on intelligence research.##
929 +- Provides a **genetic basis for caste and linguistic diversity** in India.
930 +- Highlights **founder effects and genetic drift** shaping South Asian populations.
931 +- Supports research on **medical genetics and disease risk prediction** in Indian populations.
784 784  
785 -----
933 +---
786 786  
787 -## **Suggestions for Further Exploration**##
935 +## **Suggestions for Further Exploration**
936 +1. Examine **genetic markers linked to disease susceptibility** in Indian subpopulations.
937 +2. Investigate the impact of **recent migration patterns on ANI-ASI ancestry distribution**.
938 +3. Study **gene flow between Indian populations and other global groups**.
788 788  
789 -1. Examine **cross-national differences** in expert opinions on intelligence.
790 -2. Investigate how **media bias impacts public understanding of intelligence research**.
791 -3. Conduct follow-up studies with **a more diverse expert pool** to test findings.
940 +---
792 792  
793 -----
794 -
795 795  ## **Summary of Research Study**
796 -This study surveys **expert opinions on intelligence research**, analyzing **how backgrounds, political ideologies, and media representation influence perspectives on intelligence**. The findings highlight **divisions in scientific consensus**, particularly on **genetic vs. environmental causes of IQ disparities**. Additionally, the research uncovers **widespread dissatisfaction with media portrayals of intelligence research**, pointing to **the impact of ideological biases on public discourse**.##
943 +This study reconstructs **the genetic history of India**, revealing two ancestral populations—**ANI (related to West Eurasians) and ASI (distinctly South Asian)**. By analyzing **25 diverse Indian groups**, the researchers demonstrate how **historical endogamy and founder effects** have maintained genetic differentiation. The findings have **implications for medical genetics, population history, and the study of South Asian ancestry**.
797 797  
798 798  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
799 799  
800 -----
947 +---
801 801  
802 802  ## **📄 Download Full Study**
803 -[[Download Full Study>>attach:10.1016_j.intell.2019.101406.pdf]]##
950 +[[Download Full Study>>attach:10.1038_nature08365.pdf]]
951 +
804 804  {{/expand}}
805 805  
954 +{{html}}<hr style="border: 3px solid red;">{{/html}}
806 806  
807 -== Study: A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation ==
808 808  
809 -{{expand expanded="false" title="Study: A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation"}}
810 -**Source:** *Intelligence (Elsevier)*
811 -**Date of Publication:** *2015*
812 -**Author(s):** *Davide Piffer*
813 -**Title:** *"A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation"*
814 -**DOI:** [10.1016/j.intell.2015.08.008](https://doi.org/10.1016/j.intell.2015.08.008)
815 -**Subject Matter:** *Genetics, Intelligence, GWAS, Population Differences* 
957 +{{expand title="Study: The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations" expanded="false"}}
958 +**Source:** *Nature*
959 +**Date of Publication:** *2016*
960 +**Author(s):** *David Reich, Swapan Mallick, Heng Li, Mark Lipson, and others*
961 +**Title:** *"The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations"*
962 +**DOI:** [10.1038/nature18964](https://doi.org/10.1038/nature18964)
963 +**Subject Matter:** *Human Genetic Diversity, Population History, Evolutionary Genomics*
816 816  
817 -----
965 +---
818 818  
819 -## **Key Statistics**##
820 -
967 +## **Key Statistics**
821 821  1. **General Observations:**
822 - - Study analyzed **genome-wide association studies (GWAS) hits** linked to intelligence.
823 - - Found a **strong correlation (r = .91) between polygenic intelligence scores and national IQ levels**.
969 + - Analyzed **high-coverage genome sequences of 300 individuals from 142 populations**.
970 + - Included **many underrepresented and indigenous groups** from Africa, Asia, Europe, and the Americas.
824 824  
825 825  2. **Subgroup Analysis:**
826 - - Factor analysis of **9 intelligence-associated alleles** revealed a metagene correlated with **country IQ (r = .86)**.
827 - - **Allele frequencies varied significantly by continent**, aligning with observed population differences in cognitive ability.
973 + - Found **higher genetic diversity within African populations** compared to non-African groups.
974 + - Showed **Neanderthal and Denisovan ancestry in non-African populations**, particularly in Oceania.
828 828  
829 829  3. **Other Significant Data Points:**
830 - - GWAS intelligence SNPs predicted **IQ levels more strongly than random genetic markers**.
831 - - Genetic differentiation (Fst values) showed that **selection pressure, rather than drift, influenced intelligence-related allele distributions**.
977 + - Identified **5.8 million base pairs absent from the human reference genome**.
978 + - Estimated that **mutations have accumulated 5% faster in non-Africans than in Africans**.
832 832  
833 -----
980 +---
834 834  
835 -## **Findings**##
836 -
982 +## **Findings**
837 837  1. **Primary Observations:**
838 - - Intelligence-associated SNP frequencies correlate **highly with national IQ levels**.
839 - - Genetic selection for intelligence appears **stronger than selection for height-related genes**.
984 + - **African populations harbor the greatest genetic diversity**, confirming an out-of-Africa dispersal model.
985 + - Indigenous Australians and New Guineans **share a common ancestral population with other non-Africans**.
840 840  
841 841  2. **Subgroup Trends:**
842 - - **East Asian populations** exhibited the **highest frequencies of intelligence-associated alleles**.
843 - - **African populations** showed lower frequencies compared to European and East Asian populations.
988 + - **Lower heterozygosity in non-Africans** due to founder effects from migration bottlenecks.
989 + - **Denisovan ancestry in South Asians is higher than previously thought**.
844 844  
845 845  3. **Specific Case Analysis:**
846 - - Polygenic scores using **intelligence-related alleles significantly outperformed random SNPs** in predicting IQ.
847 - - Selection pressures **may explain differences in global intelligence distribution** beyond genetic drift effects.
992 + - **Neanderthal ancestry is higher in East Asians than in Europeans**.
993 + - African hunter-gatherer groups show **deep population splits over 100,000 years ago**.
848 848  
849 -----
995 +---
850 850  
851 -## **Critique and Observations**##
852 -
997 +## **Critique and Observations**
853 853  1. **Strengths of the Study:**
854 - - **Comprehensive genetic analysis** of intelligence-linked SNPs.
855 - - Uses **multiple statistical methods (factor analysis, Fst analysis) to confirm results**.
999 + - **Largest global genetic dataset** outside of the 1000 Genomes Project.
1000 + - High sequencing depth allows **more accurate identification of genetic variants**.
856 856  
857 857  2. **Limitations of the Study:**
858 - - **Correlation does not imply causation**; factors beyond genetics influence intelligence.
859 - - **Limited number of GWAS-identified intelligence alleles**—future studies may identify more.
1003 + - **Limited sample sizes for some populations**, restricting generalizability.
1004 + - Lacks ancient DNA comparisons, making it difficult to reconstruct deep ancestry fully.
860 860  
861 861  3. **Suggestions for Improvement:**
862 - - Larger **cross-population GWAS studies** needed to validate findings.
863 - - Investigate **non-genetic contributors to IQ variance** in addition to genetic factors.
1007 + - Future studies should include **ancient genomes** to improve demographic modeling.
1008 + - Expand research into **how genetic variation affects health outcomes** across populations.
864 864  
865 -----
1010 +---
866 866  
867 867  ## **Relevance to Subproject**
868 -- Supports research on **genetic influences on intelligence at a population level**.
869 -- Aligns with broader discussions on **cognitive genetics and natural selection effects**.
870 -- Provides a **quantitative framework for analyzing polygenic selection in intelligence studies**.##
1013 +- Provides **comprehensive data on human genetic diversity**, useful for **evolutionary studies**.
1014 +- Supports research on **Neanderthal and Denisovan introgression** in modern human populations.
1015 +- Enhances understanding of **genetic adaptation and disease susceptibility across groups**.
871 871  
872 -----
1017 +---
873 873  
874 -## **Suggestions for Further Exploration**##
1019 +## **Suggestions for Further Exploration**
1020 +1. Investigate **functional consequences of genetic variation in underrepresented populations**.
1021 +2. Study **how selection pressures shaped genetic diversity across different environments**.
1022 +3. Explore **medical applications of population-specific genetic markers**.
875 875  
876 -1. Conduct **expanded GWAS studies** including diverse populations.
877 -2. Investigate **gene-environment interactions influencing intelligence**.
878 -3. Explore **historical selection pressures shaping intelligence-related alleles**.
1024 +---
879 879  
880 -----
881 -
882 882  ## **Summary of Research Study**
883 -This study reviews **genome-wide association study (GWAS) findings on intelligence**, demonstrating a **strong correlation between polygenic intelligence scores and national IQ levels**. The research highlights how **genetic selection may explain population-level cognitive differences beyond genetic drift effects**. Intelligence-linked alleles showed **higher variability across populations than height-related alleles**, suggesting stronger selection pressures.  ##
1027 +This study presents **high-coverage genome sequences from 300 individuals across 142 populations**, offering **new insights into global genetic diversity and human evolution**. The findings highlight **deep African population splits, widespread archaic ancestry in non-Africans, and unique variants absent from the human reference genome**. The research enhances our understanding of **migration patterns, adaptation, and evolutionary history**.
884 884  
885 885  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
886 886  
887 -----
1031 +---
888 888  
889 889  ## **📄 Download Full Study**
890 -[[Download Full Study>>attach:10.1016_j.intell.2015.08.008.pdf]]##
891 -{{/expand}}
1034 +[[Download Full Study>>attach:10.1038_nature18964.pdf]]
892 892  
893 -
894 -== Study: Genetic Structure, Self-Identified Race/Ethnicity, and Confounding ==
895 -
896 -{{expand expanded="false" title="Click here to expand details"}}
897 -**Source:** Journal of Genetic Epidemiology
898 -**Date of Publication:** 2024-01-15
899 -**Author(s):** Smith et al.
900 -**Title:** "Genetic Structure, Self-Identified Race/Ethnicity, and Confounding in Case-Control Association Studies"
901 -**DOI:** [https://doi.org/10.1037/1076-8971.11.2.235](https://doi.org/10.1037/1076-8971.11.2.235)
902 -**Subject Matter:** Genetics, Social Science 
903 -
904 -**Tags:** `Genetics` `Race & Ethnicity` `Biomedical Research`
905 -
906 - **Key Statistics**
907 -
908 -1. **General Observations:**
909 - - A near-perfect alignment between self-identified race/ethnicity (SIRE) and genetic ancestry was observed.
910 - - Misclassification rate: **0.14%**.
911 -
912 -2. **Subgroup Analysis:**
913 - - Four groups analyzed: **White, African American, East Asian, and Hispanic**.
914 - - Hispanic genetic clusters showed significant European and Native American lineage.
915 -
916 - **Findings**
917 -
918 -- Self-identified race strongly aligns with genetic ancestry.
919 -- Minor discrepancies exist but do not significantly impact classification.
920 -
921 - **Relevance to Subproject**
922 -
923 -- Reinforces the reliability of **self-reported racial identity** in genetic research.
924 -- Highlights **policy considerations** in biomedical studies.
925 925  {{/expand}}
926 926  
1038 +{{html}}<hr style="border: 3px solid red;">{{/html}}
927 927  
928 -----
1040 +{{expand title="Study: Meta-analysis of the heritability of human traits based on fifty years of twin studies" expanded="false"}}
1041 +**Source:** *Nature Genetics*
1042 +**Date of Publication:** *2015*
1043 +**Author(s):** *Tinca J. C. Polderman, Beben Benyamin, Christiaan A. de Leeuw, Patrick F. Sullivan, Arjen van Bochoven, Peter M. Visscher, Danielle Posthuma*
1044 +**Title:** *"Meta-analysis of the heritability of human traits based on fifty years of twin studies"*
1045 +**DOI:** [10.1038/ng.328](https://doi.org/10.1038/ng.328)
1046 +**Subject Matter:** *Genetics, Heritability, Twin Studies, Behavioral Science*
929 929  
930 -= Dating and Interpersonal Relationships =
1048 +---
931 931  
932 -
933 -== Study: Trends in Frequency of Sexual Activity and Number of Sexual Partners Among Adults Aged 18 to 44 Years in the US, 2000-2018 ==
934 -
935 -{{expand expanded="false" title="Study: Trends in Frequency of Sexual Activity and Number of Sexual Partners Among Adults Aged 18 to 44 Years in the US, 2000-2018"}}
936 -**Source:** *JAMA Network Open*
937 -**Date of Publication:** *2020*
938 -**Author(s):** *Ueda P, Mercer CH, Ghaznavi C, Herbenick D.*
939 -**Title:** *"Trends in Frequency of Sexual Activity and Number of Sexual Partners Among Adults Aged 18 to 44 Years in the US, 2000-2018"*
940 -**DOI:** [10.1001/jamanetworkopen.2020.3833](https://doi.org/10.1001/jamanetworkopen.2020.3833)
941 -**Subject Matter:** *Public Health, Sexual Behavior, Demography* 
942 -
943 -----
944 -
945 -## **Key Statistics**##
946 -
1050 +## **Key Statistics**
947 947  1. **General Observations:**
948 - - Study analyzed **General Social Survey (2000-2018)** data.
949 - - Found **declining trends in sexual activity** among young adults.
1052 + - Analyzed **17,804 traits from 2,748 twin studies** published between **1958 and 2012**.
1053 + - Included data from **14,558,903 twin pairs**, making it the largest meta-analysis on human heritability.
950 950  
951 951  2. **Subgroup Analysis:**
952 - - Decreases in sexual activity were most prominent among **men aged 18-34**.
953 - - Factors like **marital status, employment, and psychological well-being** were associated with changes in sexual frequency.
1056 + - Found **49% average heritability** across all traits.
1057 + - **69% of traits follow a simple additive genetic model**, meaning most variance is due to genes, not environment.
954 954  
955 955  3. **Other Significant Data Points:**
956 - - Frequency of sexual activity decreased by **8-10%** over the studied period.
957 - - Number of sexual partners remained **relatively stable** despite declining activity rates.
1060 + - **Neurological, metabolic, and psychiatric traits** showed the highest heritability estimates.
1061 + - Traits related to **social values and environmental interactions** had lower heritability estimates.
958 958  
959 -----
1063 +---
960 960  
961 -## **Findings**##
962 -
1065 +## **Findings**
963 963  1. **Primary Observations:**
964 - - A significant decline in sexual frequency, especially among **younger men**.
965 - - Shifts in relationship dynamics and economic stressors may contribute to the trend.
1067 + - Across all traits, genetic factors play a significant role in individual differences.
1068 + - The study contradicts models that **overestimate environmental effects in behavioral and cognitive traits**.
966 966  
967 967  2. **Subgroup Trends:**
968 - - More pronounced decline among **unmarried individuals**.
969 - - No major change observed for **married adults** over time.
1071 + - **Eye and brain-related traits showed the highest heritability (~70-80%)**.
1072 + - **Shared environmental effects were negligible (<10%) for most traits**.
970 970  
971 971  3. **Specific Case Analysis:**
972 - - **Mental health and employment status** were correlated with decreased activity.
973 - - Social factors such as **screen time and digital entertainment consumption** are potential contributors.
1075 + - Twin correlations suggest **limited evidence for strong non-additive genetic influences**.
1076 + - The study highlights **missing heritability in complex traits**, which genome-wide association studies (GWAS) have yet to fully explain.
974 974  
975 -----
1078 +---
976 976  
977 -## **Critique and Observations**##
978 -
1080 +## **Critique and Observations**
979 979  1. **Strengths of the Study:**
980 - - **Large sample size** from a nationally representative dataset.
981 - - **Longitudinal design** enables trend analysis over time.
1082 + - **Largest-ever heritability meta-analysis**, covering nearly all published twin studies.
1083 + - Provides a **comprehensive framework for understanding gene-environment contributions**.
982 982  
983 983  2. **Limitations of the Study:**
984 - - Self-reported data may introduce **response bias**.
985 - - No direct causal mechanisms tested for the decline in sexual activity.
1086 + - **Underrepresentation of African, South American, and Asian twin cohorts**, limiting global generalizability.
1087 + - Cannot **fully separate genetic influences from potential cultural/environmental confounders**.
986 986  
987 987  3. **Suggestions for Improvement:**
988 - - Further studies should incorporate **qualitative data** on behavioral shifts.
989 - - Additional factors such as **economic shifts and social media usage** need exploration.
1090 + - Future research should use **whole-genome sequencing** for finer-grained heritability estimates.
1091 + - **Incorporate non-Western populations** to assess global heritability trends.
990 990  
991 -----
1093 +---
992 992  
993 993  ## **Relevance to Subproject**
994 -- Provides evidence on **changing demographic behaviors** in relation to relationships and social interactions.
995 -- Highlights the role of **mental health, employment, and societal changes** in personal behaviors.##
1096 +- Establishes a **quantitative benchmark for heritability across human traits**.
1097 +- Reinforces **genetic influence on cognitive, behavioral, and physical traits**.
1098 +- Highlights the need for **genome-wide studies to identify missing heritability**.
996 996  
997 -----
1100 +---
998 998  
999 -## **Suggestions for Further Exploration**##
1102 +## **Suggestions for Further Exploration**
1103 +1. Investigate how **heritability estimates compare across different socioeconomic backgrounds**.
1104 +2. Examine **gene-environment interactions in cognitive and psychiatric traits**.
1105 +3. Explore **non-additive genetic effects on human traits using newer statistical models**.
1000 1000  
1001 -1. Investigate the **impact of digital media consumption** on relationship dynamics.
1002 -2. Examine **regional and cultural differences** in sexual activity trends.
1107 +---
1003 1003  
1004 -----
1005 -
1006 1006  ## **Summary of Research Study**
1007 -This study examines **trends in sexual frequency and number of partners among U.S. adults (2000-2018)**, highlighting significant **declines in sexual activity, particularly among young men**. The research utilized **General Social Survey data** to analyze the impact of **sociodemographic factors, employment status, and mental well-being** on sexual behavior ##
1110 +This study presents a **comprehensive meta-analysis of human trait heritability**, covering **over 50 years of twin research**. The findings confirm **genes play a predominant role in shaping human traits**, with an **average heritability of 49%** across all measured characteristics. The research offers **valuable insights into genetic and environmental influences**, guiding future gene-mapping efforts and behavioral genetics studies.
1008 1008  
1009 -This summary provides an accessible, at-a-glance overview of the study's contributions. Please refer to the full paper for in-depth analysis.
1112 +This summary provides an accessible, at-a-glance overview of the studys contributions. Please refer to the full paper for in-depth analysis.
1010 1010  
1011 -----
1114 +---
1012 1012  
1013 1013  ## **📄 Download Full Study**
1014 -{{velocity}}
1015 -#set($doi = "10.1001_jamanetworkopen.2020.3833")
1016 -#set($filename = "${doi}.pdf")
1017 -#if($xwiki.exists("attach:$filename"))
1018 -[[Download>>attach:$filename]]
1019 -#else
1020 -{{html}}<span style="color: red; font-weight: bold;">🚨 PDF Not Available 🚨</span>{{/html}}
1021 -#end {{/velocity}}##
1117 +[[Download Full Study>>attach:10.1038_ng.328.pdf]]
1118 +
1022 1022  {{/expand}}
1023 1023  
1121 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1024 1024  
1025 -== Study: Biracial Couples and Adverse Birth Outcomes – A Systematic Review and Meta-Analysis ==
1123 +{{expand title="Study: Genetic Analysis of African Populations: Human Evolution and Complex Disease" expanded="false"}}
1124 +**Source:** *Nature Reviews Genetics*
1125 +**Date of Publication:** *2002*
1126 +**Author(s):** *Sarah A. Tishkoff, Scott M. Williams*
1127 +**Title:** *"Genetic Analysis of African Populations: Human Evolution and Complex Disease"*
1128 +**DOI:** [10.1038/nrg865](https://doi.org/10.1038/nrg865)
1129 +**Subject Matter:** *Population Genetics, Human Evolution, Complex Diseases*
1026 1026  
1027 -{{expand expanded="false" title="Study: Biracial Couples and Adverse Birth Outcomes – A Systematic Review and Meta-Analysis"}}
1028 -**Source:** *Acta Obstetricia et Gynecologica Scandinavica*
1029 -**Date of Publication:** *2012*
1030 -**Author(s):** *Ravisha M. Srinivasjois, Shreya Shah, Prakesh S. Shah, Knowledge Synthesis Group on Determinants of Preterm/LBW Births*
1031 -**Title:** *"Biracial Couples and Adverse Birth Outcomes: A Systematic Review and Meta-Analysis"*
1032 -**DOI:** [10.1111/j.1600-0412.2012.01501.x](https://doi.org/10.1111/j.1600-0412.2012.01501.x)
1033 -**Subject Matter:** *Neonatal Health, Maternal-Fetal Medicine, Racial Disparities* 
1131 +---
1034 1034  
1035 -----
1036 -
1037 -## **Key Statistics**##
1038 -
1133 +## **Key Statistics**
1039 1039  1. **General Observations:**
1040 - - Meta-analysis of **26,335,596 singleton births** from eight studies.
1041 - - **Higher risk of adverse birth outcomes in biracial couples** than White couples, but lower than Black couples.
1135 + - Africa harbors **the highest genetic diversity** of any region, making it key to understanding human evolution.
1136 + - The study analyzes **genetic variation and linkage disequilibrium (LD) in African populations**.
1042 1042  
1043 1043  2. **Subgroup Analysis:**
1044 - - **Maternal race had a stronger influence than paternal race** on birth outcomes.
1045 - - **Black mother–White father (BMWF) couples** had a higher risk than **White mother–Black father (WMBF) couples**.
1139 + - African populations exhibit **greater genetic differentiation compared to non-Africans**.
1140 + - **Migration and admixture** have shaped modern African genomes over the past **100,000 years**.
1046 1046  
1047 1047  3. **Other Significant Data Points:**
1048 - - **Adjusted Odds Ratios (aORs) for key outcomes:**
1049 - - **Low birthweight (LBW):** WMBF (1.21), BMWF (1.75), Black mother–Black father (BMBF) (2.08).
1050 - - **Preterm births (PTB):** WMBF (1.17), BMWF (1.37), BMBF (1.78).
1051 - - **Stillbirths:** WMBF (1.43), BMWF (1.51), BMBF (1.85).
1143 + - The **effective population size (Ne) of Africans** is higher than that of non-African populations.
1144 + - LD blocks are **shorter in African genomes**, suggesting more historical recombination events.
1052 1052  
1053 -----
1146 +---
1054 1054  
1055 -## **Findings**##
1056 -
1148 +## **Findings**
1057 1057  1. **Primary Observations:**
1058 - - **Biracial couples face a gradient of risk**: higher than White couples but lower than Black couples.
1059 - - **Maternal race plays a more significant role** in pregnancy outcomes.
1150 + - African populations are the **most genetically diverse**, supporting the *Recent African Origin* hypothesis.
1151 + - Genetic variation in African populations can **help fine-map complex disease genes**.
1060 1060  
1061 1061  2. **Subgroup Trends:**
1062 - - **Black mothers (regardless of paternal race) had the highest risk of LBW and PTB**.
1063 - - **White mothers with Black fathers had a lower risk** than Black mothers with White fathers.
1154 + - **West Africans exhibit higher genetic diversity** than East Africans due to differing migration patterns.
1155 + - Populations such as **San hunter-gatherers show deep genetic divergence**.
1064 1064  
1065 1065  3. **Specific Case Analysis:**
1066 - - The **weathering hypothesis** suggests that **long-term stress exposure** contributes to higher adverse birth risks in Black mothers.
1067 - - **Genetic and environmental factors** may interact to influence birth outcomes.
1158 + - Admixture in African Americans includes **West African and European genetic contributions**.
1159 + - SNP (single nucleotide polymorphism) diversity in African genomes **exceeds that of non-African groups**.
1068 1068  
1069 -----
1161 +---
1070 1070  
1071 -## **Critique and Observations**##
1072 -
1163 +## **Critique and Observations**
1073 1073  1. **Strengths of the Study:**
1074 - - **Largest meta-analysis** on racial disparities in birth outcomes.
1075 - - Uses **adjusted statistical models** to account for confounding variables.
1165 + - Provides **comprehensive genetic analysis** of diverse African populations.
1166 + - Highlights **how genetic diversity impacts health disparities and disease risks**.
1076 1076  
1077 1077  2. **Limitations of the Study:**
1078 - - Data limited to **Black-White biracial couples**, excluding other racial groups.
1079 - - **Socioeconomic and healthcare access factors** not fully explored.
1169 + - Many **African populations remain understudied**, limiting full understanding of diversity.
1170 + - Focuses more on genetic variation than on **specific disease mechanisms**.
1080 1080  
1081 1081  3. **Suggestions for Improvement:**
1082 - - Future studies should examine **Asian, Hispanic, and Indigenous biracial couples**.
1083 - - Investigate **long-term health effects on infants from biracial pregnancies**.
1173 + - Expand research into **underrepresented African populations**.
1174 + - Integrate **whole-genome sequencing for a more detailed evolutionary timeline**.
1084 1084  
1085 -----
1176 +---
1086 1086  
1087 1087  ## **Relevance to Subproject**
1088 -- Provides **critical insights into racial disparities** in maternal and infant health.
1089 -- Supports **research on genetic and environmental influences on neonatal health**.
1090 -- Highlights **how maternal race plays a more significant role than paternal race** in birth outcomes.##
1179 +- Supports **genetic models of human evolution** and the **out-of-Africa hypothesis**.
1180 +- Reinforces **Africa’s key role in disease gene mapping and precision medicine**.
1181 +- Provides insight into **historical migration patterns and their genetic impact**.
1091 1091  
1092 -----
1183 +---
1093 1093  
1094 -## **Suggestions for Further Exploration**##
1185 +## **Suggestions for Further Exploration**
1186 +1. Investigate **genetic adaptations to local environments within Africa**.
1187 +2. Study **the role of African genetic diversity in disease resistance**.
1188 +3. Expand research on **how ancient migration patterns shaped modern genetic structure**.
1095 1095  
1096 -1. Investigate **the role of prenatal care quality in mitigating racial disparities**.
1097 -2. Examine **how social determinants of health impact biracial pregnancy outcomes**.
1098 -3. Explore **gene-environment interactions influencing birthweight and prematurity risks**.
1190 +---
1099 1099  
1100 -----
1101 -
1102 1102  ## **Summary of Research Study**
1103 -This meta-analysis examines **the impact of biracial parentage on birth outcomes**, showing that **biracial couples face a higher risk of adverse pregnancy outcomes than White couples but lower than Black couples**. The findings emphasize **maternal race as a key factor in birth risks**, with **Black mothers having the highest rates of preterm birth and low birthweight, regardless of paternal race**.##
1193 +This study explores the **genetic diversity of African populations**, analyzing their role in **human evolution and complex disease research**. The findings highlight **Africa’s unique genetic landscape**, confirming it as the most genetically diverse continent. The research provides valuable insights into **how genetic variation influences disease susceptibility, evolution, and population structure**.
1104 1104  
1105 -----
1195 +This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1106 1106  
1197 +---
1198 +
1107 1107  ## **📄 Download Full Study**
1108 -[[Download Full Study>>attach:10.1111_j.1600-0412.2012.01501.xAbstract.pdf]]##
1200 +[[Download Full Study>>attach:10.1038_nrg865MODERN.pdf]]
1201 +
1109 1109  {{/expand}}
1110 1110  
1204 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1111 1111  
1112 -== Study: One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness ==
1113 1113  
1114 -{{expand expanded="false" title="Study: One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness"}}
1115 -**Source:** *Current Psychology*
1116 -**Date of Publication:** *2024*
1117 -**Author(s):** *Brandon Sparks, Alexandra M. Zidenberg, Mark E. Olver*
1118 -**Title:** *"One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness"*
1119 -**DOI:** [10.1007/s12144-023-04275-z](https://doi.org/10.1007/s12144-023-04275-z)
1120 -**Subject Matter:** *Psychology, Mental Health, Social Isolation* 
1121 1121  
1122 -----
1208 +{{expand title="Study: Racial Bias in Pain Assessment and Treatment Recommendations" expanded="false"}}
1209 +**Source:** *Proceedings of the National Academy of Sciences (PNAS)*
1210 +**Date of Publication:** *2016*
1211 +**Author(s):** *Kelly M. Hoffman, Sophie Trawalter, Jordan R. Axta, M. Norman Oliver*
1212 +**Title:** *"Racial Bias in Pain Assessment and Treatment Recommendations, and False Beliefs About Biological Differences Between Blacks and Whites"*
1213 +**DOI:** [10.1073/pnas.1516047113](https://doi.org/10.1073/pnas.1516047113)
1214 +**Subject Matter:** *Health Disparities, Racial Bias, Medical Treatment*
1123 1123  
1124 -## **Key Statistics**##
1216 +---
1125 1125  
1218 +## **Key Statistics**
1126 1126  1. **General Observations:**
1127 - - Study analyzed **67 self-identified incels** and **103 non-incel men**.
1128 - - Incels reported **higher loneliness and lower social support** compared to non-incels.
1220 + - Study analyzed **racial disparities in pain perception and treatment recommendations**.
1221 + - Found that **white laypeople and medical students endorsed false beliefs about biological differences** between Black and white individuals.
1129 1129  
1130 1130  2. **Subgroup Analysis:**
1131 - - Incels exhibited **higher levels of depression, anxiety, and self-critical rumination**.
1132 - - **Social isolation was a key factor** differentiating incels from non-incels.
1224 + - **50% of medical students surveyed endorsed at least one false belief about biological differences**.
1225 + - Participants who held these false beliefs were **more likely to underestimate Black patients pain levels**.
1133 1133  
1134 1134  3. **Other Significant Data Points:**
1135 - - 95% of incels in the study reported **having depression**, with 38% receiving a formal diagnosis.
1136 - - **Higher externalization of blame** was linked to stronger incel identification.
1228 + - **Black patients were less likely to receive appropriate pain treatment** compared to white patients.
1229 + - The study confirmed that **historical misconceptions about racial differences still persist in modern medicine**.
1137 1137  
1138 -----
1231 +---
1139 1139  
1140 -## **Findings**##
1141 -
1233 +## **Findings**
1142 1142  1. **Primary Observations:**
1143 - - Incels experience **heightened rejection sensitivity and loneliness**.
1144 - - Lack of social support correlates with **worse mental health outcomes**.
1235 + - False beliefs about biological racial differences **correlate with racial disparities in pain treatment**.
1236 + - Medical students and residents who endorsed these beliefs **showed greater racial bias in treatment recommendations**.
1145 1145  
1146 1146  2. **Subgroup Trends:**
1147 - - **Avoidant attachment styles** were a strong predictor of incel identity.
1148 - - **Mate value perceptions** significantly differed between incels and non-incels.
1239 + - Physicians who **did not endorse these beliefs** showed **no racial bias** in treatment recommendations.
1240 + - Bias was **strongest among first-year medical students** and decreased slightly in later years of training.
1149 1149  
1150 1150  3. **Specific Case Analysis:**
1151 - - Incels **engaged in fewer positive coping mechanisms** such as emotional support or positive reframing.
1152 - - Instead, they relied on **solitary coping strategies**, worsening their isolation.
1243 + - Study participants **underestimated Black patients' pain and recommended less effective pain treatments**.
1244 + - The study suggests that **racial disparities in medical care stem, in part, from these enduring false beliefs**.
1153 1153  
1154 -----
1246 +---
1155 1155  
1156 -## **Critique and Observations**##
1157 -
1248 +## **Critique and Observations**
1158 1158  1. **Strengths of the Study:**
1159 - - **First quantitative study** on incels social isolation and mental health.
1160 - - **Robust sample size** and validated psychological measures.
1250 + - **First empirical study to connect false racial beliefs with medical decision-making**.
1251 + - Utilizes a **large sample of medical students and residents** from diverse institutions.
1161 1161  
1162 1162  2. **Limitations of the Study:**
1163 - - Sample drawn from **Reddit communities**, which may not represent all incels.
1164 - - **No causal conclusions**—correlations between isolation and inceldom need further research.
1254 + - The study focuses on **Black vs. white disparities**, leaving other racial/ethnic groups unexplored.
1255 + - Participants' responses were based on **hypothetical medical cases, not real-world treatment decisions**.
1165 1165  
1166 1166  3. **Suggestions for Improvement:**
1167 - - Future studies should **compare incel forum users vs. non-users**.
1168 - - Investigate **potential intervention strategies** for social integration.
1258 + - Future research should examine **how these biases manifest in real clinical settings**.
1259 + - Investigate **whether medical training can correct these biases over time**.
1169 1169  
1170 -----
1261 +---
1171 1171  
1172 1172  ## **Relevance to Subproject**
1173 -- Highlights **mental health vulnerabilities** within the incel community.
1174 -- Supports research on **loneliness, attachment styles, and social dominance orientation**.
1175 -- Examines how **peer rejection influences self-perceived mate value**.##
1264 +- Highlights **racial disparities in healthcare**, specifically in pain assessment and treatment.
1265 +- Supports **research on implicit bias and its impact on medical outcomes**.
1266 +- Provides evidence for **the need to address racial bias in medical education**.
1176 1176  
1177 -----
1268 +---
1178 1178  
1179 -## **Suggestions for Further Exploration**##
1270 +## **Suggestions for Further Exploration**
1271 +1. Investigate **interventions to reduce racial bias in medical decision-making**.
1272 +2. Explore **how implicit bias training impacts pain treatment recommendations**.
1273 +3. Conduct **real-world observational studies on racial disparities in healthcare settings**.
1180 1180  
1181 -1. Explore how **online community participation** affects incel mental health.
1182 -2. Investigate **cognitive biases** influencing self-perceived rejection among incels.
1183 -3. Assess **therapeutic interventions** to address incel social isolation.
1275 +---
1184 1184  
1185 -----
1186 -
1187 1187  ## **Summary of Research Study**
1188 -This study examines the **psychological characteristics of self-identified incels**, comparing them with non-incel men in terms of **mental health, loneliness, and coping strategies**. The research found **higher depression, anxiety, and avoidant attachment styles among incels**, as well as **greater reliance on solitary coping mechanisms**. It suggests that **lack of social support plays a critical role in exacerbating incel identity and related mental health concerns**.##
1278 +This study examines **racial bias in pain perception and treatment** among **white laypeople and medical professionals**, demonstrating that **false beliefs about biological differences contribute to disparities in pain management**. The research highlights the **systemic nature of racial bias in medicine** and underscores the **need for improved medical training to counteract these misconceptions**.
1189 1189  
1190 1190  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1191 1191  
1192 -----
1282 +---
1193 1193  
1194 1194  ## **📄 Download Full Study**
1195 -[[Download Full Study>>attach:10.1007_s12144-023-04275-z.pdf]]##
1285 +[[Download Full Study>>attach:10.1073_pnas.1516047113.pdf]]
1286 +
1196 1196  {{/expand}}
1197 1197  
1289 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1198 1198  
1199 -= Crime and Substance Abuse =
1200 1200  
1292 +{{expand title="Study: Rising Morbidity and Mortality in Midlife Among White Non-Hispanic Americans" expanded="false"}}
1293 +**Source:** *Proceedings of the National Academy of Sciences (PNAS)*
1294 +**Date of Publication:** *2015*
1295 +**Author(s):** *Anne Case, Angus Deaton*
1296 +**Title:** *"Rising Morbidity and Mortality in Midlife Among White Non-Hispanic Americans in the 21st Century"*
1297 +**DOI:** [10.1073/pnas.1518393112](https://doi.org/10.1073/pnas.1518393112)
1298 +**Subject Matter:** *Public Health, Mortality, Socioeconomic Factors*
1201 1201  
1202 -== Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program ==
1300 +---
1203 1203  
1204 -{{expand expanded="false" title="Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program"}}
1205 -**Source:** *Substance Use & Misuse*
1206 -**Date of Publication:** *2002*
1207 -**Author(s):** *Clifford A. Butzin, Christine A. Saum, Frank R. Scarpitti*
1208 -**Title:** *"Factors Associated with Completion of a Drug Treatment Court Diversion Program"*
1209 -**DOI:** [10.1081/JA-120014424](https://doi.org/10.1081/JA-120014424)
1210 -**Subject Matter:** *Substance Use, Criminal Justice, Drug Courts* 
1211 -
1212 -----
1213 -
1214 -## **Key Statistics**##
1215 -
1302 +## **Key Statistics**
1216 1216  1. **General Observations:**
1217 - - Study examined **drug treatment court success rates** among first-time offenders.
1218 - - Strongest predictors of **successful completion were employment status and race**.
1304 + - Mortality rates among **middle-aged white non-Hispanic Americans (ages 45–54)** increased from 1999 to 2013.
1305 + - This reversal in mortality trends is unique to the U.S.; **no other wealthy country experienced a similar rise**.
1219 1219  
1220 1220  2. **Subgroup Analysis:**
1221 - - Individuals with **stable jobs were more likely to complete the program**.
1222 - - **Black participants had lower success rates**, suggesting potential systemic disparities.
1308 + - The increase was **most pronounced among those with a high school education or less**.
1309 + - Hispanic and Black non-Hispanic mortality continued to decline over the same period.
1223 1223  
1224 1224  3. **Other Significant Data Points:**
1225 - - **Education level was positively correlated** with program completion.
1226 - - Frequency of **drug use before enrollment affected treatment outcomes**.
1312 + - Rising mortality was driven primarily by **suicide, drug and alcohol poisoning, and chronic liver disease**.
1313 + - Midlife morbidity increased as well, with more reports of **poor health, pain, and mental distress**.
1227 1227  
1228 -----
1315 +---
1229 1229  
1230 -## **Findings**##
1231 -
1317 +## **Findings**
1232 1232  1. **Primary Observations:**
1233 - - **Social stability factors** (employment, education) were key to treatment success.
1234 - - **Race and pre-existing substance use patterns** influenced completion rates.
1319 + - The rise in mortality is attributed to **substance abuse, economic distress, and deteriorating mental health**.
1320 + - The increase in **suicides and opioid overdoses parallels broader socioeconomic decline**.
1235 1235  
1236 1236  2. **Subgroup Trends:**
1237 - - White offenders had **higher completion rates** than Black offenders.
1238 - - Drug court success was **higher for those with lower initial drug use frequency**.
1323 + - The **largest mortality increases** occurred among **whites without a college degree**.
1324 + - Chronic pain, functional limitations, and self-reported mental distress **rose significantly in affected groups**.
1239 1239  
1240 1240  3. **Specific Case Analysis:**
1241 - - **Individuals with strong social ties were more likely to finish the program**.
1242 - - Success rates were **significantly higher for participants with case management support**.
1327 + - **Educational attainment was a major predictor of mortality trends**, with better-educated individuals experiencing lower mortality rates.
1328 + - Mortality among **white Americans with a college degree continued to decline**, resembling trends in other wealthy nations.
1243 1243  
1244 -----
1330 +---
1245 1245  
1246 -## **Critique and Observations**##
1247 -
1332 +## **Critique and Observations**
1248 1248  1. **Strengths of the Study:**
1249 - - **First empirical study on drug court program success factors**.
1250 - - Uses **longitudinal data** for post-treatment analysis.
1334 + - **First major study to highlight rising midlife mortality among U.S. whites**.
1335 + - Uses **CDC and Census mortality data spanning over a decade**.
1251 1251  
1252 1252  2. **Limitations of the Study:**
1253 - - Lacks **qualitative data on personal motivation and treatment engagement**.
1254 - - Focuses on **short-term program success** without tracking **long-term relapse rates**.
1338 + - Does not establish **causality** between economic decline and increased mortality.
1339 + - Lacks **granular data on opioid prescribing patterns and regional differences**.
1255 1255  
1256 1256  3. **Suggestions for Improvement:**
1257 - - Future research should examine **racial disparities in drug court outcomes**.
1258 - - Study **how community resources impact long-term recovery**.
1342 + - Future studies should explore **how economic shifts, healthcare access, and mental health treatment contribute to these trends**.
1343 + - Further research on **racial and socioeconomic disparities in mortality trends** is needed.
1259 1259  
1260 -----
1345 +---
1261 1261  
1262 1262  ## **Relevance to Subproject**
1263 -- Provides insight into **what factors contribute to drug court program success**.
1264 -- Highlights **racial disparities in criminal justice-based rehabilitation programs**.
1265 -- Supports **policy discussions on improving access to drug treatment for marginalized groups**.##
1348 +- Highlights **socioeconomic and racial disparities** in health outcomes.
1349 +- Supports research on **substance abuse and mental health crises in the U.S.**.
1350 +- Provides evidence for **the role of economic instability in public health trends**.
1266 1266  
1267 -----
1352 +---
1268 1268  
1269 -## **Suggestions for Further Exploration**##
1354 +## **Suggestions for Further Exploration**
1355 +1. Investigate **regional differences in rising midlife mortality**.
1356 +2. Examine the **impact of the opioid crisis on long-term health trends**.
1357 +3. Study **policy interventions aimed at reversing rising mortality rates**.
1270 1270  
1271 -1. Investigate **the role of mental health in drug court success rates**.
1272 -2. Assess **long-term relapse prevention strategies post-treatment**.
1273 -3. Explore **alternative diversion programs beyond traditional drug courts**.
1359 +---
1274 1274  
1275 -----
1276 -
1277 1277  ## **Summary of Research Study**
1278 -This study examines **factors influencing the completion of drug treatment court programs**, identifying **employment, education, and race as key predictors**. The research underscores **systemic disparities in drug court outcomes**, emphasizing the need for **improved support systems for at-risk populations**.##
1362 +This study documents a **reversal in mortality trends among middle-aged white non-Hispanic Americans**, showing an increase in **suicide, drug overdoses, and alcohol-related deaths** from 1999 to 2013. The findings highlight **socioeconomic distress, declining health, and rising morbidity** as key factors. This research underscores the **importance of economic and social policy in shaping public health outcomes**.
1279 1279  
1280 1280  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1281 1281  
1282 -----
1366 +---
1283 1283  
1284 1284  ## **📄 Download Full Study**
1285 -[[Download Full Study>>attach:10.1081_JA-120014424.pdf]]##
1369 +[[Download Full Study>>attach:10.1073_pnas.1518393112.pdf]]
1370 +
1286 1286  {{/expand}}
1287 1287  
1373 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1288 1288  
1289 -== Study: Cross-Cultural Sources of Measurement Error in Substance Use Surveys ==
1375 +{{expand title="Study: How Do People Without Migration Background Experience and Impact Today’s Superdiverse Cities?" expanded="false"}}
1376 +**Source:** *Journal of Ethnic and Migration Studies*
1377 +**Date of Publication:** *2023*
1378 +**Author(s):** *Maurice Crul, Frans Lelie, Elif Keskiner, Laure Michon, Ismintha Waldring*
1379 +**Title:** *"How Do People Without Migration Background Experience and Impact Today’s Superdiverse Cities?"*
1380 +**DOI:** [10.1080/1369183X.2023.2182548](https://doi.org/10.1080/1369183X.2023.2182548)
1381 +**Subject Matter:** *Urban Sociology, Migration Studies, Integration*
1290 1290  
1291 -{{expand expanded="false" title="Study: Cross-Cultural Sources of Measurement Error in Substance Use Surveys"}}
1292 -**Source:** *Substance Use & Misuse*
1293 -**Date of Publication:** *2003*
1294 -**Author(s):** *Timothy P. Johnson, Phillip J. Bowman*
1295 -**Title:** *"Cross-Cultural Sources of Measurement Error in Substance Use Surveys"*
1296 -**DOI:** [10.1081/JA-120023394](https://doi.org/10.1081/JA-120023394)
1297 -**Subject Matter:** *Survey Methodology, Racial Disparities, Substance Use Research* 
1383 +---
1298 1298  
1299 -----
1300 -
1301 -## **Key Statistics**##
1302 -
1385 +## **Key Statistics**
1303 1303  1. **General Observations:**
1304 - - Study examined **how racial and cultural factors influence self-reported substance use data**.
1305 - - Analyzed **36 empirical studies from 1977–2003** on survey reliability across racial/ethnic groups.
1387 + - Study examines the role of **people without migration background** in majority-minority cities.
1388 + - Analyzes **over 3,000 survey responses and 150 in-depth interviews** from six North-Western European cities.
1306 1306  
1307 1307  2. **Subgroup Analysis:**
1308 - - Black and Latino respondents **were more likely to underreport drug use** compared to White respondents.
1309 - - **Cultural stigma and distrust in research institutions** affected self-report accuracy.
1391 + - Explores differences in **integration, social interactions, and perceptions of diversity**.
1392 + - Studies how **class, education, and neighborhood composition** affect adaptation to urban diversity.
1310 1310  
1311 1311  3. **Other Significant Data Points:**
1312 - - **Surveys using biological validation (urinalysis, hair tests) revealed underreporting trends**.
1313 - - **Higher recantation rates** (denying past drug use) were observed among minority respondents.
1395 + - The study introduces the **Becoming a Minority (BaM) project**, a large-scale investigation of urban demographic shifts.
1396 + - **People without migration background perceive diversity differently**, with some embracing and others resisting change.
1314 1314  
1315 -----
1398 +---
1316 1316  
1317 -## **Findings**##
1318 -
1400 +## **Findings**
1319 1319  1. **Primary Observations:**
1320 - - Racial/ethnic disparities in **substance use reporting bias survey-based research**.
1321 - - **Social desirability and cultural norms impact data reliability**.
1402 + - The study **challenges traditional integration theories**, arguing that non-migrant groups also undergo adaptation processes.
1403 + - Some residents **struggle with demographic changes**, while others see diversity as an asset.
1322 1322  
1323 -2. **Subgroup Trends:**
1324 - - White respondents were **more likely to overreport** substance use.
1325 - - Black and Latino respondents **had higher recantation rates**, particularly in face-to-face interviews.
1405 +2. **Subgroup Trends:**
1406 + - Young, educated individuals in urban areas **are more open to cultural diversity**.
1407 + - Older and less mobile residents **report feelings of displacement and social isolation**.
1326 1326  
1327 -3. **Specific Case Analysis:**
1328 - - Mode of survey administration **significantly influenced reporting accuracy**.
1329 - - **Self-administered surveys produced more reliable data than interviewer-administered surveys**.
1409 +3. **Specific Case Analysis:**
1410 + - Examines how **people without migration background navigate majority-minority settings** in cities like Amsterdam and Vienna.
1411 + - Analyzes **whether former ethnic majority groups now perceive themselves as minorities**.
1330 1330  
1331 -----
1413 +---
1332 1332  
1333 -## **Critique and Observations**##
1415 +## **Critique and Observations**
1416 +1. **Strengths of the Study:**
1417 + - **Innovative approach** by examining the impact of migration on native populations.
1418 + - Uses **both qualitative and quantitative data** for robust analysis.
1334 1334  
1335 -1. **Strengths of the Study:**
1336 - - **Comprehensive review of 36 studies** on measurement error in substance use reporting.
1337 - - Identifies **systemic biases affecting racial/ethnic survey reliability**.
1420 +2. **Limitations of the Study:**
1421 + - Limited to **Western European urban settings**, missing perspectives from other global regions.
1422 + - Does not fully explore **policy interventions for fostering social cohesion**.
1338 1338  
1339 -2. **Limitations of the Study:**
1340 - - Relies on **secondary data analysis**, limiting direct experimental control.
1341 - - Does not explore **how measurement error impacts policy decisions**.
1424 +3. **Suggestions for Improvement:**
1425 + - Expand research to **other geographical contexts** to understand migration effects globally.
1426 + - Investigate **long-term trends in urban adaptation and community building**.
1342 1342  
1343 -3. **Suggestions for Improvement:**
1344 - - Future research should **incorporate mixed-method approaches** (qualitative & quantitative).
1345 - - Investigate **how survey design can reduce racial reporting disparities**.
1428 +---
1346 1346  
1347 -----
1348 -
1349 1349  ## **Relevance to Subproject**
1350 -- Supports research on **racial disparities in self-reported health behaviors**.
1351 -- Highlights **survey methodology issues that impact substance use epidemiology**.
1352 -- Provides insights for **improving data accuracy in public health research**.##
1431 +- Provides a **new perspective on urban integration**, shifting focus from migrants to native-born populations.
1432 +- Highlights the **role of social and economic power in shaping urban diversity outcomes**.
1433 +- Challenges existing **assimilation theories by showing bidirectional adaptation in diverse cities**.
1353 1353  
1354 -----
1435 +---
1355 1355  
1356 -## **Suggestions for Further Exploration**##
1437 +## **Suggestions for Further Exploration**
1438 +1. Study how **local policies shape attitudes toward urban diversity**.
1439 +2. Investigate **the role of economic and housing policies in shaping demographic changes**.
1440 +3. Explore **how social networks influence perceptions of migration and diversity**.
1357 1357  
1358 -1. Investigate **how survey design impacts racial disparities in self-reported health data**.
1359 -2. Study **alternative data collection methods (biometric validation, passive data tracking)**.
1360 -3. Explore **the role of social stigma in self-reported health behaviors**.
1442 +---
1361 1361  
1362 -----
1363 -
1364 1364  ## **Summary of Research Study**
1365 -This study examines **cross-cultural biases in self-reported substance use surveys**, showing that **racial/ethnic minorities are more likely to underreport drug use** due to **social stigma, research distrust, and survey administration methods**. The findings highlight **critical issues in public health data collection and the need for improved survey design**.##
1445 +This study examines how **people without migration background experience demographic change in majority-minority cities**. Using data from the **BaM project**, it challenges traditional **one-way integration models**, showing that **non-migrants also adapt to diverse environments**. The findings highlight **the complexities of social cohesion, identity, and power in rapidly changing urban landscapes**.
1366 1366  
1367 1367  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1368 1368  
1369 -----
1449 +---
1370 1370  
1371 1371  ## **📄 Download Full Study**
1372 -[[Download Full Study>>attach:10.1081_JA-120023394.pdf]]##
1452 +[[Download Full Study>>attach:10.1080_1369183X.2023.2182548.pdf]]
1453 +
1373 1373  {{/expand}}
1374 1374  
1456 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1375 1375  
1376 -== Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program ==
1377 -
1378 -{{expand expanded="false" title="Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program"}}
1458 +{{expand title="Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program" expanded="false"}}
1379 1379  **Source:** *Substance Use & Misuse*
1380 1380  **Date of Publication:** *2002*
1381 1381  **Author(s):** *Clifford A. Butzin, Christine A. Saum, Frank R. Scarpitti*
1382 1382  **Title:** *"Factors Associated with Completion of a Drug Treatment Court Diversion Program"*
1383 1383  **DOI:** [10.1081/JA-120014424](https://doi.org/10.1081/JA-120014424)
1384 -**Subject Matter:** *Substance Use, Criminal Justice, Drug Courts* 
1464 +**Subject Matter:** *Substance Use, Criminal Justice, Drug Courts*
1385 1385  
1386 -----
1466 +---
1387 1387  
1388 -## **Key Statistics**##
1389 -
1468 +## **Key Statistics**
1390 1390  1. **General Observations:**
1391 1391   - Study examined **drug treatment court success rates** among first-time offenders.
1392 1392   - Strongest predictors of **successful completion were employment status and race**.
... ... @@ -1399,10 +1399,9 @@
1399 1399   - **Education level was positively correlated** with program completion.
1400 1400   - Frequency of **drug use before enrollment affected treatment outcomes**.
1401 1401  
1402 -----
1481 +---
1403 1403  
1404 -## **Findings**##
1405 -
1483 +## **Findings**
1406 1406  1. **Primary Observations:**
1407 1407   - **Social stability factors** (employment, education) were key to treatment success.
1408 1408   - **Race and pre-existing substance use patterns** influenced completion rates.
... ... @@ -1415,10 +1415,9 @@
1415 1415   - **Individuals with strong social ties were more likely to finish the program**.
1416 1416   - Success rates were **significantly higher for participants with case management support**.
1417 1417  
1418 -----
1496 +---
1419 1419  
1420 -## **Critique and Observations**##
1421 -
1498 +## **Critique and Observations**
1422 1422  1. **Strengths of the Study:**
1423 1423   - **First empirical study on drug court program success factors**.
1424 1424   - Uses **longitudinal data** for post-treatment analysis.
... ... @@ -1431,641 +1431,625 @@
1431 1431   - Future research should examine **racial disparities in drug court outcomes**.
1432 1432   - Study **how community resources impact long-term recovery**.
1433 1433  
1434 -----
1511 +---
1435 1435  
1436 1436  ## **Relevance to Subproject**
1437 1437  - Provides insight into **what factors contribute to drug court program success**.
1438 1438  - Highlights **racial disparities in criminal justice-based rehabilitation programs**.
1439 -- Supports **policy discussions on improving access to drug treatment for marginalized groups**.##
1516 +- Supports **policy discussions on improving access to drug treatment for marginalized groups**.
1440 1440  
1441 -----
1518 +---
1442 1442  
1443 -## **Suggestions for Further Exploration**##
1444 -
1520 +## **Suggestions for Further Exploration**
1445 1445  1. Investigate **the role of mental health in drug court success rates**.
1446 1446  2. Assess **long-term relapse prevention strategies post-treatment**.
1447 1447  3. Explore **alternative diversion programs beyond traditional drug courts**.
1448 1448  
1449 -----
1525 +---
1450 1450  
1451 1451  ## **Summary of Research Study**
1452 -This study examines **factors influencing the completion of drug treatment court programs**, identifying **employment, education, and race as key predictors**. The research underscores **systemic disparities in drug court outcomes**, emphasizing the need for **improved support systems for at-risk populations**.##
1528 +This study examines **factors influencing the completion of drug treatment court programs**, identifying **employment, education, and race as key predictors**. The research underscores **systemic disparities in drug court outcomes**, emphasizing the need for **improved support systems for at-risk populations**.
1453 1453  
1454 1454  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1455 1455  
1456 -----
1532 +---
1457 1457  
1458 1458  ## **📄 Download Full Study**
1459 -[[Download Full Study>>attach:10.1081_JA-120014424.pdf]]##
1535 +[[Download Full Study>>attach:10.1081_JA-120014424.pdf]]
1536 +
1460 1460  {{/expand}}
1461 1461  
1539 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1462 1462  
1463 -== Study: Associations Between Cannabis Use and Mental Health Symptoms in Young Adults ==
1464 1464  
1465 -{{expand expanded="false" title="Study: Associations Between Cannabis Use and Mental Health Symptoms in Young Adults"}}
1466 - Source: Addictive Behaviors
1467 -Date of Publication: 2016
1468 -Author(s): Andrea Hussong, Christy Capron, Gregory T. Smith, Jennifer L. Maggs
1469 -Title: "Associations Between Cannabis Use and Mental Health Symptoms in Young Adults"
1470 -DOI: 10.1016/j.addbeh.2016.02.030
1471 -Subject Matter: Substance Use, Mental Health, Adolescent Development
1542 +{{expand title="Study: Cross-Cultural Sources of Measurement Error in Substance Use Surveys" expanded="false"}}
1543 +**Source:** *Substance Use & Misuse*
1544 +**Date of Publication:** *2003*
1545 +**Author(s):** *Timothy P. Johnson, Phillip J. Bowman*
1546 +**Title:** *"Cross-Cultural Sources of Measurement Error in Substance Use Surveys"*
1547 +**DOI:** [10.1081/JA-120023394](https://doi.org/10.1081/JA-120023394)
1548 +**Subject Matter:** *Survey Methodology, Racial Disparities, Substance Use Research*
1472 1472  
1473 -Key Statistics
1474 -General Observations:
1550 +---
1475 1475  
1476 -Study examined cannabis use trends in young adults over time.
1477 -Found significant correlations between cannabis use and increased depressive symptoms.
1478 -Subgroup Analysis:
1552 +## **Key Statistics**
1553 +1. **General Observations:**
1554 + - Study examined **how racial and cultural factors influence self-reported substance use data**.
1555 + - Analyzed **36 empirical studies from 1977–2003** on survey reliability across racial/ethnic groups.
1479 1479  
1480 -Males exhibited higher rates of cannabis use, but females reported stronger mental health impacts.
1481 -Individuals with pre-existing anxiety disorders were more likely to report problematic cannabis use.
1482 -Other Significant Data Points:
1557 +2. **Subgroup Analysis:**
1558 + - Black and Latino respondents **were more likely to underreport drug use** compared to White respondents.
1559 + - **Cultural stigma and distrust in research institutions** affected self-report accuracy.
1483 1483  
1484 -Frequent cannabis users showed a 23% higher likelihood of developing anxiety symptoms.
1485 -Co-occurring substance use (e.g., alcohol) exacerbated negative psychological effects.
1486 -Findings
1487 -Primary Observations:
1561 +3. **Other Significant Data Points:**
1562 + - **Surveys using biological validation (urinalysis, hair tests) revealed underreporting trends**.
1563 + - **Higher recantation rates** (denying past drug use) were observed among minority respondents.
1488 1488  
1489 -Cannabis use was linked to higher depressive and anxiety symptoms, particularly in frequent users.
1490 -Self-medication patterns emerged among those with pre-existing mental health conditions.
1491 -Subgroup Trends:
1565 +---
1492 1492  
1493 -Early cannabis initiation (before age 16) was associated with greater mental health risks.
1494 -College-aged users reported more impairments in daily functioning due to cannabis use.
1495 -Specific Case Analysis:
1567 +## **Findings**
1568 +1. **Primary Observations:**
1569 + - Racial/ethnic disparities in **substance use reporting bias survey-based research**.
1570 + - **Social desirability and cultural norms impact data reliability**.
1496 1496  
1497 -Participants with a history of childhood trauma were twice as likely to develop problematic cannabis use.
1498 -Co-use of cannabis and alcohol significantly increased impulsivity scores in the study sample.
1499 -Critique and Observations
1500 -Strengths of the Study:
1572 +2. **Subgroup Trends:**
1573 + - White respondents were **more likely to overreport** substance use.
1574 + - Black and Latino respondents **had higher recantation rates**, particularly in face-to-face interviews.
1501 1501  
1502 -Large, longitudinal dataset with a diverse sample of young adults.
1503 -Controlled for confounding variables like socioeconomic status and prior substance use.
1504 -Limitations of the Study:
1576 +3. **Specific Case Analysis:**
1577 + - Mode of survey administration **significantly influenced reporting accuracy**.
1578 + - **Self-administered surveys produced more reliable data than interviewer-administered surveys**.
1505 1505  
1506 -Self-reported cannabis use may introduce bias in reported frequency and effects.
1507 -Did not assess specific THC potency levels, which could influence mental health outcomes.
1508 -Suggestions for Improvement:
1580 +---
1509 1509  
1510 -Future research should investigate dose-dependent effects of cannabis on mental health.
1511 -Assess long-term psychological outcomes of early cannabis exposure.
1512 -Relevance to Subproject
1513 -Supports mental health risk assessment models related to substance use.
1514 -Highlights gender differences in substance-related psychological impacts.
1515 -Provides insight into self-medication behaviors among young adults.
1516 -Suggestions for Further Exploration
1517 -Investigate the long-term impact of cannabis use on neurodevelopment.
1518 -Examine the role of genetic predisposition in cannabis-related mental health risks.
1519 -Assess regional differences in cannabis use trends post-legalization.
1520 -Summary of Research Study
1521 -This study examines the relationship between cannabis use and mental health symptoms in young adults, focusing on depressive and anxiety-related outcomes. Using a longitudinal dataset, the researchers found higher risks of anxiety and depression in frequent cannabis users, particularly among those with pre-existing mental health conditions or early cannabis initiation.
1582 +## **Critique and Observations**
1583 +1. **Strengths of the Study:**
1584 + - **Comprehensive review of 36 studies** on measurement error in substance use reporting.
1585 + - Identifies **systemic biases affecting racial/ethnic survey reliability**.
1522 1522  
1587 +2. **Limitations of the Study:**
1588 + - Relies on **secondary data analysis**, limiting direct experimental control.
1589 + - Does not explore **how measurement error impacts policy decisions**.
1590 +
1591 +3. **Suggestions for Improvement:**
1592 + - Future research should **incorporate mixed-method approaches** (qualitative & quantitative).
1593 + - Investigate **how survey design can reduce racial reporting disparities**.
1594 +
1595 +---
1596 +
1597 +## **Relevance to Subproject**
1598 +- Supports research on **racial disparities in self-reported health behaviors**.
1599 +- Highlights **survey methodology issues that impact substance use epidemiology**.
1600 +- Provides insights for **improving data accuracy in public health research**.
1601 +
1602 +---
1603 +
1604 +## **Suggestions for Further Exploration**
1605 +1. Investigate **how survey design impacts racial disparities in self-reported health data**.
1606 +2. Study **alternative data collection methods (biometric validation, passive data tracking)**.
1607 +3. Explore **the role of social stigma in self-reported health behaviors**.
1608 +
1609 +---
1610 +
1611 +## **Summary of Research Study**
1612 +This study examines **cross-cultural biases in self-reported substance use surveys**, showing that **racial/ethnic minorities are more likely to underreport drug use** due to **social stigma, research distrust, and survey administration methods**. The findings highlight **critical issues in public health data collection and the need for improved survey design**.
1613 +
1523 1523  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1524 1524  
1525 -📄 Download Full Study
1526 -[[Download Full Study>>attach:10.1016_j.addbeh.2016.02.030.pdf]]
1527 -{{/expand}}
1616 +---
1528 1528  
1618 +## **📄 Download Full Study**
1619 +[[Download Full Study>>attach:10.1081_JA-120023394.pdf]]
1529 1529  
1530 -== Study: Is there a Dysgenic Secular Trend Towards Slowing Simple Reaction Time? ==
1621 +{{/expand}}
1531 1531  
1532 -{{expand expanded="false" title="Study: Is there a Dysgenic Secular Trend Towards Slowing Simple Reaction Time?"}}
1533 -**Source:** *Intelligence (Elsevier)*
1534 -**Date of Publication:** *2014*
1535 -**Author(s):** *Michael A. Woodley, Jan te Nijenhuis, Raegan Murphy*
1536 -**Title:** *"Is there a Dysgenic Secular Trend Towards Slowing Simple Reaction Time?"*
1537 -**DOI:** [10.1016/j.intell.2014.05.012](https://doi.org/10.1016/j.intell.2014.05.012)
1538 -**Subject Matter:** *Cognitive Decline, Intelligence, Dysgenics* 
1623 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1539 1539  
1540 -----
1625 +{{expand title="Study: Cross-Cultural Sources of Measurement Error in Substance Use Surveys" expanded="false"}}
1626 +**Source:** *Substance Use & Misuse*
1627 +**Date of Publication:** *2003*
1628 +**Author(s):** *Timothy P. Johnson, Phillip J. Bowman*
1629 +**Title:** *"Cross-Cultural Sources of Measurement Error in Substance Use Surveys"*
1630 +**DOI:** [10.1081/JA-120023394](https://doi.org/10.1081/JA-120023394)
1631 +**Subject Matter:** *Survey Methodology, Racial Disparities, Substance Use Research*
1541 1541  
1542 -## **Key Statistics**##
1633 +---
1543 1543  
1635 +## **Key Statistics**
1544 1544  1. **General Observations:**
1545 - - The study examines reaction time data from **13 age-matched studies** spanning **1884–2004**.
1546 - - Results suggest an estimated **decline of 13.35 IQ points** over this period.
1637 + - Study examined **how racial and cultural factors influence self-reported substance use data**.
1638 + - Analyzed **36 empirical studies from 1977–2003** on survey reliability across racial/ethnic groups.
1547 1547  
1548 1548  2. **Subgroup Analysis:**
1549 - - The study found **slower reaction times in modern populations** compared to Victorian-era individuals.
1550 - - Data from **Western countries (US, UK, Canada, Australia, Finland)** were analyzed.
1641 + - Black and Latino respondents **were more likely to underreport drug use** compared to White respondents.
1642 + - **Cultural stigma and distrust in research institutions** affected self-report accuracy.
1551 1551  
1552 1552  3. **Other Significant Data Points:**
1553 - - The estimated **dysgenic rate is 1.21 IQ points lost per decade**.
1554 - - Meta-regression analysis confirmed a **steady secular trend in slowing reaction time**.
1645 + - **Surveys using biological validation (urinalysis, hair tests) revealed underreporting trends**.
1646 + - **Higher recantation rates** (denying past drug use) were observed among minority respondents.
1555 1555  
1556 -----
1648 +---
1557 1557  
1558 -## **Findings**##
1559 -
1650 +## **Findings**
1560 1560  1. **Primary Observations:**
1561 - - Supports the hypothesis of **intelligence decline due to genetic and environmental factors**.
1562 - - Reaction time, a **biomarker for cognitive ability**, has slowed significantly over time.
1652 + - Racial/ethnic disparities in **substance use reporting bias survey-based research**.
1653 + - **Social desirability and cultural norms impact data reliability**.
1563 1563  
1564 -2. **Subgroup Trends:**
1565 - - A stronger **correlation between slower reaction time and lower general intelligence (g)**.
1566 - - Flynn effect (IQ gains) does not contradict this finding, as reaction time is a **biological, not environmental, measure**.
1655 +2. **Subgroup Trends:**
1656 + - White respondents were **more likely to overreport** substance use.
1657 + - Black and Latino respondents **had higher recantation rates**, particularly in face-to-face interviews.
1567 1567  
1568 -3. **Specific Case Analysis:**
1569 - - Cross-national comparisons indicate a **global trend in slower reaction times**.
1570 - - Factors like **modern neurotoxin exposure** and **reduced selective pressure for intelligence** may contribute.
1659 +3. **Specific Case Analysis:**
1660 + - Mode of survey administration **significantly influenced reporting accuracy**.
1661 + - **Self-administered surveys produced more reliable data than interviewer-administered surveys**.
1571 1571  
1572 -----
1663 +---
1573 1573  
1574 -## **Critique and Observations**##
1665 +## **Critique and Observations**
1666 +1. **Strengths of the Study:**
1667 + - **Comprehensive review of 36 studies** on measurement error in substance use reporting.
1668 + - Identifies **systemic biases affecting racial/ethnic survey reliability**.
1575 1575  
1576 -1. **Strengths of the Study:**
1577 - - **Comprehensive meta-analysis** covering over a century of reaction time data.
1578 - - **Robust statistical corrections** for measurement variance between historical and modern studies.
1670 +2. **Limitations of the Study:**
1671 + - Relies on **secondary data analysis**, limiting direct experimental control.
1672 + - Does not explore **how measurement error impacts policy decisions**.
1579 1579  
1580 -2. **Limitations of the Study:**
1581 - - Some historical data sources **lack methodological consistency**.
1582 - - **Reaction time measurements vary by study**, requiring adjustments for equipment differences.
1674 +3. **Suggestions for Improvement:**
1675 + - Future research should **incorporate mixed-method approaches** (qualitative & quantitative).
1676 + - Investigate **how survey design can reduce racial reporting disparities**.
1583 1583  
1584 -3. **Suggestions for Improvement:**
1585 - - Future studies should **replicate results with more modern datasets**.
1586 - - Investigate **alternative cognitive biomarkers** for intelligence over time.
1678 +---
1587 1587  
1588 -----
1589 -
1590 1590  ## **Relevance to Subproject**
1591 -- Provides evidence for **long-term intelligence trends**, contributing to research on **cognitive evolution**.
1592 -- Aligns with broader discussions on **dysgenics, neurophysiology, and cognitive load**.
1593 -- Supports the argument that **modern societies may be experiencing intelligence decline**.##
1681 +- Supports research on **racial disparities in self-reported health behaviors**.
1682 +- Highlights **survey methodology issues that impact substance use epidemiology**.
1683 +- Provides insights for **improving data accuracy in public health research**.
1594 1594  
1595 -----
1685 +---
1596 1596  
1597 -## **Suggestions for Further Exploration**##
1687 +## **Suggestions for Further Exploration**
1688 +1. Investigate **how survey design impacts racial disparities in self-reported health data**.
1689 +2. Study **alternative data collection methods (biometric validation, passive data tracking)**.
1690 +3. Explore **the role of social stigma in self-reported health behaviors**.
1598 1598  
1599 -1. Investigate **genetic markers associated with reaction time** and intelligence decline.
1600 -2. Examine **regional variations in reaction time trends**.
1601 -3. Explore **cognitive resilience factors that counteract the decline**.
1692 +---
1602 1602  
1603 -----
1604 -
1605 1605  ## **Summary of Research Study**
1606 -This study examines **historical reaction time data** as a measure of **cognitive ability and intelligence decline**, analyzing data from **Western populations between 1884 and 2004**. The results suggest a **measurable decline in intelligence, estimated at 13.35 IQ points**, likely due to **dysgenic fertility, neurophysiological factors, and reduced selection pressures**.  ##
1695 +This study examines **cross-cultural biases in self-reported substance use surveys**, showing that **racial/ethnic minorities are more likely to underreport drug use** due to **social stigma, research distrust, and survey administration methods**. The findings highlight **critical issues in public health data collection and the need for improved survey design**.
1607 1607  
1608 1608  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1609 1609  
1610 -----
1699 +---
1611 1611  
1612 1612  ## **📄 Download Full Study**
1613 -[[Download Full Study>>attach:10.1016_j.intell.2014.05.012.pdf]]##
1702 +[[Download Full Study>>attach:10.1081_JA-120023394.pdf]]
1703 +
1614 1614  {{/expand}}
1615 1615  
1706 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1616 1616  
1617 -= Whiteness & White Guilt =
1708 +{{expand title="Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program" expanded="false"}}
1709 +**Source:** *Substance Use & Misuse*
1710 +**Date of Publication:** *2002*
1711 +**Author(s):** *Clifford A. Butzin, Christine A. Saum, Frank R. Scarpitti*
1712 +**Title:** *"Factors Associated with Completion of a Drug Treatment Court Diversion Program"*
1713 +**DOI:** [10.1081/JA-120014424](https://doi.org/10.1081/JA-120014424)
1714 +**Subject Matter:** *Substance Use, Criminal Justice, Drug Courts*
1618 1618  
1619 -== Study: Segregation, Innocence, and Protection: The Institutional Conditions That Maintain Whiteness in College Sports ==
1716 +---
1620 1620  
1621 -{{expand expanded="false" title="Study: Segregation, Innocence, and Protection: The Institutional Conditions That Maintain Whiteness in College Sports"}}
1622 -**Source:** *Journal of Diversity in Higher Education*
1623 -**Date of Publication:** *2019*
1624 -**Author(s):** *Kirsten Hextrum*
1625 -**Title:** *"Segregation, Innocence, and Protection: The Institutional Conditions That Maintain Whiteness in College Sports"*
1626 -**DOI:** [10.1037/dhe0000140](https://doi.org/10.1037/dhe0000140)
1627 -**Subject Matter:** *Race and Sports, Higher Education, Institutional Racism* 
1628 -
1629 -----
1630 -
1631 -## **Key Statistics**##
1632 -
1718 +## **Key Statistics**
1633 1633  1. **General Observations:**
1634 - - Analyzed **47 college athlete narratives** to explore racial disparities in non-revenue sports.
1635 - - Found three interrelated themes: **racial segregation, racial innocence, and racial protection**.
1720 + - Study examined **drug treatment court success rates** among first-time offenders.
1721 + - Strongest predictors of **successful completion were employment status and race**.
1636 1636  
1637 1637  2. **Subgroup Analysis:**
1638 - - **Predominantly white sports programs** reinforce racial hierarchies in college athletics.
1639 - - **Recruitment policies favor white athletes** from affluent, suburban backgrounds.
1724 + - Individuals with **stable jobs were more likely to complete the program**.
1725 + - **Black participants had lower success rates**, suggesting potential systemic disparities.
1640 1640  
1641 1641  3. **Other Significant Data Points:**
1642 - - White athletes are **socialized to remain unaware of racial privilege** in their athletic careers.
1643 - - Media and institutional narratives protect white athletes from discussions on race and systemic inequities.
1728 + - **Education level was positively correlated** with program completion.
1729 + - Frequency of **drug use before enrollment affected treatment outcomes**.
1644 1644  
1645 -----
1731 +---
1646 1646  
1647 -## **Findings**##
1648 -
1733 +## **Findings**
1649 1649  1. **Primary Observations:**
1650 - - Colleges **actively recruit white athletes** from majority-white communities.
1651 - - Institutional policies **uphold whiteness** by failing to challenge racial biases in recruitment and team culture.
1735 + - **Social stability factors** (employment, education) were key to treatment success.
1736 + - **Race and pre-existing substance use patterns** influenced completion rates.
1652 1652  
1653 1653  2. **Subgroup Trends:**
1654 - - **White athletes show limited awareness** of their racial advantage in sports.
1655 - - **Black athletes are overrepresented** in revenue-generating sports but underrepresented in non-revenue teams.
1739 + - White offenders had **higher completion rates** than Black offenders.
1740 + - Drug court success was **higher for those with lower initial drug use frequency**.
1656 1656  
1657 1657  3. **Specific Case Analysis:**
1658 - - Examines **how sports serve as a mechanism for maintaining racial privilege** in higher education.
1659 - - Discusses the **role of athletics in reinforcing systemic segregation and exclusion**.
1743 + - **Individuals with strong social ties were more likely to finish the program**.
1744 + - Success rates were **significantly higher for participants with case management support**.
1660 1660  
1661 -----
1746 +---
1662 1662  
1663 -## **Critique and Observations**##
1664 -
1748 +## **Critique and Observations**
1665 1665  1. **Strengths of the Study:**
1666 - - **Comprehensive qualitative analysis** of race in college sports.
1667 - - Examines **institutional conditions** that sustain racial disparities in athletics.
1750 + - **First empirical study on drug court program success factors**.
1751 + - Uses **longitudinal data** for post-treatment analysis.
1668 1668  
1669 1669  2. **Limitations of the Study:**
1670 - - Focuses primarily on **Division I non-revenue sports**, limiting generalizability to other divisions.
1671 - - Lacks extensive **quantitative data on racial demographics** in college athletics.
1754 + - Lacks **qualitative data on personal motivation and treatment engagement**.
1755 + - Focuses on **short-term program success** without tracking **long-term relapse rates**.
1672 1672  
1673 1673  3. **Suggestions for Improvement:**
1674 - - Future research should **compare recruitment policies across different sports and divisions**.
1675 - - Investigate **how athletic scholarships contribute to racial inequities in higher education**.
1758 + - Future research should examine **racial disparities in drug court outcomes**.
1759 + - Study **how community resources impact long-term recovery**.
1676 1676  
1677 -----
1761 +---
1678 1678  
1679 1679  ## **Relevance to Subproject**
1680 -- Provides evidence of **systemic racial biases** in college sports recruitment.
1681 -- Highlights **how institutional policies protect whiteness** in non-revenue athletics.
1682 -- Supports research on **diversity, equity, and inclusion (DEI) efforts in sports and education**.##
1764 +- Provides insight into **what factors contribute to drug court program success**.
1765 +- Highlights **racial disparities in criminal justice-based rehabilitation programs**.
1766 +- Supports **policy discussions on improving access to drug treatment for marginalized groups**.
1683 1683  
1684 -----
1768 +---
1685 1685  
1686 -## **Suggestions for Further Exploration**##
1770 +## **Suggestions for Further Exploration**
1771 +1. Investigate **the role of mental health in drug court success rates**.
1772 +2. Assess **long-term relapse prevention strategies post-treatment**.
1773 +3. Explore **alternative diversion programs beyond traditional drug courts**.
1687 1687  
1688 -1. Investigate how **racial stereotypes influence college athlete recruitment**.
1689 -2. Examine **the role of media in shaping public perceptions of race in sports**.
1690 -3. Explore **policy reforms to increase racial diversity in non-revenue sports**.
1775 +---
1691 1691  
1692 -----
1693 -
1694 1694  ## **Summary of Research Study**
1695 -This study explores how **racial segregation, innocence, and protection** sustain whiteness in college sports. By analyzing **47 athlete narratives**, the research reveals **how predominantly white sports programs recruit and retain white athletes** while shielding them from discussions on race. The findings highlight **institutional biases that maintain racial privilege in athletics**, offering critical insight into the **structural inequalities in higher education sports programs**.##
1778 +This study examines **factors influencing the completion of drug treatment court programs**, identifying **employment, education, and race as key predictors**. The research underscores **systemic disparities in drug court outcomes**, emphasizing the need for **improved support systems for at-risk populations**.
1696 1696  
1697 1697  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1698 1698  
1699 -----
1782 +---
1700 1700  
1701 1701  ## **📄 Download Full Study**
1702 -[[Download Full Study>>attach:10.1037_dhe0000140.pdf]]##
1785 +[[Download Full Study>>attach:10.1081_JA-120014424.pdf]]
1786 +
1703 1703  {{/expand}}
1704 1704  
1789 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1705 1705  
1706 -== Study: Racial Bias in Pain Assessment and Treatment Recommendations ==
1791 +{{expand title="Study: The Role of Computer-Mediated Communication in Intergroup Conflict" expanded="false"}}
1792 +**Source:** *Journal of Computer-Mediated Communication*
1793 +**Date of Publication:** *2021*
1794 +**Author(s):** *Zeynep Tufekci, Jesse Fox, Andrew Chadwick*
1795 +**Title:** *"The Role of Computer-Mediated Communication in Intergroup Conflict"*
1796 +**DOI:** [10.1093/jcmc/zmab003](https://doi.org/10.1093/jcmc/zmab003)
1797 +**Subject Matter:** *Online Communication, Social Media, Conflict Studies*
1707 1707  
1708 -{{expand expanded="false" title="Study: Racial Bias in Pain Assessment and Treatment Recommendations"}}
1709 -**Source:** *Proceedings of the National Academy of Sciences (PNAS)*
1710 -**Date of Publication:** *2016*
1711 -**Author(s):** *Kelly M. Hoffman, Sophie Trawalter, Jordan R. Axta, M. Norman Oliver*
1712 -**Title:** *"Racial Bias in Pain Assessment and Treatment Recommendations, and False Beliefs About Biological Differences Between Blacks and Whites"*
1713 -**DOI:** [10.1073/pnas.1516047113](https://doi.org/10.1073/pnas.1516047113)
1714 -**Subject Matter:** *Health Disparities, Racial Bias, Medical Treatment* 
1799 +---
1715 1715  
1716 -----
1717 -
1718 -## **Key Statistics**##
1719 -
1801 +## **Key Statistics**
1720 1720  1. **General Observations:**
1721 - - Study analyzed **racial disparities in pain perception and treatment recommendations**.
1722 - - Found that **white laypeople and medical students endorsed false beliefs about biological differences** between Black and white individuals.
1803 + - Analyzed **over 500,000 social media interactions** related to intergroup conflict.
1804 + - Found that **computer-mediated communication (CMC) intensifies polarization**.
1723 1723  
1724 1724  2. **Subgroup Analysis:**
1725 - - **50% of medical students surveyed endorsed at least one false belief about biological differences**.
1726 - - Participants who held these false beliefs were **more likely to underestimate Black patients’ pain levels**.
1807 + - **Anonymity and reduced social cues** in CMC increased hostility.
1808 + - **Echo chambers formed more frequently in algorithm-driven environments**.
1727 1727  
1728 1728  3. **Other Significant Data Points:**
1729 - - **Black patients were less likely to receive appropriate pain treatment** compared to white patients.
1730 - - The study confirmed that **historical misconceptions about racial differences still persist in modern medicine**.
1811 + - **Misinformation spread 3x faster** in polarized online discussions.
1812 + - Users exposed to **conflicting viewpoints were more likely to engage in retaliatory discourse**.
1731 1731  
1732 -----
1814 +---
1733 1733  
1734 -## **Findings**##
1735 -
1816 +## **Findings**
1736 1736  1. **Primary Observations:**
1737 - - False beliefs about biological racial differences **correlate with racial disparities in pain treatment**.
1738 - - Medical students and residents who endorsed these beliefs **showed greater racial bias in treatment recommendations**.
1818 + - **Online interactions amplify intergroup conflict** due to selective exposure and confirmation bias.
1819 + - **Algorithmic sorting contributes to ideological segmentation**.
1739 1739  
1740 1740  2. **Subgroup Trends:**
1741 - - Physicians who **did not endorse these beliefs** showed **no racial bias** in treatment recommendations.
1742 - - Bias was **strongest among first-year medical students** and decreased slightly in later years of training.
1822 + - Participants with **strong pre-existing biases became more polarized** after exposure to conflicting views.
1823 + - **Moderate users were more likely to disengage** from conflict-heavy discussions.
1743 1743  
1744 1744  3. **Specific Case Analysis:**
1745 - - Study participants **underestimated Black patients' pain and recommended less effective pain treatments**.
1746 - - The study suggests that **racial disparities in medical care stem, in part, from these enduring false beliefs**.
1826 + - **CMC increased political tribalism** in digital spaces.
1827 + - **Emotional language spread more widely** than factual content.
1747 1747  
1748 -----
1829 +---
1749 1749  
1750 -## **Critique and Observations**##
1751 -
1831 +## **Critique and Observations**
1752 1752  1. **Strengths of the Study:**
1753 - - **First empirical study to connect false racial beliefs with medical decision-making**.
1754 - - Utilizes a **large sample of medical students and residents** from diverse institutions.
1833 + - **Largest dataset** to date analyzing **CMC and intergroup conflict**.
1834 + - Uses **longitudinal data tracking user behavior over time**.
1755 1755  
1756 1756  2. **Limitations of the Study:**
1757 - - The study focuses on **Black vs. white disparities**, leaving other racial/ethnic groups unexplored.
1758 - - Participants' responses were based on **hypothetical medical cases, not real-world treatment decisions**.
1837 + - Lacks **qualitative analysis of user motivations**.
1838 + - Focuses on **Western social media platforms**, missing global perspectives.
1759 1759  
1760 1760  3. **Suggestions for Improvement:**
1761 - - Future research should examine **how these biases manifest in real clinical settings**.
1762 - - Investigate **whether medical training can correct these biases over time**.
1841 + - Future studies should **analyze private messaging platforms** in conflict dynamics.
1842 + - Investigate **interventions that reduce online polarization**.
1763 1763  
1764 -----
1844 +---
1765 1765  
1766 1766  ## **Relevance to Subproject**
1767 -- Highlights **racial disparities in healthcare**, specifically in pain assessment and treatment.
1768 -- Supports **research on implicit bias and its impact on medical outcomes**.
1769 -- Provides evidence for **the need to address racial bias in medical education**.##
1847 +- Explores how **digital communication influences social division**.
1848 +- Supports research on **social media regulation and conflict mitigation**.
1849 +- Provides **data on misinformation and online radicalization trends**.
1770 1770  
1771 -----
1851 +---
1772 1772  
1773 -## **Suggestions for Further Exploration**##
1853 +## **Suggestions for Further Exploration**
1854 +1. Investigate **how online anonymity affects real-world aggression**.
1855 +2. Study **social media interventions that reduce political polarization**.
1856 +3. Explore **cross-cultural differences in CMC and intergroup hostility**.
1774 1774  
1775 -1. Investigate **interventions to reduce racial bias in medical decision-making**.
1776 -2. Explore **how implicit bias training impacts pain treatment recommendations**.
1777 -3. Conduct **real-world observational studies on racial disparities in healthcare settings**.
1858 +---
1778 1778  
1779 -----
1780 -
1781 1781  ## **Summary of Research Study**
1782 -This study examines **racial bias in pain perception and treatment** among **white laypeople and medical professionals**, demonstrating that **false beliefs about biological differences contribute to disparities in pain management**. The research highlights the **systemic nature of racial bias in medicine** and underscores the **need for improved medical training to counteract these misconceptions**.##
1861 +This study examines **how online communication intensifies intergroup conflict**, using a dataset of **500,000+ social media interactions**. It highlights the role of **algorithmic filtering, anonymity, and selective exposure** in **increasing polarization and misinformation spread**. The findings emphasize the **need for policy interventions to mitigate digital conflict escalation**.
1783 1783  
1784 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1863 +---
1785 1785  
1786 -----
1787 -
1788 1788  ## **📄 Download Full Study**
1789 -[[Download Full Study>>attach:10.1073_pnas.1516047113.pdf]]##
1866 +[[Download Full Study>>attach:10.1093_jcmc_zmab003.pdf]]
1867 +
1790 1790  {{/expand}}
1791 1791  
1870 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1792 1792  
1793 -== Study: Rising Morbidity and Mortality in Midlife Among White Non-Hispanic Americans ==
1794 1794  
1795 -{{expand expanded="false" title="Study: Rising Morbidity and Mortality in Midlife Among White Non-Hispanic Americans"}}
1796 -**Source:** *Proceedings of the National Academy of Sciences (PNAS)*
1797 -**Date of Publication:** *2015*
1798 -**Author(s):** *Anne Case, Angus Deaton*
1799 -**Title:** *"Rising Morbidity and Mortality in Midlife Among White Non-Hispanic Americans in the 21st Century"*
1800 -**DOI:** [10.1073/pnas.1518393112](https://doi.org/10.1073/pnas.1518393112)
1801 -**Subject Matter:** *Public Health, Mortality, Socioeconomic Factors* 
1873 +{{expand title="Study: The Effects of Digital Media on Political Persuasion" expanded="false"}}
1874 +**Source:** *Journal of Communication*
1875 +**Date of Publication:** *2019*
1876 +**Author(s):** *Natalie Stroud, Matthew Barnidge, Shannon McGregor*
1877 +**Title:** *"The Effects of Digital Media on Political Persuasion: Evidence from Experimental Studies"*
1878 +**DOI:** [10.1093/joc/jqx021](https://doi.org/10.1093/joc/jqx021)
1879 +**Subject Matter:** *Media Influence, Political Communication, Persuasion*
1802 1802  
1803 -----
1881 +---
1804 1804  
1805 -## **Key Statistics**##
1806 -
1883 +## **Key Statistics**
1807 1807  1. **General Observations:**
1808 - - Mortality rates among **middle-aged white non-Hispanic Americans (ages 45–54)** increased from 1999 to 2013.
1809 - - This reversal in mortality trends is unique to the U.S.; **no other wealthy country experienced a similar rise**.
1885 + - Conducted **12 experimental studies** on **digital media's impact on political beliefs**.
1886 + - **58% of participants** showed shifts in political opinion based on online content.
1810 1810  
1811 1811  2. **Subgroup Analysis:**
1812 - - The increase was **most pronounced among those with a high school education or less**.
1813 - - Hispanic and Black non-Hispanic mortality continued to decline over the same period.
1889 + - **Video-based content was 2x more persuasive** than text-based content.
1890 + - Participants **under age 35 were more susceptible to political messaging shifts**.
1814 1814  
1815 1815  3. **Other Significant Data Points:**
1816 - - Rising mortality was driven primarily by **suicide, drug and alcohol poisoning, and chronic liver disease**.
1817 - - Midlife morbidity increased as well, with more reports of **poor health, pain, and mental distress**.
1893 + - **Interactive media (comment sections, polls) increased political engagement**.
1894 + - **Exposure to counterarguments reduced partisan bias** by **14% on average**.
1818 1818  
1819 -----
1896 +---
1820 1820  
1821 -## **Findings**##
1822 -
1898 +## **Findings**
1823 1823  1. **Primary Observations:**
1824 - - The rise in mortality is attributed to **substance abuse, economic distress, and deteriorating mental health**.
1825 - - The increase in **suicides and opioid overdoses parallels broader socioeconomic decline**.
1900 + - **Digital media significantly influences political opinions**, with younger audiences being the most impacted.
1901 + - **Multimedia content is more persuasive** than traditional text-based arguments.
1826 1826  
1827 1827  2. **Subgroup Trends:**
1828 - - The **largest mortality increases** occurred among **whites without a college degree**.
1829 - - Chronic pain, functional limitations, and self-reported mental distress **rose significantly in affected groups**.
1904 + - **Social media platforms had stronger persuasive effects** than news websites.
1905 + - Participants who engaged in **online discussions retained more political knowledge**.
1830 1830  
1831 1831  3. **Specific Case Analysis:**
1832 - - **Educational attainment was a major predictor of mortality trends**, with better-educated individuals experiencing lower mortality rates.
1833 - - Mortality among **white Americans with a college degree continued to decline**, resembling trends in other wealthy nations.
1908 + - **Highly partisan users became more entrenched in their views**, even when exposed to opposing content.
1909 + - **Neutral or apolitical users were more likely to shift opinions**.
1834 1834  
1835 -----
1911 +---
1836 1836  
1837 -## **Critique and Observations**##
1838 -
1913 +## **Critique and Observations**
1839 1839  1. **Strengths of the Study:**
1840 - - **First major study to highlight rising midlife mortality among U.S. whites**.
1841 - - Uses **CDC and Census mortality data spanning over a decade**.
1915 + - **Large-scale experimental design** allows for controlled comparisons.
1916 + - Covers **multiple digital platforms**, ensuring robust findings.
1842 1842  
1843 1843  2. **Limitations of the Study:**
1844 - - Does not establish **causality** between economic decline and increased mortality.
1845 - - Lacks **granular data on opioid prescribing patterns and regional differences**.
1919 + - Limited to **short-term persuasion effects**, without long-term follow-up.
1920 + - Does not explore **the role of misinformation in political persuasion**.
1846 1846  
1847 1847  3. **Suggestions for Improvement:**
1848 - - Future studies should explore **how economic shifts, healthcare access, and mental health treatment contribute to these trends**.
1849 - - Further research on **racial and socioeconomic disparities in mortality trends** is needed.
1923 + - Future studies should track **long-term opinion changes** beyond immediate reactions.
1924 + - Investigate **the role of digital media literacy in resisting persuasion**.
1850 1850  
1851 -----
1926 +---
1852 1852  
1853 1853  ## **Relevance to Subproject**
1854 -- Highlights **socioeconomic and racial disparities** in health outcomes.
1855 -- Supports research on **substance abuse and mental health crises in the U.S.**.
1856 -- Provides evidence for **the role of economic instability in public health trends**.##
1929 +- Provides insights into **how digital media shapes political discourse**.
1930 +- Highlights **which platforms and content types are most influential**.
1931 +- Supports **research on misinformation and online political engagement**.
1857 1857  
1858 -----
1933 +---
1859 1859  
1860 -## **Suggestions for Further Exploration**##
1935 +## **Suggestions for Further Exploration**
1936 +1. Study how **fact-checking influences digital persuasion effects**.
1937 +2. Investigate the **role of political influencers in shaping opinions**.
1938 +3. Explore **long-term effects of social media exposure on political beliefs**.
1861 1861  
1862 -1. Investigate **regional differences in rising midlife mortality**.
1863 -2. Examine the **impact of the opioid crisis on long-term health trends**.
1864 -3. Study **policy interventions aimed at reversing rising mortality rates**.
1940 +---
1865 1865  
1866 -----
1867 -
1868 1868  ## **Summary of Research Study**
1869 -This study documents a **reversal in mortality trends among middle-aged white non-Hispanic Americans**, showing an increase in **suicide, drug overdoses, and alcohol-related deaths** from 1999 to 2013. The findings highlight **socioeconomic distress, declining health, and rising morbidity** as key factors. This research underscores the **importance of economic and social policy in shaping public health outcomes**.##
1943 +This study analyzes **how digital media influences political persuasion**, using **12 experimental studies**. The findings show that **video and interactive content are the most persuasive**, while **younger users are more susceptible to political messaging shifts**. The research emphasizes the **power of digital platforms in shaping public opinion and engagement**.
1870 1870  
1871 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1945 +---
1872 1872  
1873 -----
1874 -
1875 1875  ## **📄 Download Full Study**
1876 -[[Download Full Study>>attach:10.1073_pnas.1518393112.pdf]]##
1948 +[[Download Full Study>>attach:10.1093_joc_jqx021.pdf]]
1949 +
1877 1877  {{/expand}}
1878 1878  
1952 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1879 1879  
1880 -== Study: How Do People Without Migration Background Experience and Impact Today’s Superdiverse Cities? ==
1954 +{{expand title="Study: Pervasive Findings of Directional Selection in Ancient DNA" expanded="false"}}
1955 +**Source:** *bioRxiv Preprint*
1956 +**Date of Publication:** *September 15, 2024*
1957 +**Author(s):** *Ali Akbari, Alison R. Barton, Steven Gazal, Zheng Li, Mohammadreza Kariminejad, et al.*
1958 +**Title:** *"Pervasive findings of directional selection realize the promise of ancient DNA to elucidate human adaptation"*
1959 +**DOI:** [10.1101/2024.09.14.613021](https://doi.org/10.1101/2024.09.14.613021)
1960 +**Subject Matter:** *Genomics, Evolutionary Biology, Natural Selection*
1881 1881  
1882 -{{expand expanded="false" title="Study: How Do People Without Migration Background Experience and Impact Today’s Superdiverse Cities?"}}
1883 -**Source:** *Journal of Ethnic and Migration Studies*
1884 -**Date of Publication:** *2023*
1885 -**Author(s):** *Maurice Crul, Frans Lelie, Elif Keskiner, Laure Michon, Ismintha Waldring*
1886 -**Title:** *"How Do People Without Migration Background Experience and Impact Today’s Superdiverse Cities?"*
1887 -**DOI:** [10.1080/1369183X.2023.2182548](https://doi.org/10.1080/1369183X.2023.2182548)
1888 -**Subject Matter:** *Urban Sociology, Migration Studies, Integration* 
1962 +---
1889 1889  
1890 -----
1891 -
1892 -## **Key Statistics**##
1893 -
1964 +## **Key Statistics**
1894 1894  1. **General Observations:**
1895 - - Study examines the role of **people without migration background** in majority-minority cities.
1896 - - Analyzes **over 3,000 survey responses and 150 in-depth interviews** from six North-Western European cities.
1966 + - Study analyzes **8,433 ancient individuals** from the past **14,000 years**.
1967 + - Identifies **347 genome-wide significant loci** showing strong selection.
1897 1897  
1898 1898  2. **Subgroup Analysis:**
1899 - - Explores differences in **integration, social interactions, and perceptions of diversity**.
1900 - - Studies how **class, education, and neighborhood composition** affect adaptation to urban diversity.
1970 + - Examines **West Eurasian populations** and their genetic evolution.
1971 + - Tracks **changes in allele frequencies over millennia**.
1901 1901  
1902 1902  3. **Other Significant Data Points:**
1903 - - The study introduces the **Becoming a Minority (BaM) project**, a large-scale investigation of urban demographic shifts.
1904 - - **People without migration background perceive diversity differently**, with some embracing and others resisting change.
1974 + - **10,000 years of directional selection** affected metabolic, immune, and cognitive traits.
1975 + - **Strong selection signals** found for traits like **skin pigmentation, cognitive function, and immunity**.
1905 1905  
1906 -----
1977 +---
1907 1907  
1908 -## **Findings**##
1909 -
1979 +## **Findings**
1910 1910  1. **Primary Observations:**
1911 - - The study **challenges traditional integration theories**, arguing that non-migrant groups also undergo adaptation processes.
1912 - - Some residents **struggle with demographic changes**, while others see diversity as an asset.
1981 + - **Hundreds of alleles have been subject to directional selection** over recent millennia.
1982 + - Traits like **immune function, metabolism, and cognitive performance** show strong selection.
1913 1913  
1914 1914  2. **Subgroup Trends:**
1915 - - Young, educated individuals in urban areas **are more open to cultural diversity**.
1916 - - Older and less mobile residents **report feelings of displacement and social isolation**.
1985 + - Selection pressure on **energy storage genes** supports the **Thrifty Gene Hypothesis**.
1986 + - **Cognitive performance-related alleles** have undergone selection, but their historical advantages remain unclear.
1917 1917  
1918 1918  3. **Specific Case Analysis:**
1919 - - Examines how **people without migration background navigate majority-minority settings** in cities like Amsterdam and Vienna.
1920 - - Analyzes **whether former ethnic majority groups now perceive themselves as minorities**.
1989 + - **Celiac disease risk allele** increased from **0% to 20%** in 4,000 years.
1990 + - **Blood type B frequency rose from 0% to 8% in 6,000 years**.
1991 + - **Tuberculosis risk allele** fluctuated from **2% to 9% over 3,000 years before declining**.
1921 1921  
1922 -----
1993 +---
1923 1923  
1924 -## **Critique and Observations**##
1925 -
1995 +## **Critique and Observations**
1926 1926  1. **Strengths of the Study:**
1927 - - **Innovative approach** by examining the impact of migration on native populations.
1928 - - Uses **both qualitative and quantitative data** for robust analysis.
1997 + - **Largest dataset to date** on natural selection in human ancient DNA.
1998 + - Uses **direct allele frequency tracking instead of indirect measures**.
1929 1929  
1930 1930  2. **Limitations of the Study:**
1931 - - Limited to **Western European urban settings**, missing perspectives from other global regions.
1932 - - Does not fully explore **policy interventions for fostering social cohesion**.
2001 + - Findings **may not translate directly** to modern populations.
2002 + - **Unclear whether observed selection pressures persist today**.
1933 1933  
1934 1934  3. **Suggestions for Improvement:**
1935 - - Expand research to **other geographical contexts** to understand migration effects globally.
1936 - - Investigate **long-term trends in urban adaptation and community building**.
2005 + - Expanding research to **other global populations** to assess universal trends.
2006 + - Investigating **long-term evolutionary trade-offs of selected alleles**.
1937 1937  
1938 -----
2008 +---
1939 1939  
1940 1940  ## **Relevance to Subproject**
1941 -- Provides a **new perspective on urban integration**, shifting focus from migrants to native-born populations.
1942 -- Highlights the **role of social and economic power in shaping urban diversity outcomes**.
1943 -- Challenges existing **assimilation theories by showing bidirectional adaptation in diverse cities**.##
2011 +- Provides **direct evidence of long-term genetic adaptation** in human populations.
2012 +- Supports theories on **polygenic selection shaping human cognition, metabolism, and immunity**.
2013 +- Highlights **how past selection pressures may still influence modern health and disease prevalence**.
1944 1944  
1945 -----
2015 +---
1946 1946  
1947 -## **Suggestions for Further Exploration**##
2017 +## **Suggestions for Further Exploration**
2018 +1. Examine **selection patterns in non-European populations** for comparison.
2019 +2. Investigate **how environmental and cultural shifts influenced genetic selection**.
2020 +3. Explore **the genetic basis of traits linked to past and present-day human survival**.
1948 1948  
1949 -1. Study how **local policies shape attitudes toward urban diversity**.
1950 -2. Investigate **the role of economic and housing policies in shaping demographic changes**.
1951 -3. Explore **how social networks influence perceptions of migration and diversity**.
2022 +---
1952 1952  
1953 -----
1954 -
1955 1955  ## **Summary of Research Study**
1956 -This study examines how **people without migration background experience demographic change in majority-minority cities**. Using data from the **BaM project**, it challenges traditional **one-way integration models**, showing that **non-migrants also adapt to diverse environments**. The findings highlight **the complexities of social cohesion, identity, and power in rapidly changing urban landscapes**.##
2025 +This study examines **how human genetic adaptation has unfolded over 14,000 years**, using a **large dataset of ancient DNA**. It highlights **strong selection on immune function, metabolism, and cognitive traits**, revealing **hundreds of loci affected by directional selection**. The findings emphasize **the power of ancient DNA in tracking human evolution and adaptation**.
1957 1957  
1958 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
2027 +---
1959 1959  
1960 -----
1961 -
1962 1962  ## **📄 Download Full Study**
1963 -[[Download Full Study>>attach:10.1080_1369183X.2023.2182548.pdf]]##
2030 +[[Download Full Study>>attach:10.1101_2024.09.14.613021doi_.pdf]]
2031 +
1964 1964  {{/expand}}
1965 1965  
2034 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1966 1966  
1967 -= Media =
2036 +{{expand title="Study: Biracial Couples and Adverse Birth Outcomes – A Systematic Review and Meta-Analysis" expanded="false"}}
2037 +**Source:** *Acta Obstetricia et Gynecologica Scandinavica*
2038 +**Date of Publication:** *2012*
2039 +**Author(s):** *Ravisha M. Srinivasjois, Shreya Shah, Prakesh S. Shah, Knowledge Synthesis Group on Determinants of Preterm/LBW Births*
2040 +**Title:** *"Biracial Couples and Adverse Birth Outcomes: A Systematic Review and Meta-Analysis"*
2041 +**DOI:** [10.1111/j.1600-0412.2012.01501.x](https://doi.org/10.1111/j.1600-0412.2012.01501.x)
2042 +**Subject Matter:** *Neonatal Health, Maternal-Fetal Medicine, Racial Disparities*
1968 1968  
2044 +---
1969 1969  
1970 -== Study: The Role of Computer-Mediated Communication in Intergroup Conflic ==
1971 -
1972 -{{expand expanded="false" title="Study: The Role of Computer-Mediated Communication in Intergroup Conflict"}}
1973 -**Source:** *Journal of Computer-Mediated Communication*
1974 -**Date of Publication:** *2021*
1975 -**Author(s):** *Zeynep Tufekci, Jesse Fox, Andrew Chadwick*
1976 -**Title:** *"The Role of Computer-Mediated Communication in Intergroup Conflict"*
1977 -**DOI:** [10.1093/jcmc/zmab003](https://doi.org/10.1093/jcmc/zmab003)
1978 -**Subject Matter:** *Online Communication, Social Media, Conflict Studies* 
1979 -
1980 -----
1981 -
1982 -## **Key Statistics**##
1983 -
2046 +## **Key Statistics**
1984 1984  1. **General Observations:**
1985 - - Analyzed **over 500,000 social media interactions** related to intergroup conflict.
1986 - - Found that **computer-mediated communication (CMC) intensifies polarization**.
2048 + - Meta-analysis of **26,335,596 singleton births** from eight studies.
2049 + - **Higher risk of adverse birth outcomes in biracial couples** than White couples, but lower than Black couples.
1987 1987  
1988 1988  2. **Subgroup Analysis:**
1989 - - **Anonymity and reduced social cues** in CMC increased hostility.
1990 - - **Echo chambers formed more frequently in algorithm-driven environments**.
2052 + - **Maternal race had a stronger influence than paternal race** on birth outcomes.
2053 + - **Black mother–White father (BMWF) couples** had a higher risk than **White mother–Black father (WMBF) couples**.
1991 1991  
1992 1992  3. **Other Significant Data Points:**
1993 - - **Misinformation spread 3x faster** in polarized online discussions.
1994 - - Users exposed to **conflicting viewpoints were more likely to engage in retaliatory discourse**.
2056 + - **Adjusted Odds Ratios (aORs) for key outcomes:**
2057 + - **Low birthweight (LBW):** WMBF (1.21), BMWF (1.75), Black mother–Black father (BMBF) (2.08).
2058 + - **Preterm births (PTB):** WMBF (1.17), BMWF (1.37), BMBF (1.78).
2059 + - **Stillbirths:** WMBF (1.43), BMWF (1.51), BMBF (1.85).
1995 1995  
1996 -----
2061 +---
1997 1997  
1998 -## **Findings**##
1999 -
2063 +## **Findings**
2000 2000  1. **Primary Observations:**
2001 - - **Online interactions amplify intergroup conflict** due to selective exposure and confirmation bias.
2002 - - **Algorithmic sorting contributes to ideological segmentation**.
2065 + - **Biracial couples face a gradient of risk**: higher than White couples but lower than Black couples.
2066 + - **Maternal race plays a more significant role** in pregnancy outcomes.
2003 2003  
2004 2004  2. **Subgroup Trends:**
2005 - - Participants with **strong pre-existing biases became more polarized** after exposure to conflicting views.
2006 - - **Moderate users were more likely to disengage** from conflict-heavy discussions.
2069 + - **Black mothers (regardless of paternal race) had the highest risk of LBW and PTB**.
2070 + - **White mothers with Black fathers had a lower risk** than Black mothers with White fathers.
2007 2007  
2008 2008  3. **Specific Case Analysis:**
2009 - - **CMC increased political tribalism** in digital spaces.
2010 - - **Emotional language spread more widely** than factual content.
2073 + - The **weathering hypothesis** suggests that **long-term stress exposure** contributes to higher adverse birth risks in Black mothers.
2074 + - **Genetic and environmental factors** may interact to influence birth outcomes.
2011 2011  
2012 -----
2076 +---
2013 2013  
2014 -## **Critique and Observations**##
2015 -
2078 +## **Critique and Observations**
2016 2016  1. **Strengths of the Study:**
2017 - - **Largest dataset** to date analyzing **CMC and intergroup conflict**.
2018 - - Uses **longitudinal data tracking user behavior over time**.
2080 + - **Largest meta-analysis** on racial disparities in birth outcomes.
2081 + - Uses **adjusted statistical models** to account for confounding variables.
2019 2019  
2020 2020  2. **Limitations of the Study:**
2021 - - Lacks **qualitative analysis of user motivations**.
2022 - - Focuses on **Western social media platforms**, missing global perspectives.
2084 + - Data limited to **Black-White biracial couples**, excluding other racial groups.
2085 + - **Socioeconomic and healthcare access factors** not fully explored.
2023 2023  
2024 2024  3. **Suggestions for Improvement:**
2025 - - Future studies should **analyze private messaging platforms** in conflict dynamics.
2026 - - Investigate **interventions that reduce online polarization**.
2088 + - Future studies should examine **Asian, Hispanic, and Indigenous biracial couples**.
2089 + - Investigate **long-term health effects on infants from biracial pregnancies**.
2027 2027  
2028 -----
2091 +---
2029 2029  
2030 2030  ## **Relevance to Subproject**
2031 -- Explores how **digital communication influences social division**.
2032 -- Supports research on **social media regulation and conflict mitigation**.
2033 -- Provides **data on misinformation and online radicalization trends**.##
2094 +- Provides **critical insights into racial disparities** in maternal and infant health.
2095 +- Supports **research on genetic and environmental influences on neonatal health**.
2096 +- Highlights **how maternal race plays a more significant role than paternal race** in birth outcomes.
2034 2034  
2035 -----
2098 +---
2036 2036  
2037 -## **Suggestions for Further Exploration**##
2100 +## **Suggestions for Further Exploration**
2101 +1. Investigate **the role of prenatal care quality in mitigating racial disparities**.
2102 +2. Examine **how social determinants of health impact biracial pregnancy outcomes**.
2103 +3. Explore **gene-environment interactions influencing birthweight and prematurity risks**.
2038 2038  
2039 -1. Investigate **how online anonymity affects real-world aggression**.
2040 -2. Study **social media interventions that reduce political polarization**.
2041 -3. Explore **cross-cultural differences in CMC and intergroup hostility**.
2105 +---
2042 2042  
2043 -----
2044 -
2045 2045  ## **Summary of Research Study**
2046 -This study examines **how online communication intensifies intergroup conflict**, using a dataset of **500,000+ social media interactions**. It highlights the role of **algorithmic filtering, anonymity, and selective exposure** in **increasing polarization and misinformation spread**. The findings emphasize the **need for policy interventions to mitigate digital conflict escalation**.##
2108 +This meta-analysis examines **the impact of biracial parentage on birth outcomes**, showing that **biracial couples face a higher risk of adverse pregnancy outcomes than White couples but lower than Black couples**. The findings emphasize **maternal race as a key factor in birth risks**, with **Black mothers having the highest rates of preterm birth and low birthweight, regardless of paternal race**.
2047 2047  
2048 -----
2110 +---
2049 2049  
2050 2050  ## **📄 Download Full Study**
2051 -[[Download Full Study>>attach:10.1093_jcmc_zmab003.pdf]]##
2113 +[[Download Full Study>>attach:10.1111_j.1600-0412.2012.01501.xAbstract.pdf]]
2114 +
2052 2052  {{/expand}}
2053 2053  
2117 +{{html}}<hr style="border: 3px solid red;">{{/html}}
2054 2054  
2055 -== Study: Equality, Morality, and the Impact of Media Framing on Same-Sex Marriage and Civil Unions ==
2056 -
2057 -{{expand expanded="false" title="Study: Equality, Morality, and the Impact of Media Framing on Same-Sex Marriage and Civil Unions"}}
2119 +{{expand title="Study: Equality, Morality, and the Impact of Media Framing on Same-Sex Marriage and Civil Unions" expanded="false"}}
2058 2058  **Source:** *Politics & Policy*
2059 2059  **Date of Publication:** *2007*
2060 2060  **Author(s):** *Tyler Johnson*
2061 2061  **Title:** *"Equality, Morality, and the Impact of Media Framing: Explaining Opposition to Same-Sex Marriage and Civil Unions"*
2062 2062  **DOI:** [10.1111/j.1747-1346.2007.00092.x](https://doi.org/10.1111/j.1747-1346.2007.00092.x)
2063 -**Subject Matter:** *LGBTQ+ Rights, Public Opinion, Media Influence* 
2125 +**Subject Matter:** *LGBTQ+ Rights, Public Opinion, Media Influence*
2064 2064  
2065 -----
2127 +---
2066 2066  
2067 -## **Key Statistics**##
2068 -
2129 +## **Key Statistics**
2069 2069  1. **General Observations:**
2070 2070   - Examines **media coverage of same-sex marriage and civil unions from 2004 to 2011**.
2071 2071   - Analyzes how **media framing influences public opinion trends** on LGBTQ+ rights.
... ... @@ -2078,10 +2078,9 @@
2078 2078   - When **equality framing surpasses morality framing**, public opposition declines.
2079 2079   - Media framing **directly affects public attitudes** over time, shaping policy debates.
2080 2080  
2081 -----
2142 +---
2082 2082  
2083 -## **Findings**##
2084 -
2144 +## **Findings**
2085 2085  1. **Primary Observations:**
2086 2086   - **Media framing plays a critical role in shaping attitudes** toward LGBTQ+ rights.
2087 2087   - **Equality-focused narratives** lead to greater public support for same-sex marriage.
... ... @@ -2094,10 +2094,9 @@
2094 2094   - **Periods of increased equality framing** saw measurable **declines in opposition to LGBTQ+ rights**.
2095 2095   - **Major political events (elections, Supreme Court cases) influenced framing trends**.
2096 2096  
2097 -----
2157 +---
2098 2098  
2099 -## **Critique and Observations**##
2100 -
2159 +## **Critique and Observations**
2101 2101  1. **Strengths of the Study:**
2102 2102   - **Longitudinal dataset spanning multiple election cycles**.
2103 2103   - Provides **quantitative analysis of how media framing shifts public opinion**.
... ... @@ -2110,113 +2110,31 @@
2110 2110   - Expand the study to **global perspectives on LGBTQ+ rights and media influence**.
2111 2111   - Investigate how **different media platforms (TV vs. digital media) impact opinion shifts**.
2112 2112  
2113 -----
2172 +---
2114 2114  
2115 2115  ## **Relevance to Subproject**
2116 2116  - Explores **how media narratives shape policy support and public sentiment**.
2117 2117  - Highlights **the strategic importance of framing in LGBTQ+ advocacy**.
2118 -- Reinforces the need for **media literacy in understanding policy debates**.##
2177 +- Reinforces the need for **media literacy in understanding policy debates**.
2119 2119  
2120 -----
2179 +---
2121 2121  
2122 -## **Suggestions for Further Exploration**##
2123 -
2181 +## **Suggestions for Further Exploration**
2124 2124  1. Examine how **social media affects framing of LGBTQ+ issues**.
2125 2125  2. Study **differences in framing across political media outlets**.
2126 2126  3. Investigate **public opinion shifts in states that legalized same-sex marriage earlier**.
2127 2127  
2128 -----
2186 +---
2129 2129  
2130 2130  ## **Summary of Research Study**
2131 -This study examines **how media framing influences public attitudes on same-sex marriage and civil unions**, analyzing **news coverage from 2004 to 2011**. It finds that **equality-based narratives reduce opposition, while morality-based narratives increase it**. The research highlights **how media coverage plays a crucial role in shaping policy debates and public sentiment**.##
2189 +This study examines **how media framing influences public attitudes on same-sex marriage and civil unions**, analyzing **news coverage from 2004 to 2011**. It finds that **equality-based narratives reduce opposition, while morality-based narratives increase it**. The research highlights **how media coverage plays a crucial role in shaping policy debates and public sentiment**.
2132 2132  
2133 -----
2191 +---
2134 2134  
2135 2135  ## **📄 Download Full Study**
2136 -[[Download Full Study>>attach:10.1111_j.1747-1346.2007.00092.x_abstract.pdf]]##
2194 +[[Download Full Study>>attach:10.1111_j.1747-1346.2007.00092.x_abstract.pdf]]
2195 +
2137 2137  {{/expand}}
2138 2138  
2198 +{{html}}<hr style="border: 3px solid red;">{{/html}}
2139 2139  
2140 -== Study: The Effects of Digital Media on Political Persuasion ==
2141 -
2142 -{{expand expanded="false" title="Study: The Effects of Digital Media on Political Persuasion"}}
2143 -**Source:** *Journal of Communication*
2144 -**Date of Publication:** *2019*
2145 -**Author(s):** *Natalie Stroud, Matthew Barnidge, Shannon McGregor*
2146 -**Title:** *"The Effects of Digital Media on Political Persuasion: Evidence from Experimental Studies"*
2147 -**DOI:** [10.1093/joc/jqx021](https://doi.org/10.1093/joc/jqx021)
2148 -**Subject Matter:** *Media Influence, Political Communication, Persuasion* 
2149 -
2150 -----
2151 -
2152 -## **Key Statistics**##
2153 -
2154 -1. **General Observations:**
2155 - - Conducted **12 experimental studies** on **digital media's impact on political beliefs**.
2156 - - **58% of participants** showed shifts in political opinion based on online content.
2157 -
2158 -2. **Subgroup Analysis:**
2159 - - **Video-based content was 2x more persuasive** than text-based content.
2160 - - Participants **under age 35 were more susceptible to political messaging shifts**.
2161 -
2162 -3. **Other Significant Data Points:**
2163 - - **Interactive media (comment sections, polls) increased political engagement**.
2164 - - **Exposure to counterarguments reduced partisan bias** by **14% on average**.
2165 -
2166 -----
2167 -
2168 -## **Findings**##
2169 -
2170 -1. **Primary Observations:**
2171 - - **Digital media significantly influences political opinions**, with younger audiences being the most impacted.
2172 - - **Multimedia content is more persuasive** than traditional text-based arguments.
2173 -
2174 -2. **Subgroup Trends:**
2175 - - **Social media platforms had stronger persuasive effects** than news websites.
2176 - - Participants who engaged in **online discussions retained more political knowledge**.
2177 -
2178 -3. **Specific Case Analysis:**
2179 - - **Highly partisan users became more entrenched in their views**, even when exposed to opposing content.
2180 - - **Neutral or apolitical users were more likely to shift opinions**.
2181 -
2182 -----
2183 -
2184 -## **Critique and Observations**##
2185 -
2186 -1. **Strengths of the Study:**
2187 - - **Large-scale experimental design** allows for controlled comparisons.
2188 - - Covers **multiple digital platforms**, ensuring robust findings.
2189 -
2190 -2. **Limitations of the Study:**
2191 - - Limited to **short-term persuasion effects**, without long-term follow-up.
2192 - - Does not explore **the role of misinformation in political persuasion**.
2193 -
2194 -3. **Suggestions for Improvement:**
2195 - - Future studies should track **long-term opinion changes** beyond immediate reactions.
2196 - - Investigate **the role of digital media literacy in resisting persuasion**.
2197 -
2198 -----
2199 -
2200 -## **Relevance to Subproject**
2201 -- Provides insights into **how digital media shapes political discourse**.
2202 -- Highlights **which platforms and content types are most influential**.
2203 -- Supports **research on misinformation and online political engagement**.##
2204 -
2205 -----
2206 -
2207 -## **Suggestions for Further Exploration**##
2208 -
2209 -1. Study how **fact-checking influences digital persuasion effects**.
2210 -2. Investigate the **role of political influencers in shaping opinions**.
2211 -3. Explore **long-term effects of social media exposure on political beliefs**.
2212 -
2213 -----
2214 -
2215 -## **Summary of Research Study**
2216 -This study analyzes **how digital media influences political persuasion**, using **12 experimental studies**. The findings show that **video and interactive content are the most persuasive**, while **younger users are more susceptible to political messaging shifts**. The research emphasizes the **power of digital platforms in shaping public opinion and engagement**.##
2217 -
2218 -----
2219 -
2220 -## **📄 Download Full Study**
2221 -[[Download Full Study>>attach:10.1093_joc_jqx021.pdf]]##
2222 -{{/expand}}