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Summary

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1 -Main Categories.Science & Research.WebHome
1 +Main.Studies.WebHome
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1 -{{toc/}}
2 -
3 -
4 4  = Research at a Glance =
5 5  
3 +== Introduction ==
6 6  
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.
7 7  
8 - 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.
7 +=== How to Use This Repository ===
9 9  
10 -
11 - 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:
12 -
13 -
14 -
15 15  - Click on a **category** in the **Table of Contents** to browse studies related to that topic.
16 16  - Click on a **study title** to expand its details, including **key findings, critique, and relevance**.
17 17  - Use the **search function** (Ctrl + F or XWiki's built-in search) to quickly find specific topics or authors.
18 18  - If needed, you can export this page as **PDF or print-friendly format**, and all studies will automatically expand for readability.
19 -- You'll also find a download link to the original full study in pdf form at the bottom of the collapsible block.
20 20  
14 +{{toc/}}
21 21  
16 +== Research Studies Repository ==
22 22  
23 -= Genetics =
24 24  
25 -{{expandable summary="
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
26 26  
27 -Study: Reconstructing Indian Population History"}}
28 -**Source:** *Nature*
29 -**Date of Publication:** *2009*
30 -**Author(s):** *David Reich, Kumarasamy Thangaraj, Nick Patterson, Alkes L. Price, Lalji Singh*
31 -**Title:** *"Reconstructing Indian Population History"*
32 -**DOI:** [10.1038/nature08365](https://doi.org/10.1038/nature08365)
33 -**Subject Matter:** *Genetics, Population History, South Asian Ancestry* 
28 +**Tags:** `Genetics` `Race & Ethnicity` `Biomedical Research`
34 34  
35 -{{expandable summary="📊 Key Statistics"}}
30 +=== **Key Statistics** ===
31 +
36 36  1. **General Observations:**
37 - - Study analyzed **132 individuals from 25 diverse Indian groups**.
38 - - Identified two major ancestral populations: **Ancestral North Indians (ANI)** and **Ancestral South Indians (ASI)**.
33 + - A near-perfect alignment between self-identified race/ethnicity (SIRE) and genetic ancestry was observed.
34 + - Misclassification rate: **0.14%**.
39 39  
40 40  2. **Subgroup Analysis:**
41 - - ANI ancestry is closely related to **Middle Easterners, Central Asians, and Europeans**.
42 - - ASI ancestry is **genetically distinct from ANI and East Asians**.
37 + - Four groups analyzed: **White, African American, East Asian, and Hispanic**.
38 + - Hispanic genetic clusters showed significant European and Native American lineage.
43 43  
44 -3. **Other Significant Data Points:**
45 - - ANI ancestry ranges from **39% to 71%** across Indian groups.
46 - - **Caste and linguistic differences** strongly correlate with genetic variation.
47 -{{/expandable}}
40 +=== **Findings** ===
48 48  
49 -{{expandable summary="🔬 Findings"}}
50 -1. **Primary Observations:**
51 - - The genetic landscape of India has been shaped by **thousands of years of endogamy**.
52 - - Groups with **only ASI ancestry no longer exist** in mainland India.
42 +- Self-identified race strongly aligns with genetic ancestry.
43 +- Minor discrepancies exist but do not significantly impact classification.
53 53  
54 -2. **Subgroup Trends:**
55 - - **Higher ANI ancestry in upper-caste and Indo-European-speaking groups**.
56 - - **Andaman Islanders** are unique in having **ASI ancestry without ANI influence**.
45 +=== **Relevance to Subproject** ===
57 57  
58 -3. **Specific Case Analysis:**
59 - - **Founder effects** have maintained allele frequency differences among Indian groups.
60 - - Predicts **higher incidence of recessive diseases** due to historical genetic isolation.
61 -{{/expandable}}
47 +- Reinforces the reliability of **self-reported racial identity** in genetic research.
48 +- Highlights **policy considerations** in biomedical studies.
49 +{{/expand}}
62 62  
63 -{{expandable summary="📝 Critique & Observations"}}
64 -1. **Strengths of the Study:**
65 - - **First large-scale genetic analysis** of Indian population history.
66 - - Introduces **new methods for ancestry estimation without direct ancestral reference groups**.
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]
67 67  
68 -2. **Limitations of the Study:**
69 - - Limited **sample size relative to India's population diversity**.
70 - - Does not include **recent admixture events** post-colonial era.
59 +---
71 71  
72 -3. **Suggestions for Improvement:**
73 - - Future research should **expand sampling across more Indian tribal groups**.
74 - - Use **whole-genome sequencing** for finer resolution of ancestry.
75 -{{/expandable}}
76 -
77 -{{expandable summary="📌 Relevance to Subproject"}}
78 -- Provides a **genetic basis for caste and linguistic diversity** in India.
79 -- Highlights **founder effects and genetic drift** shaping South Asian populations.
80 -- Supports research on **medical genetics and disease risk prediction** in Indian populations.
81 -{{/expandable}}
82 -
83 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
84 -1. Examine **genetic markers linked to disease susceptibility** in Indian subpopulations.
85 -2. Investigate the impact of **recent migration patterns on ANI-ASI ancestry distribution**.
86 -3. Study **gene flow between Indian populations and other global groups**.
87 -{{/expandable}}
88 -
89 -{{expandable summary="📄 Download Full Study"}}
90 -[[Download Full Study>>attach:10.1038_nature08365.pdf]]
91 -{{/expandable}}
92 -{{/expandable}}
93 -
94 -{{expandable summary="Study: The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations"}}
95 -**Source:** *Nature*
96 -**Date of Publication:** *2016*
97 -**Author(s):** *David Reich, Swapan Mallick, Heng Li, Mark Lipson, and others*
98 -**Title:** *"The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations"*
99 -**DOI:** [10.1038/nature18964](https://doi.org/10.1038/nature18964)
100 -**Subject Matter:** *Human Genetic Diversity, Population History, Evolutionary Genomics*
101 -
102 -{{expandable summary="📊 Key Statistics"}}
61 +## **Key Statistics**
103 103  1. **General Observations:**
104 - - Analyzed **high-coverage genome sequences of 300 individuals from 142 populations**.
105 - - Included **many underrepresented and indigenous groups** from Africa, Asia, Europe, and the Americas.
63 + - [Statistical finding or observation]
64 + - [Statistical finding or observation]
106 106  
107 107  2. **Subgroup Analysis:**
108 - - Found **higher genetic diversity within African populations** compared to non-African groups.
109 - - Showed **Neanderthal and Denisovan ancestry in non-African populations**, particularly in Oceania.
67 + - [Breakdown of findings by gender, race, or other subgroups]
110 110  
111 111  3. **Other Significant Data Points:**
112 - - Identified **5.8 million base pairs absent from the human reference genome**.
113 - - Estimated that **mutations have accumulated 5% faster in non-Africans than in Africans**.
114 -{{/expandable}}
70 + - [Any additional findings or significant statistics]
115 115  
116 -{{expandable summary="🔬 Findings"}}
72 +---
73 +
74 +## **Findings**
117 117  1. **Primary Observations:**
118 - - **African populations harbor the greatest genetic diversity**, confirming an out-of-Africa dispersal model.
119 - - Indigenous Australians and New Guineans **share a common ancestral population with other non-Africans**.
76 + - [High-level findings or trends in the study]
120 120  
121 121  2. **Subgroup Trends:**
122 - - **Lower heterozygosity in non-Africans** due to founder effects from migration bottlenecks.
123 - - **Denisovan ancestry in South Asians is higher than previously thought**.
79 + - [Disparities or differences highlighted in the study]
124 124  
125 125  3. **Specific Case Analysis:**
126 - - **Neanderthal ancestry is higher in East Asians than in Europeans**.
127 - - African hunter-gatherer groups show **deep population splits over 100,000 years ago**.
128 -{{/expandable}}
82 + - [Detailed explanation of any notable specific findings]
129 129  
130 -{{expandable summary="📝 Critique & Observations"}}
84 +---
85 +
86 +## **Critique and Observations**
131 131  1. **Strengths of the Study:**
132 - - **Largest global genetic dataset** outside of the 1000 Genomes Project.
133 - - High sequencing depth allows **more accurate identification of genetic variants**.
88 + - [Examples: strong methodology, large dataset, etc.]
134 134  
135 135  2. **Limitations of the Study:**
136 - - **Limited sample sizes for some populations**, restricting generalizability.
137 - - Lacks ancient DNA comparisons, making it difficult to reconstruct deep ancestry fully.
91 + - [Examples: data gaps, lack of upstream analysis, etc.]
138 138  
139 139  3. **Suggestions for Improvement:**
140 - - Future studies should include **ancient genomes** to improve demographic modeling.
141 - - Expand research into **how genetic variation affects health outcomes** across populations.
142 -{{/expandable}}
94 + - [Ideas for further research or addressing limitations]
143 143  
144 -{{expandable summary="📌 Relevance to Subproject"}}
145 -- Provides **comprehensive data on human genetic diversity**, useful for **evolutionary studies**.
146 -- Supports research on **Neanderthal and Denisovan introgression** in modern human populations.
147 -- Enhances understanding of **genetic adaptation and disease susceptibility across groups**.
148 -{{/expandable}}
96 +---
149 149  
150 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
151 -1. Investigate **functional consequences of genetic variation in underrepresented populations**.
152 -2. Study **how selection pressures shaped genetic diversity across different environments**.
153 -3. Explore **medical applications of population-specific genetic markers**.
154 -{{/expandable}}
98 +## **Relevance to Subproject**
99 +- [Explanation of how this study contributes to your subproject goals.]
100 +- [Any key arguments or findings that support or challenge your views.]
155 155  
156 -{{expandable summary="📄 Download Full Study"}}
157 -[[Download Full Study>>attach:10.1038_nature18964.pdf]]
158 -{{/expandable}}
159 -{{/expandable}}
102 +---
160 160  
161 -{{expandable summary="
104 +## **Suggestions for Further Exploration**
105 +1. [Research questions or areas to investigate further.]
106 +2. [Potential studies or sources to complement this analysis.]
162 162  
163 -Study: Meta-analysis of the heritability of human traits based on fifty years of twin studies"}}
164 -**Source:** *Nature Genetics*
165 -**Date of Publication:** *2015*
166 -**Author(s):** *Tinca J. C. Polderman, Beben Benyamin, Christiaan A. de Leeuw, Patrick F. Sullivan, Arjen van Bochoven, Peter M. Visscher, Danielle Posthuma*
167 -**Title:** *"Meta-analysis of the heritability of human traits based on fifty years of twin studies"*
168 -**DOI:** [10.1038/ng.328](https://doi.org/10.1038/ng.328)
169 -**Subject Matter:** *Genetics, Heritability, Twin Studies, Behavioral Science*
108 +---
170 170  
171 -{{expandable summary="📊 Key Statistics"}}
172 -1. **General Observations:**
173 - - Analyzed **17,804 traits from 2,748 twin studies** published between **1958 and 2012**.
174 - - Included data from **14,558,903 twin pairs**, making it the largest meta-analysis on human heritability.
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]**.
175 175  
176 -2. **Subgroup Analysis:**
177 - - Found **49% average heritability** across all traits.
178 - - **69% of traits follow a simple additive genetic model**, meaning most variance is due to genes, not environment.
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.
179 179  
180 -3. **Other Significant Data Points:**
181 - - **Neurological, metabolic, and psychiatric traits** showed the highest heritability estimates.
182 - - Traits related to **social values and environmental interactions** had lower heritability estimates.
183 -{{/expandable}}
115 +---
184 184  
185 -{{expandable summary="🔬 Findings"}}
186 -1. **Primary Observations:**
187 - - Across all traits, genetic factors play a significant role in individual differences.
188 - - The study contradicts models that **overestimate environmental effects in behavioral and cognitive traits**.
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}}
189 189  
190 -2. **Subgroup Trends:**
191 - - **Eye and brain-related traits showed the highest heritability (70-80%)**.
192 - - **Shared environmental effects were negligible (<10%) for most traits**.
128 +{{/expand}}
193 193  
194 -3. **Specific Case Analysis:**
195 - - Twin correlations suggest **limited evidence for strong non-additive genetic influences**.
196 - - The study highlights **missing heritability in complex traits**, which genome-wide association studies (GWAS) have yet to fully explain.
197 -{{/expandable}}
130 +{{html}}<hr style="border: 3px solid red;">{{/html}}
198 198  
199 -{{expandable summary="📝 Critique & Observations"}}
200 -1. **Strengths of the Study:**
201 - - **Largest-ever heritability meta-analysis**, covering nearly all published twin studies.
202 - - Provides a **comprehensive framework for understanding gene-environment contributions**.
203 203  
204 -2. **Limitations of the Study:**
205 - - **Underrepresentation of African, South American, and Asian twin cohorts**, limiting global generalizability.
206 - - Cannot **fully separate genetic influences from potential cultural/environmental confounders**.
207 207  
208 -3. **Suggestions for Improvement:**
209 - - Future research should use **whole-genome sequencing** for finer-grained heritability estimates.
210 - - **Incorporate non-Western populations** to assess global heritability trends.
211 -{{/expandable}}
134 +---
212 212  
213 -{{expandable summary="📌 Relevance to Subproject"}}
214 -- Establishes a **quantitative benchmark for heritability across human traits**.
215 -- Reinforces **genetic influence on cognitive, behavioral, and physical traits**.
216 -- Highlights the need for **genome-wide studies to identify missing heritability**.
217 -{{/expandable}}
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*
218 218  
219 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
220 -1. Investigate how **heritability estimates compare across different socioeconomic backgrounds**.
221 -2. Examine **gene-environment interactions in cognitive and psychiatric traits**.
222 -3. Explore **non-additive genetic effects on human traits using newer statistical models**.
223 -{{/expandable}}
144 +---
224 224  
225 -{{expandable summary="📄 Download Full Study"}}
226 -[[Download Full Study>>attach:10.1038_ng.328.pdf]]
227 -{{/expandable}}
228 -{{/expandable}}
229 -
230 -{{expandable summary="
231 -
232 -Study: Genetic Analysis of African Populations: Human Evolution and Complex Disease"}}
233 -**Source:** *Nature Reviews Genetics*
234 -**Date of Publication:** *2002*
235 -**Author(s):** *Sarah A. Tishkoff, Scott M. Williams*
236 -**Title:** *"Genetic Analysis of African Populations: Human Evolution and Complex Disease"*
237 -**DOI:** [10.1038/nrg865](https://doi.org/10.1038/nrg865)
238 -**Subject Matter:** *Population Genetics, Human Evolution, Complex Diseases* 
239 -
240 -{{expandable summary="📊 Key Statistics"}}
146 +## **Key Statistics**
241 241  1. **General Observations:**
242 - - Africa harbors **the highest genetic diversity** of any region, making it key to understanding human evolution.
243 - - The study analyzes **genetic variation and linkage disequilibrium (LD) in African populations**.
148 + - Study analyzed **General Social Survey (2000-2018)** data.
149 + - Found **declining trends in sexual activity** among young adults.
244 244  
245 245  2. **Subgroup Analysis:**
246 - - African populations exhibit **greater genetic differentiation compared to non-Africans**.
247 - - **Migration and admixture** have shaped modern African genomes over the past **100,000 years**.
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.
248 248  
249 249  3. **Other Significant Data Points:**
250 - - The **effective population size (Ne) of Africans** is higher than that of non-African populations.
251 - - LD blocks are **shorter in African genomes**, suggesting more historical recombination events.
252 -{{/expandable}}
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.
253 253  
254 -{{expandable summary="🔬 Findings"}}
159 +---
160 +
161 +## **Findings**
255 255  1. **Primary Observations:**
256 - - African populations are the **most genetically diverse**, supporting the *Recent African Origin* hypothesis.
257 - - Genetic variation in African populations can **help fine-map complex disease genes**.
163 + - A significant decline in sexual frequency, especially among **younger men**.
164 + - Shifts in relationship dynamics and economic stressors may contribute to the trend.
258 258  
259 259  2. **Subgroup Trends:**
260 - - **West Africans exhibit higher genetic diversity** than East Africans due to differing migration patterns.
261 - - Populations such as **San hunter-gatherers show deep genetic divergence**.
167 + - More pronounced decline among **unmarried individuals**.
168 + - No major change observed for **married adults** over time.
262 262  
263 263  3. **Specific Case Analysis:**
264 - - Admixture in African Americans includes **West African and European genetic contributions**.
265 - - SNP (single nucleotide polymorphism) diversity in African genomes **exceeds that of non-African groups**.
266 -{{/expandable}}
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.
267 267  
268 -{{expandable summary="📝 Critique & Observations"}}
174 +---
175 +
176 +## **Critique and Observations**
269 269  1. **Strengths of the Study:**
270 - - Provides **comprehensive genetic analysis** of diverse African populations.
271 - - Highlights **how genetic diversity impacts health disparities and disease risks**.
178 + - **Large sample size** from a nationally representative dataset.
179 + - **Longitudinal design** enables trend analysis over time.
272 272  
273 273  2. **Limitations of the Study:**
274 - - Many **African populations remain understudied**, limiting full understanding of diversity.
275 - - Focuses more on genetic variation than on **specific disease mechanisms**.
182 + - Self-reported data may introduce **response bias**.
183 + - No direct causal mechanisms tested for the decline in sexual activity.
276 276  
277 277  3. **Suggestions for Improvement:**
278 - - Expand research into **underrepresented African populations**.
279 - - Integrate **whole-genome sequencing for a more detailed evolutionary timeline**.
280 -{{/expandable}}
186 + - Further studies should incorporate **qualitative data** on behavioral shifts.
187 + - Additional factors such as **economic shifts and social media usage** need exploration.
281 281  
282 -{{expandable summary="📌 Relevance to Subproject"}}
283 -- Supports **genetic models of human evolution** and the **out-of-Africa hypothesis**.
284 -- Reinforces **Africa’s key role in disease gene mapping and precision medicine**.
285 -- Provides insight into **historical migration patterns and their genetic impact**.
286 -{{/expandable}}
189 +---
287 287  
288 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
289 -1. Investigate **genetic adaptations to local environments within Africa**.
290 -2. Study **the role of African genetic diversity in disease resistance**.
291 -3. Expand research on **how ancient migration patterns shaped modern genetic structure**.
292 -{{/expandable}}
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.
293 293  
294 -{{expandable summary="📄 Download Full Study"}}
295 -[[Download Full Study>>attach:10.1038_nrg865MODERN.pdf]]
296 -{{/expandable}}
297 -{{/expandable}}
195 +---
298 298  
299 -{{expandable summary="
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.
300 300  
301 -Study: Pervasive Findings of Directional Selection in Ancient DNA"}}
302 -**Source:** *bioRxiv Preprint*
303 -**Date of Publication:** *September 15, 2024*
304 -**Author(s):** *Ali Akbari, Alison R. Barton, Steven Gazal, Zheng Li, Mohammadreza Kariminejad, et al.*
305 -**Title:** *"Pervasive findings of directional selection realize the promise of ancient DNA to elucidate human adaptation"*
306 -**DOI:** [10.1101/2024.09.14.613021](https://doi.org/10.1101/2024.09.14.613021)
307 -**Subject Matter:** *Genomics, Evolutionary Biology, Natural Selection*
201 +---
308 308  
309 -{{expandable summary="📊 Key Statistics"}}
203 +## **Summary of Research Study**
204 +This study examines **trends in sexual frequency and number of partners among U.S. adults (2000-2018)**, highlighting significant **declines in sexual activity, particularly among young men**. The research utilized **General Social Survey data** to analyze the impact of **sociodemographic factors, employment status, and mental well-being** on sexual behavior.
205 +
206 +This summary provides an accessible, at-a-glance overview of the study's contributions. Please refer to the full paper for in-depth analysis.
207 +
208 +---
209 +
210 +## **📄 Download Full Study**
211 +{{velocity}}
212 +#set($doi = "10.1001_jamanetworkopen.2020.3833")
213 +#set($filename = "${doi}.pdf")
214 +#if($xwiki.exists("attach:$filename"))
215 +[[Download>>attach:$filename]]
216 +#else
217 +{{html}}<span style="color: red; font-weight: bold;">🚨 PDF Not Available 🚨</span>{{/html}}
218 +#end
219 +{{/velocity}}
220 +
221 +{{/expand}}
222 +
223 +{{html}}<hr style="border: 3px solid red;">{{/html}}
224 +
225 +
226 +{{expand title="Study: One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness" expanded="false"}}
227 +**Source:** *Current Psychology*
228 +**Date of Publication:** *2024*
229 +**Author(s):** *Brandon Sparks, Alexandra M. Zidenberg, Mark E. Olver*
230 +**Title:** *"One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness"*
231 +**DOI:** [10.1007/s12144-023-04275-z](https://doi.org/10.1007/s12144-023-04275-z)
232 +**Subject Matter:** *Psychology, Mental Health, Social Isolation*
233 +
234 +---
235 +
236 +## **Key Statistics**
310 310  1. **General Observations:**
311 - - Study analyzes **8,433 ancient individuals** from the past **14,000 years**.
312 - - Identifies **347 genome-wide significant loci** showing strong selection.
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.
313 313  
314 314  2. **Subgroup Analysis:**
315 - - Examines **West Eurasian populations** and their genetic evolution.
316 - - Tracks **changes in allele frequencies over millennia**.
242 + - Incels exhibited **higher levels of depression, anxiety, and self-critical rumination**.
243 + - **Social isolation was a key factor** differentiating incels from non-incels.
317 317  
318 318  3. **Other Significant Data Points:**
319 - - **10,000 years of directional selection** affected metabolic, immune, and cognitive traits.
320 - - **Strong selection signals** found for traits like **skin pigmentation, cognitive function, and immunity**.
321 -{{/expandable}}
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.
322 322  
323 -{{expandable summary="🔬 Findings"}}
249 +---
250 +
251 +## **Findings**
324 324  1. **Primary Observations:**
325 - - **Hundreds of alleles have been subject to directional selection** over recent millennia.
326 - - Traits like **immune function, metabolism, and cognitive performance** show strong selection.
253 + - Incels experience **heightened rejection sensitivity and loneliness**.
254 + - Lack of social support correlates with **worse mental health outcomes**.
327 327  
328 328  2. **Subgroup Trends:**
329 - - Selection pressure on **energy storage genes** supports the **Thrifty Gene Hypothesis**.
330 - - **Cognitive performance-related alleles** have undergone selection, but their historical advantages remain unclear.
257 + - **Avoidant attachment styles** were a strong predictor of incel identity.
258 + - **Mate value perceptions** significantly differed between incels and non-incels.
331 331  
332 332  3. **Specific Case Analysis:**
333 - - **Celiac disease risk allele** increased from **0% to 20%** in 4,000 years.
334 - - **Blood type B frequency rose from 0% to 8% in 6,000 years**.
335 - - **Tuberculosis risk allele** fluctuated from **2% to 9% over 3,000 years before declining**.
336 -{{/expandable}}
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.
337 337  
338 -{{expandable summary="📝 Critique & Observations"}}
264 +---
265 +
266 +## **Critique and Observations**
339 339  1. **Strengths of the Study:**
340 - - **Largest dataset to date** on natural selection in human ancient DNA.
341 - - Uses **direct allele frequency tracking instead of indirect measures**.
268 + - **First quantitative study** on incels’ social isolation and mental health.
269 + - **Robust sample size** and validated psychological measures.
342 342  
343 343  2. **Limitations of the Study:**
344 - - Findings **may not translate directly** to modern populations.
345 - - **Unclear whether observed selection pressures persist today**.
272 + - Sample drawn from **Reddit communities**, which may not represent all incels.
273 + - **No causal conclusions**—correlations between isolation and inceldom need further research.
346 346  
347 347  3. **Suggestions for Improvement:**
348 - - Expanding research to **other global populations** to assess universal trends.
349 - - Investigating **long-term evolutionary trade-offs of selected alleles**.
350 -{{/expandable}}
276 + - Future studies should **compare incel forum users vs. non-users**.
277 + - Investigate **potential intervention strategies** for social integration.
351 351  
352 -{{expandable summary="📌 Relevance to Subproject"}}
353 -- Provides **direct evidence of long-term genetic adaptation** in human populations.
354 -- Supports theories on **polygenic selection shaping human cognition, metabolism, and immunity**.
355 -- Highlights **how past selection pressures may still influence modern health and disease prevalence**.
356 -{{/expandable}}
279 +---
357 357  
358 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
359 -1. Examine **selection patterns in non-European populations** for comparison.
360 -2. Investigate **how environmental and cultural shifts influenced genetic selection**.
361 -3. Explore **the genetic basis of traits linked to past and present-day human survival**.
362 -{{/expandable}}
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**.
363 363  
364 -{{expandable summary="📄 Download Full Study"}}
365 -[[Download Full Study>>attach:10.1101_2024.09.14.613021doi_.pdf]]
366 -{{/expandable}}
367 -{{/expandable}}
286 +---
368 368  
369 -{{expandable summary="Study: The Wilson Effect: The Increase in Heritability of IQ With Age"}}
370 -**Source:** *Twin Research and Human Genetics (Cambridge University Press)*
371 -**Date of Publication:** *2013*
372 -**Author(s):** *Thomas J. Bouchard Jr.*
373 -**Title:** *"The Wilson Effect: The Increase in Heritability of IQ With Age"*
374 -**DOI:** [10.1017/thg.2013.54](https://doi.org/10.1017/thg.2013.54)
375 -**Subject Matter:** *Intelligence, Heritability, Developmental Psychology*
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.
376 376  
377 -{{expandable summary="📊 Key Statistics"}}
378 -1. **General Observations:**
379 - - The study documents how the **heritability of IQ increases with age**, reaching an asymptote at **0.80 by adulthood**.
380 - - Analysis is based on **longitudinal twin and adoption studies**.
293 +---
381 381  
382 -2. **Subgroup Analysis:**
383 - - Shared environmental influence on IQ **declines with age**, reaching **0.10 in adulthood**.
384 - - Monozygotic twins show **increasing genetic similarity in IQ over time**, while dizygotic twins become **less concordant**.
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**.
385 385  
386 -3. **Other Significant Data Points:**
387 - - Data from the **Louisville Longitudinal Twin Study and cross-national twin samples** support findings.
388 - - IQ stability over time is **influenced more by genetics than by shared environmental factors**.
389 -{{/expandable}}
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.
390 390  
391 -{{expandable summary="🔬 Findings"}}
392 -1. **Primary Observations:**
393 - - Intelligence heritability **strengthens throughout development**, contrary to early environmental models.
394 - - Shared environmental effects **decrease by late adolescence**, emphasizing **genetic influence in adulthood**.
300 +---
395 395  
396 -2. **Subgroup Trends:**
397 - - Studies from **Scotland, Netherlands, and the US** show **consistent patterns of increasing heritability with age**.
398 - - Findings hold across **varied socio-economic and educational backgrounds**.
302 +## **📄 Download Full Study**
303 +[[Download Full Study>>attach:10.1007_s12144-023-04275-z.pdf]]
399 399  
400 -3. **Specific Case Analysis:**
401 - - Longitudinal adoption studies show **declining impact of adoptive parental influence on IQ** as children age.
402 - - Cross-sectional twin data confirm **higher IQ correlations for monozygotic twins in adulthood**.
403 -{{/expandable}}
305 +{{/expand}}
404 404  
405 -{{expandable summary="📝 Critique & Observations"}}
406 -1. **Strengths of the Study:**
407 - - **Robust dataset covering multiple twin and adoption studies over decades**.
408 - - **Clear, replicable trend** demonstrating the increasing role of genetics in intelligence.
307 +{{html}}<hr style="border: 3px solid red;">{{/html}}
409 409  
410 -2. **Limitations of the Study:**
411 - - Findings apply primarily to **Western industrialized nations**, limiting generalizability.
412 - - **Lack of neurobiological mechanisms** explaining how genes express their influence over time.
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
413 413  
414 -3. **Suggestions for Improvement:**
415 - - Future research should investigate **gene-environment interactions in cognitive aging**.
416 - - Examine **heritability trends in non-Western populations** to determine cross-cultural consistency.
417 -{{/expandable}}
316 +Key Statistics
317 +General Observations:
418 418  
419 -{{expandable summary="📌 Relevance to Subproject"}}
420 -- Provides **strong evidence for the genetic basis of intelligence**.
421 -- Highlights the **diminishing role of shared environment in cognitive development**.
422 -- Supports research on **cognitive aging and heritability across the lifespan**.
423 -{{/expandable}}
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:
424 424  
425 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
426 -1. Investigate **neurogenetic pathways underlying IQ development**.
427 -2. Examine **how education and socioeconomic factors interact with genetic IQ influences**.
428 -3. Study **heritability trends in aging populations and cognitive decline**.
429 -{{/expandable}}
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:
430 430  
431 -{{expandable summary="📄 Download Full Study"}}
432 -[[Download Full Study>>attach:10.1017_thg.2013.54.pdf]]
433 -{{/expandable}}
434 -{{/expandable}}
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:
435 435  
436 -{{expandable summary="Study: Is Homo sapiens polytypic? Human taxonomic diversity and its implications"}}
437 -**Source:** *Medical Hypotheses (Elsevier)*
438 -**Date of Publication:** *2010*
439 -**Author(s):** *Michael A. Woodley*
440 -**Title:** *"Is Homo sapiens polytypic? Human taxonomic diversity and its implications"*
441 -**DOI:** [10.1016/j.mehy.2009.07.046](https://doi.org/10.1016/j.mehy.2009.07.046)
442 -**Subject Matter:** *Human Taxonomy, Evolutionary Biology, Anthropology*
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:
443 443  
444 -{{expandable summary="📊 Key Statistics"}}
445 -1. **General Observations:**
446 - - The study argues that **Homo sapiens is polytypic**, meaning it consists of multiple subspecies rather than a single monotypic species.
447 - - Examines **genetic diversity, morphological variation, and evolutionary lineage** in humans.
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:
448 448  
449 -2. **Subgroup Analysis:**
450 - - Discusses **four primary definitions of race/subspecies**: Essentialist, Taxonomic, Population-based, and Lineage-based.
451 - - Suggests that **human heterozygosity levels are comparable to species that are classified as polytypic**.
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:
452 452  
453 -3. **Other Significant Data Points:**
454 - - The study evaluates **FST values (genetic differentiation measure)** and argues that human genetic differentiation is comparable to that of recognized subspecies in other species.
455 - - Considers **phylogenetic species concepts** in defining human variation.
456 -{{/expandable}}
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:
457 457  
458 -{{expandable summary="🔬 Findings"}}
459 -1. **Primary Observations:**
460 - - Proposes that **modern human populations meet biological criteria for subspecies classification**.
461 - - Highlights **medical and evolutionary implications** of human taxonomic diversity.
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:
462 462  
463 -2. **Subgroup Trends:**
464 - - Discusses **how race concepts evolved over time** in biological sciences.
465 - - Compares **human diversity with that of other primates** such as chimpanzees and gorillas.
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.
466 466  
467 -3. **Specific Case Analysis:**
468 - - Evaluates how **genetic markers correlate with population structure**.
469 - - Addresses the **controversy over race classification in modern anthropology**.
470 -{{/expandable}}
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.
471 471  
472 -{{expandable summary="📝 Critique & Observations"}}
473 -1. **Strengths of the Study:**
474 - - Uses **comparative species analysis** to assess human classification.
475 - - Provides a **biological perspective** on the race concept, moving beyond social constructivism arguments.
368 +📄 Download Full Study
369 +[[Download Full Study>>attach:10.1016_j.addbeh.2016.02.030.pdf]]
476 476  
477 -2. **Limitations of the Study:**
478 - - Controversial topic with **strong opposing views in anthropology and genetics**.
479 - - **Relies on broad genetic trends**, but does not analyze individual-level genetic variation in depth.
371 +{{/expand}}
480 480  
481 -3. **Suggestions for Improvement:**
482 - - Further research should **incorporate whole-genome studies** to refine subspecies classifications.
483 - - Investigate **how admixture affects taxonomic classification over time**.
484 -{{/expandable}}
373 +{{html}}<hr style="border: 3px solid red;">{{/html}}
485 485  
486 -{{expandable summary="📌 Relevance to Subproject"}}
487 -- Contributes to discussions on **evolutionary taxonomy and species classification**.
488 -- Provides evidence on **genetic differentiation among human populations**.
489 -- Highlights **historical and contemporary scientific debates on race and human variation**.
490 -{{/expandable}}
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*
491 491  
492 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
493 -1. Examine **FST values in modern and ancient human populations**.
494 -2. Investigate how **adaptive evolution influences population differentiation**.
495 -3. Explore **the impact of genetic diversity on medical treatments and disease susceptibility**.
496 -{{/expandable}}
383 +---
497 497  
498 -{{expandable summary="📄 Download Full Study"}}
499 -[[Download Full Study>>attach:10.1016_j.mehy.2009.07.046.pdf]]
500 -{{/expandable}}
501 -{{/expandable}}
502 -
503 -= IQ =
504 -
505 -{{expandable summary="Study: Survey of Expert Opinion on Intelligence: Intelligence Research, Experts' Background, Controversial Issues, and the Media"}}
506 -**Source:** *Intelligence (Elsevier)*
507 -**Date of Publication:** *2019*
508 -**Author(s):** *Heiner Rindermann, David Becker, Thomas R. Coyle*
509 -**Title:** *"Survey of Expert Opinion on Intelligence: Intelligence Research, Experts' Background, Controversial Issues, and the Media"*
510 -**DOI:** [10.1016/j.intell.2019.101406](https://doi.org/10.1016/j.intell.2019.101406)
511 -**Subject Matter:** *Psychology, Intelligence Research, Expert Analysis*
512 -
513 -{{expandable summary="📊 Key Statistics"}}
385 +## **Key Statistics**
514 514  1. **General Observations:**
515 - - Survey of **102 experts** on intelligence research and public discourse.
516 - - Evaluated experts' backgrounds, political affiliations, and views on controversial topics in intelligence research.
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.
517 517  
518 518  2. **Subgroup Analysis:**
519 - - **90% of experts were from Western countries**, and **83% were male**.
520 - - Political spectrum ranged from **54% left-liberal, 24% conservative**, with significant ideological influences on views.
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.
521 521  
522 522  3. **Other Significant Data Points:**
523 - - Experts rated media coverage of intelligence research as **poor (avg. 3.1 on a 9-point scale)**.
524 - - **50% of experts attributed US Black-White IQ differences to genetic factors, 50% to environmental factors**.
525 -{{/expandable}}
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**.
526 526  
527 -{{expandable summary="🔬 Findings"}}
398 +---
399 +
400 +## **Findings**
528 528  1. **Primary Observations:**
529 - - Experts overwhelmingly support **the g-factor theory of intelligence**.
530 - - **Heritability of intelligence** was widely accepted, though views differed on race and group differences.
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.
531 531  
532 532  2. **Subgroup Trends:**
533 - - **Left-leaning experts were more likely to reject genetic explanations for group IQ differences**.
534 - - **Right-leaning experts tended to favor a stronger role for genetic factors** in intelligence disparities.
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**.
535 535  
536 536  3. **Specific Case Analysis:**
537 - - The study compared **media coverage of intelligence research** with expert opinions.
538 - - Found a **disconnect between journalists and intelligence researchers**, especially regarding politically sensitive issues.
539 -{{/expandable}}
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.
540 540  
541 -{{expandable summary="📝 Critique & Observations"}}
413 +---
414 +
415 +## **Critique and Observations**
542 542  1. **Strengths of the Study:**
543 - - **Largest expert survey on intelligence research** to date.
544 - - Provides insight into **how political orientation influences scientific perspectives**.
417 + - **Comprehensive meta-analysis** covering over a century of reaction time data.
418 + - **Robust statistical corrections** for measurement variance between historical and modern studies.
545 545  
546 546  2. **Limitations of the Study:**
547 - - **Sample primarily from Western countries**, limiting global perspectives.
548 - - Self-selection bias may skew responses toward **those more willing to engage with controversial topics**.
421 + - Some historical data sources **lack methodological consistency**.
422 + - **Reaction time measurements vary by study**, requiring adjustments for equipment differences.
549 549  
550 550  3. **Suggestions for Improvement:**
551 - - Future studies should include **a broader range of global experts**.
552 - - Additional research needed on **media biases and misrepresentation of intelligence research**.
553 -{{/expandable}}
425 + - Future studies should **replicate results with more modern datasets**.
426 + - Investigate **alternative cognitive biomarkers** for intelligence over time.
554 554  
555 -{{expandable summary="📌 Relevance to Subproject"}}
556 -- Provides insight into **expert consensus and division on intelligence research**.
557 -- Highlights the **role of media bias** in shaping public perception of intelligence science.
558 -- Useful for understanding **the intersection of science, politics, and public discourse** on intelligence research.
559 -{{/expandable}}
428 +---
560 560  
561 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
562 -1. Examine **cross-national differences** in expert opinions on intelligence.
563 -2. Investigate how **media bias impacts public understanding of intelligence research**.
564 -3. Conduct follow-up studies with **a more diverse expert pool** to test findings.
565 -{{/expandable}}
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**.
566 566  
567 -{{expandable summary="📄 Download Full Study"}}
568 -[[Download Full Study>>attach:10.1016_j.intell.2019.101406.pdf]]
569 -{{/expandable}}
570 -{{/expandable}}
435 +---
571 571  
572 -{{expandable summary="Study: A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation"}}
573 -**Source:** *Intelligence (Elsevier)*
574 -**Date of Publication:** *2015*
575 -**Author(s):** *Davide Piffer*
576 -**Title:** *"A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation"*
577 -**DOI:** [10.1016/j.intell.2015.08.008](https://doi.org/10.1016/j.intell.2015.08.008)
578 -**Subject Matter:** *Genetics, Intelligence, GWAS, Population Differences*
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**.
579 579  
580 -{{expandable summary="📊 Key Statistics"}}
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**
581 581  1. **General Observations:**
582 582   - Study analyzed **genome-wide association studies (GWAS) hits** linked to intelligence.
583 583   - Found a **strong correlation (r = .91) between polygenic intelligence scores and national IQ levels**.
... ... @@ -589,9 +589,10 @@
589 589  3. **Other Significant Data Points:**
590 590   - GWAS intelligence SNPs predicted **IQ levels more strongly than random genetic markers**.
591 591   - Genetic differentiation (Fst values) showed that **selection pressure, rather than drift, influenced intelligence-related allele distributions**.
592 -{{/expandable}}
593 593  
594 -{{expandable summary="🔬 Findings"}}
481 +---
482 +
483 +## **Findings**
595 595  1. **Primary Observations:**
596 596   - Intelligence-associated SNP frequencies correlate **highly with national IQ levels**.
597 597   - Genetic selection for intelligence appears **stronger than selection for height-related genes**.
... ... @@ -603,9 +603,10 @@
603 603  3. **Specific Case Analysis:**
604 604   - Polygenic scores using **intelligence-related alleles significantly outperformed random SNPs** in predicting IQ.
605 605   - Selection pressures **may explain differences in global intelligence distribution** beyond genetic drift effects.
606 -{{/expandable}}
607 607  
608 -{{expandable summary="📝 Critique & Observations"}}
496 +---
497 +
498 +## **Critique and Observations**
609 609  1. **Strengths of the Study:**
610 610   - **Comprehensive genetic analysis** of intelligence-linked SNPs.
611 611   - Uses **multiple statistical methods (factor analysis, Fst analysis) to confirm results**.
... ... @@ -617,520 +617,297 @@
617 617  3. **Suggestions for Improvement:**
618 618   - Larger **cross-population GWAS studies** needed to validate findings.
619 619   - Investigate **non-genetic contributors to IQ variance** in addition to genetic factors.
620 -{{/expandable}}
621 621  
622 -{{expandable summary="📌 Relevance to Subproject"}}
511 +---
512 +
513 +## **Relevance to Subproject**
623 623  - Supports research on **genetic influences on intelligence at a population level**.
624 624  - Aligns with broader discussions on **cognitive genetics and natural selection effects**.
625 625  - Provides a **quantitative framework for analyzing polygenic selection in intelligence studies**.
626 -{{/expandable}}
627 627  
628 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
518 +---
519 +
520 +## **Suggestions for Further Exploration**
629 629  1. Conduct **expanded GWAS studies** including diverse populations.
630 630  2. Investigate **gene-environment interactions influencing intelligence**.
631 631  3. Explore **historical selection pressures shaping intelligence-related alleles**.
632 -{{/expandable}}
633 633  
634 -{{expandable summary="📄 Download Full Study"}}
635 -[[Download Full Study>>attach:10.1016_j.intell.2015.08.008.pdf]]
636 -{{/expandable}}
637 -{{/expandable}}
525 +---
638 638  
639 -{{expandable summary="Study: Genetic Structure, Self-Identified Race/Ethnicity, and Confounding"}}
640 -**Source:** Journal of Genetic Epidemiology
641 -**Date of Publication:** 2024-01-15
642 -**Author(s):** Smith et al.
643 -**Title:** "Genetic Structure, Self-Identified Race/Ethnicity, and Confounding in Case-Control Association Studies"
644 -**DOI:** [https://doi.org/10.1037/1076-8971.11.2.235](https://doi.org/10.1037/1076-8971.11.2.235)
645 -**Subject Matter:** Genetics, Social Science
646 -{{/expandable}}
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.
647 647  
648 -= Dating =
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.
649 649  
650 -{{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"}}
651 -**Source:** *JAMA Network Open*
652 -**Date of Publication:** *2020*
653 -**Author(s):** *Ueda P, Mercer CH, Ghaznavi C, Herbenick D.*
654 -**Title:** *"Trends in Frequency of Sexual Activity and Number of Sexual Partners Among Adults Aged 18 to 44 Years in the US, 2000-2018"*
655 -**DOI:** [10.1001/jamanetworkopen.2020.3833](https://doi.org/10.1001/jamanetworkopen.2020.3833)
656 -**Subject Matter:** *Public Health, Sexual Behavior, Demography* 
532 +---
657 657  
658 -{{expandable summary="📊 Key Statistics"}}
659 -1. **General Observations:**
660 - - Study analyzed **General Social Survey (2000-2018)** data.
661 - - Found **declining trends in sexual activity** among young adults.
534 +## **📄 Download Full Study**
535 +[[Download Full Study>>attach:10.1016_j.intell.2015.08.008.pdf]]
662 662  
663 -2. **Subgroup Analysis:**
664 - - Decreases in sexual activity were most prominent among **men aged 18-34**.
665 - - Factors like **marital status, employment, and psychological well-being** were associated with changes in sexual frequency.
537 +{{/expand}}
666 666  
667 -3. **Other Significant Data Points:**
668 - - Frequency of sexual activity decreased by **8-10%** over the studied period.
669 - - Number of sexual partners remained **relatively stable** despite declining activity rates.
670 -{{/expandable}}
539 +{{html}}<hr style="border: 3px solid red;">{{/html}}
671 671  
672 -{{expandable summary="🔬 Findings"}}
673 -1. **Primary Observations:**
674 - - A significant decline in sexual frequency, especially among **younger men**.
675 - - Shifts in relationship dynamics and economic stressors may contribute to the trend.
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*
676 676  
677 -2. **Subgroup Trends:**
678 - - More pronounced decline among **unmarried individuals**.
679 - - No major change observed for **married adults** over time.
549 +---
680 680  
681 -3. **Specific Case Analysis:**
682 - - **Mental health and employment status** were correlated with decreased activity.
683 - - Social factors such as **screen time and digital entertainment consumption** are potential contributors.
684 -{{/expandable}}
685 -
686 -{{expandable summary="📝 Critique & Observations"}}
687 -1. **Strengths of the Study:**
688 - - **Large sample size** from a nationally representative dataset.
689 - - **Longitudinal design** enables trend analysis over time.
690 -
691 -2. **Limitations of the Study:**
692 - - Self-reported data may introduce **response bias**.
693 - - No direct causal mechanisms tested for the decline in sexual activity.
694 -
695 -3. **Suggestions for Improvement:**
696 - - Further studies should incorporate **qualitative data** on behavioral shifts.
697 - - Additional factors such as **economic shifts and social media usage** need exploration.
698 -{{/expandable}}
699 -
700 -{{expandable summary="📌 Relevance to Subproject"}}
701 -- Provides evidence on **changing demographic behaviors** in relation to relationships and social interactions.
702 -- Highlights the role of **mental health, employment, and societal changes** in personal behaviors.
703 -{{/expandable}}
704 -
705 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
706 -1. Investigate the **impact of digital media consumption** on relationship dynamics.
707 -2. Examine **regional and cultural differences** in sexual activity trends.
708 -{{/expandable}}
709 -
710 -{{expandable summary="📄 Download Full Study"}}
711 -
712 -{{/expandable}}
713 -{{/expandable}}
714 -
715 -{{expandable summary="Study: Biracial Couples and Adverse Birth Outcomes – A Systematic Review and Meta-Analysis"}}
716 -**Source:** *Acta Obstetricia et Gynecologica Scandinavica*
717 -**Date of Publication:** *2012*
718 -**Author(s):** *Ravisha M. Srinivasjois, Shreya Shah, Prakesh S. Shah, Knowledge Synthesis Group on Determinants of Preterm/LBW Births*
719 -**Title:** *"Biracial Couples and Adverse Birth Outcomes: A Systematic Review and Meta-Analysis"*
720 -**DOI:** [10.1111/j.1600-0412.2012.01501.x](https://doi.org/10.1111/j.1600-0412.2012.01501.x)
721 -**Subject Matter:** *Neonatal Health, Maternal-Fetal Medicine, Racial Disparities*
722 -
723 -{{expandable summary="📊 Key Statistics"}}
551 +## **Key Statistics**
724 724  1. **General Observations:**
725 - - Meta-analysis of **26,335,596 singleton births** from eight studies.
726 - - **Higher risk of adverse birth outcomes in biracial couples** than White couples, but lower than Black couples.
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.
727 727  
728 728  2. **Subgroup Analysis:**
729 - - **Maternal race had a stronger influence than paternal race** on birth outcomes.
730 - - **Black mother–White father (BMWF) couples** had a higher risk than **White mother–Black father (WMBF) couples**.
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.
731 731  
732 732  3. **Other Significant Data Points:**
733 - - **Adjusted Odds Ratios (aORs) for key outcomes:**
734 - - **Low birthweight (LBW):** WMBF (1.21), BMWF (1.75), Black mother–Black father (BMBF) (2.08).
735 - - **Preterm births (PTB):** WMBF (1.17), BMWF (1.37), BMBF (1.78).
736 - - **Stillbirths:** WMBF (1.43), BMWF (1.51), BMBF (1.85).
737 -{{/expandable}}
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**.
738 738  
739 -{{expandable summary="🔬 Findings"}}
564 +---
565 +
566 +## **Findings**
740 740  1. **Primary Observations:**
741 - - **Biracial couples face a gradient of risk**: higher than White couples but lower than Black couples.
742 - - **Maternal race plays a more significant role** in pregnancy outcomes.
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.
743 743  
744 744  2. **Subgroup Trends:**
745 - - **Black mothers (regardless of paternal race) had the highest risk of LBW and PTB**.
746 - - **White mothers with Black fathers had a lower risk** than Black mothers with White fathers.
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.
747 747  
748 748  3. **Specific Case Analysis:**
749 - - The **weathering hypothesis** suggests that **long-term stress exposure** contributes to higher adverse birth risks in Black mothers.
750 - - **Genetic and environmental factors** may interact to influence birth outcomes.
751 -{{/expandable}}
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.
752 752  
753 -{{expandable summary="📝 Critique & Observations"}}
579 +---
580 +
581 +## **Critique and Observations**
754 754  1. **Strengths of the Study:**
755 - - **Largest meta-analysis** on racial disparities in birth outcomes.
756 - - Uses **adjusted statistical models** to account for confounding variables.
583 + - **Largest expert survey on intelligence research** to date.
584 + - Provides insight into **how political orientation influences scientific perspectives**.
757 757  
758 758  2. **Limitations of the Study:**
759 - - Data limited to **Black-White biracial couples**, excluding other racial groups.
760 - - **Socioeconomic and healthcare access factors** not fully explored.
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**.
761 761  
762 762  3. **Suggestions for Improvement:**
763 - - Future studies should examine **Asian, Hispanic, and Indigenous biracial couples**.
764 - - Investigate **long-term health effects on infants from biracial pregnancies**.
765 -{{/expandable}}
591 + - Future studies should include **a broader range of global experts**.
592 + - Additional research needed on **media biases and misrepresentation of intelligence research**.
766 766  
767 -{{expandable summary="📌 Relevance to Subproject"}}
768 -- Provides **critical insights into racial disparities** in maternal and infant health.
769 -- Supports **research on genetic and environmental influences on neonatal health**.
770 -- Highlights **how maternal race plays a more significant role than paternal race** in birth outcomes.
771 -{{/expandable}}
594 +---
772 772  
773 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
774 -1. Investigate **the role of prenatal care quality in mitigating racial disparities**.
775 -2. Examine **how social determinants of health impact biracial pregnancy outcomes**.
776 -3. Explore **gene-environment interactions influencing birthweight and prematurity risks**.
777 -{{/expandable}}
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.
778 778  
779 -{{expandable summary="📄 Download Full Study"}}
780 -[[Download Full Study>>attach:10.1111_j.1600-0412.2012.01501.xAbstract.pdf]]
781 -{{/expandable}}
782 -{{/expandable}}
601 +---
783 783  
784 -{{expandable summary="Study: One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness"}}
785 -**Source:** *Current Psychology*
786 -**Date of Publication:** *2024*
787 -**Author(s):** *Brandon Sparks, Alexandra M. Zidenberg, Mark E. Olver*
788 -**Title:** *"One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness"*
789 -**DOI:** [10.1007/s12144-023-04275-z](https://doi.org/10.1007/s12144-023-04275-z)
790 -**Subject Matter:** *Psychology, Mental Health, Social Isolation*
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.
791 791  
792 -{{expandable summary="📊 Key Statistics"}}
793 -1. **General Observations:**
794 - - Study analyzed **67 self-identified incels** and **103 non-incel men**.
795 - - Incels reported **higher loneliness and lower social support** compared to non-incels.
608 +---
796 796  
797 -2. **Subgroup Analysis:**
798 - - Incels exhibited **higher levels of depression, anxiety, and self-critical rumination**.
799 - - **Social isolation was a key factor** differentiating incels from non-incels.
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**.
800 800  
801 -3. **Other Significant Data Points:**
802 - - 95% of incels in the study reported **having depression**, with 38% receiving a formal diagnosis.
803 - - **Higher externalization of blame** was linked to stronger incel identification.
804 -{{/expandable}}
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.
805 805  
806 -{{expandable summary="🔬 Findings"}}
807 -1. **Primary Observations:**
808 - - Incels experience **heightened rejection sensitivity and loneliness**.
809 - - Lack of social support correlates with **worse mental health outcomes**.
615 +---
810 810  
811 -2. **Subgroup Trends:**
812 - - **Avoidant attachment styles** were a strong predictor of incel identity.
813 - - **Mate value perceptions** significantly differed between incels and non-incels.
617 +## **📄 Download Full Study**
618 +[[Download Full Study>>attach:10.1016_j.intell.2019.101406.pdf]]
814 814  
815 -3. **Specific Case Analysis:**
816 - - Incels **engaged in fewer positive coping mechanisms** such as emotional support or positive reframing.
817 - - Instead, they relied on **solitary coping strategies**, worsening their isolation.
818 -{{/expandable}}
620 +{{/expand}}
819 819  
820 -{{expandable summary="📝 Critique & Observations"}}
821 -1. **Strengths of the Study:**
822 - - **First quantitative study** on incels’ social isolation and mental health.
823 - - **Robust sample size** and validated psychological measures.
622 +{{html}}<hr style="border: 3px solid red;">{{/html}}
824 824  
825 -2. **Limitations of the Study:**
826 - - Sample drawn from **Reddit communities**, which may not represent all incels.
827 - - **No causal conclusions**—correlations between isolation and inceldom need further research.
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*
828 828  
829 -3. **Suggestions for Improvement:**
830 - - Future studies should **compare incel forum users vs. non-users**.
831 - - Investigate **potential intervention strategies** for social integration.
832 -{{/expandable}}
632 +---
833 833  
834 -{{expandable summary="📌 Relevance to Subproject"}}
835 -- Highlights **mental health vulnerabilities** within the incel community.
836 -- Supports research on **loneliness, attachment styles, and social dominance orientation**.
837 -- Examines how **peer rejection influences self-perceived mate value**.
838 -{{/expandable}}
839 -
840 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
841 -1. Explore how **online community participation** affects incel mental health.
842 -2. Investigate **cognitive biases** influencing self-perceived rejection among incels.
843 -3. Assess **therapeutic interventions** to address incel social isolation.
844 -{{/expandable}}
845 -
846 -{{expandable summary="📄 Download Full Study"}}
847 -[[Download Full Study>>attach:10.1007_s12144-023-04275-z.pdf]]
848 -{{/expandable}}
849 -{{/expandable}}
850 -
851 -= Crime and Substance Abuse =
852 -
853 -{{expandable summary="Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program"}}
854 -**Source:** *Substance Use & Misuse*
855 -**Date of Publication:** *2002*
856 -**Author(s):** *Clifford A. Butzin, Christine A. Saum, Frank R. Scarpitti*
857 -**Title:** *"Factors Associated with Completion of a Drug Treatment Court Diversion Program"*
858 -**DOI:** [10.1081/JA-120014424](https://doi.org/10.1081/JA-120014424)
859 -**Subject Matter:** *Substance Use, Criminal Justice, Drug Courts*
860 -
861 -{{expandable summary="📊 Key Statistics"}}
634 +## **Key Statistics**
862 862  1. **General Observations:**
863 - - Study examined **drug treatment court success rates** among first-time offenders.
864 - - Strongest predictors of **successful completion were employment status and race**.
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.
865 865  
866 866  2. **Subgroup Analysis:**
867 - - Individuals with **stable jobs were more likely to complete the program**.
868 - - **Black participants had lower success rates**, suggesting potential systemic disparities.
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**.
869 869  
870 870  3. **Other Significant Data Points:**
871 - - **Education level was positively correlated** with program completion.
872 - - Frequency of **drug use before enrollment affected treatment outcomes**.
873 -{{/expandable}}
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.
874 874  
875 -{{expandable summary="🔬 Findings"}}
647 +---
648 +
649 +## **Findings**
876 876  1. **Primary Observations:**
877 - - **Social stability factors** (employment, education) were key to treatment success.
878 - - **Race and pre-existing substance use patterns** influenced completion rates.
651 + - Proposes that **modern human populations meet biological criteria for subspecies classification**.
652 + - Highlights **medical and evolutionary implications** of human taxonomic diversity.
879 879  
880 880  2. **Subgroup Trends:**
881 - - White offenders had **higher completion rates** than Black offenders.
882 - - Drug court success was **higher for those with lower initial drug use frequency**.
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.
883 883  
884 884  3. **Specific Case Analysis:**
885 - - **Individuals with strong social ties were more likely to finish the program**.
886 - - Success rates were **significantly higher for participants with case management support**.
887 -{{/expandable}}
659 + - Evaluates how **genetic markers correlate with population structure**.
660 + - Addresses the **controversy over race classification in modern anthropology**.
888 888  
889 -{{expandable summary="📝 Critique & Observations"}}
662 +---
663 +
664 +## **Critique and Observations**
890 890  1. **Strengths of the Study:**
891 - - **First empirical study on drug court program success factors**.
892 - - Uses **longitudinal data** for post-treatment analysis.
666 + - Uses **comparative species analysis** to assess human classification.
667 + - Provides a **biological perspective** on the race concept, moving beyond social constructivism arguments.
893 893  
894 894  2. **Limitations of the Study:**
895 - - Lacks **qualitative data on personal motivation and treatment engagement**.
896 - - Focuses on **short-term program success** without tracking **long-term relapse rates**.
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.
897 897  
898 898  3. **Suggestions for Improvement:**
899 - - Future research should examine **racial disparities in drug court outcomes**.
900 - - Study **how community resources impact long-term recovery**.
901 -{{/expandable}}
674 + - Further research should **incorporate whole-genome studies** to refine subspecies classifications.
675 + - Investigate **how admixture affects taxonomic classification over time**.
902 902  
903 -{{expandable summary="📌 Relevance to Subproject"}}
904 -- Provides insight into **what factors contribute to drug court program success**.
905 -- Highlights **racial disparities in criminal justice-based rehabilitation programs**.
906 -- Supports **policy discussions on improving access to drug treatment for marginalized groups**.
907 -{{/expandable}}
677 +---
908 908  
909 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
910 -1. Investigate **the role of mental health in drug court success rates**.
911 -2. Assess **long-term relapse prevention strategies post-treatment**.
912 -3. Explore **alternative diversion programs beyond traditional drug courts**.
913 -{{/expandable}}
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**.
914 914  
915 -{{expandable summary="📄 Download Full Study"}}
916 -[[Download Full Study>>attach:10.1081_JA-120014424.pdf]]
917 -{{/expandable}}
918 -{{/expandable}}
684 +---
919 919  
920 -{{expandable summary="Study: Cross-Cultural Sources of Measurement Error in Substance Use Surveys"}}
921 -**Source:** *Substance Use & Misuse*
922 -**Date of Publication:** *2003*
923 -**Author(s):** *Timothy P. Johnson, Phillip J. Bowman*
924 -**Title:** *"Cross-Cultural Sources of Measurement Error in Substance Use Surveys"*
925 -**DOI:** [10.1081/JA-120023394](https://doi.org/10.1081/JA-120023394)
926 -**Subject Matter:** *Survey Methodology, Racial Disparities, Substance Use Research*
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**.
927 927  
928 -{{expandable summary="📊 Key Statistics"}}
929 -1. **General Observations:**
930 - - Study examined **how racial and cultural factors influence self-reported substance use data**.
931 - - Analyzed **36 empirical studies from 1977–2003** on survey reliability across racial/ethnic groups.
691 +---
932 932  
933 -2. **Subgroup Analysis:**
934 - - Black and Latino respondents **were more likely to underreport drug use** compared to White respondents.
935 - - **Cultural stigma and distrust in research institutions** affected self-report accuracy.
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**.
936 936  
937 -3. **Other Significant Data Points:**
938 - - **Surveys using biological validation (urinalysis, hair tests) revealed underreporting trends**.
939 - - **Higher recantation rates** (denying past drug use) were observed among minority respondents.
940 -{{/expandable}}
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.
941 941  
942 -{{expandable summary="🔬 Findings"}}
943 -1. **Primary Observations:**
944 - - Racial/ethnic disparities in **substance use reporting bias survey-based research**.
945 - - **Social desirability and cultural norms impact data reliability**.
698 +---
946 946  
947 -2. **Subgroup Trends:**
948 - - White respondents were **more likely to overreport** substance use.
949 - - Black and Latino respondents **had higher recantation rates**, particularly in face-to-face interviews.
700 +## **📄 Download Full Study**
701 +[[Download Full Study>>attach:10.1016_j.mehy.2009.07.046.pdf]]
950 950  
951 -3. **Specific Case Analysis:**
952 - - Mode of survey administration **significantly influenced reporting accuracy**.
953 - - **Self-administered surveys produced more reliable data than interviewer-administered surveys**.
954 -{{/expandable}}
703 +{{/expand}}
955 955  
956 -{{expandable summary="📝 Critique & Observations"}}
957 -1. **Strengths of the Study:**
958 - - **Comprehensive review of 36 studies** on measurement error in substance use reporting.
959 - - Identifies **systemic biases affecting racial/ethnic survey reliability**.
705 +{{html}}<hr style="border: 3px solid red;">{{/html}}
960 960  
961 -2. **Limitations of the Study:**
962 - - Relies on **secondary data analysis**, limiting direct experimental control.
963 - - Does not explore **how measurement error impacts policy decisions**.
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*
964 964  
965 -3. **Suggestions for Improvement:**
966 - - Future research should **incorporate mixed-method approaches** (qualitative & quantitative).
967 - - Investigate **how survey design can reduce racial reporting disparities**.
968 -{{/expandable}}
715 +---
969 969  
970 -{{expandable summary="📌 Relevance to Subproject"}}
971 -- Supports research on **racial disparities in self-reported health behaviors**.
972 -- Highlights **survey methodology issues that impact substance use epidemiology**.
973 -- Provides insights for **improving data accuracy in public health research**.
974 -{{/expandable}}
975 -
976 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
977 -1. Investigate **how survey design impacts racial disparities in self-reported health data**.
978 -2. Study **alternative data collection methods (biometric validation, passive data tracking)**.
979 -3. Explore **the role of social stigma in self-reported health behaviors**.
980 -{{/expandable}}
981 -
982 -{{expandable summary="📄 Download Full Study"}}
983 -[[Download Full Study>>attach:10.1081_JA-120023394.pdf]]
984 -{{/expandable}}
985 -{{/expandable}}
986 -
987 -{{expandable summary="Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program"}}
988 -**Source:** *Substance Use & Misuse*
989 -**Date of Publication:** *2002*
990 -**Author(s):** *Clifford A. Butzin, Christine A. Saum, Frank R. Scarpitti*
991 -**Title:** *"Factors Associated with Completion of a Drug Treatment Court Diversion Program"*
992 -**DOI:** [10.1081/JA-120014424](https://doi.org/10.1081/JA-120014424)
993 -**Subject Matter:** *Substance Use, Criminal Justice, Drug Courts*
994 -
995 -{{expandable summary="📊 Key Statistics"}}
717 +## **Key Statistics**
996 996  1. **General Observations:**
997 - - Study examined **drug treatment court success rates** among first-time offenders.
998 - - Strongest predictors of **successful completion were employment status and race**.
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**.
999 999  
1000 1000  2. **Subgroup Analysis:**
1001 - - Individuals with **stable jobs were more likely to complete the program**.
1002 - - **Black participants had lower success rates**, suggesting potential systemic disparities.
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**.
1003 1003  
1004 1004  3. **Other Significant Data Points:**
1005 - - **Education level was positively correlated** with program completion.
1006 - - Frequency of **drug use before enrollment affected treatment outcomes**.
1007 -{{/expandable}}
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**.
1008 1008  
1009 -{{expandable summary="🔬 Findings"}}
730 +---
731 +
732 +## **Findings**
1010 1010  1. **Primary Observations:**
1011 - - **Social stability factors** (employment, education) were key to treatment success.
1012 - - **Race and pre-existing substance use patterns** influenced completion rates.
734 + - Intelligence heritability **strengthens throughout development**, contrary to early environmental models.
735 + - Shared environmental effects **decrease by late adolescence**, emphasizing **genetic influence in adulthood**.
1013 1013  
1014 1014  2. **Subgroup Trends:**
1015 - - White offenders had **higher completion rates** than Black offenders.
1016 - - Drug court success was **higher for those with lower initial drug use frequency**.
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**.
1017 1017  
1018 1018  3. **Specific Case Analysis:**
1019 - - **Individuals with strong social ties were more likely to finish the program**.
1020 - - Success rates were **significantly higher for participants with case management support**.
1021 -{{/expandable}}
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**.
1022 1022  
1023 -{{expandable summary="📝 Critique & Observations"}}
745 +---
746 +
747 +## **Critique and Observations**
1024 1024  1. **Strengths of the Study:**
1025 - - **First empirical study on drug court program success factors**.
1026 - - Uses **longitudinal data** for post-treatment analysis.
749 + - **Robust dataset covering multiple twin and adoption studies over decades**.
750 + - **Clear, replicable trend** demonstrating the increasing role of genetics in intelligence.
1027 1027  
1028 1028  2. **Limitations of the Study:**
1029 - - Lacks **qualitative data on personal motivation and treatment engagement**.
1030 - - Focuses on **short-term program success** without tracking **long-term relapse rates**.
753 + - Findings apply primarily to **Western industrialized nations**, limiting generalizability.
754 + - **Lack of neurobiological mechanisms** explaining how genes express their influence over time.
1031 1031  
1032 1032  3. **Suggestions for Improvement:**
1033 - - Future research should examine **racial disparities in drug court outcomes**.
1034 - - Study **how community resources impact long-term recovery**.
1035 -{{/expandable}}
757 + - Future research should investigate **gene-environment interactions in cognitive aging**.
758 + - Examine **heritability trends in non-Western populations** to determine cross-cultural consistency.
1036 1036  
1037 -{{expandable summary="📌 Relevance to Subproject"}}
1038 -- Provides insight into **what factors contribute to drug court program success**.
1039 -- Highlights **racial disparities in criminal justice-based rehabilitation programs**.
1040 -- Supports **policy discussions on improving access to drug treatment for marginalized groups**.
1041 -{{/expandable}}
760 +---
1042 1042  
1043 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
1044 -1. Investigate **the role of mental health in drug court success rates**.
1045 -2. Assess **long-term relapse prevention strategies post-treatment**.
1046 -3. Explore **alternative diversion programs beyond traditional drug courts**.
1047 -{{/expandable}}
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**.
1048 1048  
1049 -{{expandable summary="📄 Download Full Study"}}
1050 -[[Download Full Study>>attach:10.1081_JA-120014424.pdf]]
1051 -{{/expandable}}
1052 -{{/expandable}}
767 +---
1053 1053  
1054 -{{expandable summary="
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**.
1055 1055  
1056 -Study: Is there a Dysgenic Secular Trend Towards Slowing Simple Reaction Time?"}}
1057 -**Source:** *Intelligence (Elsevier)*
1058 -**Date of Publication:** *2014*
1059 -**Author(s):** *Michael A. Woodley, Jan te Nijenhuis, Raegan Murphy*
1060 -**Title:** *"Is there a Dysgenic Secular Trend Towards Slowing Simple Reaction Time?"*
1061 -**DOI:** [10.1016/j.intell.2014.05.012](https://doi.org/10.1016/j.intell.2014.05.012)
1062 -**Subject Matter:** *Cognitive Decline, Intelligence, Dysgenics*
774 +---
1063 1063  
1064 -{{expandable summary="📊 Key Statistics"}}
1065 -1. **General Observations:**
1066 - - The study examines reaction time data from **13 age-matched studies** spanning **1884–2004**.
1067 - - Results suggest an estimated **decline of 13.35 IQ points** over this period.
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**.
1068 1068  
1069 -2. **Subgroup Analysis:**
1070 - - The study found **slower reaction times in modern populations** compared to Victorian-era individuals.
1071 - - Data from **Western countries (US, UK, Canada, Australia, Finland)** were analyzed.
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.
1072 1072  
1073 -3. **Other Significant Data Points:**
1074 - - The estimated **dysgenic rate is 1.21 IQ points lost per decade**.
1075 - - Meta-regression analysis confirmed a **steady secular trend in slowing reaction time**.
1076 -{{/expandable}}
781 +---
1077 1077  
1078 -{{expandable summary="🔬 Findings"}}
1079 -1. **Primary Observations:**
1080 - - Supports the hypothesis of **intelligence decline due to genetic and environmental factors**.
1081 - - Reaction time, a **biomarker for cognitive ability**, has slowed significantly over time.
783 +## **📄 Download Full Study**
784 +[[Download Full Study>>attach:10.1017_thg.2013.54.pdf]]
1082 1082  
1083 -2. **Subgroup Trends:**
1084 - - A stronger **correlation between slower reaction time and lower general intelligence (g)**.
1085 - - Flynn effect (IQ gains) does not contradict this finding, as reaction time is a **biological, not environmental, measure**.
786 +{{/expand}}
1086 1086  
1087 -3. **Specific Case Analysis:**
1088 - - Cross-national comparisons indicate a **global trend in slower reaction times**.
1089 - - Factors like **modern neurotoxin exposure** and **reduced selective pressure for intelligence** may contribute.
1090 -{{/expandable}}
788 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1091 1091  
1092 -{{expandable summary="📝 Critique & Observations"}}
1093 -1. **Strengths of the Study:**
1094 - - **Comprehensive meta-analysis** covering over a century of reaction time data.
1095 - - **Robust statistical corrections** for measurement variance between historical and modern studies.
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*
1096 1096  
1097 -2. **Limitations of the Study:**
1098 - - Some historical data sources **lack methodological consistency**.
1099 - - **Reaction time measurements vary by study**, requiring adjustments for equipment differences.
798 +---
1100 1100  
1101 -3. **Suggestions for Improvement:**
1102 - - Future studies should **replicate results with more modern datasets**.
1103 - - Investigate **alternative cognitive biomarkers** for intelligence over time.
1104 -{{/expandable}}
1105 -
1106 -{{expandable summary="📌 Relevance to Subproject"}}
1107 -- Provides evidence for **long-term intelligence trends**, contributing to research on **cognitive evolution**.
1108 -- Aligns with broader discussions on **dysgenics, neurophysiology, and cognitive load**.
1109 -- Supports the argument that **modern societies may be experiencing intelligence decline**.
1110 -{{/expandable}}
1111 -
1112 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
1113 -1. Investigate **genetic markers associated with reaction time** and intelligence decline.
1114 -2. Examine **regional variations in reaction time trends**.
1115 -3. Explore **cognitive resilience factors that counteract the decline**.
1116 -{{/expandable}}
1117 -
1118 -{{expandable summary="📄 Download Full Study"}}
1119 -[[Download Full Study>>attach:10.1016_j.intell.2014.05.012.pdf]]
1120 -{{/expandable}}
1121 -{{/expandable}}
1122 -
1123 -= Whiteness & White Guilt =
1124 -
1125 -{{expandable summary="Study: Segregation, Innocence, and Protection: The Institutional Conditions That Maintain Whiteness in College Sports"}}
1126 -**Source:** *Journal of Diversity in Higher Education*
1127 -**Date of Publication:** *2019*
1128 -**Author(s):** *Kirsten Hextrum*
1129 -**Title:** *"Segregation, Innocence, and Protection: The Institutional Conditions That Maintain Whiteness in College Sports"*
1130 -**DOI:** [10.1037/dhe0000140](https://doi.org/10.1037/dhe0000140)
1131 -**Subject Matter:** *Race and Sports, Higher Education, Institutional Racism*
1132 -
1133 -{{expandable summary="📊 Key Statistics"}}
800 +## **Key Statistics**
1134 1134  1. **General Observations:**
1135 1135   - Analyzed **47 college athlete narratives** to explore racial disparities in non-revenue sports.
1136 1136   - Found three interrelated themes: **racial segregation, racial innocence, and racial protection**.
... ... @@ -1142,9 +1142,10 @@
1142 1142  3. **Other Significant Data Points:**
1143 1143   - White athletes are **socialized to remain unaware of racial privilege** in their athletic careers.
1144 1144   - Media and institutional narratives protect white athletes from discussions on race and systemic inequities.
1145 -{{/expandable}}
1146 1146  
1147 -{{expandable summary="🔬 Findings"}}
813 +---
814 +
815 +## **Findings**
1148 1148  1. **Primary Observations:**
1149 1149   - Colleges **actively recruit white athletes** from majority-white communities.
1150 1150   - Institutional policies **uphold whiteness** by failing to challenge racial biases in recruitment and team culture.
... ... @@ -1156,9 +1156,10 @@
1156 1156  3. **Specific Case Analysis:**
1157 1157   - Examines **how sports serve as a mechanism for maintaining racial privilege** in higher education.
1158 1158   - Discusses the **role of athletics in reinforcing systemic segregation and exclusion**.
1159 -{{/expandable}}
1160 1160  
1161 -{{expandable summary="📝 Critique & Observations"}}
828 +---
829 +
830 +## **Critique and Observations**
1162 1162  1. **Strengths of the Study:**
1163 1163   - **Comprehensive qualitative analysis** of race in college sports.
1164 1164   - Examines **institutional conditions** that sustain racial disparities in athletics.
... ... @@ -1170,531 +1170,452 @@
1170 1170  3. **Suggestions for Improvement:**
1171 1171   - Future research should **compare recruitment policies across different sports and divisions**.
1172 1172   - Investigate **how athletic scholarships contribute to racial inequities in higher education**.
1173 -{{/expandable}}
1174 1174  
1175 -{{expandable summary="📌 Relevance to Subproject"}}
843 +---
844 +
845 +## **Relevance to Subproject**
1176 1176  - Provides evidence of **systemic racial biases** in college sports recruitment.
1177 1177  - Highlights **how institutional policies protect whiteness** in non-revenue athletics.
1178 1178  - Supports research on **diversity, equity, and inclusion (DEI) efforts in sports and education**.
1179 -{{/expandable}}
1180 1180  
1181 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
850 +---
851 +
852 +## **Suggestions for Further Exploration**
1182 1182  1. Investigate how **racial stereotypes influence college athlete recruitment**.
1183 1183  2. Examine **the role of media in shaping public perceptions of race in sports**.
1184 1184  3. Explore **policy reforms to increase racial diversity in non-revenue sports**.
1185 -{{/expandable}}
1186 1186  
1187 -{{expandable summary="📄 Download Full Study"}}
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**
1188 1188  [[Download Full Study>>attach:10.1037_dhe0000140.pdf]]
1189 -{{/expandable}}
1190 -{{/expandable}}
1191 1191  
1192 -{{expandable summary="Study: Racial Bias in Pain Assessment and Treatment Recommendations"}}
1193 -**Source:** *Proceedings of the National Academy of Sciences (PNAS)*
1194 -**Date of Publication:** *2016*
1195 -**Author(s):** *Kelly M. Hoffman, Sophie Trawalter, Jordan R. Axta, M. Norman Oliver*
1196 -**Title:** *"Racial Bias in Pain Assessment and Treatment Recommendations, and False Beliefs About Biological Differences Between Blacks and Whites"*
1197 -**DOI:** [10.1073/pnas.1516047113](https://doi.org/10.1073/pnas.1516047113)
1198 -**Subject Matter:** *Health Disparities, Racial Bias, Medical Treatment*
869 +{{/expand}}
1199 1199  
1200 -{{expandable summary="📊 Key Statistics"}}
871 +{{html}}<hr style="border: 3px solid red;">{{/html}}
872 +
873 +{{expand title="Study: Reconstructing Indian Population History" expanded="false"}}
874 +**Source:** *Nature*
875 +**Date of Publication:** *2009*
876 +**Author(s):** *David Reich, Kumarasamy Thangaraj, Nick Patterson, Alkes L. Price, Lalji Singh*
877 +**Title:** *"Reconstructing Indian Population History"*
878 +**DOI:** [10.1038/nature08365](https://doi.org/10.1038/nature08365)
879 +**Subject Matter:** *Genetics, Population History, South Asian Ancestry*
880 +
881 +---
882 +
883 +## **Key Statistics**
1201 1201  1. **General Observations:**
1202 - - Study analyzed **racial disparities in pain perception and treatment recommendations**.
1203 - - Found that **white laypeople and medical students endorsed false beliefs about biological differences** between Black and white individuals.
885 + - Study analyzed **132 individuals from 25 diverse Indian groups**.
886 + - Identified two major ancestral populations: **Ancestral North Indians (ANI)** and **Ancestral South Indians (ASI)**.
1204 1204  
1205 1205  2. **Subgroup Analysis:**
1206 - - **50% of medical students surveyed endorsed at least one false belief about biological differences**.
1207 - - Participants who held these false beliefs were **more likely to underestimate Black patients’ pain levels**.
889 + - ANI ancestry is closely related to **Middle Easterners, Central Asians, and Europeans**.
890 + - ASI ancestry is **genetically distinct from ANI and East Asians**.
1208 1208  
1209 1209  3. **Other Significant Data Points:**
1210 - - **Black patients were less likely to receive appropriate pain treatment** compared to white patients.
1211 - - The study confirmed that **historical misconceptions about racial differences still persist in modern medicine**.
1212 -{{/expandable}}
893 + - ANI ancestry ranges from **39% to 71%** across Indian groups.
894 + - **Caste and linguistic differences** strongly correlate with genetic variation.
1213 1213  
1214 -{{expandable summary="🔬 Findings"}}
896 +---
897 +
898 +## **Findings**
1215 1215  1. **Primary Observations:**
1216 - - False beliefs about biological racial differences **correlate with racial disparities in pain treatment**.
1217 - - Medical students and residents who endorsed these beliefs **showed greater racial bias in treatment recommendations**.
900 + - The genetic landscape of India has been shaped by **thousands of years of endogamy**.
901 + - Groups with **only ASI ancestry no longer exist** in mainland India.
1218 1218  
1219 1219  2. **Subgroup Trends:**
1220 - - Physicians who **did not endorse these beliefs** showed **no racial bias** in treatment recommendations.
1221 - - Bias was **strongest among first-year medical students** and decreased slightly in later years of training.
904 + - **Higher ANI ancestry in upper-caste and Indo-European-speaking groups**.
905 + - **Andaman Islanders** are unique in having **ASI ancestry without ANI influence**.
1222 1222  
1223 1223  3. **Specific Case Analysis:**
1224 - - Study participants **underestimated Black patients' pain and recommended less effective pain treatments**.
1225 - - The study suggests that **racial disparities in medical care stem, in part, from these enduring false beliefs**.
1226 -{{/expandable}}
908 + - **Founder effects** have maintained allele frequency differences among Indian groups.
909 + - Predicts **higher incidence of recessive diseases** due to historical genetic isolation.
1227 1227  
1228 -{{expandable summary="📝 Critique & Observations"}}
911 +---
912 +
913 +## **Critique and Observations**
1229 1229  1. **Strengths of the Study:**
1230 - - **First empirical study to connect false racial beliefs with medical decision-making**.
1231 - - Utilizes a **large sample of medical students and residents** from diverse institutions.
915 + - **First large-scale genetic analysis** of Indian population history.
916 + - Introduces **new methods for ancestry estimation without direct ancestral reference groups**.
1232 1232  
1233 1233  2. **Limitations of the Study:**
1234 - - The study focuses on **Black vs. white disparities**, leaving other racial/ethnic groups unexplored.
1235 - - Participants' responses were based on **hypothetical medical cases, not real-world treatment decisions**.
919 + - Limited **sample size relative to India's population diversity**.
920 + - Does not include **recent admixture events** post-colonial era.
1236 1236  
1237 1237  3. **Suggestions for Improvement:**
1238 - - Future research should examine **how these biases manifest in real clinical settings**.
1239 - - Investigate **whether medical training can correct these biases over time**.
1240 -{{/expandable}}
923 + - Future research should **expand sampling across more Indian tribal groups**.
924 + - Use **whole-genome sequencing** for finer resolution of ancestry.
1241 1241  
1242 -{{expandable summary="📌 Relevance to Subproject"}}
1243 -- Highlights **racial disparities in healthcare**, specifically in pain assessment and treatment.
1244 -- Supports **research on implicit bias and its impact on medical outcomes**.
1245 -- Provides evidence for **the need to address racial bias in medical education**.
1246 -{{/expandable}}
926 +---
1247 1247  
1248 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
1249 -1. Investigate **interventions to reduce racial bias in medical decision-making**.
1250 -2. Explore **how implicit bias training impacts pain treatment recommendations**.
1251 -3. Conduct **real-world observational studies on racial disparities in healthcare settings**.
1252 -{{/expandable}}
928 +## **Relevance to Subproject**
929 +- Provides a **genetic basis for caste and linguistic diversity** in India.
930 +- Highlights **founder effects and genetic drift** shaping South Asian populations.
931 +- Supports research on **medical genetics and disease risk prediction** in Indian populations.
1253 1253  
1254 -{{expandable summary="📄 Download Full Study"}}
1255 -[[Download Full Study>>attach:10.1073_pnas.1516047113.pdf]]
1256 -{{/expandable}}
1257 -{{/expandable}}
933 +---
1258 1258  
1259 -{{expandable summary="Study: Rising Morbidity and Mortality in Midlife Among White Non-Hispanic Americans"}}
1260 -**Source:** *Proceedings of the National Academy of Sciences (PNAS)*
1261 -**Date of Publication:** *2015*
1262 -**Author(s):** *Anne Case, Angus Deaton*
1263 -**Title:** *"Rising Morbidity and Mortality in Midlife Among White Non-Hispanic Americans in the 21st Century"*
1264 -**DOI:** [10.1073/pnas.1518393112](https://doi.org/10.1073/pnas.1518393112)
1265 -**Subject Matter:** *Public Health, Mortality, Socioeconomic Factors*
935 +## **Suggestions for Further Exploration**
936 +1. Examine **genetic markers linked to disease susceptibility** in Indian subpopulations.
937 +2. Investigate the impact of **recent migration patterns on ANI-ASI ancestry distribution**.
938 +3. Study **gene flow between Indian populations and other global groups**.
1266 1266  
1267 -{{expandable summary="📊 Key Statistics"}}
1268 -1. **General Observations:**
1269 - - Mortality rates among **middle-aged white non-Hispanic Americans (ages 45–54)** increased from 1999 to 2013.
1270 - - This reversal in mortality trends is unique to the U.S.; **no other wealthy country experienced a similar rise**.
940 +---
1271 1271  
1272 -2. **Subgroup Analysis:**
1273 - - The increase was **most pronounced among those with a high school education or less**.
1274 - - Hispanic and Black non-Hispanic mortality continued to decline over the same period.
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**.
1275 1275  
1276 -3. **Other Significant Data Points:**
1277 - - Rising mortality was driven primarily by **suicide, drug and alcohol poisoning, and chronic liver disease**.
1278 - - Midlife morbidity increased as well, with more reports of **poor health, pain, and mental distress**.
1279 -{{/expandable}}
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.
1280 1280  
1281 -{{expandable summary="🔬 Findings"}}
1282 -1. **Primary Observations:**
1283 - - The rise in mortality is attributed to **substance abuse, economic distress, and deteriorating mental health**.
1284 - - The increase in **suicides and opioid overdoses parallels broader socioeconomic decline**.
947 +---
1285 1285  
1286 -2. **Subgroup Trends:**
1287 - - The **largest mortality increases** occurred among **whites without a college degree**.
1288 - - Chronic pain, functional limitations, and self-reported mental distress **rose significantly in affected groups**.
949 +## **📄 Download Full Study**
950 +[[Download Full Study>>attach:10.1038_nature08365.pdf]]
1289 1289  
1290 -3. **Specific Case Analysis:**
1291 - - **Educational attainment was a major predictor of mortality trends**, with better-educated individuals experiencing lower mortality rates.
1292 - - Mortality among **white Americans with a college degree continued to decline**, resembling trends in other wealthy nations.
1293 -{{/expandable}}
952 +{{/expand}}
1294 1294  
1295 -{{expandable summary="📝 Critique & Observations"}}
1296 -1. **Strengths of the Study:**
1297 - - **First major study to highlight rising midlife mortality among U.S. whites**.
1298 - - Uses **CDC and Census mortality data spanning over a decade**.
954 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1299 1299  
1300 -2. **Limitations of the Study:**
1301 - - Does not establish **causality** between economic decline and increased mortality.
1302 - - Lacks **granular data on opioid prescribing patterns and regional differences**.
1303 1303  
1304 -3. **Suggestions for Improvement:**
1305 - - Future studies should explore **how economic shifts, healthcare access, and mental health treatment contribute to these trends**.
1306 - - Further research on **racial and socioeconomic disparities in mortality trends** is needed.
1307 -{{/expandable}}
957 +{{expand title="Study: The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations" expanded="false"}}
958 +**Source:** *Nature*
959 +**Date of Publication:** *2016*
960 +**Author(s):** *David Reich, Swapan Mallick, Heng Li, Mark Lipson, and others*
961 +**Title:** *"The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations"*
962 +**DOI:** [10.1038/nature18964](https://doi.org/10.1038/nature18964)
963 +**Subject Matter:** *Human Genetic Diversity, Population History, Evolutionary Genomics*
1308 1308  
1309 -{{expandable summary="📌 Relevance to Subproject"}}
1310 -- Highlights **socioeconomic and racial disparities** in health outcomes.
1311 -- Supports research on **substance abuse and mental health crises in the U.S.**.
1312 -- Provides evidence for **the role of economic instability in public health trends**.
1313 -{{/expandable}}
965 +---
1314 1314  
1315 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
1316 -1. Investigate **regional differences in rising midlife mortality**.
1317 -2. Examine the **impact of the opioid crisis on long-term health trends**.
1318 -3. Study **policy interventions aimed at reversing rising mortality rates**.
1319 -{{/expandable}}
1320 -
1321 -{{expandable summary="📄 Download Full Study"}}
1322 -[[Download Full Study>>attach:10.1073_pnas.1518393112.pdf]]
1323 -{{/expandable}}
1324 -{{/expandable}}
1325 -
1326 -{{expandable summary="Study: How Do People Without Migration Background Experience and Impact Today’s Superdiverse Cities?"}}
1327 -**Source:** *Journal of Ethnic and Migration Studies*
1328 -**Date of Publication:** *2023*
1329 -**Author(s):** *Maurice Crul, Frans Lelie, Elif Keskiner, Laure Michon, Ismintha Waldring*
1330 -**Title:** *"How Do People Without Migration Background Experience and Impact Today’s Superdiverse Cities?"*
1331 -**DOI:** [10.1080/1369183X.2023.2182548](https://doi.org/10.1080/1369183X.2023.2182548)
1332 -**Subject Matter:** *Urban Sociology, Migration Studies, Integration*
1333 -
1334 -{{expandable summary="📊 Key Statistics"}}
967 +## **Key Statistics**
1335 1335  1. **General Observations:**
1336 - - Study examines the role of **people without migration background** in majority-minority cities.
1337 - - Analyzes **over 3,000 survey responses and 150 in-depth interviews** from six North-Western European cities.
969 + - Analyzed **high-coverage genome sequences of 300 individuals from 142 populations**.
970 + - Included **many underrepresented and indigenous groups** from Africa, Asia, Europe, and the Americas.
1338 1338  
1339 1339  2. **Subgroup Analysis:**
1340 - - Explores differences in **integration, social interactions, and perceptions of diversity**.
1341 - - Studies how **class, education, and neighborhood composition** affect adaptation to urban diversity.
973 + - Found **higher genetic diversity within African populations** compared to non-African groups.
974 + - Showed **Neanderthal and Denisovan ancestry in non-African populations**, particularly in Oceania.
1342 1342  
1343 1343  3. **Other Significant Data Points:**
1344 - - The study introduces the **Becoming a Minority (BaM) project**, a large-scale investigation of urban demographic shifts.
1345 - - **People without migration background perceive diversity differently**, with some embracing and others resisting change.
1346 -{{/expandable}}
977 + - Identified **5.8 million base pairs absent from the human reference genome**.
978 + - Estimated that **mutations have accumulated 5% faster in non-Africans than in Africans**.
1347 1347  
1348 -{{expandable summary="🔬 Findings"}}
980 +---
981 +
982 +## **Findings**
1349 1349  1. **Primary Observations:**
1350 - - The study **challenges traditional integration theories**, arguing that non-migrant groups also undergo adaptation processes.
1351 - - Some residents **struggle with demographic changes**, while others see diversity as an asset.
984 + - **African populations harbor the greatest genetic diversity**, confirming an out-of-Africa dispersal model.
985 + - Indigenous Australians and New Guineans **share a common ancestral population with other non-Africans**.
1352 1352  
1353 1353  2. **Subgroup Trends:**
1354 - - Young, educated individuals in urban areas **are more open to cultural diversity**.
1355 - - Older and less mobile residents **report feelings of displacement and social isolation**.
988 + - **Lower heterozygosity in non-Africans** due to founder effects from migration bottlenecks.
989 + - **Denisovan ancestry in South Asians is higher than previously thought**.
1356 1356  
1357 1357  3. **Specific Case Analysis:**
1358 - - Examines how **people without migration background navigate majority-minority settings** in cities like Amsterdam and Vienna.
1359 - - Analyzes **whether former ethnic majority groups now perceive themselves as minorities**.
1360 -{{/expandable}}
992 + - **Neanderthal ancestry is higher in East Asians than in Europeans**.
993 + - African hunter-gatherer groups show **deep population splits over 100,000 years ago**.
1361 1361  
1362 -{{expandable summary="📝 Critique & Observations"}}
995 +---
996 +
997 +## **Critique and Observations**
1363 1363  1. **Strengths of the Study:**
1364 - - **Innovative approach** by examining the impact of migration on native populations.
1365 - - Uses **both qualitative and quantitative data** for robust analysis.
999 + - **Largest global genetic dataset** outside of the 1000 Genomes Project.
1000 + - High sequencing depth allows **more accurate identification of genetic variants**.
1366 1366  
1367 1367  2. **Limitations of the Study:**
1368 - - Limited to **Western European urban settings**, missing perspectives from other global regions.
1369 - - Does not fully explore **policy interventions for fostering social cohesion**.
1003 + - **Limited sample sizes for some populations**, restricting generalizability.
1004 + - Lacks ancient DNA comparisons, making it difficult to reconstruct deep ancestry fully.
1370 1370  
1371 1371  3. **Suggestions for Improvement:**
1372 - - Expand research to **other geographical contexts** to understand migration effects globally.
1373 - - Investigate **long-term trends in urban adaptation and community building**.
1374 -{{/expandable}}
1007 + - Future studies should include **ancient genomes** to improve demographic modeling.
1008 + - Expand research into **how genetic variation affects health outcomes** across populations.
1375 1375  
1376 -{{expandable summary="📌 Relevance to Subproject"}}
1377 -- Provides a **new perspective on urban integration**, shifting focus from migrants to native-born populations.
1378 -- Highlights the **role of social and economic power in shaping urban diversity outcomes**.
1379 -- Challenges existing **assimilation theories by showing bidirectional adaptation in diverse cities**.
1380 -{{/expandable}}
1010 +---
1381 1381  
1382 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
1383 -1. Study how **local policies shape attitudes toward urban diversity**.
1384 -2. Investigate **the role of economic and housing policies in shaping demographic changes**.
1385 -3. Explore **how social networks influence perceptions of migration and diversity**.
1386 -{{/expandable}}
1012 +## **Relevance to Subproject**
1013 +- Provides **comprehensive data on human genetic diversity**, useful for **evolutionary studies**.
1014 +- Supports research on **Neanderthal and Denisovan introgression** in modern human populations.
1015 +- Enhances understanding of **genetic adaptation and disease susceptibility across groups**.
1387 1387  
1388 -{{expandable summary="📄 Download Full Study"}}
1389 -[[Download Full Study>>attach:10.1080_1369183X.2023.2182548.pdf]]
1390 -{{/expandable}}
1391 -{{/expandable}}
1017 +---
1392 1392  
1393 -= Media =
1019 +## **Suggestions for Further Exploration**
1020 +1. Investigate **functional consequences of genetic variation in underrepresented populations**.
1021 +2. Study **how selection pressures shaped genetic diversity across different environments**.
1022 +3. Explore **medical applications of population-specific genetic markers**.
1394 1394  
1395 -{{expandable summary="Study: The Role of Computer-Mediated Communication in Intergroup Conflic"}}
1396 -**Source:** *Journal of Computer-Mediated Communication*
1397 -**Date of Publication:** *2021*
1398 -**Author(s):** *Zeynep Tufekci, Jesse Fox, Andrew Chadwick*
1399 -**Title:** *"The Role of Computer-Mediated Communication in Intergroup Conflict"*
1400 -**DOI:** [10.1093/jcmc/zmab003](https://doi.org/10.1093/jcmc/zmab003)
1401 -**Subject Matter:** *Online Communication, Social Media, Conflict Studies*
1024 +---
1402 1402  
1403 -{{expandable summary="📊 Key Statistics"}}
1404 -1. **General Observations:**
1405 - - Analyzed **over 500,000 social media interactions** related to intergroup conflict.
1406 - - Found that **computer-mediated communication (CMC) intensifies polarization**.
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**.
1407 1407  
1408 -2. **Subgroup Analysis:**
1409 - - **Anonymity and reduced social cues** in CMC increased hostility.
1410 - - **Echo chambers formed more frequently in algorithm-driven environments**.
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.
1411 1411  
1412 -3. **Other Significant Data Points:**
1413 - - **Misinformation spread 3x faster** in polarized online discussions.
1414 - - Users exposed to **conflicting viewpoints were more likely to engage in retaliatory discourse**.
1415 -{{/expandable}}
1031 +---
1416 1416  
1417 -{{expandable summary="🔬 Findings"}}
1418 -1. **Primary Observations:**
1419 - - **Online interactions amplify intergroup conflict** due to selective exposure and confirmation bias.
1420 - - **Algorithmic sorting contributes to ideological segmentation**.
1033 +## **📄 Download Full Study**
1034 +[[Download Full Study>>attach:10.1038_nature18964.pdf]]
1421 1421  
1422 -2. **Subgroup Trends:**
1423 - - Participants with **strong pre-existing biases became more polarized** after exposure to conflicting views.
1424 - - **Moderate users were more likely to disengage** from conflict-heavy discussions.
1036 +{{/expand}}
1425 1425  
1426 -3. **Specific Case Analysis:**
1427 - - **CMC increased political tribalism** in digital spaces.
1428 - - **Emotional language spread more widely** than factual content.
1429 -{{/expandable}}
1038 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1430 1430  
1431 -{{expandable summary="📝 Critique & Observations"}}
1432 -1. **Strengths of the Study:**
1433 - - **Largest dataset** to date analyzing **CMC and intergroup conflict**.
1434 - - Uses **longitudinal data tracking user behavior over time**.
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*
1435 1435  
1436 -2. **Limitations of the Study:**
1437 - - Lacks **qualitative analysis of user motivations**.
1438 - - Focuses on **Western social media platforms**, missing global perspectives.
1048 +---
1439 1439  
1440 -3. **Suggestions for Improvement:**
1441 - - Future studies should **analyze private messaging platforms** in conflict dynamics.
1442 - - Investigate **interventions that reduce online polarization**.
1443 -{{/expandable}}
1444 -
1445 -{{expandable summary="📌 Relevance to Subproject"}}
1446 -- Explores how **digital communication influences social division**.
1447 -- Supports research on **social media regulation and conflict mitigation**.
1448 -- Provides **data on misinformation and online radicalization trends**.
1449 -{{/expandable}}
1450 -
1451 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
1452 -1. Investigate **how online anonymity affects real-world aggression**.
1453 -2. Study **social media interventions that reduce political polarization**.
1454 -3. Explore **cross-cultural differences in CMC and intergroup hostility**.
1455 -{{/expandable}}
1456 -
1457 -{{expandable summary="📄 Download Full Study"}}
1458 -[[Download Full Study>>attach:10.1093_jcmc_zmab003.pdf]]
1459 -{{/expandable}}
1460 -{{/expandable}}
1461 -
1462 -{{expandable summary="Study: Equality, Morality, and the Impact of Media Framing on Same-Sex Marriage and Civil Unions"}}
1463 -**Source:** *Politics & Policy*
1464 -**Date of Publication:** *2007*
1465 -**Author(s):** *Tyler Johnson*
1466 -**Title:** *"Equality, Morality, and the Impact of Media Framing: Explaining Opposition to Same-Sex Marriage and Civil Unions"*
1467 -**DOI:** [10.1111/j.1747-1346.2007.00092.x](https://doi.org/10.1111/j.1747-1346.2007.00092.x)
1468 -**Subject Matter:** *LGBTQ+ Rights, Public Opinion, Media Influence*
1469 -
1470 -{{expandable summary="📊 Key Statistics"}}
1050 +## **Key Statistics**
1471 1471  1. **General Observations:**
1472 - - Examines **media coverage of same-sex marriage and civil unions from 2004 to 2011**.
1473 - - Analyzes how **media framing influences public opinion trends** on LGBTQ+ rights.
1052 + - Analyzed **17,804 traits from 2,748 twin studies** published between **1958 and 2012**.
1053 + - Included data from **14,558,903 twin pairs**, making it the largest meta-analysis on human heritability.
1474 1474  
1475 1475  2. **Subgroup Analysis:**
1476 - - **Equality-based framing decreases opposition** to same-sex marriage.
1477 - - **Morality-based framing increases opposition** to same-sex marriage.
1056 + - Found **49% average heritability** across all traits.
1057 + - **69% of traits follow a simple additive genetic model**, meaning most variance is due to genes, not environment.
1478 1478  
1479 1479  3. **Other Significant Data Points:**
1480 - - When **equality framing surpasses morality framing**, public opposition declines.
1481 - - Media framing **directly affects public attitudes** over time, shaping policy debates.
1482 -{{/expandable}}
1060 + - **Neurological, metabolic, and psychiatric traits** showed the highest heritability estimates.
1061 + - Traits related to **social values and environmental interactions** had lower heritability estimates.
1483 1483  
1484 -{{expandable summary="🔬 Findings"}}
1063 +---
1064 +
1065 +## **Findings**
1485 1485  1. **Primary Observations:**
1486 - - **Media framing plays a critical role in shaping attitudes** toward LGBTQ+ rights.
1487 - - **Equality-focused narratives** lead to greater public support for same-sex marriage.
1067 + - Across all traits, genetic factors play a significant role in individual differences.
1068 + - The study contradicts models that **overestimate environmental effects in behavioral and cognitive traits**.
1488 1488  
1489 1489  2. **Subgroup Trends:**
1490 - - **Religious and conservative audiences** respond more to morality-based framing.
1491 - - **Younger and progressive audiences** respond more to equality-based framing.
1071 + - **Eye and brain-related traits showed the highest heritability (~70-80%)**.
1072 + - **Shared environmental effects were negligible (<10%) for most traits**.
1492 1492  
1493 1493  3. **Specific Case Analysis:**
1494 - - **Periods of increased equality framing** saw measurable **declines in opposition to LGBTQ+ rights**.
1495 - - **Major political events (elections, Supreme Court cases) influenced framing trends**.
1496 -{{/expandable}}
1075 + - Twin correlations suggest **limited evidence for strong non-additive genetic influences**.
1076 + - The study highlights **missing heritability in complex traits**, which genome-wide association studies (GWAS) have yet to fully explain.
1497 1497  
1498 -{{expandable summary="📝 Critique & Observations"}}
1078 +---
1079 +
1080 +## **Critique and Observations**
1499 1499  1. **Strengths of the Study:**
1500 - - **Longitudinal dataset spanning multiple election cycles**.
1501 - - Provides **quantitative analysis of how media framing shifts public opinion**.
1082 + - **Largest-ever heritability meta-analysis**, covering nearly all published twin studies.
1083 + - Provides a **comprehensive framework for understanding gene-environment contributions**.
1502 1502  
1503 1503  2. **Limitations of the Study:**
1504 - - Focuses **only on U.S. media coverage**, limiting global applicability.
1505 - - Does not account for **social media's growing influence** on public opinion.
1086 + - **Underrepresentation of African, South American, and Asian twin cohorts**, limiting global generalizability.
1087 + - Cannot **fully separate genetic influences from potential cultural/environmental confounders**.
1506 1506  
1507 1507  3. **Suggestions for Improvement:**
1508 - - Expand the study to **global perspectives on LGBTQ+ rights and media influence**.
1509 - - Investigate how **different media platforms (TV vs. digital media) impact opinion shifts**.
1510 -{{/expandable}}
1090 + - Future research should use **whole-genome sequencing** for finer-grained heritability estimates.
1091 + - **Incorporate non-Western populations** to assess global heritability trends.
1511 1511  
1512 -{{expandable summary="📌 Relevance to Subproject"}}
1513 -- Explores **how media narratives shape policy support and public sentiment**.
1514 -- Highlights **the strategic importance of framing in LGBTQ+ advocacy**.
1515 -- Reinforces the need for **media literacy in understanding policy debates**.
1516 -{{/expandable}}
1093 +---
1517 1517  
1518 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
1519 -1. Examine how **social media affects framing of LGBTQ+ issues**.
1520 -2. Study **differences in framing across political media outlets**.
1521 -3. Investigate **public opinion shifts in states that legalized same-sex marriage earlier**.
1522 -{{/expandable}}
1095 +## **Relevance to Subproject**
1096 +- Establishes a **quantitative benchmark for heritability across human traits**.
1097 +- Reinforces **genetic influence on cognitive, behavioral, and physical traits**.
1098 +- Highlights the need for **genome-wide studies to identify missing heritability**.
1523 1523  
1524 -{{expandable summary="📄 Download Full Study"}}
1525 -[[Download Full Study>>attach:10.1111_j.1747-1346.2007.00092.x_abstract.pdf]]
1526 -{{/expandable}}
1527 -{{/expandable}}
1100 +---
1528 1528  
1529 -{{expandable summary="Study: The Effects of Digital Media on Political Persuasion"}}
1530 -**Source:** *Journal of Communication*
1531 -**Date of Publication:** *2019*
1532 -**Author(s):** *Natalie Stroud, Matthew Barnidge, Shannon McGregor*
1533 -**Title:** *"The Effects of Digital Media on Political Persuasion: Evidence from Experimental Studies"*
1534 -**DOI:** [10.1093/joc/jqx021](https://doi.org/10.1093/joc/jqx021)
1535 -**Subject Matter:** *Media Influence, Political Communication, Persuasion*
1102 +## **Suggestions for Further Exploration**
1103 +1. Investigate how **heritability estimates compare across different socioeconomic backgrounds**.
1104 +2. Examine **gene-environment interactions in cognitive and psychiatric traits**.
1105 +3. Explore **non-additive genetic effects on human traits using newer statistical models**.
1536 1536  
1537 -{{expandable summary="📊 Key Statistics"}}
1538 -1. **General Observations:**
1539 - - Conducted **12 experimental studies** on **digital media's impact on political beliefs**.
1540 - - **58% of participants** showed shifts in political opinion based on online content.
1107 +---
1541 1541  
1542 -2. **Subgroup Analysis:**
1543 - - **Video-based content was 2x more persuasive** than text-based content.
1544 - - Participants **under age 35 were more susceptible to political messaging shifts**.
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.
1545 1545  
1546 -3. **Other Significant Data Points:**
1547 - - **Interactive media (comment sections, polls) increased political engagement**.
1548 - - **Exposure to counterarguments reduced partisan bias** by **14% on average**.
1549 -{{/expandable}}
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.
1550 1550  
1551 -{{expandable summary="🔬 Findings"}}
1552 -1. **Primary Observations:**
1553 - - **Digital media significantly influences political opinions**, with younger audiences being the most impacted.
1554 - - **Multimedia content is more persuasive** than traditional text-based arguments.
1114 +---
1555 1555  
1556 -2. **Subgroup Trends:**
1557 - - **Social media platforms had stronger persuasive effects** than news websites.
1558 - - Participants who engaged in **online discussions retained more political knowledge**.
1116 +## **📄 Download Full Study**
1117 +[[Download Full Study>>attach:10.1038_ng.328.pdf]]
1559 1559  
1560 -3. **Specific Case Analysis:**
1561 - - **Highly partisan users became more entrenched in their views**, even when exposed to opposing content.
1562 - - **Neutral or apolitical users were more likely to shift opinions**.
1563 -{{/expandable}}
1119 +{{/expand}}
1564 1564  
1565 -{{expandable summary="📝 Critique & Observations"}}
1566 -1. **Strengths of the Study:**
1567 - - **Large-scale experimental design** allows for controlled comparisons.
1568 - - Covers **multiple digital platforms**, ensuring robust findings.
1121 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1569 1569  
1570 -2. **Limitations of the Study:**
1571 - - Limited to **short-term persuasion effects**, without long-term follow-up.
1572 - - Does not explore **the role of misinformation in political persuasion**.
1123 +{{expand title="Study: Genetic Analysis of African Populations: Human Evolution and Complex Disease" expanded="false"}}
1124 +**Source:** *Nature Reviews Genetics*
1125 +**Date of Publication:** *2002*
1126 +**Author(s):** *Sarah A. Tishkoff, Scott M. Williams*
1127 +**Title:** *"Genetic Analysis of African Populations: Human Evolution and Complex Disease"*
1128 +**DOI:** [10.1038/nrg865](https://doi.org/10.1038/nrg865)
1129 +**Subject Matter:** *Population Genetics, Human Evolution, Complex Diseases*
1573 1573  
1574 -3. **Suggestions for Improvement:**
1575 - - Future studies should track **long-term opinion changes** beyond immediate reactions.
1576 - - Investigate **the role of digital media literacy in resisting persuasion**.
1577 -{{/expandable}}
1131 +---
1578 1578  
1579 -{{expandable summary="📌 Relevance to Subproject"}}
1580 -- Provides insights into **how digital media shapes political discourse**.
1581 -- Highlights **which platforms and content types are most influential**.
1582 -- Supports **research on misinformation and online political engagement**.
1583 -{{/expandable}}
1133 +## **Key Statistics**
1134 +1. **General Observations:**
1135 + - Africa harbors **the highest genetic diversity** of any region, making it key to understanding human evolution.
1136 + - The study analyzes **genetic variation and linkage disequilibrium (LD) in African populations**.
1584 1584  
1585 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
1586 -1. Study how **fact-checking influences digital persuasion effects**.
1587 -2. Investigate the **role of political influencers in shaping opinions**.
1588 -3. Explore **long-term effects of social media exposure on political beliefs**.
1589 -{{/expandable}}
1138 +2. **Subgroup Analysis:**
1139 + - African populations exhibit **greater genetic differentiation compared to non-Africans**.
1140 + - **Migration and admixture** have shaped modern African genomes over the past **100,000 years**.
1590 1590  
1591 -{{expandable summary="📄 Download Full Study"}}
1592 -[[Download Full Study>>attach:10.1093_joc_jqx021.pdf]]
1593 -{{/expandable}}
1594 -{{/expandable}}
1142 +3. **Other Significant Data Points:**
1143 + - The **effective population size (Ne) of Africans** is higher than that of non-African populations.
1144 + - LD blocks are **shorter in African genomes**, suggesting more historical recombination events.
1595 1595  
1596 -{{expandable summary="Study: White Americans’ Preference for Black People in Advertising Has Increased in the Past 66 Years"}}
1597 -Source: Proceedings of the National Academy of Sciences (PNAS)
1598 -Date of Publication: February 20, 2024
1599 -Author(s): Julia Diana Lenk, Jochen Hartmann, Henrik Sattler
1600 -Title: "White Americans’ Preference for Black People in Advertising Has Increased in the Past 66 Years: A Meta-Analysis"
1601 -DOI: 10.1073/pnas.2307505121
1602 -Subject Matter: Advertising, Race, Consumer Behavior, Meta-Analysis
1146 +---
1603 1603  
1604 -{{expandable summary="📊 Key Statistics"}}
1148 +## **Findings**
1149 +1. **Primary Observations:**
1150 + - African populations are the **most genetically diverse**, supporting the *Recent African Origin* hypothesis.
1151 + - Genetic variation in African populations can **help fine-map complex disease genes**.
1605 1605  
1606 -Study Scale:
1153 +2. **Subgroup Trends:**
1154 + - **West Africans exhibit higher genetic diversity** than East Africans due to differing migration patterns.
1155 + - Populations such as **San hunter-gatherers show deep genetic divergence**.
1607 1607  
1608 -62 studies, 332 effect sizes, 10,186 participants (Black and White Americans).
1157 +3. **Specific Case Analysis:**
1158 + - Admixture in African Americans includes **West African and European genetic contributions**.
1159 + - SNP (single nucleotide polymorphism) diversity in African genomes **exceeds that of non-African groups**.
1609 1609  
1610 -Covers the period 1956–2022.
1161 +---
1611 1611  
1612 -Cohen’s d Effect Sizes (Model-Free):
1163 +## **Critique and Observations**
1164 +1. **Strengths of the Study:**
1165 + - Provides **comprehensive genetic analysis** of diverse African populations.
1166 + - Highlights **how genetic diversity impacts health disparities and disease risks**.
1613 1613  
1614 -Black viewers: d = 0.50 → strong, consistent ingroup preference for Black models.
1168 +2. **Limitations of the Study:**
1169 + - Many **African populations remain understudied**, limiting full understanding of diversity.
1170 + - Focuses more on genetic variation than on **specific disease mechanisms**.
1615 1615  
1616 -White viewers: d = –0.08 overall; pre-2000: d = –0.16 (ingroup); post-2000: d = +0.02 (outgroup leaning).
1172 +3. **Suggestions for Improvement:**
1173 + - Expand research into **underrepresented African populations**.
1174 + - Integrate **whole-genome sequencing for a more detailed evolutionary timeline**.
1617 1617  
1618 -Regression Findings:
1176 +---
1619 1619  
1620 -White viewers’ preference for Black models increases by ~0.0128 d/year since 1956 (p < 0.05).
1178 +## **Relevance to Subproject**
1179 +- Supports **genetic models of human evolution** and the **out-of-Africa hypothesis**.
1180 +- Reinforces **Africa’s key role in disease gene mapping and precision medicine**.
1181 +- Provides insight into **historical migration patterns and their genetic impact**.
1621 1621  
1622 -By 2022, White viewers showed positive directional preference for Black endorsers.
1183 +---
1623 1623  
1624 -Black viewer preferences remained stable across the 66 years.
1625 -{{/expandable}}
1185 +## **Suggestions for Further Exploration**
1186 +1. Investigate **genetic adaptations to local environments within Africa**.
1187 +2. Study **the role of African genetic diversity in disease resistance**.
1188 +3. Expand research on **how ancient migration patterns shaped modern genetic structure**.
1626 1626  
1627 -{{expandable summary="🔬 Findings"}}
1190 +---
1628 1628  
1629 -Primary Observations:
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**.
1630 1630  
1631 -Ingroup favoritism is evident: Black viewers consistently prefer Black endorsers.
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.
1632 1632  
1633 -White viewers’ preferences have shifted significantly over time toward favoring Black endorsers.
1197 +---
1634 1634  
1635 -Temporal Trends:
1199 +## **📄 Download Full Study**
1200 +[[Download Full Study>>attach:10.1038_nrg865MODERN.pdf]]
1636 1636  
1637 -Turning point: Around 2002–2003, White viewers began showing a positive (though small) preference for Black endorsers.
1202 +{{/expand}}
1638 1638  
1639 -Moderator Effects:
1204 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1640 1640  
1641 -Low anti-Black prejudice and low White ethnic identification correlate with greater White preference for Black endorsers.
1206 +{{expand title="Study: Genetic Analysis of African Populations: Human Evolution and Complex Disease" expanded="false"}}
1207 +**Source:** *Nature Reviews Genetics*
1208 +**Date of Publication:** *2002*
1209 +**Author(s):** *Sarah A. Tishkoff, Scott M. Williams*
1210 +**Title:** *"Genetic Analysis of African Populations: Human Evolution and Complex Disease"*
1211 +**DOI:** [10.1038/nrg865](https://doi.org/10.1038/nrg865)
1212 +**Subject Matter:** *Population Genetics, Human Evolution, Complex Diseases*
1642 1642  
1643 -Economic hardship (e.g., high unemployment) slightly reduces White preference for Black endorsers.
1214 +---
1644 1644  
1645 -Identification Model:
1216 +## **Key Statistics**
1217 +1. **General Observations:**
1218 + - Africa harbors **the highest genetic diversity** of any region, making it key to understanding human evolution.
1219 + - The study analyzes **genetic variation and linkage disequilibrium (LD) in African populations**.
1646 1646  
1647 -Preference changes are stronger when outcomes measure identification with endorsers (e.g., similarity, attractiveness).
1648 -{{/expandable}}
1221 +2. **Subgroup Analysis:**
1222 + - African populations exhibit **greater genetic differentiation compared to non-Africans**.
1223 + - **Migration and admixture** have shaped modern African genomes over the past **100,000 years**.
1649 1649  
1650 -{{expandable summary="📝 Critique & Observations"}}
1225 +3. **Other Significant Data Points:**
1226 + - The **effective population size (Ne) of Africans** is higher than that of non-African populations.
1227 + - LD blocks are **shorter in African genomes**, suggesting more historical recombination events.
1651 1651  
1652 -Strengths of the Study:
1229 +---
1653 1653  
1654 -Longest-running meta-analysis on interracial preferences in advertising.
1231 +## **Findings**
1232 +1. **Primary Observations:**
1233 + - African populations are the **most genetically diverse**, supporting the *Recent African Origin* hypothesis.
1234 + - Genetic variation in African populations can **help fine-map complex disease genes**.
1655 1655  
1656 -Includes multilevel modeling and 21 meta-analytic covariates.
1236 +2. **Subgroup Trends:**
1237 + - **West Africans exhibit higher genetic diversity** than East Africans due to differing migration patterns.
1238 + - Populations such as **San hunter-gatherers show deep genetic divergence**.
1657 1657  
1658 -Accounts for both perceiver and societal context, and controls for publication bias.
1240 +3. **Specific Case Analysis:**
1241 + - Admixture in African Americans includes **West African and European genetic contributions**.
1242 + - SNP (single nucleotide polymorphism) diversity in African genomes **exceeds that of non-African groups**.
1659 1659  
1660 -Limitations:
1244 +---
1661 1661  
1662 -Only examines Black and White racial dynamics—doesn’t cover Hispanic, Asian, or multiracial groups.
1246 +## **Critique and Observations**
1247 +1. **Strengths of the Study:**
1248 + - Provides **comprehensive genetic analysis** of diverse African populations.
1249 + - Highlights **how genetic diversity impacts health disparities and disease risks**.
1663 1663  
1664 -72% of effect sizes are from student samples (not fully generalizable).
1251 +2. **Limitations of the Study:**
1252 + - Many **African populations remain understudied**, limiting full understanding of diversity.
1253 + - Focuses more on genetic variation than on **specific disease mechanisms**.
1665 1665  
1666 -Social desirability bias may affect lab-based responses.
1255 +3. **Suggestions for Improvement:**
1256 + - Expand research into **underrepresented African populations**.
1257 + - Integrate **whole-genome sequencing for a more detailed evolutionary timeline**.
1667 1667  
1668 -Suggestions for Improvement:
1259 +---
1669 1669  
1670 -Include field experiments and more representative samples (age, class, ideology).
1261 +## **Relevance to Subproject**
1262 +- Supports **genetic models of human evolution** and the **out-of-Africa hypothesis**.
1263 +- Reinforces **Africa’s key role in disease gene mapping and precision medicine**.
1264 +- Provides insight into **historical migration patterns and their genetic impact**.
1671 1671  
1672 -Examine how Black models are portrayed, not just if they are shown.
1266 +---
1673 1673  
1674 -Extend research to other racial groups and multiracial representations.
1675 -{{/expandable}}
1268 +## **Suggestions for Further Exploration**
1269 +1. Investigate **genetic adaptations to local environments within Africa**.
1270 +2. Study **the role of African genetic diversity in disease resistance**.
1271 +3. Expand research on **how ancient migration patterns shaped modern genetic structure**.
1676 1676  
1677 -{{expandable summary="📌 Relevance to Subproject"}}
1273 +---
1678 1678  
1679 -Provides empirical support for the dynamic shift in White American attitudes over time.
1275 +## **Summary of Research Study**
1276 +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**.
1680 1680  
1681 -Directly informs discussions about media representation, consumer behavior, and racial identity.
1278 +This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1682 1682  
1683 -Supports policy and commercial arguments for including more diverse models in advertising.
1684 -{{/expandable}}
1280 +---
1685 1685  
1686 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
1282 +## **📄 Download Full Study**
1283 +[[Download Full Study>>attach:10.1038_nrg865MODERN.pdf]]
1687 1687  
1688 -Expand analysis to Latino, Asian, and multiracial models in media.
1285 +{{/expand}}
1689 1689  
1690 -Study real-world (non-lab) consumer reactions to racial diversity in advertising.
1287 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1691 1691  
1692 -Investigate how economic anxiety influences racial preferences in other domains (e.g., hiring, education).
1693 1693  
1694 -Explore how virtual influencers or AI-generated models affect racial perceptions.
1695 -{{/expandable}}
1696 1696  
1697 -{{expandable summary="📄 Download Full Study"}}
1698 -[[Download Full Study>>attach:lenk-et-al-white-americans-preference-for-black-people-in-advertising-has-increased-in-the-past-66-years-a-meta-analysis.pdf]]
1699 -{{/expandable}}
1700 -{{/expandable}}
Cultural Voyeurism A New Framework for Understanding Race, Ethnicity, and Mediated Intergroup Intera.pdf
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