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1 1  = Research at a Glance =
2 2  
3 -== Introduction ==
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 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.
6 6  
7 -=== How to Use This Repository ===
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 conclusion in most cases. That's because I haven't gotten to going through and pointing out the reasons I put all of them in here.
8 8  
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.
13 13  
8 + There is often an underlying hypocrisy or double standard, 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 14  
10 +{{example}}
11 +~= Study: [Study Title] =
15 15  
16 -== Research Studies Repository ==
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]* 
17 17  
21 +~-~--
18 18  
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
27 -
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:**
23 +~#~# ~*~*Key Statistics~*~*
24 +~1. ~*~*General Observations:~*~*
63 63   - [Statistical finding or observation]
64 64   - [Statistical finding or observation]
65 65  
66 -2. **Subgroup Analysis:**
28 +2. ~*~*Subgroup Analysis:~*~*
67 67   - [Breakdown of findings by gender, race, or other subgroups]
68 68  
69 -3. **Other Significant Data Points:**
31 +3. ~*~*Other Significant Data Points:~*~*
70 70   - [Any additional findings or significant statistics]
71 71  
72 ----
34 +~-~--
73 73  
74 -## **Findings**
75 -1. **Primary Observations:**
36 +~#~# ~*~*Findings~*~*
37 +~1. ~*~*Primary Observations:~*~*
76 76   - [High-level findings or trends in the study]
77 77  
78 -2. **Subgroup Trends:**
40 +2. ~*~*Subgroup Trends:~*~*
79 79   - [Disparities or differences highlighted in the study]
80 80  
81 -3. **Specific Case Analysis:**
43 +3. ~*~*Specific Case Analysis:~*~*
82 82   - [Detailed explanation of any notable specific findings]
83 83  
84 ----
46 +~-~--
85 85  
86 -## **Critique and Observations**
87 -1. **Strengths of the Study:**
48 +~#~# ~*~*Critique and Observations~*~*
49 +~1. ~*~*Strengths of the Study:~*~*
88 88   - [Examples: strong methodology, large dataset, etc.]
89 89  
90 -2. **Limitations of the Study:**
52 +2. ~*~*Limitations of the Study:~*~*
91 91   - [Examples: data gaps, lack of upstream analysis, etc.]
92 92  
93 -3. **Suggestions for Improvement:**
55 +3. ~*~*Suggestions for Improvement:~*~*
94 94   - [Ideas for further research or addressing limitations]
95 95  
96 ----
58 +~-~--
97 97  
98 -## **Relevance to Subproject**
60 +~#~# ~*~*Relevance to Subproject~*~*
99 99  - [Explanation of how this study contributes to your subproject goals.]
100 100  - [Any key arguments or findings that support or challenge your views.]
101 101  
102 ----
64 +~-~--
103 103  
104 -## **Suggestions for Further Exploration**
105 -1. [Research questions or areas to investigate further.]
66 +~#~# ~*~*Suggestions for Further Exploration~*~*
67 +~1. [Research questions or areas to investigate further.]
106 106  2. [Potential studies or sources to complement this analysis.]
107 107  
108 ----
70 +~-~--
109 109  
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]**.
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]~*~*. 
112 112  
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.
75 +This summary provides an accessible, at-a-glance overview of the studys contributions. Please refer to the full paper for in-depth analysis.
114 114  
115 ----
77 +~-~--
116 116  
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}}
127 -
128 -{{/expand}}
129 -
130 -{{html}}<hr style="border: 3px solid red;">{{/html}}
131 -
132 -
133 -
134 ----
135 -
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*
143 -
144 ----
145 -
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.
150 -
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.
154 -
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.
158 -
159 ----
160 -
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.
165 -
166 -2. **Subgroup Trends:**
167 - - More pronounced decline among **unmarried individuals**.
168 - - No major change observed for **married adults** over time.
169 -
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.
173 -
174 ----
175 -
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.
180 -
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($doi = "10.1001_jamanetworkopen.2020.3833")
79 +~#~# ~*~*📄 Download Full Study~*~*
80 +~{~{velocity}}
81 +#set($doi = "[Insert DOI Here]")
213 213  #set($filename = "${doi}.pdf")
214 -#if($xwiki.exists("attach:$filename"))
215 -[[Download>>attach:$filename]]
83 +#if($xwiki.exists("attach~:$filename"))
84 +~[~[Download Full Study>>attach~:$filename]]
216 216  #else
217 -{{html}}<span style="color: red; font-weight: bold;">🚨 PDF Not Available 🚨</span>{{/html}}
86 +~{~{html}}<span style="color:red; font-weight:bold;">🚨 PDF Not Available 🚨</span>~{~{/html}}
218 218  #end
219 -{{/velocity}}
88 +~{~{/velocity}}
220 220  
221 -{{/expand}}
90 +~{~{/expand}}
222 222  
223 -{{html}}<hr style="border: 3px solid red;">{{/html}}
92 +
93 +{{/example}}
224 224  
225 225  
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*
233 233  
234 ----
97 +- Click on a **category** in the **Table of Contents** to browse studies related to that topic.
98 +- Click on a **study title** to expand its details, including **key findings, critique, and relevance**.
99 +- Use the **search function** (Ctrl + F or XWiki's built-in search) to quickly find specific topics or authors.
100 +- If needed, you can export this page as **PDF or print-friendly format**, and all studies will automatically expand for readability.
101 +- You'll also find a download link to the original full study in pdf form at the bottom of the collapsible block.
235 235  
236 -## **Key Statistics**
237 -1. **General Observations:**
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.
240 240  
241 -2. **Subgroup Analysis:**
242 - - Incels exhibited **higher levels of depression, anxiety, and self-critical rumination**.
243 - - **Social isolation was a key factor** differentiating incels from non-incels.
104 +{{toc/}}
244 244  
245 -3. **Other Significant Data Points:**
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.
248 248  
249 ----
250 250  
251 -## **Findings**
252 -1. **Primary Observations:**
253 - - Incels experience **heightened rejection sensitivity and loneliness**.
254 - - Lack of social support correlates with **worse mental health outcomes**.
255 255  
256 -2. **Subgroup Trends:**
257 - - **Avoidant attachment styles** were a strong predictor of incel identity.
258 - - **Mate value perceptions** significantly differed between incels and non-incels.
259 259  
260 -3. **Specific Case Analysis:**
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.
110 += Genetics =
263 263  
264 ----
265 265  
266 -## **Critique and Observations**
267 -1. **Strengths of the Study:**
268 - - **First quantitative study** on incels’ social isolation and mental health.
269 - - **Robust sample size** and validated psychological measures.
270 -
271 -2. **Limitations of the Study:**
272 - - Sample drawn from **Reddit communities**, which may not represent all incels.
273 - - **No causal conclusions**—correlations between isolation and inceldom need further research.
274 -
275 -3. **Suggestions for Improvement:**
276 - - Future studies should **compare incel forum users vs. non-users**.
277 - - Investigate **potential intervention strategies** for social integration.
278 -
279 ----
280 -
281 -## **Relevance to Subproject**
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**.
285 -
286 ----
287 -
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.
292 -
293 ----
294 -
295 -## **Summary of Research Study**
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**.
297 -
298 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
299 -
300 ----
301 -
302 -## **📄 Download Full Study**
303 -[[Download Full Study>>attach:10.1007_s12144-023-04275-z.pdf]]
304 -
305 -{{/expand}}
306 -
307 -{{html}}<hr style="border: 3px solid red;">{{/html}}
308 -
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
315 -
316 -Key Statistics
317 -General Observations:
318 -
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:
322 -
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:
326 -
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**
386 -1. **General Observations:**
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.
389 -
390 -2. **Subgroup Analysis:**
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.
393 -
394 -3. **Other Significant Data Points:**
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**.
397 -
398 ----
399 -
400 -## **Findings**
401 -1. **Primary Observations:**
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.
404 -
405 -2. **Subgroup Trends:**
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**.
408 -
409 -3. **Specific Case Analysis:**
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.
412 -
413 ----
414 -
415 -## **Critique and Observations**
416 -1. **Strengths of the Study:**
417 - - **Comprehensive meta-analysis** covering over a century of reaction time data.
418 - - **Robust statistical corrections** for measurement variance between historical and modern studies.
419 -
420 -2. **Limitations of the Study:**
421 - - Some historical data sources **lack methodological consistency**.
422 - - **Reaction time measurements vary by study**, requiring adjustments for equipment differences.
423 -
424 -3. **Suggestions for Improvement:**
425 - - Future studies should **replicate results with more modern datasets**.
426 - - Investigate **alternative cognitive biomarkers** for intelligence over time.
427 -
428 ----
429 -
430 -## **Relevance to Subproject**
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**.
434 -
435 ----
436 -
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**.
441 -
442 ----
443 -
444 -## **Summary of Research Study**
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**.
446 -
447 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
448 -
449 ----
450 -
451 -## **📄 Download Full Study**
452 -[[Download Full Study>>attach:10.1016_j.intell.2014.05.012.pdf]]
453 -
454 -{{/expand}}
455 -
456 -{{html}}<hr style="border: 3px solid red;">{{/html}}
457 -
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)*
460 -**Date of Publication:** *2015*
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*
465 -
466 ----
467 -
468 -## **Key Statistics**
469 -1. **General Observations:**
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**.
472 -
473 -2. **Subgroup Analysis:**
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.
476 -
477 -3. **Other Significant Data Points:**
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**.
480 -
481 ----
482 -
483 -## **Findings**
484 -1. **Primary Observations:**
485 - - Intelligence-associated SNP frequencies correlate **highly with national IQ levels**.
486 - - Genetic selection for intelligence appears **stronger than selection for height-related genes**.
487 -
488 -2. **Subgroup Trends:**
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.
491 -
492 -3. **Specific Case Analysis:**
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.
495 -
496 ----
497 -
498 -## **Critique and Observations**
499 -1. **Strengths of the Study:**
500 - - **Comprehensive genetic analysis** of intelligence-linked SNPs.
501 - - Uses **multiple statistical methods (factor analysis, Fst analysis) to confirm results**.
502 -
503 -2. **Limitations of the Study:**
504 - - **Correlation does not imply causation**; factors beyond genetics influence intelligence.
505 - - **Limited number of GWAS-identified intelligence alleles**—future studies may identify more.
506 -
507 -3. **Suggestions for Improvement:**
508 - - Larger **cross-population GWAS studies** needed to validate findings.
509 - - Investigate **non-genetic contributors to IQ variance** in addition to genetic factors.
510 -
511 ----
512 -
513 -## **Relevance to Subproject**
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**.
517 -
518 ----
519 -
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**.
524 -
525 ----
526 -
527 -## **Summary of Research Study**
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.
529 -
530 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
531 -
532 ----
533 -
534 -## **📄 Download Full Study**
535 -[[Download Full Study>>attach:10.1016_j.intell.2015.08.008.pdf]]
536 -
537 -{{/expand}}
538 -
539 -{{html}}<hr style="border: 3px solid red;">{{/html}}
540 -
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*
548 -
549 ----
550 -
551 -## **Key Statistics**
552 -1. **General Observations:**
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.
555 -
556 -2. **Subgroup Analysis:**
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.
559 -
560 -3. **Other Significant Data Points:**
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**.
563 -
564 ----
565 -
566 -## **Findings**
567 -1. **Primary Observations:**
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.
570 -
571 -2. **Subgroup Trends:**
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.
574 -
575 -3. **Specific Case Analysis:**
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.
578 -
579 ----
580 -
581 -## **Critique and Observations**
582 -1. **Strengths of the Study:**
583 - - **Largest expert survey on intelligence research** to date.
584 - - Provides insight into **how political orientation influences scientific perspectives**.
585 -
586 -2. **Limitations of the Study:**
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**.
589 -
590 -3. **Suggestions for Improvement:**
591 - - Future studies should include **a broader range of global experts**.
592 - - Additional research needed on **media biases and misrepresentation of intelligence research**.
593 -
594 ----
595 -
596 -## **Relevance to Subproject**
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.
600 -
601 ----
602 -
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.
607 -
608 ----
609 -
610 -## **Summary of Research Study**
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**.
612 -
613 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
614 -
615 ----
616 -
617 -## **📄 Download Full Study**
618 -[[Download Full Study>>attach:10.1016_j.intell.2019.101406.pdf]]
619 -
620 -{{/expand}}
621 -
622 -{{html}}<hr style="border: 3px solid red;">{{/html}}
623 -
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*
631 -
632 ----
633 -
634 -## **Key Statistics**
635 -1. **General Observations:**
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.
638 -
639 -2. **Subgroup Analysis:**
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**.
642 -
643 -3. **Other Significant Data Points:**
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.
646 -
647 ----
648 -
649 -## **Findings**
650 -1. **Primary Observations:**
651 - - Proposes that **modern human populations meet biological criteria for subspecies classification**.
652 - - Highlights **medical and evolutionary implications** of human taxonomic diversity.
653 -
654 -2. **Subgroup Trends:**
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.
657 -
658 -3. **Specific Case Analysis:**
659 - - Evaluates how **genetic markers correlate with population structure**.
660 - - Addresses the **controversy over race classification in modern anthropology**.
661 -
662 ----
663 -
664 -## **Critique and Observations**
665 -1. **Strengths of the Study:**
666 - - Uses **comparative species analysis** to assess human classification.
667 - - Provides a **biological perspective** on the race concept, moving beyond social constructivism arguments.
668 -
669 -2. **Limitations of the Study:**
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.
672 -
673 -3. **Suggestions for Improvement:**
674 - - Further research should **incorporate whole-genome studies** to refine subspecies classifications.
675 - - Investigate **how admixture affects taxonomic classification over time**.
676 -
677 ----
678 -
679 -## **Relevance to Subproject**
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**.
683 -
684 ----
685 -
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**.
690 -
691 ----
692 -
693 -## **Summary of Research Study**
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**.
695 -
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.
697 -
698 ----
699 -
700 -## **📄 Download Full Study**
701 -[[Download Full Study>>attach:10.1016_j.mehy.2009.07.046.pdf]]
702 -
703 -{{/expand}}
704 -
705 -{{html}}<hr style="border: 3px solid red;">{{/html}}
706 -
707 -{{expand title="Study: The Wilson Effect: The Increase in Heritability of IQ With Age" expanded="false"}}
708 -**Source:** *Twin Research and Human Genetics (Cambridge University Press)*
709 -**Date of Publication:** *2013*
710 -**Author(s):** *Thomas J. Bouchard Jr.*
711 -**Title:** *"The Wilson Effect: The Increase in Heritability of IQ With Age"*
712 -**DOI:** [10.1017/thg.2013.54](https://doi.org/10.1017/thg.2013.54)
713 -**Subject Matter:** *Intelligence, Heritability, Developmental Psychology*
714 -
715 ----
716 -
717 -## **Key Statistics**
718 -1. **General Observations:**
719 - - The study documents how the **heritability of IQ increases with age**, reaching an asymptote at **0.80 by adulthood**.
720 - - Analysis is based on **longitudinal twin and adoption studies**.
721 -
722 -2. **Subgroup Analysis:**
723 - - Shared environmental influence on IQ **declines with age**, reaching **0.10 in adulthood**.
724 - - Monozygotic twins show **increasing genetic similarity in IQ over time**, while dizygotic twins become **less concordant**.
725 -
726 -3. **Other Significant Data Points:**
727 - - Data from the **Louisville Longitudinal Twin Study and cross-national twin samples** support findings.
728 - - IQ stability over time is **influenced more by genetics than by shared environmental factors**.
729 -
730 ----
731 -
732 -## **Findings**
733 -1. **Primary Observations:**
734 - - Intelligence heritability **strengthens throughout development**, contrary to early environmental models.
735 - - Shared environmental effects **decrease by late adolescence**, emphasizing **genetic influence in adulthood**.
736 -
737 -2. **Subgroup Trends:**
738 - - Studies from **Scotland, Netherlands, and the US** show **consistent patterns of increasing heritability with age**.
739 - - Findings hold across **varied socio-economic and educational backgrounds**.
740 -
741 -3. **Specific Case Analysis:**
742 - - Longitudinal adoption studies show **declining impact of adoptive parental influence on IQ** as children age.
743 - - Cross-sectional twin data confirm **higher IQ correlations for monozygotic twins in adulthood**.
744 -
745 ----
746 -
747 -## **Critique and Observations**
748 -1. **Strengths of the Study:**
749 - - **Robust dataset covering multiple twin and adoption studies over decades**.
750 - - **Clear, replicable trend** demonstrating the increasing role of genetics in intelligence.
751 -
752 -2. **Limitations of the Study:**
753 - - Findings apply primarily to **Western industrialized nations**, limiting generalizability.
754 - - **Lack of neurobiological mechanisms** explaining how genes express their influence over time.
755 -
756 -3. **Suggestions for Improvement:**
757 - - Future research should investigate **gene-environment interactions in cognitive aging**.
758 - - Examine **heritability trends in non-Western populations** to determine cross-cultural consistency.
759 -
760 ----
761 -
762 -## **Relevance to Subproject**
763 -- Provides **strong evidence for the genetic basis of intelligence**.
764 -- Highlights the **diminishing role of shared environment in cognitive development**.
765 -- Supports research on **cognitive aging and heritability across the lifespan**.
766 -
767 ----
768 -
769 -## **Suggestions for Further Exploration**
770 -1. Investigate **neurogenetic pathways underlying IQ development**.
771 -2. Examine **how education and socioeconomic factors interact with genetic IQ influences**.
772 -3. Study **heritability trends in aging populations and cognitive decline**.
773 -
774 ----
775 -
776 -## **Summary of Research Study**
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**.
778 -
779 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
780 -
781 ----
782 -
783 -## **📄 Download Full Study**
784 -[[Download Full Study>>attach:10.1017_thg.2013.54.pdf]]
785 -
786 -{{/expand}}
787 -
788 -{{html}}<hr style="border: 3px solid red;">{{/html}}
789 -
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*
797 -
798 ----
799 -
800 -## **Key Statistics**
801 -1. **General Observations:**
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**.
804 -
805 -2. **Subgroup Analysis:**
806 - - **Predominantly white sports programs** reinforce racial hierarchies in college athletics.
807 - - **Recruitment policies favor white athletes** from affluent, suburban backgrounds.
808 -
809 -3. **Other Significant Data Points:**
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.
812 -
813 ----
814 -
815 -## **Findings**
816 -1. **Primary Observations:**
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.
819 -
820 -2. **Subgroup Trends:**
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.
823 -
824 -3. **Specific Case Analysis:**
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**.
827 -
828 ----
829 -
830 -## **Critique and Observations**
831 -1. **Strengths of the Study:**
832 - - **Comprehensive qualitative analysis** of race in college sports.
833 - - Examines **institutional conditions** that sustain racial disparities in athletics.
834 -
835 -2. **Limitations of the Study:**
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.
838 -
839 -3. **Suggestions for Improvement:**
840 - - Future research should **compare recruitment policies across different sports and divisions**.
841 - - Investigate **how athletic scholarships contribute to racial inequities in higher education**.
842 -
843 ----
844 -
845 -## **Relevance to Subproject**
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**.
849 -
850 ----
851 -
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**.
856 -
857 ----
858 -
859 -## **Summary of Research Study**
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**.
861 -
862 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
863 -
864 ----
865 -
866 -## **📄 Download Full Study**
867 -[[Download Full Study>>attach:10.1037_dhe0000140.pdf]]
868 -
869 -{{/expand}}
870 -
871 -{{html}}<hr style="border: 3px solid red;">{{/html}}
872 -
873 -{{expand title="Study: Reconstructing Indian Population History" expanded="false"}}
113 +{{expandable summary="Study: Reconstructing Indian Population History"}}
874 874  **Source:** *Nature*
875 875  **Date of Publication:** *2009*
876 876  **Author(s):** *David Reich, Kumarasamy Thangaraj, Nick Patterson, Alkes L. Price, Lalji Singh*
877 877  **Title:** *"Reconstructing Indian Population History"*
878 878  **DOI:** [10.1038/nature08365](https://doi.org/10.1038/nature08365)
879 -**Subject Matter:** *Genetics, Population History, South Asian Ancestry*
119 +**Subject Matter:** *Genetics, Population History, South Asian Ancestry* 
880 880  
881 ----
882 -
883 -## **Key Statistics**
121 +{{expandable summary="📊 Key Statistics"}}
884 884  1. **General Observations:**
885 885   - Study analyzed **132 individuals from 25 diverse Indian groups**.
886 886   - Identified two major ancestral populations: **Ancestral North Indians (ANI)** and **Ancestral South Indians (ASI)**.
... ... @@ -892,10 +892,9 @@
892 892  3. **Other Significant Data Points:**
893 893   - ANI ancestry ranges from **39% to 71%** across Indian groups.
894 894   - **Caste and linguistic differences** strongly correlate with genetic variation.
133 +{{/expandable}}
895 895  
896 ----
897 -
898 -## **Findings**
135 +{{expandable summary="🔬 Findings"}}
899 899  1. **Primary Observations:**
900 900   - The genetic landscape of India has been shaped by **thousands of years of endogamy**.
901 901   - Groups with **only ASI ancestry no longer exist** in mainland India.
... ... @@ -907,10 +907,9 @@
907 907  3. **Specific Case Analysis:**
908 908   - **Founder effects** have maintained allele frequency differences among Indian groups.
909 909   - Predicts **higher incidence of recessive diseases** due to historical genetic isolation.
147 +{{/expandable}}
910 910  
911 ----
912 -
913 -## **Critique and Observations**
149 +{{expandable summary="📝 Critique & Observations"}}
914 914  1. **Strengths of the Study:**
915 915   - **First large-scale genetic analysis** of Indian population history.
916 916   - Introduces **new methods for ancestry estimation without direct ancestral reference groups**.
... ... @@ -922,49 +922,39 @@
922 922  3. **Suggestions for Improvement:**
923 923   - Future research should **expand sampling across more Indian tribal groups**.
924 924   - Use **whole-genome sequencing** for finer resolution of ancestry.
161 +{{/expandable}}
925 925  
926 ----
927 -
928 -## **Relevance to Subproject**
163 +{{expandable summary="📌 Relevance to Subproject"}}
929 929  - Provides a **genetic basis for caste and linguistic diversity** in India.
930 930  - Highlights **founder effects and genetic drift** shaping South Asian populations.
931 931  - Supports research on **medical genetics and disease risk prediction** in Indian populations.
167 +{{/expandable}}
932 932  
933 ----
934 -
935 -## **Suggestions for Further Exploration**
169 +{{expandable summary="🔍 Suggestions for Further Exploration"}}
936 936  1. Examine **genetic markers linked to disease susceptibility** in Indian subpopulations.
937 937  2. Investigate the impact of **recent migration patterns on ANI-ASI ancestry distribution**.
938 938  3. Study **gene flow between Indian populations and other global groups**.
173 +{{/expandable}}
939 939  
940 ----
941 -
942 -## **Summary of Research Study**
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**.
944 -
945 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
946 -
947 ----
948 -
949 -## **📄 Download Full Study**
175 +{{expandable summary="📄 Download Full Study"}}
950 950  [[Download Full Study>>attach:10.1038_nature08365.pdf]]
177 +##
178 + ##
179 +{{/expandable}}
180 +{{/expandable}}
951 951  
952 -{{/expand}}
182 +{{expandable summary="
953 953  
954 -{{html}}<hr style="border: 3px solid red;">{{/html}}
955 955  
956 -
957 -{{expand title="Study: The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations" expanded="false"}}
185 +Study: The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations"}}
958 958  **Source:** *Nature*
959 959  **Date of Publication:** *2016*
960 960  **Author(s):** *David Reich, Swapan Mallick, Heng Li, Mark Lipson, and others*
961 961  **Title:** *"The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations"*
962 962  **DOI:** [10.1038/nature18964](https://doi.org/10.1038/nature18964)
963 -**Subject Matter:** *Human Genetic Diversity, Population History, Evolutionary Genomics*
191 +**Subject Matter:** *Human Genetic Diversity, Population History, Evolutionary Genomics* 
964 964  
965 ----
966 -
967 -## **Key Statistics**
193 +{{expandable summary="📊 Key Statistics"}}
968 968  1. **General Observations:**
969 969   - Analyzed **high-coverage genome sequences of 300 individuals from 142 populations**.
970 970   - Included **many underrepresented and indigenous groups** from Africa, Asia, Europe, and the Americas.
... ... @@ -976,10 +976,9 @@
976 976  3. **Other Significant Data Points:**
977 977   - Identified **5.8 million base pairs absent from the human reference genome**.
978 978   - Estimated that **mutations have accumulated 5% faster in non-Africans than in Africans**.
205 +{{/expandable}}
979 979  
980 ----
981 -
982 -## **Findings**
207 +{{expandable summary="🔬 Findings"}}
983 983  1. **Primary Observations:**
984 984   - **African populations harbor the greatest genetic diversity**, confirming an out-of-Africa dispersal model.
985 985   - Indigenous Australians and New Guineans **share a common ancestral population with other non-Africans**.
... ... @@ -991,10 +991,9 @@
991 991  3. **Specific Case Analysis:**
992 992   - **Neanderthal ancestry is higher in East Asians than in Europeans**.
993 993   - African hunter-gatherer groups show **deep population splits over 100,000 years ago**.
219 +{{/expandable}}
994 994  
995 ----
996 -
997 -## **Critique and Observations**
221 +{{expandable summary="📝 Critique & Observations"}}
998 998  1. **Strengths of the Study:**
999 999   - **Largest global genetic dataset** outside of the 1000 Genomes Project.
1000 1000   - High sequencing depth allows **more accurate identification of genetic variants**.
... ... @@ -1006,48 +1006,39 @@
1006 1006  3. **Suggestions for Improvement:**
1007 1007   - Future studies should include **ancient genomes** to improve demographic modeling.
1008 1008   - Expand research into **how genetic variation affects health outcomes** across populations.
233 +{{/expandable}}
1009 1009  
1010 ----
1011 -
1012 -## **Relevance to Subproject**
235 +{{expandable summary="📌 Relevance to Subproject"}}
1013 1013  - Provides **comprehensive data on human genetic diversity**, useful for **evolutionary studies**.
1014 1014  - Supports research on **Neanderthal and Denisovan introgression** in modern human populations.
1015 1015  - Enhances understanding of **genetic adaptation and disease susceptibility across groups**.
239 +{{/expandable}}
1016 1016  
1017 ----
1018 -
1019 -## **Suggestions for Further Exploration**
241 +{{expandable summary="🔍 Suggestions for Further Exploration"}}
1020 1020  1. Investigate **functional consequences of genetic variation in underrepresented populations**.
1021 1021  2. Study **how selection pressures shaped genetic diversity across different environments**.
1022 1022  3. Explore **medical applications of population-specific genetic markers**.
245 +{{/expandable}}
1023 1023  
1024 ----
1025 -
1026 -## **Summary of Research Study**
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**.
1028 -
1029 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1030 -
1031 ----
1032 -
1033 -## **📄 Download Full Study**
247 +{{expandable summary="📄 Download Full Study"}}
1034 1034  [[Download Full Study>>attach:10.1038_nature18964.pdf]]
249 +##
250 + ##
251 +{{/expandable}}
252 +{{/expandable}}
1035 1035  
1036 -{{/expand}}
254 +{{expandable summary="
1037 1037  
1038 -{{html}}<hr style="border: 3px solid red;">{{/html}}
1039 1039  
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*
257 +Study: Meta-analysis of the heritability of human traits based on fifty years of twin studies"}}
258 +**Source:** *Nature Genetics*
259 +**Date of Publication:** *2015*
260 +**Author(s):** *Tinca J. C. Polderman, Beben Benyamin, Christiaan A. de Leeuw, Patrick F. Sullivan, Arjen van Bochoven, Peter M. Visscher, Danielle Posthuma*
261 +**Title:** *"Meta-analysis of the heritability of human traits based on fifty years of twin studies"*
262 +**DOI:** [10.1038/ng.328](https://doi.org/10.1038/ng.328)
263 +**Subject Matter:** *Genetics, Heritability, Twin Studies, Behavioral Science*
1047 1047  
1048 ----
1049 -
1050 -## **Key Statistics**
265 +{{expandable summary="📊 Key Statistics"}}
1051 1051  1. **General Observations:**
1052 1052   - Analyzed **17,804 traits from 2,748 twin studies** published between **1958 and 2012**.
1053 1053   - Included data from **14,558,903 twin pairs**, making it the largest meta-analysis on human heritability.
... ... @@ -1059,25 +1059,23 @@
1059 1059  3. **Other Significant Data Points:**
1060 1060   - **Neurological, metabolic, and psychiatric traits** showed the highest heritability estimates.
1061 1061   - Traits related to **social values and environmental interactions** had lower heritability estimates.
277 +{{/expandable}}
1062 1062  
1063 ----
1064 -
1065 -## **Findings**
279 +{{expandable summary="🔬 Findings"}}
1066 1066  1. **Primary Observations:**
1067 1067   - Across all traits, genetic factors play a significant role in individual differences.
1068 1068   - The study contradicts models that **overestimate environmental effects in behavioral and cognitive traits**.
1069 1069  
1070 1070  2. **Subgroup Trends:**
1071 - - **Eye and brain-related traits showed the highest heritability (~70-80%)**.
285 + - **Eye and brain-related traits showed the highest heritability (70-80%)**.
1072 1072   - **Shared environmental effects were negligible (<10%) for most traits**.
1073 1073  
1074 1074  3. **Specific Case Analysis:**
1075 1075   - Twin correlations suggest **limited evidence for strong non-additive genetic influences**.
1076 1076   - The study highlights **missing heritability in complex traits**, which genome-wide association studies (GWAS) have yet to fully explain.
291 +{{/expandable}}
1077 1077  
1078 ----
1079 -
1080 -## **Critique and Observations**
293 +{{expandable summary="📝 Critique & Observations"}}
1081 1081  1. **Strengths of the Study:**
1082 1082   - **Largest-ever heritability meta-analysis**, covering nearly all published twin studies.
1083 1083   - Provides a **comprehensive framework for understanding gene-environment contributions**.
... ... @@ -1089,48 +1089,37 @@
1089 1089  3. **Suggestions for Improvement:**
1090 1090   - Future research should use **whole-genome sequencing** for finer-grained heritability estimates.
1091 1091   - **Incorporate non-Western populations** to assess global heritability trends.
305 +{{/expandable}}
1092 1092  
1093 ----
1094 -
1095 -## **Relevance to Subproject**
307 +{{expandable summary="📌 Relevance to Subproject"}}
1096 1096  - Establishes a **quantitative benchmark for heritability across human traits**.
1097 1097  - Reinforces **genetic influence on cognitive, behavioral, and physical traits**.
1098 1098  - Highlights the need for **genome-wide studies to identify missing heritability**.
311 +{{/expandable}}
1099 1099  
1100 ----
1101 -
1102 -## **Suggestions for Further Exploration**
313 +{{expandable summary="🔍 Suggestions for Further Exploration"}}
1103 1103  1. Investigate how **heritability estimates compare across different socioeconomic backgrounds**.
1104 1104  2. Examine **gene-environment interactions in cognitive and psychiatric traits**.
1105 1105  3. Explore **non-additive genetic effects on human traits using newer statistical models**.
317 +{{/expandable}}
1106 1106  
1107 ----
1108 -
1109 -## **Summary of Research Study**
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.
1111 -
1112 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1113 -
1114 ----
1115 -
1116 -## **📄 Download Full Study**
319 +{{expandable summary="📄 Download Full Study"}}
1117 1117  [[Download Full Study>>attach:10.1038_ng.328.pdf]]
321 +{{/expandable}}
322 +{{/expandable}}
1118 1118  
1119 -{{/expand}}
324 +{{expandable summary="
1120 1120  
1121 -{{html}}<hr style="border: 3px solid red;">{{/html}}
1122 1122  
1123 -{{expand title="Study: Genetic Analysis of African Populations: Human Evolution and Complex Disease" expanded="false"}}
327 +Study: Genetic Analysis of African Populations: Human Evolution and Complex Disease"}}
1124 1124  **Source:** *Nature Reviews Genetics*
1125 1125  **Date of Publication:** *2002*
1126 1126  **Author(s):** *Sarah A. Tishkoff, Scott M. Williams*
1127 1127  **Title:** *"Genetic Analysis of African Populations: Human Evolution and Complex Disease"*
1128 1128  **DOI:** [10.1038/nrg865](https://doi.org/10.1038/nrg865)
1129 -**Subject Matter:** *Population Genetics, Human Evolution, Complex Diseases*
333 +**Subject Matter:** *Population Genetics, Human Evolution, Complex Diseases* 
1130 1130  
1131 ----
1132 -
1133 -## **Key Statistics**
335 +{{expandable summary="📊 Key Statistics"}}
1134 1134  1. **General Observations:**
1135 1135   - Africa harbors **the highest genetic diversity** of any region, making it key to understanding human evolution.
1136 1136   - The study analyzes **genetic variation and linkage disequilibrium (LD) in African populations**.
... ... @@ -1142,10 +1142,9 @@
1142 1142  3. **Other Significant Data Points:**
1143 1143   - The **effective population size (Ne) of Africans** is higher than that of non-African populations.
1144 1144   - LD blocks are **shorter in African genomes**, suggesting more historical recombination events.
347 +{{/expandable}}
1145 1145  
1146 ----
1147 -
1148 -## **Findings**
349 +{{expandable summary="🔬 Findings"}}
1149 1149  1. **Primary Observations:**
1150 1150   - African populations are the **most genetically diverse**, supporting the *Recent African Origin* hypothesis.
1151 1151   - Genetic variation in African populations can **help fine-map complex disease genes**.
... ... @@ -1157,10 +1157,9 @@
1157 1157  3. **Specific Case Analysis:**
1158 1158   - Admixture in African Americans includes **West African and European genetic contributions**.
1159 1159   - SNP (single nucleotide polymorphism) diversity in African genomes **exceeds that of non-African groups**.
361 +{{/expandable}}
1160 1160  
1161 ----
1162 -
1163 -## **Critique and Observations**
363 +{{expandable summary="📝 Critique & Observations"}}
1164 1164  1. **Strengths of the Study:**
1165 1165   - Provides **comprehensive genetic analysis** of diverse African populations.
1166 1166   - Highlights **how genetic diversity impacts health disparities and disease risks**.
... ... @@ -1172,300 +1172,599 @@
1172 1172  3. **Suggestions for Improvement:**
1173 1173   - Expand research into **underrepresented African populations**.
1174 1174   - Integrate **whole-genome sequencing for a more detailed evolutionary timeline**.
375 +{{/expandable}}
1175 1175  
1176 ----
1177 -
1178 -## **Relevance to Subproject**
377 +{{expandable summary="📌 Relevance to Subproject"}}
1179 1179  - Supports **genetic models of human evolution** and the **out-of-Africa hypothesis**.
1180 1180  - Reinforces **Africa’s key role in disease gene mapping and precision medicine**.
1181 1181  - Provides insight into **historical migration patterns and their genetic impact**.
381 +{{/expandable}}
1182 1182  
1183 ----
1184 -
1185 -## **Suggestions for Further Exploration**
383 +{{expandable summary="🔍 Suggestions for Further Exploration"}}
1186 1186  1. Investigate **genetic adaptations to local environments within Africa**.
1187 1187  2. Study **the role of African genetic diversity in disease resistance**.
1188 1188  3. Expand research on **how ancient migration patterns shaped modern genetic structure**.
387 +{{/expandable}}
1189 1189  
1190 ----
389 +{{expandable summary="📄 Download Full Study"}}
390 +[[Download Full Study>>attach:10.1038_nrg865MODERN.pdf]]
391 +{{/expandable}}
392 +{{/expandable}}
1191 1191  
1192 -## **Summary of Research Study**
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**.
394 +{{expandable summary="
1194 1194  
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.
1196 1196  
1197 ----
397 +Study: Pervasive Findings of Directional Selection in Ancient DNA"}}
398 +**Source:** *bioRxiv Preprint*
399 +**Date of Publication:** *September 15, 2024*
400 +**Author(s):** *Ali Akbari, Alison R. Barton, Steven Gazal, Zheng Li, Mohammadreza Kariminejad, et al.*
401 +**Title:** *"Pervasive findings of directional selection realize the promise of ancient DNA to elucidate human adaptation"*
402 +**DOI:** [10.1101/2024.09.14.613021](https://doi.org/10.1101/2024.09.14.613021)
403 +**Subject Matter:** *Genomics, Evolutionary Biology, Natural Selection*
1198 1198  
1199 -## **📄 Download Full Study**
1200 -[[Download Full Study>>attach:10.1038_nrg865MODERN.pdf]]
405 +{{expandable summary="📊 Key Statistics"}}
406 +1. **General Observations:**
407 + - Study analyzes **8,433 ancient individuals** from the past **14,000 years**.
408 + - Identifies **347 genome-wide significant loci** showing strong selection.
1201 1201  
1202 -{{/expand}}
410 +2. **Subgroup Analysis:**
411 + - Examines **West Eurasian populations** and their genetic evolution.
412 + - Tracks **changes in allele frequencies over millennia**.
1203 1203  
1204 -{{html}}<hr style="border: 3px solid red;">{{/html}}
414 +3. **Other Significant Data Points:**
415 + - **10,000 years of directional selection** affected metabolic, immune, and cognitive traits.
416 + - **Strong selection signals** found for traits like **skin pigmentation, cognitive function, and immunity**.
417 +{{/expandable}}
1205 1205  
419 +{{expandable summary="🔬 Findings"}}
420 +1. **Primary Observations:**
421 + - **Hundreds of alleles have been subject to directional selection** over recent millennia.
422 + - Traits like **immune function, metabolism, and cognitive performance** show strong selection.
1206 1206  
424 +2. **Subgroup Trends:**
425 + - Selection pressure on **energy storage genes** supports the **Thrifty Gene Hypothesis**.
426 + - **Cognitive performance-related alleles** have undergone selection, but their historical advantages remain unclear.
1207 1207  
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*
428 +3. **Specific Case Analysis:**
429 + - **Celiac disease risk allele** increased from **0% to 20%** in 4,000 years.
430 + - **Blood type B frequency rose from 0% to 8% in 6,000 years**.
431 + - **Tuberculosis risk allele** fluctuated from **2% to 9% over 3,000 years before declining**.
432 +{{/expandable}}
1215 1215  
1216 ----
434 +{{expandable summary="📝 Critique & Observations"}}
435 +1. **Strengths of the Study:**
436 + - **Largest dataset to date** on natural selection in human ancient DNA.
437 + - Uses **direct allele frequency tracking instead of indirect measures**.
1217 1217  
1218 -## **Key Statistics**
439 +2. **Limitations of the Study:**
440 + - Findings **may not translate directly** to modern populations.
441 + - **Unclear whether observed selection pressures persist today**.
442 +
443 +3. **Suggestions for Improvement:**
444 + - Expanding research to **other global populations** to assess universal trends.
445 + - Investigating **long-term evolutionary trade-offs of selected alleles**.
446 +{{/expandable}}
447 +
448 +{{expandable summary="📌 Relevance to Subproject"}}
449 +- Provides **direct evidence of long-term genetic adaptation** in human populations.
450 +- Supports theories on **polygenic selection shaping human cognition, metabolism, and immunity**.
451 +- Highlights **how past selection pressures may still influence modern health and disease prevalence**.
452 +{{/expandable}}
453 +
454 +{{expandable summary="🔍 Suggestions for Further Exploration"}}
455 +1. Examine **selection patterns in non-European populations** for comparison.
456 +2. Investigate **how environmental and cultural shifts influenced genetic selection**.
457 +3. Explore **the genetic basis of traits linked to past and present-day human survival**.
458 +{{/expandable}}
459 +
460 +{{expandable summary="📄 Download Full Study"}}
461 +[[Download Full Study>>attach:10.1101_2024.09.14.613021doi_.pdf]]
462 +{{/expandable}}
463 +{{/expandable}}
464 +
465 +{{expandable summary="
466 +
467 +
468 +Study: The Wilson Effect: The Increase in Heritability of IQ With Age"}}
469 +**Source:** *Twin Research and Human Genetics (Cambridge University Press)*
470 +**Date of Publication:** *2013*
471 +**Author(s):** *Thomas J. Bouchard Jr.*
472 +**Title:** *"The Wilson Effect: The Increase in Heritability of IQ With Age"*
473 +**DOI:** [10.1017/thg.2013.54](https://doi.org/10.1017/thg.2013.54)
474 +**Subject Matter:** *Intelligence, Heritability, Developmental Psychology*
475 +
476 +{{expandable summary="📊 Key Statistics"}}
1219 1219  1. **General Observations:**
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.
478 + - The study documents how the **heritability of IQ increases with age**, reaching an asymptote at **0.80 by adulthood**.
479 + - Analysis is based on **longitudinal twin and adoption studies**.
1222 1222  
1223 1223  2. **Subgroup Analysis:**
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**.
482 + - Shared environmental influence on IQ **declines with age**, reaching **0.10 in adulthood**.
483 + - Monozygotic twins show **increasing genetic similarity in IQ over time**, while dizygotic twins become **less concordant**.
1226 1226  
1227 1227  3. **Other Significant Data Points:**
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**.
486 + - Data from the **Louisville Longitudinal Twin Study and cross-national twin samples** support findings.
487 + - IQ stability over time is **influenced more by genetics than by shared environmental factors**.
488 +{{/expandable}}
1230 1230  
1231 ----
1232 -
1233 -## **Findings**
490 +{{expandable summary="🔬 Findings"}}
1234 1234  1. **Primary Observations:**
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**.
492 + - Intelligence heritability **strengthens throughout development**, contrary to early environmental models.
493 + - Shared environmental effects **decrease by late adolescence**, emphasizing **genetic influence in adulthood**.
1237 1237  
1238 1238  2. **Subgroup Trends:**
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.
496 + - Studies from **Scotland, Netherlands, and the US** show **consistent patterns of increasing heritability with age**.
497 + - Findings hold across **varied socio-economic and educational backgrounds**.
1241 1241  
1242 1242  3. **Specific Case Analysis:**
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**.
500 + - Longitudinal adoption studies show **declining impact of adoptive parental influence on IQ** as children age.
501 + - Cross-sectional twin data confirm **higher IQ correlations for monozygotic twins in adulthood**.
502 +{{/expandable}}
1245 1245  
1246 ----
1247 -
1248 -## **Critique and Observations**
504 +{{expandable summary="📝 Critique & Observations"}}
1249 1249  1. **Strengths of the Study:**
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.
506 + - **Robust dataset covering multiple twin and adoption studies over decades**.
507 + - **Clear, replicable trend** demonstrating the increasing role of genetics in intelligence.
1252 1252  
1253 1253  2. **Limitations of the Study:**
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**.
510 + - Findings apply primarily to **Western industrialized nations**, limiting generalizability.
511 + - **Lack of neurobiological mechanisms** explaining how genes express their influence over time.
1256 1256  
1257 1257  3. **Suggestions for Improvement:**
1258 - - Future research should examine **how these biases manifest in real clinical settings**.
1259 - - Investigate **whether medical training can correct these biases over time**.
514 + - Future research should investigate **gene-environment interactions in cognitive aging**.
515 + - Examine **heritability trends in non-Western populations** to determine cross-cultural consistency.
516 +{{/expandable}}
1260 1260  
1261 ----
518 +{{expandable summary="📌 Relevance to Subproject"}}
519 +- Provides **strong evidence for the genetic basis of intelligence**.
520 +- Highlights the **diminishing role of shared environment in cognitive development**.
521 +- Supports research on **cognitive aging and heritability across the lifespan**.
522 +{{/expandable}}
1262 1262  
1263 -## **Relevance to Subproject**
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**.
524 +{{expandable summary="🔍 Suggestions for Further Exploration"}}
525 +1. Investigate **neurogenetic pathways underlying IQ development**.
526 +2. Examine **how education and socioeconomic factors interact with genetic IQ influences**.
527 +3. Study **heritability trends in aging populations and cognitive decline**.
528 +{{/expandable}}
1267 1267  
1268 ----
530 +{{expandable summary="📄 Download Full Study"}}
531 +[[Download Full Study>>attach:10.1017_thg.2013.54.pdf]]
532 +{{/expandable}}
533 +{{/expandable}}
1269 1269  
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**.
535 +{{expandable summary="
1274 1274  
1275 ----
1276 1276  
1277 -## **Summary of Research Study**
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**.
538 +Study: Is Homo sapiens polytypic? Human taxonomic diversity and its implications"}}
539 +**Source:** *Medical Hypotheses (Elsevier)*
540 +**Date of Publication:** *2010*
541 +**Author(s):** *Michael A. Woodley*
542 +**Title:** *"Is Homo sapiens polytypic? Human taxonomic diversity and its implications"*
543 +**DOI:** [10.1016/j.mehy.2009.07.046](https://doi.org/10.1016/j.mehy.2009.07.046)
544 +**Subject Matter:** *Human Taxonomy, Evolutionary Biology, Anthropology*
1279 1279  
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.
546 +{{expandable summary="📊 Key Statistics"}}
547 +1. **General Observations:**
548 + - The study argues that **Homo sapiens is polytypic**, meaning it consists of multiple subspecies rather than a single monotypic species.
549 + - Examines **genetic diversity, morphological variation, and evolutionary lineage** in humans.
1281 1281  
1282 ----
551 +2. **Subgroup Analysis:**
552 + - Discusses **four primary definitions of race/subspecies**: Essentialist, Taxonomic, Population-based, and Lineage-based.
553 + - Suggests that **human heterozygosity levels are comparable to species that are classified as polytypic**.
1283 1283  
1284 -## **📄 Download Full Study**
1285 -[[Download Full Study>>attach:10.1073_pnas.1516047113.pdf]]
555 +3. **Other Significant Data Points:**
556 + - The study evaluates **FST values (genetic differentiation measure)** and argues that human genetic differentiation is comparable to that of recognized subspecies in other species.
557 + - Considers **phylogenetic species concepts** in defining human variation.
558 +{{/expandable}}
1286 1286  
1287 -{{/expand}}
560 +{{expandable summary="🔬 Findings"}}
561 +1. **Primary Observations:**
562 + - Proposes that **modern human populations meet biological criteria for subspecies classification**.
563 + - Highlights **medical and evolutionary implications** of human taxonomic diversity.
1288 1288  
1289 -{{html}}<hr style="border: 3px solid red;">{{/html}}
565 +2. **Subgroup Trends:**
566 + - Discusses **how race concepts evolved over time** in biological sciences.
567 + - Compares **human diversity with that of other primates** such as chimpanzees and gorillas.
1290 1290  
569 +3. **Specific Case Analysis:**
570 + - Evaluates how **genetic markers correlate with population structure**.
571 + - Addresses the **controversy over race classification in modern anthropology**.
572 +{{/expandable}}
1291 1291  
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*
574 +{{expandable summary="📝 Critique & Observations"}}
575 +1. **Strengths of the Study:**
576 + - Uses **comparative species analysis** to assess human classification.
577 + - Provides a **biological perspective** on the race concept, moving beyond social constructivism arguments.
1299 1299  
1300 ----
579 +2. **Limitations of the Study:**
580 + - Controversial topic with **strong opposing views in anthropology and genetics**.
581 + - **Relies on broad genetic trends**, but does not analyze individual-level genetic variation in depth.
1301 1301  
1302 -## **Key Statistics**
583 +3. **Suggestions for Improvement:**
584 + - Further research should **incorporate whole-genome studies** to refine subspecies classifications.
585 + - Investigate **how admixture affects taxonomic classification over time**.
586 +{{/expandable}}
587 +
588 +{{expandable summary="📌 Relevance to Subproject"}}
589 +- Contributes to discussions on **evolutionary taxonomy and species classification**.
590 +- Provides evidence on **genetic differentiation among human populations**.
591 +- Highlights **historical and contemporary scientific debates on race and human variation**.
592 +{{/expandable}}
593 +
594 +{{expandable summary="🔍 Suggestions for Further Exploration"}}
595 +1. Examine **FST values in modern and ancient human populations**.
596 +2. Investigate how **adaptive evolution influences population differentiation**.
597 +3. Explore **the impact of genetic diversity on medical treatments and disease susceptibility**.
598 +{{/expandable}}
599 +
600 +{{expandable summary="📄 Download Full Study"}}
601 +[[Download Full Study>>attach:10.1016_j.mehy.2009.07.046.pdf]]
602 +{{/expandable}}
603 +{{/expandable}}
604 +
605 += IQ =
606 +
607 +{{expandable summary="Study: Survey of Expert Opinion on Intelligence: Intelligence Research, Experts' Background, Controversial Issues, and the Media"}}
608 +**Source:** *Intelligence (Elsevier)*
609 +**Date of Publication:** *2019*
610 +**Author(s):** *Heiner Rindermann, David Becker, Thomas R. Coyle*
611 +**Title:** *"Survey of Expert Opinion on Intelligence: Intelligence Research, Experts' Background, Controversial Issues, and the Media"*
612 +**DOI:** [10.1016/j.intell.2019.101406](https://doi.org/10.1016/j.intell.2019.101406)
613 +**Subject Matter:** *Psychology, Intelligence Research, Expert Analysis*
614 +
615 +{{expandable summary="📊 Key Statistics"}}
1303 1303  1. **General Observations:**
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**.
617 + - Survey of **102 experts** on intelligence research and public discourse.
618 + - Evaluated experts' backgrounds, political affiliations, and views on controversial topics in intelligence research.
1306 1306  
1307 1307  2. **Subgroup Analysis:**
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.
621 + - **90% of experts were from Western countries**, and **83% were male**.
622 + - Political spectrum ranged from **54% left-liberal, 24% conservative**, with significant ideological influences on views.
1310 1310  
1311 1311  3. **Other Significant Data Points:**
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**.
625 + - Experts rated media coverage of intelligence research as **poor (avg. 3.1 on a 9-point scale)**.
626 + - **50% of experts attributed US Black-White IQ differences to genetic factors, 50% to environmental factors**.
627 +{{/expandable}}
1314 1314  
1315 ----
1316 -
1317 -## **Findings**
629 +{{expandable summary="🔬 Findings"}}
1318 1318  1. **Primary Observations:**
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**.
631 + - Experts overwhelmingly support **the g-factor theory of intelligence**.
632 + - **Heritability of intelligence** was widely accepted, though views differed on race and group differences.
1321 1321  
1322 1322  2. **Subgroup Trends:**
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**.
635 + - **Left-leaning experts were more likely to reject genetic explanations for group IQ differences**.
636 + - **Right-leaning experts tended to favor a stronger role for genetic factors** in intelligence disparities.
1325 1325  
1326 1326  3. **Specific Case Analysis:**
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.
639 + - The study compared **media coverage of intelligence research** with expert opinions.
640 + - Found a **disconnect between journalists and intelligence researchers**, especially regarding politically sensitive issues.
641 +{{/expandable}}
1329 1329  
1330 ----
1331 -
1332 -## **Critique and Observations**
643 +{{expandable summary="📝 Critique & Observations"}}
1333 1333  1. **Strengths of the Study:**
1334 - - **First major study to highlight rising midlife mortality among U.S. whites**.
1335 - - Uses **CDC and Census mortality data spanning over a decade**.
645 + - **Largest expert survey on intelligence research** to date.
646 + - Provides insight into **how political orientation influences scientific perspectives**.
1336 1336  
1337 1337  2. **Limitations of the Study:**
1338 - - Does not establish **causality** between economic decline and increased mortality.
1339 - - Lacks **granular data on opioid prescribing patterns and regional differences**.
649 + - **Sample primarily from Western countries**, limiting global perspectives.
650 + - Self-selection bias may skew responses toward **those more willing to engage with controversial topics**.
1340 1340  
1341 1341  3. **Suggestions for Improvement:**
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.
653 + - Future studies should include **a broader range of global experts**.
654 + - Additional research needed on **media biases and misrepresentation of intelligence research**.
655 +{{/expandable}}
1344 1344  
1345 ----
657 +{{expandable summary="📌 Relevance to Subproject"}}
658 +- Provides insight into **expert consensus and division on intelligence research**.
659 +- Highlights the **role of media bias** in shaping public perception of intelligence science.
660 +- Useful for understanding **the intersection of science, politics, and public discourse** on intelligence research.
661 +{{/expandable}}
1346 1346  
1347 -## **Relevance to Subproject**
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**.
663 +{{expandable summary="🔍 Suggestions for Further Exploration"}}
664 +1. Examine **cross-national differences** in expert opinions on intelligence.
665 +2. Investigate how **media bias impacts public understanding of intelligence research**.
666 +3. Conduct follow-up studies with **a more diverse expert pool** to test findings.
667 +{{/expandable}}
1351 1351  
1352 ----
669 +{{expandable summary="📄 Download Full Study"}}
670 +[[Download Full Study>>attach:10.1016_j.intell.2019.101406.pdf]]
671 +{{/expandable}}
672 +{{/expandable}}
1353 1353  
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**.
674 +{{expandable summary="Study: A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation"}}
675 +**Source:** *Intelligence (Elsevier)*
676 +**Date of Publication:** *2015*
677 +**Author(s):** *Davide Piffer*
678 +**Title:** *"A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation"*
679 +**DOI:** [10.1016/j.intell.2015.08.008](https://doi.org/10.1016/j.intell.2015.08.008)
680 +**Subject Matter:** *Genetics, Intelligence, GWAS, Population Differences*
1358 1358  
1359 ----
682 +{{expandable summary="📊 Key Statistics"}}
683 +1. **General Observations:**
684 + - Study analyzed **genome-wide association studies (GWAS) hits** linked to intelligence.
685 + - Found a **strong correlation (r = .91) between polygenic intelligence scores and national IQ levels**.
1360 1360  
1361 -## **Summary of Research Study**
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**.
687 +2. **Subgroup Analysis:**
688 + - Factor analysis of **9 intelligence-associated alleles** revealed a metagene correlated with **country IQ (r = .86)**.
689 + - **Allele frequencies varied significantly by continent**, aligning with observed population differences in cognitive ability.
1363 1363  
1364 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
691 +3. **Other Significant Data Points:**
692 + - GWAS intelligence SNPs predicted **IQ levels more strongly than random genetic markers**.
693 + - Genetic differentiation (Fst values) showed that **selection pressure, rather than drift, influenced intelligence-related allele distributions**.
694 +{{/expandable}}
1365 1365  
1366 ----
696 +{{expandable summary="🔬 Findings"}}
697 +1. **Primary Observations:**
698 + - Intelligence-associated SNP frequencies correlate **highly with national IQ levels**.
699 + - Genetic selection for intelligence appears **stronger than selection for height-related genes**.
1367 1367  
1368 -## **📄 Download Full Study**
1369 -[[Download Full Study>>attach:10.1073_pnas.1518393112.pdf]]
701 +2. **Subgroup Trends:**
702 + - **East Asian populations** exhibited the **highest frequencies of intelligence-associated alleles**.
703 + - **African populations** showed lower frequencies compared to European and East Asian populations.
1370 1370  
1371 -{{/expand}}
705 +3. **Specific Case Analysis:**
706 + - Polygenic scores using **intelligence-related alleles significantly outperformed random SNPs** in predicting IQ.
707 + - Selection pressures **may explain differences in global intelligence distribution** beyond genetic drift effects.
708 +{{/expandable}}
1372 1372  
1373 -{{html}}<hr style="border: 3px solid red;">{{/html}}
710 +{{expandable summary="📝 Critique & Observations"}}
711 +1. **Strengths of the Study:**
712 + - **Comprehensive genetic analysis** of intelligence-linked SNPs.
713 + - Uses **multiple statistical methods (factor analysis, Fst analysis) to confirm results**.
1374 1374  
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*
715 +2. **Limitations of the Study:**
716 + - **Correlation does not imply causation**; factors beyond genetics influence intelligence.
717 + - **Limited number of GWAS-identified intelligence alleles**—future studies may identify more.
1382 1382  
1383 ----
719 +3. **Suggestions for Improvement:**
720 + - Larger **cross-population GWAS studies** needed to validate findings.
721 + - Investigate **non-genetic contributors to IQ variance** in addition to genetic factors.
722 +{{/expandable}}
1384 1384  
1385 -## **Key Statistics**
724 +{{expandable summary="📌 Relevance to Subproject"}}
725 +- Supports research on **genetic influences on intelligence at a population level**.
726 +- Aligns with broader discussions on **cognitive genetics and natural selection effects**.
727 +- Provides a **quantitative framework for analyzing polygenic selection in intelligence studies**.
728 +{{/expandable}}
729 +
730 +{{expandable summary="🔍 Suggestions for Further Exploration"}}
731 +1. Conduct **expanded GWAS studies** including diverse populations.
732 +2. Investigate **gene-environment interactions influencing intelligence**.
733 +3. Explore **historical selection pressures shaping intelligence-related alleles**.
734 +{{/expandable}}
735 +
736 +{{expandable summary="📄 Download Full Study"}}
737 +[[Download Full Study>>attach:10.1016_j.intell.2015.08.008.pdf]]
738 +{{/expandable}}
739 +{{/expandable}}
740 +
741 +{{expandable summary="Study: Genetic Structure, Self-Identified Race/Ethnicity, and Confounding"}}
742 +**Source:** Journal of Genetic Epidemiology
743 +**Date of Publication:** 2024-01-15
744 +**Author(s):** Smith et al.
745 +**Title:** "Genetic Structure, Self-Identified Race/Ethnicity, and Confounding in Case-Control Association Studies"
746 +**DOI:** [https://doi.org/10.1037/1076-8971.11.2.235](https://doi.org/10.1037/1076-8971.11.2.235)
747 +**Subject Matter:** Genetics, Social Science
748 +{{/expandable}}
749 +
750 += Dating =
751 +
752 +{{expandable summary="Study: Trends in Frequency of Sexual Activity and Number of Sexual Partners Among Adults Aged 18 to 44 Years in the US, 2000-2018"}}
753 +**Source:** *JAMA Network Open*
754 +**Date of Publication:** *2020*
755 +**Author(s):** *Ueda P, Mercer CH, Ghaznavi C, Herbenick D.*
756 +**Title:** *"Trends in Frequency of Sexual Activity and Number of Sexual Partners Among Adults Aged 18 to 44 Years in the US, 2000-2018"*
757 +**DOI:** [10.1001/jamanetworkopen.2020.3833](https://doi.org/10.1001/jamanetworkopen.2020.3833)
758 +**Subject Matter:** *Public Health, Sexual Behavior, Demography* 
759 +
760 +{{expandable summary="📊 Key Statistics"}}
1386 1386  1. **General Observations:**
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.
762 + - Study analyzed **General Social Survey (2000-2018)** data.
763 + - Found **declining trends in sexual activity** among young adults.
1389 1389  
1390 1390  2. **Subgroup Analysis:**
1391 - - Explores differences in **integration, social interactions, and perceptions of diversity**.
1392 - - Studies how **class, education, and neighborhood composition** affect adaptation to urban diversity.
766 + - Decreases in sexual activity were most prominent among **men aged 18-34**.
767 + - Factors like **marital status, employment, and psychological well-being** were associated with changes in sexual frequency.
1393 1393  
1394 1394  3. **Other Significant Data Points:**
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.
770 + - Frequency of sexual activity decreased by **8-10%** over the studied period.
771 + - Number of sexual partners remained **relatively stable** despite declining activity rates.
772 +{{/expandable}}
1397 1397  
1398 ----
1399 -
1400 -## **Findings**
774 +{{expandable summary="🔬 Findings"}}
1401 1401  1. **Primary Observations:**
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.
776 + - A significant decline in sexual frequency, especially among **younger men**.
777 + - Shifts in relationship dynamics and economic stressors may contribute to the trend.
1404 1404  
1405 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**.
780 + - More pronounced decline among **unmarried individuals**.
781 + - No major change observed for **married adults** over time.
1408 1408  
1409 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**.
784 + - **Mental health and employment status** were correlated with decreased activity.
785 + - Social factors such as **screen time and digital entertainment consumption** are potential contributors.
786 +{{/expandable}}
1412 1412  
1413 ----
788 +{{expandable summary="📝 Critique & Observations"}}
789 +1. **Strengths of the Study:**
790 + - **Large sample size** from a nationally representative dataset.
791 + - **Longitudinal design** enables trend analysis over time.
1414 1414  
1415 -## **Critique and Observations**
793 +2. **Limitations of the Study:**
794 + - Self-reported data may introduce **response bias**.
795 + - No direct causal mechanisms tested for the decline in sexual activity.
796 +
797 +3. **Suggestions for Improvement:**
798 + - Further studies should incorporate **qualitative data** on behavioral shifts.
799 + - Additional factors such as **economic shifts and social media usage** need exploration.
800 +{{/expandable}}
801 +
802 +{{expandable summary="📌 Relevance to Subproject"}}
803 +- Provides evidence on **changing demographic behaviors** in relation to relationships and social interactions.
804 +- Highlights the role of **mental health, employment, and societal changes** in personal behaviors.
805 +{{/expandable}}
806 +
807 +{{expandable summary="🔍 Suggestions for Further Exploration"}}
808 +1. Investigate the **impact of digital media consumption** on relationship dynamics.
809 +2. Examine **regional and cultural differences** in sexual activity trends.
810 +{{/expandable}}
811 +
812 +{{expandable summary="📄 Download Full Study"}}
813 +
814 +{{/expandable}}
815 +{{/expandable}}
816 +
817 +{{expandable summary="Study: Biracial Couples and Adverse Birth Outcomes – A Systematic Review and Meta-Analysis"}}
818 +**Source:** *Acta Obstetricia et Gynecologica Scandinavica*
819 +**Date of Publication:** *2012*
820 +**Author(s):** *Ravisha M. Srinivasjois, Shreya Shah, Prakesh S. Shah, Knowledge Synthesis Group on Determinants of Preterm/LBW Births*
821 +**Title:** *"Biracial Couples and Adverse Birth Outcomes: A Systematic Review and Meta-Analysis"*
822 +**DOI:** [10.1111/j.1600-0412.2012.01501.x](https://doi.org/10.1111/j.1600-0412.2012.01501.x)
823 +**Subject Matter:** *Neonatal Health, Maternal-Fetal Medicine, Racial Disparities*
824 +
825 +{{expandable summary="📊 Key Statistics"}}
826 +1. **General Observations:**
827 + - Meta-analysis of **26,335,596 singleton births** from eight studies.
828 + - **Higher risk of adverse birth outcomes in biracial couples** than White couples, but lower than Black couples.
829 +
830 +2. **Subgroup Analysis:**
831 + - **Maternal race had a stronger influence than paternal race** on birth outcomes.
832 + - **Black mother–White father (BMWF) couples** had a higher risk than **White mother–Black father (WMBF) couples**.
833 +
834 +3. **Other Significant Data Points:**
835 + - **Adjusted Odds Ratios (aORs) for key outcomes:**
836 + - **Low birthweight (LBW):** WMBF (1.21), BMWF (1.75), Black mother–Black father (BMBF) (2.08).
837 + - **Preterm births (PTB):** WMBF (1.17), BMWF (1.37), BMBF (1.78).
838 + - **Stillbirths:** WMBF (1.43), BMWF (1.51), BMBF (1.85).
839 +{{/expandable}}
840 +
841 +{{expandable summary="🔬 Findings"}}
842 +1. **Primary Observations:**
843 + - **Biracial couples face a gradient of risk**: higher than White couples but lower than Black couples.
844 + - **Maternal race plays a more significant role** in pregnancy outcomes.
845 +
846 +2. **Subgroup Trends:**
847 + - **Black mothers (regardless of paternal race) had the highest risk of LBW and PTB**.
848 + - **White mothers with Black fathers had a lower risk** than Black mothers with White fathers.
849 +
850 +3. **Specific Case Analysis:**
851 + - The **weathering hypothesis** suggests that **long-term stress exposure** contributes to higher adverse birth risks in Black mothers.
852 + - **Genetic and environmental factors** may interact to influence birth outcomes.
853 +{{/expandable}}
854 +
855 +{{expandable summary="📝 Critique & Observations"}}
1416 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.
857 + - **Largest meta-analysis** on racial disparities in birth outcomes.
858 + - Uses **adjusted statistical models** to account for confounding variables.
1419 1419  
1420 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**.
861 + - Data limited to **Black-White biracial couples**, excluding other racial groups.
862 + - **Socioeconomic and healthcare access factors** not fully explored.
1423 1423  
1424 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**.
865 + - Future studies should examine **Asian, Hispanic, and Indigenous biracial couples**.
866 + - Investigate **long-term health effects on infants from biracial pregnancies**.
867 +{{/expandable}}
1427 1427  
1428 ----
869 +{{expandable summary="📌 Relevance to Subproject"}}
870 +- Provides **critical insights into racial disparities** in maternal and infant health.
871 +- Supports **research on genetic and environmental influences on neonatal health**.
872 +- Highlights **how maternal race plays a more significant role than paternal race** in birth outcomes.
873 +{{/expandable}}
1429 1429  
1430 -## **Relevance to Subproject**
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**.
875 +{{expandable summary="🔍 Suggestions for Further Exploration"}}
876 +1. Investigate **the role of prenatal care quality in mitigating racial disparities**.
877 +2. Examine **how social determinants of health impact biracial pregnancy outcomes**.
878 +3. Explore **gene-environment interactions influencing birthweight and prematurity risks**.
879 +{{/expandable}}
1434 1434  
1435 ----
881 +{{expandable summary="📄 Download Full Study"}}
882 +[[Download Full Study>>attach:10.1111_j.1600-0412.2012.01501.xAbstract.pdf]]
883 +{{/expandable}}
884 +{{/expandable}}
1436 1436  
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**.
886 +{{expandable summary="
1441 1441  
1442 ----
1443 1443  
1444 -## **Summary of Research Study**
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**.
889 +Study: One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness"}}
890 +**Source:** *Current Psychology*
891 +**Date of Publication:** *2024*
892 +**Author(s):** *Brandon Sparks, Alexandra M. Zidenberg, Mark E. Olver*
893 +**Title:** *"One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness"*
894 +**DOI:** [10.1007/s12144-023-04275-z](https://doi.org/10.1007/s12144-023-04275-z)
895 +**Subject Matter:** *Psychology, Mental Health, Social Isolation* 
1446 1446  
1447 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
897 +{{expandable summary="📊 Key Statistics"}}
898 +1. **General Observations:**
899 + - Study analyzed **67 self-identified incels** and **103 non-incel men**.
900 + - Incels reported **higher loneliness and lower social support** compared to non-incels.
1448 1448  
1449 ----
902 +2. **Subgroup Analysis:**
903 + - Incels exhibited **higher levels of depression, anxiety, and self-critical rumination**.
904 + - **Social isolation was a key factor** differentiating incels from non-incels.
1450 1450  
1451 -## **📄 Download Full Study**
1452 -[[Download Full Study>>attach:10.1080_1369183X.2023.2182548.pdf]]
906 +3. **Other Significant Data Points:**
907 + - 95% of incels in the study reported **having depression**, with 38% receiving a formal diagnosis.
908 + - **Higher externalization of blame** was linked to stronger incel identification.
909 +{{/expandable}}
1453 1453  
1454 -{{/expand}}
911 +{{expandable summary="🔬 Findings"}}
912 +1. **Primary Observations:**
913 + - Incels experience **heightened rejection sensitivity and loneliness**.
914 + - Lack of social support correlates with **worse mental health outcomes**.
1455 1455  
1456 -{{html}}<hr style="border: 3px solid red;">{{/html}}
916 +2. **Subgroup Trends:**
917 + - **Avoidant attachment styles** were a strong predictor of incel identity.
918 + - **Mate value perceptions** significantly differed between incels and non-incels.
1457 1457  
1458 -{{expand title="Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program" expanded="false"}}
1459 -**Source:** *Substance Use & Misuse*
1460 -**Date of Publication:** *2002*
1461 -**Author(s):** *Clifford A. Butzin, Christine A. Saum, Frank R. Scarpitti*
1462 -**Title:** *"Factors Associated with Completion of a Drug Treatment Court Diversion Program"*
1463 -**DOI:** [10.1081/JA-120014424](https://doi.org/10.1081/JA-120014424)
1464 -**Subject Matter:** *Substance Use, Criminal Justice, Drug Courts*
920 +3. **Specific Case Analysis:**
921 + - Incels **engaged in fewer positive coping mechanisms** such as emotional support or positive reframing.
922 + - Instead, they relied on **solitary coping strategies**, worsening their isolation.
923 +{{/expandable}}
1465 1465  
1466 ----
925 +{{expandable summary="📝 Critique & Observations"}}
926 +1. **Strengths of the Study:**
927 + - **First quantitative study** on incels’ social isolation and mental health.
928 + - **Robust sample size** and validated psychological measures.
1467 1467  
1468 -## **Key Statistics**
930 +2. **Limitations of the Study:**
931 + - Sample drawn from **Reddit communities**, which may not represent all incels.
932 + - **No causal conclusions**—correlations between isolation and inceldom need further research.
933 +
934 +3. **Suggestions for Improvement:**
935 + - Future studies should **compare incel forum users vs. non-users**.
936 + - Investigate **potential intervention strategies** for social integration.
937 +{{/expandable}}
938 +
939 +{{expandable summary="📌 Relevance to Subproject"}}
940 +- Highlights **mental health vulnerabilities** within the incel community.
941 +- Supports research on **loneliness, attachment styles, and social dominance orientation**.
942 +- Examines how **peer rejection influences self-perceived mate value**.
943 +{{/expandable}}
944 +
945 +{{expandable summary="🔍 Suggestions for Further Exploration"}}
946 +1. Explore how **online community participation** affects incel mental health.
947 +2. Investigate **cognitive biases** influencing self-perceived rejection among incels.
948 +3. Assess **therapeutic interventions** to address incel social isolation.
949 +{{/expandable}}
950 +
951 +{{expandable summary="📄 Download Full Study"}}
952 +[[Download Full Study>>attach:10.1007_s12144-023-04275-z.pdf]]
953 +{{/expandable}}
954 +
955 += Crime and Substance Abuse =
956 +
957 +{{/expandable}}
958 +
959 +{{expandable summary="Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program"}}
960 +**Source:** *Substance Use & Misuse*
961 +**Date of Publication:** *2002*
962 +**Author(s):** *Clifford A. Butzin, Christine A. Saum, Frank R. Scarpitti*
963 +**Title:** *"Factors Associated with Completion of a Drug Treatment Court Diversion Program"*
964 +**DOI:** [10.1081/JA-120014424](https://doi.org/10.1081/JA-120014424)
965 +**Subject Matter:** *Substance Use, Criminal Justice, Drug Courts*
966 +
967 +{{expandable summary="📊 Key Statistics"}}
1469 1469  1. **General Observations:**
1470 1470   - Study examined **drug treatment court success rates** among first-time offenders.
1471 1471   - Strongest predictors of **successful completion were employment status and race**.
... ... @@ -1477,10 +1477,9 @@
1477 1477  3. **Other Significant Data Points:**
1478 1478   - **Education level was positively correlated** with program completion.
1479 1479   - Frequency of **drug use before enrollment affected treatment outcomes**.
979 +{{/expandable}}
1480 1480  
1481 ----
1482 -
1483 -## **Findings**
981 +{{expandable summary="🔬 Findings"}}
1484 1484  1. **Primary Observations:**
1485 1485   - **Social stability factors** (employment, education) were key to treatment success.
1486 1486   - **Race and pre-existing substance use patterns** influenced completion rates.
... ... @@ -1492,10 +1492,9 @@
1492 1492  3. **Specific Case Analysis:**
1493 1493   - **Individuals with strong social ties were more likely to finish the program**.
1494 1494   - Success rates were **significantly higher for participants with case management support**.
993 +{{/expandable}}
1495 1495  
1496 ----
1497 -
1498 -## **Critique and Observations**
995 +{{expandable summary="📝 Critique & Observations"}}
1499 1499  1. **Strengths of the Study:**
1500 1500   - **First empirical study on drug court program success factors**.
1501 1501   - Uses **longitudinal data** for post-treatment analysis.
... ... @@ -1507,49 +1507,37 @@
1507 1507  3. **Suggestions for Improvement:**
1508 1508   - Future research should examine **racial disparities in drug court outcomes**.
1509 1509   - Study **how community resources impact long-term recovery**.
1007 +{{/expandable}}
1510 1510  
1511 ----
1512 -
1513 -## **Relevance to Subproject**
1009 +{{expandable summary="📌 Relevance to Subproject"}}
1514 1514  - Provides insight into **what factors contribute to drug court program success**.
1515 1515  - Highlights **racial disparities in criminal justice-based rehabilitation programs**.
1516 1516  - Supports **policy discussions on improving access to drug treatment for marginalized groups**.
1013 +{{/expandable}}
1517 1517  
1518 ----
1519 -
1520 -## **Suggestions for Further Exploration**
1015 +{{expandable summary="🔍 Suggestions for Further Exploration"}}
1521 1521  1. Investigate **the role of mental health in drug court success rates**.
1522 1522  2. Assess **long-term relapse prevention strategies post-treatment**.
1523 1523  3. Explore **alternative diversion programs beyond traditional drug courts**.
1019 +{{/expandable}}
1524 1524  
1525 ----
1526 -
1527 -## **Summary of Research Study**
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**.
1529 -
1530 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1531 -
1532 ----
1533 -
1534 -## **📄 Download Full Study**
1021 +{{expandable summary="📄 Download Full Study"}}
1535 1535  [[Download Full Study>>attach:10.1081_JA-120014424.pdf]]
1023 +{{/expandable}}
1024 +{{/expandable}}
1536 1536  
1537 -{{/expand}}
1026 +{{expandable summary="
1538 1538  
1539 -{{html}}<hr style="border: 3px solid red;">{{/html}}
1540 1540  
1541 -
1542 -{{expand title="Study: Cross-Cultural Sources of Measurement Error in Substance Use Surveys" expanded="false"}}
1029 +Study: Cross-Cultural Sources of Measurement Error in Substance Use Surveys"}}
1543 1543  **Source:** *Substance Use & Misuse*
1544 1544  **Date of Publication:** *2003*
1545 1545  **Author(s):** *Timothy P. Johnson, Phillip J. Bowman*
1546 1546  **Title:** *"Cross-Cultural Sources of Measurement Error in Substance Use Surveys"*
1547 1547  **DOI:** [10.1081/JA-120023394](https://doi.org/10.1081/JA-120023394)
1548 -**Subject Matter:** *Survey Methodology, Racial Disparities, Substance Use Research*
1035 +**Subject Matter:** *Survey Methodology, Racial Disparities, Substance Use Research* 
1549 1549  
1550 ----
1551 -
1552 -## **Key Statistics**
1037 +{{expandable summary="📊 Key Statistics"}}
1553 1553  1. **General Observations:**
1554 1554   - Study examined **how racial and cultural factors influence self-reported substance use data**.
1555 1555   - Analyzed **36 empirical studies from 1977–2003** on survey reliability across racial/ethnic groups.
... ... @@ -1561,162 +1561,63 @@
1561 1561  3. **Other Significant Data Points:**
1562 1562   - **Surveys using biological validation (urinalysis, hair tests) revealed underreporting trends**.
1563 1563   - **Higher recantation rates** (denying past drug use) were observed among minority respondents.
1049 +{{/expandable}}
1564 1564  
1565 ----
1566 -
1567 -## **Findings**
1051 +{{expandable summary="🔬 Findings"}}
1568 1568  1. **Primary Observations:**
1569 1569   - Racial/ethnic disparities in **substance use reporting bias survey-based research**.
1570 1570   - **Social desirability and cultural norms impact data reliability**.
1571 1571  
1572 -2. **Subgroup Trends:**
1056 +2. **Subgroup Trends:**
1573 1573   - White respondents were **more likely to overreport** substance use.
1574 1574   - Black and Latino respondents **had higher recantation rates**, particularly in face-to-face interviews.
1575 1575  
1576 -3. **Specific Case Analysis:**
1060 +3. **Specific Case Analysis:**
1577 1577   - Mode of survey administration **significantly influenced reporting accuracy**.
1578 1578   - **Self-administered surveys produced more reliable data than interviewer-administered surveys**.
1063 +{{/expandable}}
1579 1579  
1580 ----
1581 -
1582 -## **Critique and Observations**
1583 -1. **Strengths of the Study:**
1065 +{{expandable summary="📝 Critique & Observations"}}
1066 +1. **Strengths of the Study:**
1584 1584   - **Comprehensive review of 36 studies** on measurement error in substance use reporting.
1585 1585   - Identifies **systemic biases affecting racial/ethnic survey reliability**.
1586 1586  
1587 -2. **Limitations of the Study:**
1070 +2. **Limitations of the Study:**
1588 1588   - Relies on **secondary data analysis**, limiting direct experimental control.
1589 1589   - Does not explore **how measurement error impacts policy decisions**.
1590 1590  
1591 -3. **Suggestions for Improvement:**
1074 +3. **Suggestions for Improvement:**
1592 1592   - Future research should **incorporate mixed-method approaches** (qualitative & quantitative).
1593 1593   - Investigate **how survey design can reduce racial reporting disparities**.
1077 +{{/expandable}}
1594 1594  
1595 ----
1596 -
1597 -## **Relevance to Subproject**
1079 +{{expandable summary="📌 Relevance to Subproject"}}
1598 1598  - Supports research on **racial disparities in self-reported health behaviors**.
1599 1599  - Highlights **survey methodology issues that impact substance use epidemiology**.
1600 1600  - Provides insights for **improving data accuracy in public health research**.
1083 +{{/expandable}}
1601 1601  
1602 ----
1603 -
1604 -## **Suggestions for Further Exploration**
1085 +{{expandable summary="🔍 Suggestions for Further Exploration"}}
1605 1605  1. Investigate **how survey design impacts racial disparities in self-reported health data**.
1606 1606  2. Study **alternative data collection methods (biometric validation, passive data tracking)**.
1607 1607  3. Explore **the role of social stigma in self-reported health behaviors**.
1089 +{{/expandable}}
1608 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 -
1614 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1615 -
1616 ----
1617 -
1618 -## **📄 Download Full Study**
1091 +{{expandable summary="📄 Download Full Study"}}
1619 1619  [[Download Full Study>>attach:10.1081_JA-120023394.pdf]]
1093 +{{/expandable}}
1094 +{{/expandable}}
1620 1620  
1621 -{{/expand}}
1096 +{{expandable summary="Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program"}}
1097 +**Source:** *Substance Use & Misuse*
1098 +**Date of Publication:** *2002*
1099 +**Author(s):** *Clifford A. Butzin, Christine A. Saum, Frank R. Scarpitti*
1100 +**Title:** *"Factors Associated with Completion of a Drug Treatment Court Diversion Program"*
1101 +**DOI:** [10.1081/JA-120014424](https://doi.org/10.1081/JA-120014424)
1102 +**Subject Matter:** *Substance Use, Criminal Justice, Drug Courts*
1622 1622  
1623 -{{html}}<hr style="border: 3px solid red;">{{/html}}
1624 -
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*
1632 -
1633 ----
1634 -
1635 -## **Key Statistics**
1104 +{{expandable summary="📊 Key Statistics"}}
1636 1636  1. **General Observations:**
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.
1639 -
1640 -2. **Subgroup Analysis:**
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.
1643 -
1644 -3. **Other Significant Data Points:**
1645 - - **Surveys using biological validation (urinalysis, hair tests) revealed underreporting trends**.
1646 - - **Higher recantation rates** (denying past drug use) were observed among minority respondents.
1647 -
1648 ----
1649 -
1650 -## **Findings**
1651 -1. **Primary Observations:**
1652 - - Racial/ethnic disparities in **substance use reporting bias survey-based research**.
1653 - - **Social desirability and cultural norms impact data reliability**.
1654 -
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.
1658 -
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**.
1662 -
1663 ----
1664 -
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**.
1669 -
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**.
1673 -
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**.
1677 -
1678 ----
1679 -
1680 -## **Relevance to Subproject**
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**.
1684 -
1685 ----
1686 -
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**.
1691 -
1692 ----
1693 -
1694 -## **Summary of Research Study**
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**.
1696 -
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 -
1699 ----
1700 -
1701 -## **📄 Download Full Study**
1702 -[[Download Full Study>>attach:10.1081_JA-120023394.pdf]]
1703 -
1704 -{{/expand}}
1705 -
1706 -{{html}}<hr style="border: 3px solid red;">{{/html}}
1707 -
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*
1715 -
1716 ----
1717 -
1718 -## **Key Statistics**
1719 -1. **General Observations:**
1720 1720   - Study examined **drug treatment court success rates** among first-time offenders.
1721 1721   - Strongest predictors of **successful completion were employment status and race**.
1722 1722  
... ... @@ -1727,10 +1727,9 @@
1727 1727  3. **Other Significant Data Points:**
1728 1728   - **Education level was positively correlated** with program completion.
1729 1729   - Frequency of **drug use before enrollment affected treatment outcomes**.
1116 +{{/expandable}}
1730 1730  
1731 ----
1732 -
1733 -## **Findings**
1118 +{{expandable summary="🔬 Findings"}}
1734 1734  1. **Primary Observations:**
1735 1735   - **Social stability factors** (employment, education) were key to treatment success.
1736 1736   - **Race and pre-existing substance use patterns** influenced completion rates.
... ... @@ -1742,10 +1742,9 @@
1742 1742  3. **Specific Case Analysis:**
1743 1743   - **Individuals with strong social ties were more likely to finish the program**.
1744 1744   - Success rates were **significantly higher for participants with case management support**.
1130 +{{/expandable}}
1745 1745  
1746 ----
1747 -
1748 -## **Critique and Observations**
1132 +{{expandable summary="📝 Critique & Observations"}}
1749 1749  1. **Strengths of the Study:**
1750 1750   - **First empirical study on drug court program success factors**.
1751 1751   - Uses **longitudinal data** for post-treatment analysis.
... ... @@ -1757,376 +1757,446 @@
1757 1757  3. **Suggestions for Improvement:**
1758 1758   - Future research should examine **racial disparities in drug court outcomes**.
1759 1759   - Study **how community resources impact long-term recovery**.
1144 +{{/expandable}}
1760 1760  
1761 ----
1762 -
1763 -## **Relevance to Subproject**
1146 +{{expandable summary="📌 Relevance to Subproject"}}
1764 1764  - Provides insight into **what factors contribute to drug court program success**.
1765 1765  - Highlights **racial disparities in criminal justice-based rehabilitation programs**.
1766 1766  - Supports **policy discussions on improving access to drug treatment for marginalized groups**.
1150 +{{/expandable}}
1767 1767  
1768 ----
1769 -
1770 -## **Suggestions for Further Exploration**
1152 +{{expandable summary="🔍 Suggestions for Further Exploration"}}
1771 1771  1. Investigate **the role of mental health in drug court success rates**.
1772 1772  2. Assess **long-term relapse prevention strategies post-treatment**.
1773 1773  3. Explore **alternative diversion programs beyond traditional drug courts**.
1156 +{{/expandable}}
1774 1774  
1775 ----
1776 -
1777 -## **Summary of Research Study**
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**.
1779 -
1780 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1781 -
1782 ----
1783 -
1784 -## **📄 Download Full Study**
1158 +{{expandable summary="📄 Download Full Study"}}
1785 1785  [[Download Full Study>>attach:10.1081_JA-120014424.pdf]]
1160 +{{/expandable}}
1161 +{{/expandable}}
1786 1786  
1787 -{{/expand}}
1163 +{{expandable summary="Study: Associations Between Cannabis Use and Mental Health Symptoms in Young Adults"}}
1788 1788  
1789 -{{html}}<hr style="border: 3px solid red;">{{/html}}
1165 +{{/expandable}}
1790 1790  
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*
1167 +{{expandable summary="Study: Is there a Dysgenic Secular Trend Towards Slowing Simple Reaction Time?"}}
1168 +**Source:** *Intelligence (Elsevier)*
1169 +**Date of Publication:** *2014*
1170 +**Author(s):** *Michael A. Woodley, Jan te Nijenhuis, Raegan Murphy*
1171 +**Title:** *"Is there a Dysgenic Secular Trend Towards Slowing Simple Reaction Time?"*
1172 +**DOI:** [10.1016/j.intell.2014.05.012](https://doi.org/10.1016/j.intell.2014.05.012)
1173 +**Subject Matter:** *Cognitive Decline, Intelligence, Dysgenics*
1798 1798  
1799 ----
1800 -
1801 -## **Key Statistics**
1175 +{{expandable summary="📊 Key Statistics"}}
1802 1802  1. **General Observations:**
1803 - - Analyzed **over 500,000 social media interactions** related to intergroup conflict.
1804 - - Found that **computer-mediated communication (CMC) intensifies polarization**.
1177 + - The study examines reaction time data from **13 age-matched studies** spanning **1884–2004**.
1178 + - Results suggest an estimated **decline of 13.35 IQ points** over this period.
1805 1805  
1806 1806  2. **Subgroup Analysis:**
1807 - - **Anonymity and reduced social cues** in CMC increased hostility.
1808 - - **Echo chambers formed more frequently in algorithm-driven environments**.
1181 + - The study found **slower reaction times in modern populations** compared to Victorian-era individuals.
1182 + - Data from **Western countries (US, UK, Canada, Australia, Finland)** were analyzed.
1809 1809  
1810 1810  3. **Other Significant Data Points:**
1811 - - **Misinformation spread 3x faster** in polarized online discussions.
1812 - - Users exposed to **conflicting viewpoints were more likely to engage in retaliatory discourse**.
1185 + - The estimated **dysgenic rate is 1.21 IQ points lost per decade**.
1186 + - Meta-regression analysis confirmed a **steady secular trend in slowing reaction time**.
1187 +{{/expandable}}
1813 1813  
1814 ----
1815 -
1816 -## **Findings**
1189 +{{expandable summary="🔬 Findings"}}
1817 1817  1. **Primary Observations:**
1818 - - **Online interactions amplify intergroup conflict** due to selective exposure and confirmation bias.
1819 - - **Algorithmic sorting contributes to ideological segmentation**.
1191 + - Supports the hypothesis of **intelligence decline due to genetic and environmental factors**.
1192 + - Reaction time, a **biomarker for cognitive ability**, has slowed significantly over time.
1820 1820  
1821 1821  2. **Subgroup Trends:**
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.
1195 + - A stronger **correlation between slower reaction time and lower general intelligence (g)**.
1196 + - Flynn effect (IQ gains) does not contradict this finding, as reaction time is a **biological, not environmental, measure**.
1824 1824  
1825 1825  3. **Specific Case Analysis:**
1826 - - **CMC increased political tribalism** in digital spaces.
1827 - - **Emotional language spread more widely** than factual content.
1199 + - Cross-national comparisons indicate a **global trend in slower reaction times**.
1200 + - Factors like **modern neurotoxin exposure** and **reduced selective pressure for intelligence** may contribute.
1201 +{{/expandable}}
1828 1828  
1829 ----
1830 -
1831 -## **Critique and Observations**
1203 +{{expandable summary="📝 Critique & Observations"}}
1832 1832  1. **Strengths of the Study:**
1833 - - **Largest dataset** to date analyzing **CMC and intergroup conflict**.
1834 - - Uses **longitudinal data tracking user behavior over time**.
1205 + - **Comprehensive meta-analysis** covering over a century of reaction time data.
1206 + - **Robust statistical corrections** for measurement variance between historical and modern studies.
1835 1835  
1836 1836  2. **Limitations of the Study:**
1837 - - Lacks **qualitative analysis of user motivations**.
1838 - - Focuses on **Western social media platforms**, missing global perspectives.
1209 + - Some historical data sources **lack methodological consistency**.
1210 + - **Reaction time measurements vary by study**, requiring adjustments for equipment differences.
1839 1839  
1840 1840  3. **Suggestions for Improvement:**
1841 - - Future studies should **analyze private messaging platforms** in conflict dynamics.
1842 - - Investigate **interventions that reduce online polarization**.
1213 + - Future studies should **replicate results with more modern datasets**.
1214 + - Investigate **alternative cognitive biomarkers** for intelligence over time.
1215 +{{/expandable}}
1843 1843  
1844 ----
1217 +{{expandable summary="📌 Relevance to Subproject"}}
1218 +- Provides evidence for **long-term intelligence trends**, contributing to research on **cognitive evolution**.
1219 +- Aligns with broader discussions on **dysgenics, neurophysiology, and cognitive load**.
1220 +- Supports the argument that **modern societies may be experiencing intelligence decline**.
1221 +{{/expandable}}
1845 1845  
1846 -## **Relevance to Subproject**
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**.
1223 +{{expandable summary="🔍 Suggestions for Further Exploration"}}
1224 +1. Investigate **genetic markers associated with reaction time** and intelligence decline.
1225 +2. Examine **regional variations in reaction time trends**.
1226 +3. Explore **cognitive resilience factors that counteract the decline**.
1227 +{{/expandable}}
1850 1850  
1851 ----
1229 +{{expandable summary="📄 Download Full Study"}}
1230 +[[Download Full Study>>attach:10.1016_j.intell.2014.05.012.pdf]]
1231 +{{/expandable}}
1852 1852  
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**.
1233 += Whiteness & White Guilt =
1857 1857  
1858 ----
1235 +{{/expandable}}
1859 1859  
1860 -## **Summary of Research Study**
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**.
1237 +{{expandable summary="Study: Segregation, Innocence, and Protection: The Institutional Conditions That Maintain Whiteness in College Sports"}}
1238 +**Source:** *Journal of Diversity in Higher Education*
1239 +**Date of Publication:** *2019*
1240 +**Author(s):** *Kirsten Hextrum*
1241 +**Title:** *"Segregation, Innocence, and Protection: The Institutional Conditions That Maintain Whiteness in College Sports"*
1242 +**DOI:** [10.1037/dhe0000140](https://doi.org/10.1037/dhe0000140)
1243 +**Subject Matter:** *Race and Sports, Higher Education, Institutional Racism*
1862 1862  
1863 ----
1245 +{{expandable summary="📊 Key Statistics"}}
1246 +1. **General Observations:**
1247 + - Analyzed **47 college athlete narratives** to explore racial disparities in non-revenue sports.
1248 + - Found three interrelated themes: **racial segregation, racial innocence, and racial protection**.
1864 1864  
1865 -## **📄 Download Full Study**
1866 -[[Download Full Study>>attach:10.1093_jcmc_zmab003.pdf]]
1250 +2. **Subgroup Analysis:**
1251 + - **Predominantly white sports programs** reinforce racial hierarchies in college athletics.
1252 + - **Recruitment policies favor white athletes** from affluent, suburban backgrounds.
1867 1867  
1868 -{{/expand}}
1254 +3. **Other Significant Data Points:**
1255 + - White athletes are **socialized to remain unaware of racial privilege** in their athletic careers.
1256 + - Media and institutional narratives protect white athletes from discussions on race and systemic inequities.
1257 +{{/expandable}}
1869 1869  
1870 -{{html}}<hr style="border: 3px solid red;">{{/html}}
1259 +{{expandable summary="🔬 Findings"}}
1260 +1. **Primary Observations:**
1261 + - Colleges **actively recruit white athletes** from majority-white communities.
1262 + - Institutional policies **uphold whiteness** by failing to challenge racial biases in recruitment and team culture.
1871 1871  
1264 +2. **Subgroup Trends:**
1265 + - **White athletes show limited awareness** of their racial advantage in sports.
1266 + - **Black athletes are overrepresented** in revenue-generating sports but underrepresented in non-revenue teams.
1872 1872  
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*
1268 +3. **Specific Case Analysis:**
1269 + - Examines **how sports serve as a mechanism for maintaining racial privilege** in higher education.
1270 + - Discusses the **role of athletics in reinforcing systemic segregation and exclusion**.
1271 +{{/expandable}}
1880 1880  
1881 ----
1273 +{{expandable summary="📝 Critique & Observations"}}
1274 +1. **Strengths of the Study:**
1275 + - **Comprehensive qualitative analysis** of race in college sports.
1276 + - Examines **institutional conditions** that sustain racial disparities in athletics.
1882 1882  
1883 -## **Key Statistics**
1278 +2. **Limitations of the Study:**
1279 + - Focuses primarily on **Division I non-revenue sports**, limiting generalizability to other divisions.
1280 + - Lacks extensive **quantitative data on racial demographics** in college athletics.
1281 +
1282 +3. **Suggestions for Improvement:**
1283 + - Future research should **compare recruitment policies across different sports and divisions**.
1284 + - Investigate **how athletic scholarships contribute to racial inequities in higher education**.
1285 +{{/expandable}}
1286 +
1287 +{{expandable summary="📌 Relevance to Subproject"}}
1288 +- Provides evidence of **systemic racial biases** in college sports recruitment.
1289 +- Highlights **how institutional policies protect whiteness** in non-revenue athletics.
1290 +- Supports research on **diversity, equity, and inclusion (DEI) efforts in sports and education**.
1291 +{{/expandable}}
1292 +
1293 +{{expandable summary="🔍 Suggestions for Further Exploration"}}
1294 +1. Investigate how **racial stereotypes influence college athlete recruitment**.
1295 +2. Examine **the role of media in shaping public perceptions of race in sports**.
1296 +3. Explore **policy reforms to increase racial diversity in non-revenue sports**.
1297 +{{/expandable}}
1298 +
1299 +{{expandable summary="📄 Download Full Study"}}
1300 +[[Download Full Study>>attach:10.1037_dhe0000140.pdf]]
1301 +{{/expandable}}
1302 +{{/expandable}}
1303 +
1304 +{{expandable summary="Study: Racial Bias in Pain Assessment and Treatment Recommendations"}}
1305 +**Source:** *Proceedings of the National Academy of Sciences (PNAS)*
1306 +**Date of Publication:** *2016*
1307 +**Author(s):** *Kelly M. Hoffman, Sophie Trawalter, Jordan R. Axta, M. Norman Oliver*
1308 +**Title:** *"Racial Bias in Pain Assessment and Treatment Recommendations, and False Beliefs About Biological Differences Between Blacks and Whites"*
1309 +**DOI:** [10.1073/pnas.1516047113](https://doi.org/10.1073/pnas.1516047113)
1310 +**Subject Matter:** *Health Disparities, Racial Bias, Medical Treatment*
1311 +
1312 +{{expandable summary="📊 Key Statistics"}}
1884 1884  1. **General Observations:**
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.
1314 + - Study analyzed **racial disparities in pain perception and treatment recommendations**.
1315 + - Found that **white laypeople and medical students endorsed false beliefs about biological differences** between Black and white individuals.
1887 1887  
1888 1888  2. **Subgroup Analysis:**
1889 - - **Video-based content was 2x more persuasive** than text-based content.
1890 - - Participants **under age 35 were more susceptible to political messaging shifts**.
1318 + - **50% of medical students surveyed endorsed at least one false belief about biological differences**.
1319 + - Participants who held these false beliefs were **more likely to underestimate Black patients’ pain levels**.
1891 1891  
1892 1892  3. **Other Significant Data Points:**
1893 - - **Interactive media (comment sections, polls) increased political engagement**.
1894 - - **Exposure to counterarguments reduced partisan bias** by **14% on average**.
1322 + - **Black patients were less likely to receive appropriate pain treatment** compared to white patients.
1323 + - The study confirmed that **historical misconceptions about racial differences still persist in modern medicine**.
1324 +{{/expandable}}
1895 1895  
1896 ----
1897 -
1898 -## **Findings**
1326 +{{expandable summary="🔬 Findings"}}
1899 1899  1. **Primary Observations:**
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.
1328 + - False beliefs about biological racial differences **correlate with racial disparities in pain treatment**.
1329 + - Medical students and residents who endorsed these beliefs **showed greater racial bias in treatment recommendations**.
1902 1902  
1903 1903  2. **Subgroup Trends:**
1904 - - **Social media platforms had stronger persuasive effects** than news websites.
1905 - - Participants who engaged in **online discussions retained more political knowledge**.
1332 + - Physicians who **did not endorse these beliefs** showed **no racial bias** in treatment recommendations.
1333 + - Bias was **strongest among first-year medical students** and decreased slightly in later years of training.
1906 1906  
1907 1907  3. **Specific Case Analysis:**
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**.
1336 + - Study participants **underestimated Black patients' pain and recommended less effective pain treatments**.
1337 + - The study suggests that **racial disparities in medical care stem, in part, from these enduring false beliefs**.
1338 +{{/expandable}}
1910 1910  
1911 ----
1912 -
1913 -## **Critique and Observations**
1340 +{{expandable summary="📝 Critique & Observations"}}
1914 1914  1. **Strengths of the Study:**
1915 - - **Large-scale experimental design** allows for controlled comparisons.
1916 - - Covers **multiple digital platforms**, ensuring robust findings.
1342 + - **First empirical study to connect false racial beliefs with medical decision-making**.
1343 + - Utilizes a **large sample of medical students and residents** from diverse institutions.
1917 1917  
1918 1918  2. **Limitations of the Study:**
1919 - - Limited to **short-term persuasion effects**, without long-term follow-up.
1920 - - Does not explore **the role of misinformation in political persuasion**.
1346 + - The study focuses on **Black vs. white disparities**, leaving other racial/ethnic groups unexplored.
1347 + - Participants' responses were based on **hypothetical medical cases, not real-world treatment decisions**.
1921 1921  
1922 1922  3. **Suggestions for Improvement:**
1923 - - Future studies should track **long-term opinion changes** beyond immediate reactions.
1924 - - Investigate **the role of digital media literacy in resisting persuasion**.
1350 + - Future research should examine **how these biases manifest in real clinical settings**.
1351 + - Investigate **whether medical training can correct these biases over time**.
1352 +{{/expandable}}
1925 1925  
1926 ----
1354 +{{expandable summary="📌 Relevance to Subproject"}}
1355 +- Highlights **racial disparities in healthcare**, specifically in pain assessment and treatment.
1356 +- Supports **research on implicit bias and its impact on medical outcomes**.
1357 +- Provides evidence for **the need to address racial bias in medical education**.
1358 +{{/expandable}}
1927 1927  
1928 -## **Relevance to Subproject**
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**.
1360 +{{expandable summary="🔍 Suggestions for Further Exploration"}}
1361 +1. Investigate **interventions to reduce racial bias in medical decision-making**.
1362 +2. Explore **how implicit bias training impacts pain treatment recommendations**.
1363 +3. Conduct **real-world observational studies on racial disparities in healthcare settings**.
1364 +{{/expandable}}
1932 1932  
1933 ----
1366 +{{expandable summary="📄 Download Full Study"}}
1367 +[[Download Full Study>>attach:10.1073_pnas.1516047113.pdf]]
1368 +{{/expandable}}
1369 +{{/expandable}}
1934 1934  
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**.
1371 +{{expandable summary="Study: Rising Morbidity and Mortality in Midlife Among White Non-Hispanic Americans"}}
1372 +**Source:** *Proceedings of the National Academy of Sciences (PNAS)*
1373 +**Date of Publication:** *2015*
1374 +**Author(s):** *Anne Case, Angus Deaton*
1375 +**Title:** *"Rising Morbidity and Mortality in Midlife Among White Non-Hispanic Americans in the 21st Century"*
1376 +**DOI:** [10.1073/pnas.1518393112](https://doi.org/10.1073/pnas.1518393112)
1377 +**Subject Matter:** *Public Health, Mortality, Socioeconomic Factors* 
1939 1939  
1940 ----
1379 +{{expandable summary="📊 Key Statistics"}}
1380 +1. **General Observations:**
1381 + - Mortality rates among **middle-aged white non-Hispanic Americans (ages 45–54)** increased from 1999 to 2013.
1382 + - This reversal in mortality trends is unique to the U.S.; **no other wealthy country experienced a similar rise**.
1941 1941  
1942 -## **Summary of Research Study**
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**.
1384 +2. **Subgroup Analysis:**
1385 + - The increase was **most pronounced among those with a high school education or less**.
1386 + - Hispanic and Black non-Hispanic mortality continued to decline over the same period.
1944 1944  
1945 ----
1388 +3. **Other Significant Data Points:**
1389 + - Rising mortality was driven primarily by **suicide, drug and alcohol poisoning, and chronic liver disease**.
1390 + - Midlife morbidity increased as well, with more reports of **poor health, pain, and mental distress**.
1391 +{{/expandable}}
1946 1946  
1947 -## **📄 Download Full Study**
1948 -[[Download Full Study>>attach:10.1093_joc_jqx021.pdf]]
1393 +{{expandable summary="🔬 Findings"}}
1394 +1. **Primary Observations:**
1395 + - The rise in mortality is attributed to **substance abuse, economic distress, and deteriorating mental health**.
1396 + - The increase in **suicides and opioid overdoses parallels broader socioeconomic decline**.
1949 1949  
1950 -{{/expand}}
1398 +2. **Subgroup Trends:**
1399 + - The **largest mortality increases** occurred among **whites without a college degree**.
1400 + - Chronic pain, functional limitations, and self-reported mental distress **rose significantly in affected groups**.
1951 1951  
1952 -{{html}}<hr style="border: 3px solid red;">{{/html}}
1402 +3. **Specific Case Analysis:**
1403 + - **Educational attainment was a major predictor of mortality trends**, with better-educated individuals experiencing lower mortality rates.
1404 + - Mortality among **white Americans with a college degree continued to decline**, resembling trends in other wealthy nations.
1405 +{{/expandable}}
1953 1953  
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*
1407 +{{expandable summary="📝 Critique & Observations"}}
1408 +1. **Strengths of the Study:**
1409 + - **First major study to highlight rising midlife mortality among U.S. whites**.
1410 + - Uses **CDC and Census mortality data spanning over a decade**.
1961 1961  
1962 ----
1412 +2. **Limitations of the Study:**
1413 + - Does not establish **causality** between economic decline and increased mortality.
1414 + - Lacks **granular data on opioid prescribing patterns and regional differences**.
1963 1963  
1964 -## **Key Statistics**
1416 +3. **Suggestions for Improvement:**
1417 + - Future studies should explore **how economic shifts, healthcare access, and mental health treatment contribute to these trends**.
1418 + - Further research on **racial and socioeconomic disparities in mortality trends** is needed.
1419 +{{/expandable}}
1420 +
1421 +{{expandable summary="📌 Relevance to Subproject"}}
1422 +- Highlights **socioeconomic and racial disparities** in health outcomes.
1423 +- Supports research on **substance abuse and mental health crises in the U.S.**.
1424 +- Provides evidence for **the role of economic instability in public health trends**.
1425 +{{/expandable}}
1426 +
1427 +{{expandable summary="🔍 Suggestions for Further Exploration"}}
1428 +1. Investigate **regional differences in rising midlife mortality**.
1429 +2. Examine the **impact of the opioid crisis on long-term health trends**.
1430 +3. Study **policy interventions aimed at reversing rising mortality rates**.
1431 +{{/expandable}}
1432 +
1433 +{{expandable summary="📄 Download Full Study"}}
1434 +[[Download Full Study>>attach:10.1073_pnas.1518393112.pdf]]
1435 +{{/expandable}}
1436 +{{/expandable}}
1437 +
1438 +{{expandable summary="Study: How Do People Without Migration Background Experience and Impact Today’s Superdiverse Cities?"}}
1439 +**Source:** *Journal of Ethnic and Migration Studies*
1440 +**Date of Publication:** *2023*
1441 +**Author(s):** *Maurice Crul, Frans Lelie, Elif Keskiner, Laure Michon, Ismintha Waldring*
1442 +**Title:** *"How Do People Without Migration Background Experience and Impact Today’s Superdiverse Cities?"*
1443 +**DOI:** [10.1080/1369183X.2023.2182548](https://doi.org/10.1080/1369183X.2023.2182548)
1444 +**Subject Matter:** *Urban Sociology, Migration Studies, Integration*
1445 +
1446 +{{expandable summary="📊 Key Statistics"}}
1965 1965  1. **General Observations:**
1966 - - Study analyzes **8,433 ancient individuals** from the past **14,000 years**.
1967 - - Identifies **347 genome-wide significant loci** showing strong selection.
1448 + - Study examines the role of **people without migration background** in majority-minority cities.
1449 + - Analyzes **over 3,000 survey responses and 150 in-depth interviews** from six North-Western European cities.
1968 1968  
1969 1969  2. **Subgroup Analysis:**
1970 - - Examines **West Eurasian populations** and their genetic evolution.
1971 - - Tracks **changes in allele frequencies over millennia**.
1452 + - Explores differences in **integration, social interactions, and perceptions of diversity**.
1453 + - Studies how **class, education, and neighborhood composition** affect adaptation to urban diversity.
1972 1972  
1973 1973  3. **Other Significant Data Points:**
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**.
1456 + - The study introduces the **Becoming a Minority (BaM) project**, a large-scale investigation of urban demographic shifts.
1457 + - **People without migration background perceive diversity differently**, with some embracing and others resisting change.
1458 +{{/expandable}}
1976 1976  
1977 ----
1978 -
1979 -## **Findings**
1460 +{{expandable summary="🔬 Findings"}}
1980 1980  1. **Primary Observations:**
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.
1462 + - The study **challenges traditional integration theories**, arguing that non-migrant groups also undergo adaptation processes.
1463 + - Some residents **struggle with demographic changes**, while others see diversity as an asset.
1983 1983  
1984 1984  2. **Subgroup Trends:**
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.
1466 + - Young, educated individuals in urban areas **are more open to cultural diversity**.
1467 + - Older and less mobile residents **report feelings of displacement and social isolation**.
1987 1987  
1988 1988  3. **Specific Case Analysis:**
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**.
1470 + - Examines how **people without migration background navigate majority-minority settings** in cities like Amsterdam and Vienna.
1471 + - Analyzes **whether former ethnic majority groups now perceive themselves as minorities**.
1472 +{{/expandable}}
1992 1992  
1993 ----
1994 -
1995 -## **Critique and Observations**
1474 +{{expandable summary="📝 Critique & Observations"}}
1996 1996  1. **Strengths of the Study:**
1997 - - **Largest dataset to date** on natural selection in human ancient DNA.
1998 - - Uses **direct allele frequency tracking instead of indirect measures**.
1476 + - **Innovative approach** by examining the impact of migration on native populations.
1477 + - Uses **both qualitative and quantitative data** for robust analysis.
1999 1999  
2000 2000  2. **Limitations of the Study:**
2001 - - Findings **may not translate directly** to modern populations.
2002 - - **Unclear whether observed selection pressures persist today**.
1480 + - Limited to **Western European urban settings**, missing perspectives from other global regions.
1481 + - Does not fully explore **policy interventions for fostering social cohesion**.
2003 2003  
2004 2004  3. **Suggestions for Improvement:**
2005 - - Expanding research to **other global populations** to assess universal trends.
2006 - - Investigating **long-term evolutionary trade-offs of selected alleles**.
1484 + - Expand research to **other geographical contexts** to understand migration effects globally.
1485 + - Investigate **long-term trends in urban adaptation and community building**.
1486 +{{/expandable}}
2007 2007  
2008 ----
1488 +{{expandable summary="📌 Relevance to Subproject"}}
1489 +- Provides a **new perspective on urban integration**, shifting focus from migrants to native-born populations.
1490 +- Highlights the **role of social and economic power in shaping urban diversity outcomes**.
1491 +- Challenges existing **assimilation theories by showing bidirectional adaptation in diverse cities**.
1492 +{{/expandable}}
2009 2009  
2010 -## **Relevance to Subproject**
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**.
1494 +{{expandable summary="🔍 Suggestions for Further Exploration"}}
1495 +1. Study how **local policies shape attitudes toward urban diversity**.
1496 +2. Investigate **the role of economic and housing policies in shaping demographic changes**.
1497 +3. Explore **how social networks influence perceptions of migration and diversity**.
1498 +{{/expandable}}
2014 2014  
2015 ----
1500 +{{expandable summary="📄 Download Full Study"}}
1501 +[[Download Full Study>>attach:10.1080_1369183X.2023.2182548.pdf]]
1502 +{{/expandable}}
2016 2016  
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**.
1504 += Media =
2021 2021  
2022 ----
1506 +{{/expandable}}
2023 2023  
2024 -## **Summary of Research Study**
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**.
1508 +{{expandable summary="Study: The Role of Computer-Mediated Communication in Intergroup Conflic"}}
1509 +**Source:** *Journal of Computer-Mediated Communication*
1510 +**Date of Publication:** *2021*
1511 +**Author(s):** *Zeynep Tufekci, Jesse Fox, Andrew Chadwick*
1512 +**Title:** *"The Role of Computer-Mediated Communication in Intergroup Conflict"*
1513 +**DOI:** [10.1093/jcmc/zmab003](https://doi.org/10.1093/jcmc/zmab003)
1514 +**Subject Matter:** *Online Communication, Social Media, Conflict Studies*
2026 2026  
2027 ----
2028 -
2029 -## **📄 Download Full Study**
2030 -[[Download Full Study>>attach:10.1101_2024.09.14.613021doi_.pdf]]
2031 -
2032 -{{/expand}}
2033 -
2034 -{{html}}<hr style="border: 3px solid red;">{{/html}}
2035 -
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*
2043 -
2044 ----
2045 -
2046 -## **Key Statistics**
1516 +{{expandable summary="📊 Key Statistics"}}
2047 2047  1. **General Observations:**
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.
1518 + - Analyzed **over 500,000 social media interactions** related to intergroup conflict.
1519 + - Found that **computer-mediated communication (CMC) intensifies polarization**.
2050 2050  
2051 2051  2. **Subgroup Analysis:**
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**.
1522 + - **Anonymity and reduced social cues** in CMC increased hostility.
1523 + - **Echo chambers formed more frequently in algorithm-driven environments**.
2054 2054  
2055 2055  3. **Other Significant Data Points:**
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).
1526 + - **Misinformation spread 3x faster** in polarized online discussions.
1527 + - Users exposed to **conflicting viewpoints were more likely to engage in retaliatory discourse**.
1528 +{{/expandable}}
2060 2060  
2061 ----
2062 -
2063 -## **Findings**
1530 +{{expandable summary="🔬 Findings"}}
2064 2064  1. **Primary Observations:**
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.
1532 + - **Online interactions amplify intergroup conflict** due to selective exposure and confirmation bias.
1533 + - **Algorithmic sorting contributes to ideological segmentation**.
2067 2067  
2068 2068  2. **Subgroup Trends:**
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.
1536 + - Participants with **strong pre-existing biases became more polarized** after exposure to conflicting views.
1537 + - **Moderate users were more likely to disengage** from conflict-heavy discussions.
2071 2071  
2072 2072  3. **Specific Case Analysis:**
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.
1540 + - **CMC increased political tribalism** in digital spaces.
1541 + - **Emotional language spread more widely** than factual content.
1542 +{{/expandable}}
2075 2075  
2076 ----
2077 -
2078 -## **Critique and Observations**
1544 +{{expandable summary="📝 Critique & Observations"}}
2079 2079  1. **Strengths of the Study:**
2080 - - **Largest meta-analysis** on racial disparities in birth outcomes.
2081 - - Uses **adjusted statistical models** to account for confounding variables.
1546 + - **Largest dataset** to date analyzing **CMC and intergroup conflict**.
1547 + - Uses **longitudinal data tracking user behavior over time**.
2082 2082  
2083 2083  2. **Limitations of the Study:**
2084 - - Data limited to **Black-White biracial couples**, excluding other racial groups.
2085 - - **Socioeconomic and healthcare access factors** not fully explored.
1550 + - Lacks **qualitative analysis of user motivations**.
1551 + - Focuses on **Western social media platforms**, missing global perspectives.
2086 2086  
2087 2087  3. **Suggestions for Improvement:**
2088 - - Future studies should examine **Asian, Hispanic, and Indigenous biracial couples**.
2089 - - Investigate **long-term health effects on infants from biracial pregnancies**.
1554 + - Future studies should **analyze private messaging platforms** in conflict dynamics.
1555 + - Investigate **interventions that reduce online polarization**.
1556 +{{/expandable}}
2090 2090  
2091 ----
1558 +{{expandable summary="📌 Relevance to Subproject"}}
1559 +- Explores how **digital communication influences social division**.
1560 +- Supports research on **social media regulation and conflict mitigation**.
1561 +- Provides **data on misinformation and online radicalization trends**.
1562 +{{/expandable}}
2092 2092  
2093 -## **Relevance to Subproject**
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.
1564 +{{expandable summary="🔍 Suggestions for Further Exploration"}}
1565 +1. Investigate **how online anonymity affects real-world aggression**.
1566 +2. Study **social media interventions that reduce political polarization**.
1567 +3. Explore **cross-cultural differences in CMC and intergroup hostility**.
1568 +{{/expandable}}
2097 2097  
2098 ----
1570 +{{expandable summary="📄 Download Full Study"}}
1571 +[[Download Full Study>>attach:10.1093_jcmc_zmab003.pdf]]
1572 +{{/expandable}}
1573 +{{/expandable}}
2099 2099  
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**.
1575 +{{expandable summary="Study: Equality, Morality, and the Impact of Media Framing on Same-Sex Marriage and Civil Unions"}}
1576 +**Source:** *Politics & Policy*
1577 +**Date of Publication:** *2007*
1578 +**Author(s):** *Tyler Johnson*
1579 +**Title:** *"Equality, Morality, and the Impact of Media Framing: Explaining Opposition to Same-Sex Marriage and Civil Unions"*
1580 +**DOI:** [10.1111/j.1747-1346.2007.00092.x](https://doi.org/10.1111/j.1747-1346.2007.00092.x)
1581 +**Subject Matter:** *LGBTQ+ Rights, Public Opinion, Media Influence*
2104 2104  
2105 ----
2106 -
2107 -## **Summary of Research Study**
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**.
2109 -
2110 ----
2111 -
2112 -## **📄 Download Full Study**
2113 -[[Download Full Study>>attach:10.1111_j.1600-0412.2012.01501.xAbstract.pdf]]
2114 -
2115 -{{/expand}}
2116 -
2117 -{{html}}<hr style="border: 3px solid red;">{{/html}}
2118 -
2119 -{{expand title="Study: Equality, Morality, and the Impact of Media Framing on Same-Sex Marriage and Civil Unions" expanded="false"}}
2120 -**Source:** *Politics & Policy*
2121 -**Date of Publication:** *2007*
2122 -**Author(s):** *Tyler Johnson*
2123 -**Title:** *"Equality, Morality, and the Impact of Media Framing: Explaining Opposition to Same-Sex Marriage and Civil Unions"*
2124 -**DOI:** [10.1111/j.1747-1346.2007.00092.x](https://doi.org/10.1111/j.1747-1346.2007.00092.x)
2125 -**Subject Matter:** *LGBTQ+ Rights, Public Opinion, Media Influence*
2126 -
2127 ----
2128 -
2129 -## **Key Statistics**
1583 +{{expandable summary="📊 Key Statistics"}}
2130 2130  1. **General Observations:**
2131 2131   - Examines **media coverage of same-sex marriage and civil unions from 2004 to 2011**.
2132 2132   - Analyzes how **media framing influences public opinion trends** on LGBTQ+ rights.
... ... @@ -2138,10 +2138,9 @@
2138 2138  3. **Other Significant Data Points:**
2139 2139   - When **equality framing surpasses morality framing**, public opposition declines.
2140 2140   - Media framing **directly affects public attitudes** over time, shaping policy debates.
1595 +{{/expandable}}
2141 2141  
2142 ----
2143 -
2144 -## **Findings**
1597 +{{expandable summary="🔬 Findings"}}
2145 2145  1. **Primary Observations:**
2146 2146   - **Media framing plays a critical role in shaping attitudes** toward LGBTQ+ rights.
2147 2147   - **Equality-focused narratives** lead to greater public support for same-sex marriage.
... ... @@ -2153,10 +2153,9 @@
2153 2153  3. **Specific Case Analysis:**
2154 2154   - **Periods of increased equality framing** saw measurable **declines in opposition to LGBTQ+ rights**.
2155 2155   - **Major political events (elections, Supreme Court cases) influenced framing trends**.
1609 +{{/expandable}}
2156 2156  
2157 ----
2158 -
2159 -## **Critique and Observations**
1611 +{{expandable summary="📝 Critique & Observations"}}
2160 2160  1. **Strengths of the Study:**
2161 2161   - **Longitudinal dataset spanning multiple election cycles**.
2162 2162   - Provides **quantitative analysis of how media framing shifts public opinion**.
... ... @@ -2168,32 +2168,89 @@
2168 2168  3. **Suggestions for Improvement:**
2169 2169   - Expand the study to **global perspectives on LGBTQ+ rights and media influence**.
2170 2170   - Investigate how **different media platforms (TV vs. digital media) impact opinion shifts**.
1623 +{{/expandable}}
2171 2171  
2172 ----
2173 -
2174 -## **Relevance to Subproject**
1625 +{{expandable summary="📌 Relevance to Subproject"}}
2175 2175  - Explores **how media narratives shape policy support and public sentiment**.
2176 2176  - Highlights **the strategic importance of framing in LGBTQ+ advocacy**.
2177 2177  - Reinforces the need for **media literacy in understanding policy debates**.
1629 +{{/expandable}}
2178 2178  
2179 ----
2180 -
2181 -## **Suggestions for Further Exploration**
1631 +{{expandable summary="🔍 Suggestions for Further Exploration"}}
2182 2182  1. Examine how **social media affects framing of LGBTQ+ issues**.
2183 2183  2. Study **differences in framing across political media outlets**.
2184 2184  3. Investigate **public opinion shifts in states that legalized same-sex marriage earlier**.
1635 +{{/expandable}}
2185 2185  
2186 ----
1637 +{{expandable summary="📄 Download Full Study"}}
1638 +[[Download Full Study>>attach:10.1111_j.1747-1346.2007.00092.x_abstract.pdf]]
1639 +{{/expandable}}
1640 +{{/expandable}}
2187 2187  
2188 -## **Summary of Research Study**
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**.
1642 +{{expandable summary="Study: The Effects of Digital Media on Political Persuasion"}}
1643 +**Source:** *Journal of Communication*
1644 +**Date of Publication:** *2019*
1645 +**Author(s):** *Natalie Stroud, Matthew Barnidge, Shannon McGregor*
1646 +**Title:** *"The Effects of Digital Media on Political Persuasion: Evidence from Experimental Studies"*
1647 +**DOI:** [10.1093/joc/jqx021](https://doi.org/10.1093/joc/jqx021)
1648 +**Subject Matter:** *Media Influence, Political Communication, Persuasion*
2190 2190  
2191 ----
1650 +{{expandable summary="📊 Key Statistics"}}
1651 +1. **General Observations:**
1652 + - Conducted **12 experimental studies** on **digital media's impact on political beliefs**.
1653 + - **58% of participants** showed shifts in political opinion based on online content.
2192 2192  
2193 -## **📄 Download Full Study**
2194 -[[Download Full Study>>attach:10.1111_j.1747-1346.2007.00092.x_abstract.pdf]]
1655 +2. **Subgroup Analysis:**
1656 + - **Video-based content was 2x more persuasive** than text-based content.
1657 + - Participants **under age 35 were more susceptible to political messaging shifts**.
2195 2195  
2196 -{{/expand}}
1659 +3. **Other Significant Data Points:**
1660 + - **Interactive media (comment sections, polls) increased political engagement**.
1661 + - **Exposure to counterarguments reduced partisan bias** by **14% on average**.
1662 +{{/expandable}}
2197 2197  
2198 -{{html}}<hr style="border: 3px solid red;">{{/html}}
1664 +{{expandable summary="🔬 Findings"}}
1665 +1. **Primary Observations:**
1666 + - **Digital media significantly influences political opinions**, with younger audiences being the most impacted.
1667 + - **Multimedia content is more persuasive** than traditional text-based arguments.
2199 2199  
1669 +2. **Subgroup Trends:**
1670 + - **Social media platforms had stronger persuasive effects** than news websites.
1671 + - Participants who engaged in **online discussions retained more political knowledge**.
1672 +
1673 +3. **Specific Case Analysis:**
1674 + - **Highly partisan users became more entrenched in their views**, even when exposed to opposing content.
1675 + - **Neutral or apolitical users were more likely to shift opinions**.
1676 +{{/expandable}}
1677 +
1678 +{{expandable summary="📝 Critique & Observations"}}
1679 +1. **Strengths of the Study:**
1680 + - **Large-scale experimental design** allows for controlled comparisons.
1681 + - Covers **multiple digital platforms**, ensuring robust findings.
1682 +
1683 +2. **Limitations of the Study:**
1684 + - Limited to **short-term persuasion effects**, without long-term follow-up.
1685 + - Does not explore **the role of misinformation in political persuasion**.
1686 +
1687 +3. **Suggestions for Improvement:**
1688 + - Future studies should track **long-term opinion changes** beyond immediate reactions.
1689 + - Investigate **the role of digital media literacy in resisting persuasion**.
1690 +{{/expandable}}
1691 +
1692 +{{expandable summary="📌 Relevance to Subproject"}}
1693 +- Provides insights into **how digital media shapes political discourse**.
1694 +- Highlights **which platforms and content types are most influential**.
1695 +- Supports **research on misinformation and online political engagement**.
1696 +{{/expandable}}
1697 +
1698 +{{expandable summary="🔍 Suggestions for Further Exploration"}}
1699 +1. Study how **fact-checking influences digital persuasion effects**.
1700 +2. Investigate the **role of political influencers in shaping opinions**.
1701 +3. Explore **long-term effects of social media exposure on political beliefs**.
1702 +{{/expandable}}
1703 +
1704 +{{expandable summary="📄 Download Full Study"}}
1705 +[[Download Full Study>>attach:10.1093_joc_jqx021.pdf]]
1706 +##~{~{/expand}}##
1707 +{{/expandable}}
1708 +{{/expandable}}
Cultural Voyeurism A New Framework for Understanding Race, Ethnicity, and Mediated Intergroup Intera.pdf
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