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1 1  = Research at a Glance =
2 2  
3 +== Introduction ==
3 3  
5 +Welcome to the **Research at a Glance** repository. This section serves as a **centralized reference hub** for key academic studies related to various fields such as **social psychology, public policy, behavioral economics, and more**. Each study is categorized for easy navigation and presented in a **collapsible format** to maintain a clean layout.
4 4  
5 -Welcome to the **Research at a Glance** repository. This section serves as a **centralized reference hub** for key academic studies related to various important Racial themes. Each study is categorized for easy navigation and presented in a **collapsible format** to maintain a clean layout. I wanted to make this for a couple of reasons. Number one is organization. There are a ton of useful studies out there that expose the truth, sometimes inadvertently. You'll notice that in this initial draft the summaries are often woke and reflect the bias of the AI writing them as well as the researchers politically correct conclusions in most cases. That's because I havent gotten to going through and pointing out the reasons I put all of them in here. There is often an underlying hypocrisy or double standar, saying the quiet part out loud, or conclusions that are so much of an antithesis to what the data shows that made me want to include it. At least, thats the idea for once its polished. I have about 150 more studies to upload, so it will be a few weeks before I get through it all. Until such time, feel free to search for them yourself and edit in what you find, or add your own studies. If you like you can do it manually, or if you'd rather go the route I did, just feed the study into an AI and tell them to summarize the study using the following format:
7 +=== How to Use This Repository ===
6 6  
7 -{{example}}
8 -~{~{expand title="Study: [Study Title] (Click to Expand)" expanded="false"}}
9 -~*~*Source:~*~* [Journal/Institution Name]
10 -~*~*Date of Publication:~*~* [Publication Date]
11 -~*~*Author (s):~*~* [Author (s) Name (s)]
12 -~*~*Title:~*~* "[Study Title]"
13 -~*~*DOI:~*~* [DOI or Link]
14 -~*~*Subject Matter:~*~* [Broad Research Area, e.g., Social Psychology, Public Policy, Behavioral Economics]
15 -
16 -~-~--
17 -
18 -~#~# ~*~*Key Statistics~*~*
19 -~1. ~*~*General Observations:~*~*
20 - - [Statistical finding or observation]
21 - - [Statistical finding or observation]
22 -
23 -2. ~*~*Subgroup Analysis:~*~*
24 - - [Breakdown of findings by gender, race, or other subgroups]
25 -
26 -3. ~*~*Other Significant Data Points:~*~*
27 - - [Any additional findings or significant statistics]
28 -
29 -~-~--
30 -
31 -~#~# ~*~*Findings~*~*
32 -~1. ~*~*Primary Observations:~*~*
33 - - [High-level findings or trends in the study]
34 -
35 -2. ~*~*Subgroup Trends:~*~*
36 - - [Disparities or differences highlighted in the study]
37 -
38 -3. ~*~*Specific Case Analysis:~*~*
39 - - [Detailed explanation of any notable specific findings]
40 -
41 -~-~--
42 -
43 -~#~# ~*~*Critique and Observations~*~*
44 -~1. ~*~*Strengths of the Study:~*~*
45 - - [Examples: strong methodology, large dataset, etc.]
46 -
47 -2. ~*~*Limitations of the Study:~*~*
48 - - [Examples: data gaps, lack of upstream analysis, etc.]
49 -
50 -3. ~*~*Suggestions for Improvement:~*~*
51 - - [Ideas for further research or addressing limitations]
52 -
53 -~-~--
54 -
55 -~#~# ~*~*Relevance to Subproject~*~*
56 -- [Explanation of how this study contributes to your subproject goals.]
57 -- [Any key arguments or findings that support or challenge your views.]
58 -
59 -~-~--
60 -
61 -~#~# ~*~*Suggestions for Further Exploration~*~*
62 -~1. [Research questions or areas to investigate further.]
63 -2. [Potential studies or sources to complement this analysis.]
64 -
65 -~-~--
66 -
67 -~#~# ~*~*Summary of Research Study~*~*
68 -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]~*~*.
69 -
70 -~{~{/expand}}
71 -
72 -{{/example}}
73 -
74 74  - Click on a **category** in the **Table of Contents** to browse studies related to that topic.
75 75  - Click on a **study title** to expand its details, including **key findings, critique, and relevance**.
76 76  - Use the **search function** (Ctrl + F or XWiki's built-in search) to quickly find specific topics or authors.
77 77  - If needed, you can export this page as **PDF or print-friendly format**, and all studies will automatically expand for readability.
78 -- You'll also find a download link to the original full study in pdf form at the bottom of the collapsible block.
79 79  
80 -
81 81  {{toc/}}
82 82  
16 +== Research Studies Repository ==
83 83  
84 84  
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
85 85  
28 +**Tags:** `Genetics` `Race & Ethnicity` `Biomedical Research`
86 86  
87 -= Genetics =
30 +=== **Key Statistics** ===
88 88  
89 -
90 -== Study: Reconstructing Indian Population History ==
91 -
92 -{{expand expanded="false" title="Study: Reconstructing Indian Population History"}}
93 -**Source:** *Nature*
94 -**Date of Publication:** *2009*
95 -**Author(s):** *David Reich, Kumarasamy Thangaraj, Nick Patterson, Alkes L. Price, Lalji Singh*
96 -**Title:** *"Reconstructing Indian Population History"*
97 -**DOI:** [10.1038/nature08365](https://doi.org/10.1038/nature08365)
98 -**Subject Matter:** *Genetics, Population History, South Asian Ancestry* 
99 -
100 -----
101 -
102 -## **Key Statistics**##
103 -
104 104  1. **General Observations:**
105 - - Study analyzed **132 individuals from 25 diverse Indian groups**.
106 - - 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%**.
107 107  
108 108  2. **Subgroup Analysis:**
109 - - ANI ancestry is closely related to **Middle Easterners, Central Asians, and Europeans**.
110 - - 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.
111 111  
112 -3. **Other Significant Data Points:**
113 - - ANI ancestry ranges from **39% to 71%** across Indian groups.
114 - - **Caste and linguistic differences** strongly correlate with genetic variation.
40 +=== **Findings** ===
115 115  
116 -----
42 +- Self-identified race strongly aligns with genetic ancestry.
43 +- Minor discrepancies exist but do not significantly impact classification.
117 117  
118 -## **Findings**##
45 +=== **Relevance to Subproject** ===
119 119  
120 -1. **Primary Observations:**
121 - - The genetic landscape of India has been shaped by **thousands of years of endogamy**.
122 - - Groups with **only ASI ancestry no longer exist** in mainland India.
123 -
124 -2. **Subgroup Trends:**
125 - - **Higher ANI ancestry in upper-caste and Indo-European-speaking groups**.
126 - - **Andaman Islanders** are unique in having **ASI ancestry without ANI influence**.
127 -
128 -3. **Specific Case Analysis:**
129 - - **Founder effects** have maintained allele frequency differences among Indian groups.
130 - - Predicts **higher incidence of recessive diseases** due to historical genetic isolation.
131 -
132 -----
133 -
134 -## **Critique and Observations**##
135 -
136 -1. **Strengths of the Study:**
137 - - **First large-scale genetic analysis** of Indian population history.
138 - - Introduces **new methods for ancestry estimation without direct ancestral reference groups**.
139 -
140 -2. **Limitations of the Study:**
141 - - Limited **sample size relative to India's population diversity**.
142 - - Does not include **recent admixture events** post-colonial era.
143 -
144 -3. **Suggestions for Improvement:**
145 - - Future research should **expand sampling across more Indian tribal groups**.
146 - - Use **whole-genome sequencing** for finer resolution of ancestry.
147 -
148 -----
149 -
150 -## **Relevance to Subproject**
151 -- Provides a **genetic basis for caste and linguistic diversity** in India.
152 -- Highlights **founder effects and genetic drift** shaping South Asian populations.
153 -- Supports research on **medical genetics and disease risk prediction** in Indian populations.##
154 -
155 -----
156 -
157 -## **Suggestions for Further Exploration**##
158 -
159 -1. Examine **genetic markers linked to disease susceptibility** in Indian subpopulations.
160 -2. Investigate the impact of **recent migration patterns on ANI-ASI ancestry distribution**.
161 -3. Study **gene flow between Indian populations and other global groups**.
162 -
163 -----
164 -
165 -## **Summary of Research Study**
166 -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**.##
167 -
168 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
169 -
170 -----
171 -
172 -## **📄 Download Full Study**
173 -[[Download Full Study>>attach:10.1038_nature08365.pdf]]##
47 +- Reinforces the reliability of **self-reported racial identity** in genetic research.
48 +- Highlights **policy considerations** in biomedical studies.
174 174  {{/expand}}
175 175  
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]
176 176  
177 -== Study: The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations ==
59 +---
178 178  
179 -{{expand expanded="false" title="Study: The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations"}}
180 -**Source:** *Nature*
181 -**Date of Publication:** *2016*
182 -**Author(s):** *David Reich, Swapan Mallick, Heng Li, Mark Lipson, and others*
183 -**Title:** *"The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations"*
184 -**DOI:** [10.1038/nature18964](https://doi.org/10.1038/nature18964)
185 -**Subject Matter:** *Human Genetic Diversity, Population History, Evolutionary Genomics* 
186 -
187 -----
188 -
189 -## **Key Statistics**##
190 -
61 +## **Key Statistics**
191 191  1. **General Observations:**
192 - - Analyzed **high-coverage genome sequences of 300 individuals from 142 populations**.
193 - - Included **many underrepresented and indigenous groups** from Africa, Asia, Europe, and the Americas.
63 + - [Statistical finding or observation]
64 + - [Statistical finding or observation]
194 194  
195 195  2. **Subgroup Analysis:**
196 - - Found **higher genetic diversity within African populations** compared to non-African groups.
197 - - Showed **Neanderthal and Denisovan ancestry in non-African populations**, particularly in Oceania.
67 + - [Breakdown of findings by gender, race, or other subgroups]
198 198  
199 199  3. **Other Significant Data Points:**
200 - - Identified **5.8 million base pairs absent from the human reference genome**.
201 - - Estimated that **mutations have accumulated 5% faster in non-Africans than in Africans**.
70 + - [Any additional findings or significant statistics]
202 202  
203 -----
72 +---
204 204  
205 -## **Findings**##
206 -
74 +## **Findings**
207 207  1. **Primary Observations:**
208 - - **African populations harbor the greatest genetic diversity**, confirming an out-of-Africa dispersal model.
209 - - Indigenous Australians and New Guineans **share a common ancestral population with other non-Africans**.
76 + - [High-level findings or trends in the study]
210 210  
211 211  2. **Subgroup Trends:**
212 - - **Lower heterozygosity in non-Africans** due to founder effects from migration bottlenecks.
213 - - **Denisovan ancestry in South Asians is higher than previously thought**.
79 + - [Disparities or differences highlighted in the study]
214 214  
215 215  3. **Specific Case Analysis:**
216 - - **Neanderthal ancestry is higher in East Asians than in Europeans**.
217 - - African hunter-gatherer groups show **deep population splits over 100,000 years ago**.
82 + - [Detailed explanation of any notable specific findings]
218 218  
219 -----
84 +---
220 220  
221 -## **Critique and Observations**##
222 -
86 +## **Critique and Observations**
223 223  1. **Strengths of the Study:**
224 - - **Largest global genetic dataset** outside of the 1000 Genomes Project.
225 - - High sequencing depth allows **more accurate identification of genetic variants**.
88 + - [Examples: strong methodology, large dataset, etc.]
226 226  
227 227  2. **Limitations of the Study:**
228 - - **Limited sample sizes for some populations**, restricting generalizability.
229 - - Lacks ancient DNA comparisons, making it difficult to reconstruct deep ancestry fully.
91 + - [Examples: data gaps, lack of upstream analysis, etc.]
230 230  
231 231  3. **Suggestions for Improvement:**
232 - - Future studies should include **ancient genomes** to improve demographic modeling.
233 - - Expand research into **how genetic variation affects health outcomes** across populations.
94 + - [Ideas for further research or addressing limitations]
234 234  
235 -----
96 +---
236 236  
237 237  ## **Relevance to Subproject**
238 -- Provides **comprehensive data on human genetic diversity**, useful for **evolutionary studies**.
239 -- Supports research on **Neanderthal and Denisovan introgression** in modern human populations.
240 -- Enhances understanding of **genetic adaptation and disease susceptibility across groups**.##
99 +- [Explanation of how this study contributes to your subproject goals.]
100 +- [Any key arguments or findings that support or challenge your views.]
241 241  
242 -----
102 +---
243 243  
244 -## **Suggestions for Further Exploration**##
104 +## **Suggestions for Further Exploration**
105 +1. [Research questions or areas to investigate further.]
106 +2. [Potential studies or sources to complement this analysis.]
245 245  
246 -1. Investigate **functional consequences of genetic variation in underrepresented populations**.
247 -2. Study **how selection pressures shaped genetic diversity across different environments**.
248 -3. Explore **medical applications of population-specific genetic markers**.
108 +---
249 249  
250 -----
251 -
252 252  ## **Summary of Research Study**
253 -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**.##
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]**.
254 254  
255 -This summary provides an accessible, at-a-glance overview of the studys contributions. Please refer to the full paper for in-depth analysis.
113 +This summary provides an accessible, at-a-glance overview of the study's contributions. Please refer to the full paper for in-depth analysis.
256 256  
257 -----
115 +---
258 258  
259 259  ## **📄 Download Full Study**
260 -[[Download Full Study>>attach:10.1038_nature18964.pdf]]##
261 -{{/expand}}
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}}
262 262  
263 -
264 -== Study: Meta-analysis of the heritability of human traits based on fifty years of twin studies ==
265 -
266 -{{expand expanded="false" title="Study: Meta-analysis of the heritability of human traits based on fifty years of twin studies"}}
267 -**Source:** *Nature Genetics*
268 -**Date of Publication:** *2015*
269 -**Author(s):** *Tinca J. C. Polderman, Beben Benyamin, Christiaan A. de Leeuw, Patrick F. Sullivan, Arjen van Bochoven, Peter M. Visscher, Danielle Posthuma*
270 -**Title:** *"Meta-analysis of the heritability of human traits based on fifty years of twin studies"*
271 -**DOI:** [10.1038/ng.328](https://doi.org/10.1038/ng.328)
272 -**Subject Matter:** *Genetics, Heritability, Twin Studies, Behavioral Science* 
273 -
274 -----
275 -
276 -## **Key Statistics**##
277 -
278 -1. **General Observations:**
279 - - Analyzed **17,804 traits from 2,748 twin studies** published between **1958 and 2012**.
280 - - Included data from **14,558,903 twin pairs**, making it the largest meta-analysis on human heritability.
281 -
282 -2. **Subgroup Analysis:**
283 - - Found **49% average heritability** across all traits.
284 - - **69% of traits follow a simple additive genetic model**, meaning most variance is due to genes, not environment.
285 -
286 -3. **Other Significant Data Points:**
287 - - **Neurological, metabolic, and psychiatric traits** showed the highest heritability estimates.
288 - - Traits related to **social values and environmental interactions** had lower heritability estimates.
289 -
290 -----
291 -
292 -## **Findings**##
293 -
294 -1. **Primary Observations:**
295 - - Across all traits, genetic factors play a significant role in individual differences.
296 - - The study contradicts models that **overestimate environmental effects in behavioral and cognitive traits**.
297 -
298 -2. **Subgroup Trends:**
299 - - **Eye and brain-related traits showed the highest heritability (70-80%)**.
300 - - **Shared environmental effects were negligible (<10%) for most traits**.
301 -
302 -3. **Specific Case Analysis:**
303 - - Twin correlations suggest **limited evidence for strong non-additive genetic influences**.
304 - - The study highlights **missing heritability in complex traits**, which genome-wide association studies (GWAS) have yet to fully explain.
305 -
306 -----
307 -
308 -## **Critique and Observations**##
309 -
310 -1. **Strengths of the Study:**
311 - - **Largest-ever heritability meta-analysis**, covering nearly all published twin studies.
312 - - Provides a **comprehensive framework for understanding gene-environment contributions**.
313 -
314 -2. **Limitations of the Study:**
315 - - **Underrepresentation of African, South American, and Asian twin cohorts**, limiting global generalizability.
316 - - Cannot **fully separate genetic influences from potential cultural/environmental confounders**.
317 -
318 -3. **Suggestions for Improvement:**
319 - - Future research should use **whole-genome sequencing** for finer-grained heritability estimates.
320 - - **Incorporate non-Western populations** to assess global heritability trends.
321 -
322 -----
323 -
324 -## **Relevance to Subproject**
325 -- Establishes a **quantitative benchmark for heritability across human traits**.
326 -- Reinforces **genetic influence on cognitive, behavioral, and physical traits**.
327 -- Highlights the need for **genome-wide studies to identify missing heritability**.##
328 -
329 -----
330 -
331 -## **Suggestions for Further Exploration**##
332 -
333 -1. Investigate how **heritability estimates compare across different socioeconomic backgrounds**.
334 -2. Examine **gene-environment interactions in cognitive and psychiatric traits**.
335 -3. Explore **non-additive genetic effects on human traits using newer statistical models**.
336 -
337 -----
338 -
339 -## **Summary of Research Study**
340 -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.##
341 -
342 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
343 -
344 -----
345 -
346 -## **📄 Download Full Study**
347 -[[Download Full Study>>attach:10.1038_ng.328.pdf]]##
348 348  {{/expand}}
349 349  
130 +{{html}}<hr style="border: 3px solid red;">{{/html}}
350 350  
351 -== Study: Genetic Analysis of African Populations: Human Evolution and Complex Disease ==
352 352  
353 -{{expand expanded="false" title="Study: Genetic Analysis of African Populations: Human Evolution and Complex Disease"}}
354 -**Source:** *Nature Reviews Genetics*
355 -**Date of Publication:** *2002*
356 -**Author(s):** *Sarah A. Tishkoff, Scott M. Williams*
357 -**Title:** *"Genetic Analysis of African Populations: Human Evolution and Complex Disease"*
358 -**DOI:** [10.1038/nrg865](https://doi.org/10.1038/nrg865)
359 -**Subject Matter:** *Population Genetics, Human Evolution, Complex Diseases* 
360 360  
361 -----
134 +---
362 362  
363 -## **Key Statistics**##
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*
364 364  
144 +---
145 +
146 +## **Key Statistics**
365 365  1. **General Observations:**
366 - - Africa harbors **the highest genetic diversity** of any region, making it key to understanding human evolution.
367 - - 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.
368 368  
369 369  2. **Subgroup Analysis:**
370 - - African populations exhibit **greater genetic differentiation compared to non-Africans**.
371 - - **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.
372 372  
373 373  3. **Other Significant Data Points:**
374 - - The **effective population size (Ne) of Africans** is higher than that of non-African populations.
375 - - LD blocks are **shorter in African genomes**, suggesting more historical recombination events.
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.
376 376  
377 -----
159 +---
378 378  
379 -## **Findings**##
380 -
161 +## **Findings**
381 381  1. **Primary Observations:**
382 - - African populations are the **most genetically diverse**, supporting the *Recent African Origin* hypothesis.
383 - - 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.
384 384  
385 385  2. **Subgroup Trends:**
386 - - **West Africans exhibit higher genetic diversity** than East Africans due to differing migration patterns.
387 - - 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.
388 388  
389 389  3. **Specific Case Analysis:**
390 - - Admixture in African Americans includes **West African and European genetic contributions**.
391 - - SNP (single nucleotide polymorphism) diversity in African genomes **exceeds that of non-African groups**.
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.
392 392  
393 -----
174 +---
394 394  
395 -## **Critique and Observations**##
396 -
176 +## **Critique and Observations**
397 397  1. **Strengths of the Study:**
398 - - Provides **comprehensive genetic analysis** of diverse African populations.
399 - - 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.
400 400  
401 401  2. **Limitations of the Study:**
402 - - Many **African populations remain understudied**, limiting full understanding of diversity.
403 - - 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.
404 404  
405 405  3. **Suggestions for Improvement:**
406 - - Expand research into **underrepresented African populations**.
407 - - Integrate **whole-genome sequencing for a more detailed evolutionary timeline**.
186 + - Further studies should incorporate **qualitative data** on behavioral shifts.
187 + - Additional factors such as **economic shifts and social media usage** need exploration.
408 408  
409 -----
189 +---
410 410  
411 411  ## **Relevance to Subproject**
412 -- Supports **genetic models of human evolution** and the **out-of-Africa hypothesis**.
413 -- Reinforces **Africa’s key role in disease gene mapping and precision medicine**.
414 -- Provides insight into **historical migration patterns and their genetic impact**.##
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.
415 415  
416 -----
195 +---
417 417  
418 -## **Suggestions for Further Exploration**##
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.
419 419  
420 -1. Investigate **genetic adaptations to local environments within Africa**.
421 -2. Study **the role of African genetic diversity in disease resistance**.
422 -3. Expand research on **how ancient migration patterns shaped modern genetic structure**.
201 +---
423 423  
424 -----
425 -
426 426  ## **Summary of Research Study**
427 -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**.##
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.
428 428  
429 -This summary provides an accessible, at-a-glance overview of the studys contributions. Please refer to the full paper for in-depth analysis.
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.
430 430  
431 -----
208 +---
432 432  
433 433  ## **📄 Download Full Study**
434 -[[Download Full Study>>attach:10.1038_nrg865MODERN.pdf]]##
435 -{{/expand}}
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}}
436 436  
437 -
438 -== Study: Pervasive Findings of Directional Selection in Ancient DNA ==
439 -
440 -{{expand expanded="false" title="Study: Pervasive Findings of Directional Selection in Ancient DNA"}}
441 -**Source:** *bioRxiv Preprint*
442 -**Date of Publication:** *September 15, 2024*
443 -**Author(s):** *Ali Akbari, Alison R. Barton, Steven Gazal, Zheng Li, Mohammadreza Kariminejad, et al.*
444 -**Title:** *"Pervasive findings of directional selection realize the promise of ancient DNA to elucidate human adaptation"*
445 -**DOI:** [10.1101/2024.09.14.613021](https://doi.org/10.1101/2024.09.14.613021)
446 -**Subject Matter:** *Genomics, Evolutionary Biology, Natural Selection* 
447 -
448 -----
449 -
450 -## **Key Statistics**##
451 -
452 -1. **General Observations:**
453 - - Study analyzes **8,433 ancient individuals** from the past **14,000 years**.
454 - - Identifies **347 genome-wide significant loci** showing strong selection.
455 -
456 -2. **Subgroup Analysis:**
457 - - Examines **West Eurasian populations** and their genetic evolution.
458 - - Tracks **changes in allele frequencies over millennia**.
459 -
460 -3. **Other Significant Data Points:**
461 - - **10,000 years of directional selection** affected metabolic, immune, and cognitive traits.
462 - - **Strong selection signals** found for traits like **skin pigmentation, cognitive function, and immunity**.
463 -
464 -----
465 -
466 -## **Findings**##
467 -
468 -1. **Primary Observations:**
469 - - **Hundreds of alleles have been subject to directional selection** over recent millennia.
470 - - Traits like **immune function, metabolism, and cognitive performance** show strong selection.
471 -
472 -2. **Subgroup Trends:**
473 - - Selection pressure on **energy storage genes** supports the **Thrifty Gene Hypothesis**.
474 - - **Cognitive performance-related alleles** have undergone selection, but their historical advantages remain unclear.
475 -
476 -3. **Specific Case Analysis:**
477 - - **Celiac disease risk allele** increased from **0% to 20%** in 4,000 years.
478 - - **Blood type B frequency rose from 0% to 8% in 6,000 years**.
479 - - **Tuberculosis risk allele** fluctuated from **2% to 9% over 3,000 years before declining**.
480 -
481 -----
482 -
483 -## **Critique and Observations**##
484 -
485 -1. **Strengths of the Study:**
486 - - **Largest dataset to date** on natural selection in human ancient DNA.
487 - - Uses **direct allele frequency tracking instead of indirect measures**.
488 -
489 -2. **Limitations of the Study:**
490 - - Findings **may not translate directly** to modern populations.
491 - - **Unclear whether observed selection pressures persist today**.
492 -
493 -3. **Suggestions for Improvement:**
494 - - Expanding research to **other global populations** to assess universal trends.
495 - - Investigating **long-term evolutionary trade-offs of selected alleles**.
496 -
497 -----
498 -
499 -## **Relevance to Subproject**
500 -- Provides **direct evidence of long-term genetic adaptation** in human populations.
501 -- Supports theories on **polygenic selection shaping human cognition, metabolism, and immunity**.
502 -- Highlights **how past selection pressures may still influence modern health and disease prevalence**.##
503 -
504 -----
505 -
506 -## **Suggestions for Further Exploration**##
507 -
508 -1. Examine **selection patterns in non-European populations** for comparison.
509 -2. Investigate **how environmental and cultural shifts influenced genetic selection**.
510 -3. Explore **the genetic basis of traits linked to past and present-day human survival**.
511 -
512 -----
513 -
514 -## **Summary of Research Study**
515 -This study examines **how human genetic adaptation has unfolded over 14,000 years**, using a **large dataset of ancient DNA**. It highlights **strong selection on immune function, metabolism, and cognitive traits**, revealing **hundreds of loci affected by directional selection**. The findings emphasize **the power of ancient DNA in tracking human evolution and adaptation**.##
516 -
517 -----
518 -
519 -## **📄 Download Full Study**
520 -[[Download Full Study>>attach:10.1101_2024.09.14.613021doi_.pdf]]##
521 521  {{/expand}}
522 522  
223 +{{html}}<hr style="border: 3px solid red;">{{/html}}
523 523  
524 -== Study: The Wilson Effect: The Increase in Heritability of IQ With Age ==
525 525  
526 -{{expand expanded="false" title="Study: The Wilson Effect: The Increase in Heritability of IQ With Age"}}
527 -**Source:** *Twin Research and Human Genetics (Cambridge University Press)*
528 -**Date of Publication:** *2013*
529 -**Author(s):** *Thomas J. Bouchard Jr.*
530 -**Title:** *"The Wilson Effect: The Increase in Heritability of IQ With Age"*
531 -**DOI:** [10.1017/thg.2013.54](https://doi.org/10.1017/thg.2013.54)
532 -**Subject Matter:** *Intelligence, Heritability, Developmental Psychology* 
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*
533 533  
534 -----
234 +---
535 535  
536 -## **Key Statistics**##
537 -
236 +## **Key Statistics**
538 538  1. **General Observations:**
539 - - The study documents how the **heritability of IQ increases with age**, reaching an asymptote at **0.80 by adulthood**.
540 - - Analysis is based on **longitudinal twin and adoption studies**.
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.
541 541  
542 542  2. **Subgroup Analysis:**
543 - - Shared environmental influence on IQ **declines with age**, reaching **0.10 in adulthood**.
544 - - Monozygotic twins show **increasing genetic similarity in IQ over time**, while dizygotic twins become **less concordant**.
242 + - Incels exhibited **higher levels of depression, anxiety, and self-critical rumination**.
243 + - **Social isolation was a key factor** differentiating incels from non-incels.
545 545  
546 546  3. **Other Significant Data Points:**
547 - - Data from the **Louisville Longitudinal Twin Study and cross-national twin samples** support findings.
548 - - IQ stability over time is **influenced more by genetics than by shared environmental factors**.
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.
549 549  
550 -----
249 +---
551 551  
552 -## **Findings**##
553 -
251 +## **Findings**
554 554  1. **Primary Observations:**
555 - - Intelligence heritability **strengthens throughout development**, contrary to early environmental models.
556 - - Shared environmental effects **decrease by late adolescence**, emphasizing **genetic influence in adulthood**.
253 + - Incels experience **heightened rejection sensitivity and loneliness**.
254 + - Lack of social support correlates with **worse mental health outcomes**.
557 557  
558 558  2. **Subgroup Trends:**
559 - - Studies from **Scotland, Netherlands, and the US** show **consistent patterns of increasing heritability with age**.
560 - - Findings hold across **varied socio-economic and educational backgrounds**.
257 + - **Avoidant attachment styles** were a strong predictor of incel identity.
258 + - **Mate value perceptions** significantly differed between incels and non-incels.
561 561  
562 562  3. **Specific Case Analysis:**
563 - - Longitudinal adoption studies show **declining impact of adoptive parental influence on IQ** as children age.
564 - - Cross-sectional twin data confirm **higher IQ correlations for monozygotic twins in adulthood**.
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.
565 565  
566 -----
264 +---
567 567  
568 -## **Critique and Observations**##
569 -
266 +## **Critique and Observations**
570 570  1. **Strengths of the Study:**
571 - - **Robust dataset covering multiple twin and adoption studies over decades**.
572 - - **Clear, replicable trend** demonstrating the increasing role of genetics in intelligence.
268 + - **First quantitative study** on incels’ social isolation and mental health.
269 + - **Robust sample size** and validated psychological measures.
573 573  
574 574  2. **Limitations of the Study:**
575 - - Findings apply primarily to **Western industrialized nations**, limiting generalizability.
576 - - **Lack of neurobiological mechanisms** explaining how genes express their influence over time.
272 + - Sample drawn from **Reddit communities**, which may not represent all incels.
273 + - **No causal conclusions**—correlations between isolation and inceldom need further research.
577 577  
578 578  3. **Suggestions for Improvement:**
579 - - Future research should investigate **gene-environment interactions in cognitive aging**.
580 - - Examine **heritability trends in non-Western populations** to determine cross-cultural consistency.
276 + - Future studies should **compare incel forum users vs. non-users**.
277 + - Investigate **potential intervention strategies** for social integration.
581 581  
582 -----
279 +---
583 583  
584 584  ## **Relevance to Subproject**
585 -- Provides **strong evidence for the genetic basis of intelligence**.
586 -- Highlights the **diminishing role of shared environment in cognitive development**.
587 -- Supports research on **cognitive aging and heritability across the lifespan**.##
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**.
588 588  
589 -----
286 +---
590 590  
591 -## **Suggestions for Further Exploration**##
288 +## **Suggestions for Further Exploration**
289 +1. Explore how **online community participation** affects incel mental health.
290 +2. Investigate **cognitive biases** influencing self-perceived rejection among incels.
291 +3. Assess **therapeutic interventions** to address incel social isolation.
592 592  
593 -1. Investigate **neurogenetic pathways underlying IQ development**.
594 -2. Examine **how education and socioeconomic factors interact with genetic IQ influences**.
595 -3. Study **heritability trends in aging populations and cognitive decline**.
293 +---
596 596  
597 -----
598 -
599 599  ## **Summary of Research Study**
600 -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**.##
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**.
601 601  
602 602  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
603 603  
604 -----
300 +---
605 605  
606 606  ## **📄 Download Full Study**
607 -[[Download Full Study>>attach:10.1017_thg.2013.54.pdf]]##
303 +[[Download Full Study>>attach:10.1007_s12144-023-04275-z.pdf]]
304 +
608 608  {{/expand}}
609 609  
307 +{{html}}<hr style="border: 3px solid red;">{{/html}}
610 610  
611 -== Study: Is Homo sapiens polytypic? Human taxonomic diversity and its implications ==
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
612 612  
613 -{{expand expanded="false" title="Study: Is Homo sapiens polytypic? Human taxonomic diversity and its implications"}}
614 -**Source:** *Medical Hypotheses (Elsevier)*
615 -**Date of Publication:** *2010*
616 -**Author(s):** *Michael A. Woodley*
617 -**Title:** *"Is Homo sapiens polytypic? Human taxonomic diversity and its implications"*
618 -**DOI:** [10.1016/j.mehy.2009.07.046](https://doi.org/10.1016/j.mehy.2009.07.046)
619 -**Subject Matter:** *Human Taxonomy, Evolutionary Biology, Anthropology* 
316 +Key Statistics
317 +General Observations:
620 620  
621 -----
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:
622 622  
623 -## **Key Statistics**##
323 +Males exhibited higher rates of cannabis use, but females reported stronger mental health impacts.
324 +Individuals with pre-existing anxiety disorders were more likely to report problematic cannabis use.
325 +Other Significant Data Points:
624 624  
625 -1. **General Observations:**
626 - - The study argues that **Homo sapiens is polytypic**, meaning it consists of multiple subspecies rather than a single monotypic species.
627 - - Examines **genetic diversity, morphological variation, and evolutionary lineage** in humans.
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:
628 628  
629 -2. **Subgroup Analysis:**
630 - - Discusses **four primary definitions of race/subspecies**: Essentialist, Taxonomic, Population-based, and Lineage-based.
631 - - Suggests that **human heterozygosity levels are comparable to species that are classified as polytypic**.
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:
632 632  
633 -3. **Other Significant Data Points:**
634 - - The study evaluates **FST values (genetic differentiation measure)** and argues that human genetic differentiation is comparable to that of recognized subspecies in other species.
635 - - Considers **phylogenetic species concepts** in defining human variation.
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:
636 636  
637 -----
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:
638 638  
639 -## **Findings**##
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:
640 640  
641 -1. **Primary Observations:**
642 - - Proposes that **modern human populations meet biological criteria for subspecies classification**.
643 - - 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:
644 644  
645 -2. **Subgroup Trends:**
646 - - Discusses **how race concepts evolved over time** in biological sciences.
647 - - 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.
648 648  
649 -3. **Specific Case Analysis:**
650 - - Evaluates how **genetic markers correlate with population structure**.
651 - - Addresses the **controversy over race classification in modern anthropology**.
652 -
653 -----
654 -
655 -## **Critique and Observations**##
656 -
657 -1. **Strengths of the Study:**
658 - - Uses **comparative species analysis** to assess human classification.
659 - - Provides a **biological perspective** on the race concept, moving beyond social constructivism arguments.
660 -
661 -2. **Limitations of the Study:**
662 - - Controversial topic with **strong opposing views in anthropology and genetics**.
663 - - **Relies on broad genetic trends**, but does not analyze individual-level genetic variation in depth.
664 -
665 -3. **Suggestions for Improvement:**
666 - - Further research should **incorporate whole-genome studies** to refine subspecies classifications.
667 - - Investigate **how admixture affects taxonomic classification over time**.
668 -
669 -----
670 -
671 -## **Relevance to Subproject**
672 -- Contributes to discussions on **evolutionary taxonomy and species classification**.
673 -- Provides evidence on **genetic differentiation among human populations**.
674 -- Highlights **historical and contemporary scientific debates on race and human variation**.##
675 -
676 -----
677 -
678 -## **Suggestions for Further Exploration**##
679 -
680 -1. Examine **FST values in modern and ancient human populations**.
681 -2. Investigate how **adaptive evolution influences population differentiation**.
682 -3. Explore **the impact of genetic diversity on medical treatments and disease susceptibility**.
683 -
684 -----
685 -
686 -## **Summary of Research Study**
687 -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**.##
688 -
689 689  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
690 690  
691 -----
368 +📄 Download Full Study
369 +[[Download Full Study>>attach:10.1016_j.addbeh.2016.02.030.pdf]]
692 692  
693 -## **📄 Download Full Study**
694 -[[Download Full Study>>attach:10.1016_j.mehy.2009.07.046.pdf]]##
695 695  {{/expand}}
696 696  
373 +{{html}}<hr style="border: 3px solid red;">{{/html}}
697 697  
698 -== Study: Survey of Expert Opinion on Intelligence: Intelligence Research, Experts' Background, Controversial Issues, and the Media ==
699 -
700 -{{expand expanded="false" title="Study: Survey of Expert Opinion on Intelligence: Intelligence Research, Experts' Background, Controversial Issues, and the Media"}}
375 +{{expand title="Study: Is there a Dysgenic Secular Trend Towards Slowing Simple Reaction Time?" expanded="false"}}
701 701  **Source:** *Intelligence (Elsevier)*
702 -**Date of Publication:** *2019*
703 -**Author(s):** *Heiner Rindermann, David Becker, Thomas R. Coyle*
704 -**Title:** *"Survey of Expert Opinion on Intelligence: Intelligence Research, Experts' Background, Controversial Issues, and the Media"*
705 -**DOI:** [10.1016/j.intell.2019.101406](https://doi.org/10.1016/j.intell.2019.101406)
706 -**Subject Matter:** *Psychology, Intelligence Research, Expert Analysis* 
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*
707 707  
708 -----
383 +---
709 709  
710 -## **Key Statistics**##
711 -
385 +## **Key Statistics**
712 712  1. **General Observations:**
713 - - Survey of **102 experts** on intelligence research and public discourse.
714 - - 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.
715 715  
716 716  2. **Subgroup Analysis:**
717 - - **90% of experts were from Western countries**, and **83% were male**.
718 - - 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.
719 719  
720 720  3. **Other Significant Data Points:**
721 - - Experts rated media coverage of intelligence research as **poor (avg. 3.1 on a 9-point scale)**.
722 - - **50% of experts attributed US Black-White IQ differences to genetic factors, 50% to environmental factors**.
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**.
723 723  
724 -----
398 +---
725 725  
726 -## **Findings**##
727 -
400 +## **Findings**
728 728  1. **Primary Observations:**
729 - - Experts overwhelmingly support **the g-factor theory of intelligence**.
730 - - **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.
731 731  
732 732  2. **Subgroup Trends:**
733 - - **Left-leaning experts were more likely to reject genetic explanations for group IQ differences**.
734 - - **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**.
735 735  
736 736  3. **Specific Case Analysis:**
737 - - The study compared **media coverage of intelligence research** with expert opinions.
738 - - Found a **disconnect between journalists and intelligence researchers**, especially regarding politically sensitive issues.
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.
739 739  
740 -----
413 +---
741 741  
742 -## **Critique and Observations**##
743 -
415 +## **Critique and Observations**
744 744  1. **Strengths of the Study:**
745 - - **Largest expert survey on intelligence research** to date.
746 - - 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.
747 747  
748 748  2. **Limitations of the Study:**
749 - - **Sample primarily from Western countries**, limiting global perspectives.
750 - - 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.
751 751  
752 752  3. **Suggestions for Improvement:**
753 - - Future studies should include **a broader range of global experts**.
754 - - Additional research needed on **media biases and misrepresentation of intelligence research**.
425 + - Future studies should **replicate results with more modern datasets**.
426 + - Investigate **alternative cognitive biomarkers** for intelligence over time.
755 755  
756 -----
428 +---
757 757  
758 758  ## **Relevance to Subproject**
759 -- Provides insight into **expert consensus and division on intelligence research**.
760 -- Highlights the **role of media bias** in shaping public perception of intelligence science.
761 -- Useful for understanding **the intersection of science, politics, and public discourse** on intelligence research.##
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**.
762 762  
763 -----
435 +---
764 764  
765 -## **Suggestions for Further Exploration**##
437 +## **Suggestions for Further Exploration**
438 +1. Investigate **genetic markers associated with reaction time** and intelligence decline.
439 +2. Examine **regional variations in reaction time trends**.
440 +3. Explore **cognitive resilience factors that counteract the decline**.
766 766  
767 -1. Examine **cross-national differences** in expert opinions on intelligence.
768 -2. Investigate how **media bias impacts public understanding of intelligence research**.
769 -3. Conduct follow-up studies with **a more diverse expert pool** to test findings.
442 +---
770 770  
771 -----
772 -
773 773  ## **Summary of Research Study**
774 -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**.##
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**.
775 775  
776 776  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
777 777  
778 -----
449 +---
779 779  
780 780  ## **📄 Download Full Study**
781 -[[Download Full Study>>attach:10.1016_j.intell.2019.101406.pdf]]##
452 +[[Download Full Study>>attach:10.1016_j.intell.2014.05.012.pdf]]
453 +
782 782  {{/expand}}
783 783  
456 +{{html}}<hr style="border: 3px solid red;">{{/html}}
784 784  
785 -== Study: A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation ==
786 -
787 -{{expand expanded="false" title="Study: A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation"}}
458 +{{expand title="Study: A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation" expanded="false"}}
788 788  **Source:** *Intelligence (Elsevier)*
789 789  **Date of Publication:** *2015*
790 790  **Author(s):** *Davide Piffer*
791 791  **Title:** *"A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation"*
792 792  **DOI:** [10.1016/j.intell.2015.08.008](https://doi.org/10.1016/j.intell.2015.08.008)
793 -**Subject Matter:** *Genetics, Intelligence, GWAS, Population Differences* 
464 +**Subject Matter:** *Genetics, Intelligence, GWAS, Population Differences*
794 794  
795 -----
466 +---
796 796  
797 -## **Key Statistics**##
798 -
468 +## **Key Statistics**
799 799  1. **General Observations:**
800 800   - Study analyzed **genome-wide association studies (GWAS) hits** linked to intelligence.
801 801   - Found a **strong correlation (r = .91) between polygenic intelligence scores and national IQ levels**.
... ... @@ -808,10 +808,9 @@
808 808   - GWAS intelligence SNPs predicted **IQ levels more strongly than random genetic markers**.
809 809   - Genetic differentiation (Fst values) showed that **selection pressure, rather than drift, influenced intelligence-related allele distributions**.
810 810  
811 -----
481 +---
812 812  
813 -## **Findings**##
814 -
483 +## **Findings**
815 815  1. **Primary Observations:**
816 816   - Intelligence-associated SNP frequencies correlate **highly with national IQ levels**.
817 817   - Genetic selection for intelligence appears **stronger than selection for height-related genes**.
... ... @@ -824,10 +824,9 @@
824 824   - Polygenic scores using **intelligence-related alleles significantly outperformed random SNPs** in predicting IQ.
825 825   - Selection pressures **may explain differences in global intelligence distribution** beyond genetic drift effects.
826 826  
827 -----
496 +---
828 828  
829 -## **Critique and Observations**##
830 -
498 +## **Critique and Observations**
831 831  1. **Strengths of the Study:**
832 832   - **Comprehensive genetic analysis** of intelligence-linked SNPs.
833 833   - Uses **multiple statistical methods (factor analysis, Fst analysis) to confirm results**.
... ... @@ -840,774 +840,296 @@
840 840   - Larger **cross-population GWAS studies** needed to validate findings.
841 841   - Investigate **non-genetic contributors to IQ variance** in addition to genetic factors.
842 842  
843 -----
511 +---
844 844  
845 845  ## **Relevance to Subproject**
846 846  - Supports research on **genetic influences on intelligence at a population level**.
847 847  - Aligns with broader discussions on **cognitive genetics and natural selection effects**.
848 -- Provides a **quantitative framework for analyzing polygenic selection in intelligence studies**.##
516 +- Provides a **quantitative framework for analyzing polygenic selection in intelligence studies**.
849 849  
850 -----
518 +---
851 851  
852 -## **Suggestions for Further Exploration**##
853 -
520 +## **Suggestions for Further Exploration**
854 854  1. Conduct **expanded GWAS studies** including diverse populations.
855 855  2. Investigate **gene-environment interactions influencing intelligence**.
856 856  3. Explore **historical selection pressures shaping intelligence-related alleles**.
857 857  
858 -----
525 +---
859 859  
860 860  ## **Summary of Research Study**
861 -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.  ##
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.
862 862  
863 863  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
864 864  
865 -----
532 +---
866 866  
867 867  ## **📄 Download Full Study**
868 -[[Download Full Study>>attach:10.1016_j.intell.2015.08.008.pdf]]##
869 -{{/expand}}
535 +[[Download Full Study>>attach:10.1016_j.intell.2015.08.008.pdf]]
870 870  
871 -
872 -== Study: Genetic Structure, Self-Identified Race/Ethnicity, and Confounding ==
873 -
874 -{{expand expanded="false" title="Click here to expand details"}}
875 -**Source:** Journal of Genetic Epidemiology
876 -**Date of Publication:** 2024-01-15
877 -**Author(s):** Smith et al.
878 -**Title:** "Genetic Structure, Self-Identified Race/Ethnicity, and Confounding in Case-Control Association Studies"
879 -**DOI:** [https://doi.org/10.1037/1076-8971.11.2.235](https://doi.org/10.1037/1076-8971.11.2.235)
880 -**Subject Matter:** Genetics, Social Science 
881 -
882 -**Tags:** `Genetics` `Race & Ethnicity` `Biomedical Research`
883 -
884 - **Key Statistics**
885 -
886 -1. **General Observations:**
887 - - A near-perfect alignment between self-identified race/ethnicity (SIRE) and genetic ancestry was observed.
888 - - Misclassification rate: **0.14%**.
889 -
890 -2. **Subgroup Analysis:**
891 - - Four groups analyzed: **White, African American, East Asian, and Hispanic**.
892 - - Hispanic genetic clusters showed significant European and Native American lineage.
893 -
894 - **Findings**
895 -
896 -- Self-identified race strongly aligns with genetic ancestry.
897 -- Minor discrepancies exist but do not significantly impact classification.
898 -
899 - **Relevance to Subproject**
900 -
901 -- Reinforces the reliability of **self-reported racial identity** in genetic research.
902 -- Highlights **policy considerations** in biomedical studies.
903 903  {{/expand}}
904 904  
539 +{{html}}<hr style="border: 3px solid red;">{{/html}}
905 905  
906 -----
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*
907 907  
908 -= Dating and Interpersonal Relationships =
549 +---
909 909  
910 -
911 -== Study: Trends in Frequency of Sexual Activity and Number of Sexual Partners Among Adults Aged 18 to 44 Years in the US, 2000-2018 ==
912 -
913 -{{expand expanded="false" title="Study: Trends in Frequency of Sexual Activity and Number of Sexual Partners Among Adults Aged 18 to 44 Years in the US, 2000-2018"}}
914 -**Source:** *JAMA Network Open*
915 -**Date of Publication:** *2020*
916 -**Author(s):** *Ueda P, Mercer CH, Ghaznavi C, Herbenick D.*
917 -**Title:** *"Trends in Frequency of Sexual Activity and Number of Sexual Partners Among Adults Aged 18 to 44 Years in the US, 2000-2018"*
918 -**DOI:** [10.1001/jamanetworkopen.2020.3833](https://doi.org/10.1001/jamanetworkopen.2020.3833)
919 -**Subject Matter:** *Public Health, Sexual Behavior, Demography* 
920 -
921 -----
922 -
923 -## **Key Statistics**##
924 -
551 +## **Key Statistics**
925 925  1. **General Observations:**
926 - - Study analyzed **General Social Survey (2000-2018)** data.
927 - - Found **declining trends in sexual activity** among young adults.
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.
928 928  
929 929  2. **Subgroup Analysis:**
930 - - Decreases in sexual activity were most prominent among **men aged 18-34**.
931 - - Factors like **marital status, employment, and psychological well-being** were associated with changes in sexual frequency.
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.
932 932  
933 933  3. **Other Significant Data Points:**
934 - - Frequency of sexual activity decreased by **8-10%** over the studied period.
935 - - Number of sexual partners remained **relatively stable** despite declining activity rates.
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**.
936 936  
937 -----
564 +---
938 938  
939 -## **Findings**##
940 -
566 +## **Findings**
941 941  1. **Primary Observations:**
942 - - A significant decline in sexual frequency, especially among **younger men**.
943 - - Shifts in relationship dynamics and economic stressors may contribute to the trend.
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.
944 944  
945 945  2. **Subgroup Trends:**
946 - - More pronounced decline among **unmarried individuals**.
947 - - No major change observed for **married adults** over time.
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.
948 948  
949 949  3. **Specific Case Analysis:**
950 - - **Mental health and employment status** were correlated with decreased activity.
951 - - Social factors such as **screen time and digital entertainment consumption** are potential contributors.
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.
952 952  
953 -----
579 +---
954 954  
955 -## **Critique and Observations**##
956 -
581 +## **Critique and Observations**
957 957  1. **Strengths of the Study:**
958 - - **Large sample size** from a nationally representative dataset.
959 - - **Longitudinal design** enables trend analysis over time.
583 + - **Largest expert survey on intelligence research** to date.
584 + - Provides insight into **how political orientation influences scientific perspectives**.
960 960  
961 961  2. **Limitations of the Study:**
962 - - Self-reported data may introduce **response bias**.
963 - - No direct causal mechanisms tested for the decline in sexual activity.
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**.
964 964  
965 965  3. **Suggestions for Improvement:**
966 - - Further studies should incorporate **qualitative data** on behavioral shifts.
967 - - Additional factors such as **economic shifts and social media usage** need exploration.
591 + - Future studies should include **a broader range of global experts**.
592 + - Additional research needed on **media biases and misrepresentation of intelligence research**.
968 968  
969 -----
594 +---
970 970  
971 971  ## **Relevance to Subproject**
972 -- Provides evidence on **changing demographic behaviors** in relation to relationships and social interactions.
973 -- Highlights the role of **mental health, employment, and societal changes** in personal behaviors.##
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.
974 974  
975 -----
601 +---
976 976  
977 -## **Suggestions for Further Exploration**##
603 +## **Suggestions for Further Exploration**
604 +1. Examine **cross-national differences** in expert opinions on intelligence.
605 +2. Investigate how **media bias impacts public understanding of intelligence research**.
606 +3. Conduct follow-up studies with **a more diverse expert pool** to test findings.
978 978  
979 -1. Investigate the **impact of digital media consumption** on relationship dynamics.
980 -2. Examine **regional and cultural differences** in sexual activity trends.
608 +---
981 981  
982 -----
983 -
984 984  ## **Summary of Research Study**
985 -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.  ##
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**.
986 986  
987 -This summary provides an accessible, at-a-glance overview of the study's contributions. Please refer to the full paper for in-depth analysis.
613 +This summary provides an accessible, at-a-glance overview of the studys contributions. Please refer to the full paper for in-depth analysis.
988 988  
989 -----
615 +---
990 990  
991 991  ## **📄 Download Full Study**
992 -{{velocity}}
993 -#set($doi = "10.1001_jamanetworkopen.2020.3833")
994 -#set($filename = "${doi}.pdf")
995 -#if($xwiki.exists("attach:$filename"))
996 -[[Download>>attach:$filename]]
997 -#else
998 -{{html}}<span style="color: red; font-weight: bold;">🚨 PDF Not Available 🚨</span>{{/html}}
999 -#end {{/velocity}}##
1000 -{{/expand}}
618 +[[Download Full Study>>attach:10.1016_j.intell.2019.101406.pdf]]
1001 1001  
1002 -
1003 -== Study: Biracial Couples and Adverse Birth Outcomes – A Systematic Review and Meta-Analysis ==
1004 -
1005 -{{expand expanded="false" title="Study: Biracial Couples and Adverse Birth Outcomes – A Systematic Review and Meta-Analysis"}}
1006 -**Source:** *Acta Obstetricia et Gynecologica Scandinavica*
1007 -**Date of Publication:** *2012*
1008 -**Author(s):** *Ravisha M. Srinivasjois, Shreya Shah, Prakesh S. Shah, Knowledge Synthesis Group on Determinants of Preterm/LBW Births*
1009 -**Title:** *"Biracial Couples and Adverse Birth Outcomes: A Systematic Review and Meta-Analysis"*
1010 -**DOI:** [10.1111/j.1600-0412.2012.01501.x](https://doi.org/10.1111/j.1600-0412.2012.01501.x)
1011 -**Subject Matter:** *Neonatal Health, Maternal-Fetal Medicine, Racial Disparities* 
1012 -
1013 -----
1014 -
1015 -## **Key Statistics**##
1016 -
1017 -1. **General Observations:**
1018 - - Meta-analysis of **26,335,596 singleton births** from eight studies.
1019 - - **Higher risk of adverse birth outcomes in biracial couples** than White couples, but lower than Black couples.
1020 -
1021 -2. **Subgroup Analysis:**
1022 - - **Maternal race had a stronger influence than paternal race** on birth outcomes.
1023 - - **Black mother–White father (BMWF) couples** had a higher risk than **White mother–Black father (WMBF) couples**.
1024 -
1025 -3. **Other Significant Data Points:**
1026 - - **Adjusted Odds Ratios (aORs) for key outcomes:**
1027 - - **Low birthweight (LBW):** WMBF (1.21), BMWF (1.75), Black mother–Black father (BMBF) (2.08).
1028 - - **Preterm births (PTB):** WMBF (1.17), BMWF (1.37), BMBF (1.78).
1029 - - **Stillbirths:** WMBF (1.43), BMWF (1.51), BMBF (1.85).
1030 -
1031 -----
1032 -
1033 -## **Findings**##
1034 -
1035 -1. **Primary Observations:**
1036 - - **Biracial couples face a gradient of risk**: higher than White couples but lower than Black couples.
1037 - - **Maternal race plays a more significant role** in pregnancy outcomes.
1038 -
1039 -2. **Subgroup Trends:**
1040 - - **Black mothers (regardless of paternal race) had the highest risk of LBW and PTB**.
1041 - - **White mothers with Black fathers had a lower risk** than Black mothers with White fathers.
1042 -
1043 -3. **Specific Case Analysis:**
1044 - - The **weathering hypothesis** suggests that **long-term stress exposure** contributes to higher adverse birth risks in Black mothers.
1045 - - **Genetic and environmental factors** may interact to influence birth outcomes.
1046 -
1047 -----
1048 -
1049 -## **Critique and Observations**##
1050 -
1051 -1. **Strengths of the Study:**
1052 - - **Largest meta-analysis** on racial disparities in birth outcomes.
1053 - - Uses **adjusted statistical models** to account for confounding variables.
1054 -
1055 -2. **Limitations of the Study:**
1056 - - Data limited to **Black-White biracial couples**, excluding other racial groups.
1057 - - **Socioeconomic and healthcare access factors** not fully explored.
1058 -
1059 -3. **Suggestions for Improvement:**
1060 - - Future studies should examine **Asian, Hispanic, and Indigenous biracial couples**.
1061 - - Investigate **long-term health effects on infants from biracial pregnancies**.
1062 -
1063 -----
1064 -
1065 -## **Relevance to Subproject**
1066 -- Provides **critical insights into racial disparities** in maternal and infant health.
1067 -- Supports **research on genetic and environmental influences on neonatal health**.
1068 -- Highlights **how maternal race plays a more significant role than paternal race** in birth outcomes.##
1069 -
1070 -----
1071 -
1072 -## **Suggestions for Further Exploration**##
1073 -
1074 -1. Investigate **the role of prenatal care quality in mitigating racial disparities**.
1075 -2. Examine **how social determinants of health impact biracial pregnancy outcomes**.
1076 -3. Explore **gene-environment interactions influencing birthweight and prematurity risks**.
1077 -
1078 -----
1079 -
1080 -## **Summary of Research Study**
1081 -This meta-analysis examines **the impact of biracial parentage on birth outcomes**, showing that **biracial couples face a higher risk of adverse pregnancy outcomes than White couples but lower than Black couples**. The findings emphasize **maternal race as a key factor in birth risks**, with **Black mothers having the highest rates of preterm birth and low birthweight, regardless of paternal race**.##
1082 -
1083 -----
1084 -
1085 -## **📄 Download Full Study**
1086 -[[Download Full Study>>attach:10.1111_j.1600-0412.2012.01501.xAbstract.pdf]]##
1087 1087  {{/expand}}
1088 1088  
622 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1089 1089  
1090 -== Study: One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness ==
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*
1091 1091  
1092 -{{expand expanded="false" title="Study: One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness"}}
1093 -**Source:** *Current Psychology*
1094 -**Date of Publication:** *2024*
1095 -**Author(s):** *Brandon Sparks, Alexandra M. Zidenberg, Mark E. Olver*
1096 -**Title:** *"One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness"*
1097 -**DOI:** [10.1007/s12144-023-04275-z](https://doi.org/10.1007/s12144-023-04275-z)
1098 -**Subject Matter:** *Psychology, Mental Health, Social Isolation* 
632 +---
1099 1099  
1100 -----
1101 -
1102 -## **Key Statistics**##
1103 -
634 +## **Key Statistics**
1104 1104  1. **General Observations:**
1105 - - Study analyzed **67 self-identified incels** and **103 non-incel men**.
1106 - - Incels reported **higher loneliness and lower social support** compared to non-incels.
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.
1107 1107  
1108 1108  2. **Subgroup Analysis:**
1109 - - Incels exhibited **higher levels of depression, anxiety, and self-critical rumination**.
1110 - - **Social isolation was a key factor** differentiating incels from non-incels.
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**.
1111 1111  
1112 1112  3. **Other Significant Data Points:**
1113 - - 95% of incels in the study reported **having depression**, with 38% receiving a formal diagnosis.
1114 - - **Higher externalization of blame** was linked to stronger incel identification.
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.
1115 1115  
1116 -----
647 +---
1117 1117  
1118 -## **Findings**##
1119 -
649 +## **Findings**
1120 1120  1. **Primary Observations:**
1121 - - Incels experience **heightened rejection sensitivity and loneliness**.
1122 - - Lack of social support correlates with **worse mental health outcomes**.
651 + - Proposes that **modern human populations meet biological criteria for subspecies classification**.
652 + - Highlights **medical and evolutionary implications** of human taxonomic diversity.
1123 1123  
1124 1124  2. **Subgroup Trends:**
1125 - - **Avoidant attachment styles** were a strong predictor of incel identity.
1126 - - **Mate value perceptions** significantly differed between incels and non-incels.
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.
1127 1127  
1128 1128  3. **Specific Case Analysis:**
1129 - - Incels **engaged in fewer positive coping mechanisms** such as emotional support or positive reframing.
1130 - - Instead, they relied on **solitary coping strategies**, worsening their isolation.
659 + - Evaluates how **genetic markers correlate with population structure**.
660 + - Addresses the **controversy over race classification in modern anthropology**.
1131 1131  
1132 -----
662 +---
1133 1133  
1134 -## **Critique and Observations**##
1135 -
664 +## **Critique and Observations**
1136 1136  1. **Strengths of the Study:**
1137 - - **First quantitative study** on incels social isolation and mental health.
1138 - - **Robust sample size** and validated psychological measures.
666 + - Uses **comparative species analysis** to assess human classification.
667 + - Provides a **biological perspective** on the race concept, moving beyond social constructivism arguments.
1139 1139  
1140 1140  2. **Limitations of the Study:**
1141 - - Sample drawn from **Reddit communities**, which may not represent all incels.
1142 - - **No causal conclusions**—correlations between isolation and inceldom need further research.
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.
1143 1143  
1144 1144  3. **Suggestions for Improvement:**
1145 - - Future studies should **compare incel forum users vs. non-users**.
1146 - - Investigate **potential intervention strategies** for social integration.
674 + - Further research should **incorporate whole-genome studies** to refine subspecies classifications.
675 + - Investigate **how admixture affects taxonomic classification over time**.
1147 1147  
1148 -----
677 +---
1149 1149  
1150 1150  ## **Relevance to Subproject**
1151 -- Highlights **mental health vulnerabilities** within the incel community.
1152 -- Supports research on **loneliness, attachment styles, and social dominance orientation**.
1153 -- Examines how **peer rejection influences self-perceived mate value**.##
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**.
1154 1154  
1155 -----
684 +---
1156 1156  
1157 -## **Suggestions for Further Exploration**##
686 +## **Suggestions for Further Exploration**
687 +1. Examine **FST values in modern and ancient human populations**.
688 +2. Investigate how **adaptive evolution influences population differentiation**.
689 +3. Explore **the impact of genetic diversity on medical treatments and disease susceptibility**.
1158 1158  
1159 -1. Explore how **online community participation** affects incel mental health.
1160 -2. Investigate **cognitive biases** influencing self-perceived rejection among incels.
1161 -3. Assess **therapeutic interventions** to address incel social isolation.
691 +---
1162 1162  
1163 -----
1164 -
1165 1165  ## **Summary of Research Study**
1166 -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**.##
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**.
1167 1167  
1168 1168  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1169 1169  
1170 -----
698 +---
1171 1171  
1172 1172  ## **📄 Download Full Study**
1173 -[[Download Full Study>>attach:10.1007_s12144-023-04275-z.pdf]]##
1174 -{{/expand}}
701 +[[Download Full Study>>attach:10.1016_j.mehy.2009.07.046.pdf]]
1175 1175  
1176 -
1177 -= Crime and Substance Abuse =
1178 -
1179 -
1180 -== Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program ==
1181 -
1182 -{{expand expanded="false" title="Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program"}}
1183 -**Source:** *Substance Use & Misuse*
1184 -**Date of Publication:** *2002*
1185 -**Author(s):** *Clifford A. Butzin, Christine A. Saum, Frank R. Scarpitti*
1186 -**Title:** *"Factors Associated with Completion of a Drug Treatment Court Diversion Program"*
1187 -**DOI:** [10.1081/JA-120014424](https://doi.org/10.1081/JA-120014424)
1188 -**Subject Matter:** *Substance Use, Criminal Justice, Drug Courts* 
1189 -
1190 -----
1191 -
1192 -## **Key Statistics**##
1193 -
1194 -1. **General Observations:**
1195 - - Study examined **drug treatment court success rates** among first-time offenders.
1196 - - Strongest predictors of **successful completion were employment status and race**.
1197 -
1198 -2. **Subgroup Analysis:**
1199 - - Individuals with **stable jobs were more likely to complete the program**.
1200 - - **Black participants had lower success rates**, suggesting potential systemic disparities.
1201 -
1202 -3. **Other Significant Data Points:**
1203 - - **Education level was positively correlated** with program completion.
1204 - - Frequency of **drug use before enrollment affected treatment outcomes**.
1205 -
1206 -----
1207 -
1208 -## **Findings**##
1209 -
1210 -1. **Primary Observations:**
1211 - - **Social stability factors** (employment, education) were key to treatment success.
1212 - - **Race and pre-existing substance use patterns** influenced completion rates.
1213 -
1214 -2. **Subgroup Trends:**
1215 - - White offenders had **higher completion rates** than Black offenders.
1216 - - Drug court success was **higher for those with lower initial drug use frequency**.
1217 -
1218 -3. **Specific Case Analysis:**
1219 - - **Individuals with strong social ties were more likely to finish the program**.
1220 - - Success rates were **significantly higher for participants with case management support**.
1221 -
1222 -----
1223 -
1224 -## **Critique and Observations**##
1225 -
1226 -1. **Strengths of the Study:**
1227 - - **First empirical study on drug court program success factors**.
1228 - - Uses **longitudinal data** for post-treatment analysis.
1229 -
1230 -2. **Limitations of the Study:**
1231 - - Lacks **qualitative data on personal motivation and treatment engagement**.
1232 - - Focuses on **short-term program success** without tracking **long-term relapse rates**.
1233 -
1234 -3. **Suggestions for Improvement:**
1235 - - Future research should examine **racial disparities in drug court outcomes**.
1236 - - Study **how community resources impact long-term recovery**.
1237 -
1238 -----
1239 -
1240 -## **Relevance to Subproject**
1241 -- Provides insight into **what factors contribute to drug court program success**.
1242 -- Highlights **racial disparities in criminal justice-based rehabilitation programs**.
1243 -- Supports **policy discussions on improving access to drug treatment for marginalized groups**.##
1244 -
1245 -----
1246 -
1247 -## **Suggestions for Further Exploration**##
1248 -
1249 -1. Investigate **the role of mental health in drug court success rates**.
1250 -2. Assess **long-term relapse prevention strategies post-treatment**.
1251 -3. Explore **alternative diversion programs beyond traditional drug courts**.
1252 -
1253 -----
1254 -
1255 -## **Summary of Research Study**
1256 -This study examines **factors influencing the completion of drug treatment court programs**, identifying **employment, education, and race as key predictors**. The research underscores **systemic disparities in drug court outcomes**, emphasizing the need for **improved support systems for at-risk populations**.##
1257 -
1258 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1259 -
1260 -----
1261 -
1262 -## **📄 Download Full Study**
1263 -[[Download Full Study>>attach:10.1081_JA-120014424.pdf]]##
1264 1264  {{/expand}}
1265 1265  
705 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1266 1266  
1267 -== Study: Cross-Cultural Sources of Measurement Error in Substance Use Surveys ==
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*
1268 1268  
1269 -{{expand expanded="false" title="Study: Cross-Cultural Sources of Measurement Error in Substance Use Surveys"}}
1270 -**Source:** *Substance Use & Misuse*
1271 -**Date of Publication:** *2003*
1272 -**Author(s):** *Timothy P. Johnson, Phillip J. Bowman*
1273 -**Title:** *"Cross-Cultural Sources of Measurement Error in Substance Use Surveys"*
1274 -**DOI:** [10.1081/JA-120023394](https://doi.org/10.1081/JA-120023394)
1275 -**Subject Matter:** *Survey Methodology, Racial Disparities, Substance Use Research* 
715 +---
1276 1276  
1277 -----
1278 -
1279 -## **Key Statistics**##
1280 -
717 +## **Key Statistics**
1281 1281  1. **General Observations:**
1282 - - Study examined **how racial and cultural factors influence self-reported substance use data**.
1283 - - Analyzed **36 empirical studies from 1977–2003** on survey reliability across racial/ethnic groups.
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**.
1284 1284  
1285 1285  2. **Subgroup Analysis:**
1286 - - Black and Latino respondents **were more likely to underreport drug use** compared to White respondents.
1287 - - **Cultural stigma and distrust in research institutions** affected self-report accuracy.
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**.
1288 1288  
1289 1289  3. **Other Significant Data Points:**
1290 - - **Surveys using biological validation (urinalysis, hair tests) revealed underreporting trends**.
1291 - - **Higher recantation rates** (denying past drug use) were observed among minority respondents.
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**.
1292 1292  
1293 -----
730 +---
1294 1294  
1295 -## **Findings**##
1296 -
732 +## **Findings**
1297 1297  1. **Primary Observations:**
1298 - - Racial/ethnic disparities in **substance use reporting bias survey-based research**.
1299 - - **Social desirability and cultural norms impact data reliability**.
734 + - Intelligence heritability **strengthens throughout development**, contrary to early environmental models.
735 + - Shared environmental effects **decrease by late adolescence**, emphasizing **genetic influence in adulthood**.
1300 1300  
1301 -2. **Subgroup Trends:**
1302 - - White respondents were **more likely to overreport** substance use.
1303 - - Black and Latino respondents **had higher recantation rates**, particularly in face-to-face interviews.
1304 -
1305 -3. **Specific Case Analysis:**
1306 - - Mode of survey administration **significantly influenced reporting accuracy**.
1307 - - **Self-administered surveys produced more reliable data than interviewer-administered surveys**.
1308 -
1309 -----
1310 -
1311 -## **Critique and Observations**##
1312 -
1313 -1. **Strengths of the Study:**
1314 - - **Comprehensive review of 36 studies** on measurement error in substance use reporting.
1315 - - Identifies **systemic biases affecting racial/ethnic survey reliability**.
1316 -
1317 -2. **Limitations of the Study:**
1318 - - Relies on **secondary data analysis**, limiting direct experimental control.
1319 - - Does not explore **how measurement error impacts policy decisions**.
1320 -
1321 -3. **Suggestions for Improvement:**
1322 - - Future research should **incorporate mixed-method approaches** (qualitative & quantitative).
1323 - - Investigate **how survey design can reduce racial reporting disparities**.
1324 -
1325 -----
1326 -
1327 -## **Relevance to Subproject**
1328 -- Supports research on **racial disparities in self-reported health behaviors**.
1329 -- Highlights **survey methodology issues that impact substance use epidemiology**.
1330 -- Provides insights for **improving data accuracy in public health research**.##
1331 -
1332 -----
1333 -
1334 -## **Suggestions for Further Exploration**##
1335 -
1336 -1. Investigate **how survey design impacts racial disparities in self-reported health data**.
1337 -2. Study **alternative data collection methods (biometric validation, passive data tracking)**.
1338 -3. Explore **the role of social stigma in self-reported health behaviors**.
1339 -
1340 -----
1341 -
1342 -## **Summary of Research Study**
1343 -This study examines **cross-cultural biases in self-reported substance use surveys**, showing that **racial/ethnic minorities are more likely to underreport drug use** due to **social stigma, research distrust, and survey administration methods**. The findings highlight **critical issues in public health data collection and the need for improved survey design**.##
1344 -
1345 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1346 -
1347 -----
1348 -
1349 -## **📄 Download Full Study**
1350 -[[Download Full Study>>attach:10.1081_JA-120023394.pdf]]##
1351 -{{/expand}}
1352 -
1353 -
1354 -== Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program ==
1355 -
1356 -{{expand expanded="false" title="Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program"}}
1357 -**Source:** *Substance Use & Misuse*
1358 -**Date of Publication:** *2002*
1359 -**Author(s):** *Clifford A. Butzin, Christine A. Saum, Frank R. Scarpitti*
1360 -**Title:** *"Factors Associated with Completion of a Drug Treatment Court Diversion Program"*
1361 -**DOI:** [10.1081/JA-120014424](https://doi.org/10.1081/JA-120014424)
1362 -**Subject Matter:** *Substance Use, Criminal Justice, Drug Courts* 
1363 -
1364 -----
1365 -
1366 -## **Key Statistics**##
1367 -
1368 -1. **General Observations:**
1369 - - Study examined **drug treatment court success rates** among first-time offenders.
1370 - - Strongest predictors of **successful completion were employment status and race**.
1371 -
1372 -2. **Subgroup Analysis:**
1373 - - Individuals with **stable jobs were more likely to complete the program**.
1374 - - **Black participants had lower success rates**, suggesting potential systemic disparities.
1375 -
1376 -3. **Other Significant Data Points:**
1377 - - **Education level was positively correlated** with program completion.
1378 - - Frequency of **drug use before enrollment affected treatment outcomes**.
1379 -
1380 -----
1381 -
1382 -## **Findings**##
1383 -
1384 -1. **Primary Observations:**
1385 - - **Social stability factors** (employment, education) were key to treatment success.
1386 - - **Race and pre-existing substance use patterns** influenced completion rates.
1387 -
1388 1388  2. **Subgroup Trends:**
1389 - - White offenders had **higher completion rates** than Black offenders.
1390 - - 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**.
1391 1391  
1392 1392  3. **Specific Case Analysis:**
1393 - - **Individuals with strong social ties were more likely to finish the program**.
1394 - - Success rates were **significantly higher for participants with case management support**.
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**.
1395 1395  
1396 -----
745 +---
1397 1397  
1398 -## **Critique and Observations**##
1399 -
747 +## **Critique and Observations**
1400 1400  1. **Strengths of the Study:**
1401 - - **First empirical study on drug court program success factors**.
1402 - - 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.
1403 1403  
1404 1404  2. **Limitations of the Study:**
1405 - - Lacks **qualitative data on personal motivation and treatment engagement**.
1406 - - 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.
1407 1407  
1408 1408  3. **Suggestions for Improvement:**
1409 - - Future research should examine **racial disparities in drug court outcomes**.
1410 - - Study **how community resources impact long-term recovery**.
757 + - Future research should investigate **gene-environment interactions in cognitive aging**.
758 + - Examine **heritability trends in non-Western populations** to determine cross-cultural consistency.
1411 1411  
1412 -----
760 +---
1413 1413  
1414 1414  ## **Relevance to Subproject**
1415 -- Provides insight into **what factors contribute to drug court program success**.
1416 -- Highlights **racial disparities in criminal justice-based rehabilitation programs**.
1417 -- Supports **policy discussions on improving access to drug treatment for marginalized groups**.##
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**.
1418 1418  
1419 -----
767 +---
1420 1420  
1421 -## **Suggestions for Further Exploration**##
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**.
1422 1422  
1423 -1. Investigate **the role of mental health in drug court success rates**.
1424 -2. Assess **long-term relapse prevention strategies post-treatment**.
1425 -3. Explore **alternative diversion programs beyond traditional drug courts**.
774 +---
1426 1426  
1427 -----
1428 -
1429 1429  ## **Summary of Research Study**
1430 -This study examines **factors influencing the completion of drug treatment court programs**, identifying **employment, education, and race as key predictors**. The research underscores **systemic disparities in drug court outcomes**, emphasizing the need for **improved support systems for at-risk populations**.##
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**.
1431 1431  
1432 1432  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1433 1433  
1434 -----
781 +---
1435 1435  
1436 1436  ## **📄 Download Full Study**
1437 -[[Download Full Study>>attach:10.1081_JA-120014424.pdf]]##
1438 -{{/expand}}
784 +[[Download Full Study>>attach:10.1017_thg.2013.54.pdf]]
1439 1439  
1440 -
1441 -== Study: Associations Between Cannabis Use and Mental Health Symptoms in Young Adults ==
1442 -
1443 -{{expand expanded="false" title="Study: Associations Between Cannabis Use and Mental Health Symptoms in Young Adults"}}
1444 - Source: Addictive Behaviors
1445 -Date of Publication: 2016
1446 -Author(s): Andrea Hussong, Christy Capron, Gregory T. Smith, Jennifer L. Maggs
1447 -Title: "Associations Between Cannabis Use and Mental Health Symptoms in Young Adults"
1448 -DOI: 10.1016/j.addbeh.2016.02.030
1449 -Subject Matter: Substance Use, Mental Health, Adolescent Development
1450 -
1451 -Key Statistics
1452 -General Observations:
1453 -
1454 -Study examined cannabis use trends in young adults over time.
1455 -Found significant correlations between cannabis use and increased depressive symptoms.
1456 -Subgroup Analysis:
1457 -
1458 -Males exhibited higher rates of cannabis use, but females reported stronger mental health impacts.
1459 -Individuals with pre-existing anxiety disorders were more likely to report problematic cannabis use.
1460 -Other Significant Data Points:
1461 -
1462 -Frequent cannabis users showed a 23% higher likelihood of developing anxiety symptoms.
1463 -Co-occurring substance use (e.g., alcohol) exacerbated negative psychological effects.
1464 -Findings
1465 -Primary Observations:
1466 -
1467 -Cannabis use was linked to higher depressive and anxiety symptoms, particularly in frequent users.
1468 -Self-medication patterns emerged among those with pre-existing mental health conditions.
1469 -Subgroup Trends:
1470 -
1471 -Early cannabis initiation (before age 16) was associated with greater mental health risks.
1472 -College-aged users reported more impairments in daily functioning due to cannabis use.
1473 -Specific Case Analysis:
1474 -
1475 -Participants with a history of childhood trauma were twice as likely to develop problematic cannabis use.
1476 -Co-use of cannabis and alcohol significantly increased impulsivity scores in the study sample.
1477 -Critique and Observations
1478 -Strengths of the Study:
1479 -
1480 -Large, longitudinal dataset with a diverse sample of young adults.
1481 -Controlled for confounding variables like socioeconomic status and prior substance use.
1482 -Limitations of the Study:
1483 -
1484 -Self-reported cannabis use may introduce bias in reported frequency and effects.
1485 -Did not assess specific THC potency levels, which could influence mental health outcomes.
1486 -Suggestions for Improvement:
1487 -
1488 -Future research should investigate dose-dependent effects of cannabis on mental health.
1489 -Assess long-term psychological outcomes of early cannabis exposure.
1490 -Relevance to Subproject
1491 -Supports mental health risk assessment models related to substance use.
1492 -Highlights gender differences in substance-related psychological impacts.
1493 -Provides insight into self-medication behaviors among young adults.
1494 -Suggestions for Further Exploration
1495 -Investigate the long-term impact of cannabis use on neurodevelopment.
1496 -Examine the role of genetic predisposition in cannabis-related mental health risks.
1497 -Assess regional differences in cannabis use trends post-legalization.
1498 -Summary of Research Study
1499 -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.
1500 -
1501 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1502 -
1503 -📄 Download Full Study
1504 -[[Download Full Study>>attach:10.1016_j.addbeh.2016.02.030.pdf]]
1505 1505  {{/expand}}
1506 1506  
788 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1507 1507  
1508 -== Study: Is there a Dysgenic Secular Trend Towards Slowing Simple Reaction Time? ==
1509 -
1510 -{{expand expanded="false" title="Study: Is there a Dysgenic Secular Trend Towards Slowing Simple Reaction Time?"}}
1511 -**Source:** *Intelligence (Elsevier)*
1512 -**Date of Publication:** *2014*
1513 -**Author(s):** *Michael A. Woodley, Jan te Nijenhuis, Raegan Murphy*
1514 -**Title:** *"Is there a Dysgenic Secular Trend Towards Slowing Simple Reaction Time?"*
1515 -**DOI:** [10.1016/j.intell.2014.05.012](https://doi.org/10.1016/j.intell.2014.05.012)
1516 -**Subject Matter:** *Cognitive Decline, Intelligence, Dysgenics* 
1517 -
1518 -----
1519 -
1520 -## **Key Statistics**##
1521 -
1522 -1. **General Observations:**
1523 - - The study examines reaction time data from **13 age-matched studies** spanning **1884–2004**.
1524 - - Results suggest an estimated **decline of 13.35 IQ points** over this period.
1525 -
1526 -2. **Subgroup Analysis:**
1527 - - The study found **slower reaction times in modern populations** compared to Victorian-era individuals.
1528 - - Data from **Western countries (US, UK, Canada, Australia, Finland)** were analyzed.
1529 -
1530 -3. **Other Significant Data Points:**
1531 - - The estimated **dysgenic rate is 1.21 IQ points lost per decade**.
1532 - - Meta-regression analysis confirmed a **steady secular trend in slowing reaction time**.
1533 -
1534 -----
1535 -
1536 -## **Findings**##
1537 -
1538 -1. **Primary Observations:**
1539 - - Supports the hypothesis of **intelligence decline due to genetic and environmental factors**.
1540 - - Reaction time, a **biomarker for cognitive ability**, has slowed significantly over time.
1541 -
1542 -2. **Subgroup Trends:**
1543 - - A stronger **correlation between slower reaction time and lower general intelligence (g)**.
1544 - - Flynn effect (IQ gains) does not contradict this finding, as reaction time is a **biological, not environmental, measure**.
1545 -
1546 -3. **Specific Case Analysis:**
1547 - - Cross-national comparisons indicate a **global trend in slower reaction times**.
1548 - - Factors like **modern neurotoxin exposure** and **reduced selective pressure for intelligence** may contribute.
1549 -
1550 -----
1551 -
1552 -## **Critique and Observations**##
1553 -
1554 -1. **Strengths of the Study:**
1555 - - **Comprehensive meta-analysis** covering over a century of reaction time data.
1556 - - **Robust statistical corrections** for measurement variance between historical and modern studies.
1557 -
1558 -2. **Limitations of the Study:**
1559 - - Some historical data sources **lack methodological consistency**.
1560 - - **Reaction time measurements vary by study**, requiring adjustments for equipment differences.
1561 -
1562 -3. **Suggestions for Improvement:**
1563 - - Future studies should **replicate results with more modern datasets**.
1564 - - Investigate **alternative cognitive biomarkers** for intelligence over time.
1565 -
1566 -----
1567 -
1568 -## **Relevance to Subproject**
1569 -- Provides evidence for **long-term intelligence trends**, contributing to research on **cognitive evolution**.
1570 -- Aligns with broader discussions on **dysgenics, neurophysiology, and cognitive load**.
1571 -- Supports the argument that **modern societies may be experiencing intelligence decline**.##
1572 -
1573 -----
1574 -
1575 -## **Suggestions for Further Exploration**##
1576 -
1577 -1. Investigate **genetic markers associated with reaction time** and intelligence decline.
1578 -2. Examine **regional variations in reaction time trends**.
1579 -3. Explore **cognitive resilience factors that counteract the decline**.
1580 -
1581 -----
1582 -
1583 -## **Summary of Research Study**
1584 -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**.  ##
1585 -
1586 -This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1587 -
1588 -----
1589 -
1590 -## **📄 Download Full Study**
1591 -[[Download Full Study>>attach:10.1016_j.intell.2014.05.012.pdf]]##
1592 -{{/expand}}
1593 -
1594 -
1595 -= Whiteness & White Guilt =
1596 -
1597 -== Study: Segregation, Innocence, and Protection: The Institutional Conditions That Maintain Whiteness in College Sports ==
1598 -
1599 -{{expand expanded="false" title="Study: Segregation, Innocence, and Protection: The Institutional Conditions That Maintain Whiteness in College Sports"}}
790 +{{expand title="Study: Segregation, Innocence, and Protection: The Institutional Conditions That Maintain Whiteness in College Sports" expanded="false"}}
1600 1600  **Source:** *Journal of Diversity in Higher Education*
1601 1601  **Date of Publication:** *2019*
1602 1602  **Author(s):** *Kirsten Hextrum*
1603 1603  **Title:** *"Segregation, Innocence, and Protection: The Institutional Conditions That Maintain Whiteness in College Sports"*
1604 1604  **DOI:** [10.1037/dhe0000140](https://doi.org/10.1037/dhe0000140)
1605 -**Subject Matter:** *Race and Sports, Higher Education, Institutional Racism* 
796 +**Subject Matter:** *Race and Sports, Higher Education, Institutional Racism*
1606 1606  
1607 -----
798 +---
1608 1608  
1609 -## **Key Statistics**##
1610 -
800 +## **Key Statistics**
1611 1611  1. **General Observations:**
1612 1612   - Analyzed **47 college athlete narratives** to explore racial disparities in non-revenue sports.
1613 1613   - Found three interrelated themes: **racial segregation, racial innocence, and racial protection**.
... ... @@ -1620,10 +1620,9 @@
1620 1620   - White athletes are **socialized to remain unaware of racial privilege** in their athletic careers.
1621 1621   - Media and institutional narratives protect white athletes from discussions on race and systemic inequities.
1622 1622  
1623 -----
813 +---
1624 1624  
1625 -## **Findings**##
1626 -
815 +## **Findings**
1627 1627  1. **Primary Observations:**
1628 1628   - Colleges **actively recruit white athletes** from majority-white communities.
1629 1629   - Institutional policies **uphold whiteness** by failing to challenge racial biases in recruitment and team culture.
... ... @@ -1636,10 +1636,9 @@
1636 1636   - Examines **how sports serve as a mechanism for maintaining racial privilege** in higher education.
1637 1637   - Discusses the **role of athletics in reinforcing systemic segregation and exclusion**.
1638 1638  
1639 -----
828 +---
1640 1640  
1641 -## **Critique and Observations**##
1642 -
830 +## **Critique and Observations**
1643 1643  1. **Strengths of the Study:**
1644 1644   - **Comprehensive qualitative analysis** of race in college sports.
1645 1645   - Examines **institutional conditions** that sustain racial disparities in athletics.
... ... @@ -1652,549 +1652,451 @@
1652 1652   - Future research should **compare recruitment policies across different sports and divisions**.
1653 1653   - Investigate **how athletic scholarships contribute to racial inequities in higher education**.
1654 1654  
1655 -----
843 +---
1656 1656  
1657 1657  ## **Relevance to Subproject**
1658 1658  - Provides evidence of **systemic racial biases** in college sports recruitment.
1659 1659  - Highlights **how institutional policies protect whiteness** in non-revenue athletics.
1660 -- Supports research on **diversity, equity, and inclusion (DEI) efforts in sports and education**.##
848 +- Supports research on **diversity, equity, and inclusion (DEI) efforts in sports and education**.
1661 1661  
1662 -----
850 +---
1663 1663  
1664 -## **Suggestions for Further Exploration**##
1665 -
852 +## **Suggestions for Further Exploration**
1666 1666  1. Investigate how **racial stereotypes influence college athlete recruitment**.
1667 1667  2. Examine **the role of media in shaping public perceptions of race in sports**.
1668 1668  3. Explore **policy reforms to increase racial diversity in non-revenue sports**.
1669 1669  
1670 -----
857 +---
1671 1671  
1672 1672  ## **Summary of Research Study**
1673 -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**.##
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**.
1674 1674  
1675 1675  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1676 1676  
1677 -----
864 +---
1678 1678  
1679 1679  ## **📄 Download Full Study**
1680 -[[Download Full Study>>attach:10.1037_dhe0000140.pdf]]##
867 +[[Download Full Study>>attach:10.1037_dhe0000140.pdf]]
868 +
1681 1681  {{/expand}}
1682 1682  
871 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1683 1683  
1684 -== Study: Racial Bias in Pain Assessment and Treatment Recommendations ==
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*
1685 1685  
1686 -{{expand expanded="false" title="Study: Racial Bias in Pain Assessment and Treatment Recommendations"}}
1687 -**Source:** *Proceedings of the National Academy of Sciences (PNAS)*
1688 -**Date of Publication:** *2016*
1689 -**Author(s):** *Kelly M. Hoffman, Sophie Trawalter, Jordan R. Axta, M. Norman Oliver*
1690 -**Title:** *"Racial Bias in Pain Assessment and Treatment Recommendations, and False Beliefs About Biological Differences Between Blacks and Whites"*
1691 -**DOI:** [10.1073/pnas.1516047113](https://doi.org/10.1073/pnas.1516047113)
1692 -**Subject Matter:** *Health Disparities, Racial Bias, Medical Treatment* 
881 +---
1693 1693  
1694 -----
1695 -
1696 -## **Key Statistics**##
1697 -
883 +## **Key Statistics**
1698 1698  1. **General Observations:**
1699 - - Study analyzed **racial disparities in pain perception and treatment recommendations**.
1700 - - 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)**.
1701 1701  
1702 1702  2. **Subgroup Analysis:**
1703 - - **50% of medical students surveyed endorsed at least one false belief about biological differences**.
1704 - - 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**.
1705 1705  
1706 1706  3. **Other Significant Data Points:**
1707 - - **Black patients were less likely to receive appropriate pain treatment** compared to white patients.
1708 - - The study confirmed that **historical misconceptions about racial differences still persist in modern medicine**.
893 + - ANI ancestry ranges from **39% to 71%** across Indian groups.
894 + - **Caste and linguistic differences** strongly correlate with genetic variation.
1709 1709  
1710 -----
896 +---
1711 1711  
1712 -## **Findings**##
1713 -
898 +## **Findings**
1714 1714  1. **Primary Observations:**
1715 - - False beliefs about biological racial differences **correlate with racial disparities in pain treatment**.
1716 - - 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.
1717 1717  
1718 1718  2. **Subgroup Trends:**
1719 - - Physicians who **did not endorse these beliefs** showed **no racial bias** in treatment recommendations.
1720 - - 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**.
1721 1721  
1722 1722  3. **Specific Case Analysis:**
1723 - - Study participants **underestimated Black patients' pain and recommended less effective pain treatments**.
1724 - - The study suggests that **racial disparities in medical care stem, in part, from these enduring false beliefs**.
908 + - **Founder effects** have maintained allele frequency differences among Indian groups.
909 + - Predicts **higher incidence of recessive diseases** due to historical genetic isolation.
1725 1725  
1726 -----
911 +---
1727 1727  
1728 -## **Critique and Observations**##
1729 -
913 +## **Critique and Observations**
1730 1730  1. **Strengths of the Study:**
1731 - - **First empirical study to connect false racial beliefs with medical decision-making**.
1732 - - 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**.
1733 1733  
1734 1734  2. **Limitations of the Study:**
1735 - - The study focuses on **Black vs. white disparities**, leaving other racial/ethnic groups unexplored.
1736 - - 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.
1737 1737  
1738 1738  3. **Suggestions for Improvement:**
1739 - - Future research should examine **how these biases manifest in real clinical settings**.
1740 - - Investigate **whether medical training can correct these biases over time**.
923 + - Future research should **expand sampling across more Indian tribal groups**.
924 + - Use **whole-genome sequencing** for finer resolution of ancestry.
1741 1741  
1742 -----
926 +---
1743 1743  
1744 1744  ## **Relevance to Subproject**
1745 -- Highlights **racial disparities in healthcare**, specifically in pain assessment and treatment.
1746 -- Supports **research on implicit bias and its impact on medical outcomes**.
1747 -- Provides evidence for **the need to address racial bias in medical education**.##
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.
1748 1748  
1749 -----
933 +---
1750 1750  
1751 -## **Suggestions for Further Exploration**##
935 +## **Suggestions for Further Exploration**
936 +1. Examine **genetic markers linked to disease susceptibility** in Indian subpopulations.
937 +2. Investigate the impact of **recent migration patterns on ANI-ASI ancestry distribution**.
938 +3. Study **gene flow between Indian populations and other global groups**.
1752 1752  
1753 -1. Investigate **interventions to reduce racial bias in medical decision-making**.
1754 -2. Explore **how implicit bias training impacts pain treatment recommendations**.
1755 -3. Conduct **real-world observational studies on racial disparities in healthcare settings**.
940 +---
1756 1756  
1757 -----
1758 -
1759 1759  ## **Summary of Research Study**
1760 -This study examines **racial bias in pain perception and treatment** among **white laypeople and medical professionals**, demonstrating that **false beliefs about biological differences contribute to disparities in pain management**. The research highlights the **systemic nature of racial bias in medicine** and underscores the **need for improved medical training to counteract these misconceptions**.##
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**.
1761 1761  
1762 1762  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1763 1763  
1764 -----
947 +---
1765 1765  
1766 1766  ## **📄 Download Full Study**
1767 -[[Download Full Study>>attach:10.1073_pnas.1516047113.pdf]]##
950 +[[Download Full Study>>attach:10.1038_nature08365.pdf]]
951 +
1768 1768  {{/expand}}
1769 1769  
954 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1770 1770  
1771 -== Study: Rising Morbidity and Mortality in Midlife Among White Non-Hispanic Americans ==
1772 1772  
1773 -{{expand expanded="false" title="Study: Rising Morbidity and Mortality in Midlife Among White Non-Hispanic Americans"}}
1774 -**Source:** *Proceedings of the National Academy of Sciences (PNAS)*
1775 -**Date of Publication:** *2015*
1776 -**Author(s):** *Anne Case, Angus Deaton*
1777 -**Title:** *"Rising Morbidity and Mortality in Midlife Among White Non-Hispanic Americans in the 21st Century"*
1778 -**DOI:** [10.1073/pnas.1518393112](https://doi.org/10.1073/pnas.1518393112)
1779 -**Subject Matter:** *Public Health, Mortality, Socioeconomic Factors* 
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*
1780 1780  
1781 -----
965 +---
1782 1782  
1783 -## **Key Statistics**##
1784 -
967 +## **Key Statistics**
1785 1785  1. **General Observations:**
1786 - - Mortality rates among **middle-aged white non-Hispanic Americans (ages 45–54)** increased from 1999 to 2013.
1787 - - This reversal in mortality trends is unique to the U.S.; **no other wealthy country experienced a similar rise**.
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.
1788 1788  
1789 1789  2. **Subgroup Analysis:**
1790 - - The increase was **most pronounced among those with a high school education or less**.
1791 - - Hispanic and Black non-Hispanic mortality continued to decline over the same period.
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.
1792 1792  
1793 1793  3. **Other Significant Data Points:**
1794 - - Rising mortality was driven primarily by **suicide, drug and alcohol poisoning, and chronic liver disease**.
1795 - - Midlife morbidity increased as well, with more reports of **poor health, pain, and mental distress**.
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**.
1796 1796  
1797 -----
980 +---
1798 1798  
1799 -## **Findings**##
1800 -
982 +## **Findings**
1801 1801  1. **Primary Observations:**
1802 - - The rise in mortality is attributed to **substance abuse, economic distress, and deteriorating mental health**.
1803 - - The increase in **suicides and opioid overdoses parallels broader socioeconomic decline**.
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**.
1804 1804  
1805 1805  2. **Subgroup Trends:**
1806 - - The **largest mortality increases** occurred among **whites without a college degree**.
1807 - - Chronic pain, functional limitations, and self-reported mental distress **rose significantly in affected groups**.
988 + - **Lower heterozygosity in non-Africans** due to founder effects from migration bottlenecks.
989 + - **Denisovan ancestry in South Asians is higher than previously thought**.
1808 1808  
1809 1809  3. **Specific Case Analysis:**
1810 - - **Educational attainment was a major predictor of mortality trends**, with better-educated individuals experiencing lower mortality rates.
1811 - - Mortality among **white Americans with a college degree continued to decline**, resembling trends in other wealthy nations.
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**.
1812 1812  
1813 -----
995 +---
1814 1814  
1815 -## **Critique and Observations**##
1816 -
997 +## **Critique and Observations**
1817 1817  1. **Strengths of the Study:**
1818 - - **First major study to highlight rising midlife mortality among U.S. whites**.
1819 - - Uses **CDC and Census mortality data spanning over a decade**.
999 + - **Largest global genetic dataset** outside of the 1000 Genomes Project.
1000 + - High sequencing depth allows **more accurate identification of genetic variants**.
1820 1820  
1821 1821  2. **Limitations of the Study:**
1822 - - Does not establish **causality** between economic decline and increased mortality.
1823 - - Lacks **granular data on opioid prescribing patterns and regional differences**.
1003 + - **Limited sample sizes for some populations**, restricting generalizability.
1004 + - Lacks ancient DNA comparisons, making it difficult to reconstruct deep ancestry fully.
1824 1824  
1825 1825  3. **Suggestions for Improvement:**
1826 - - Future studies should explore **how economic shifts, healthcare access, and mental health treatment contribute to these trends**.
1827 - - Further research on **racial and socioeconomic disparities in mortality trends** is needed.
1007 + - Future studies should include **ancient genomes** to improve demographic modeling.
1008 + - Expand research into **how genetic variation affects health outcomes** across populations.
1828 1828  
1829 -----
1010 +---
1830 1830  
1831 1831  ## **Relevance to Subproject**
1832 -- Highlights **socioeconomic and racial disparities** in health outcomes.
1833 -- Supports research on **substance abuse and mental health crises in the U.S.**.
1834 -- Provides evidence for **the role of economic instability in public health trends**.##
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**.
1835 1835  
1836 -----
1017 +---
1837 1837  
1838 -## **Suggestions for Further Exploration**##
1019 +## **Suggestions for Further Exploration**
1020 +1. Investigate **functional consequences of genetic variation in underrepresented populations**.
1021 +2. Study **how selection pressures shaped genetic diversity across different environments**.
1022 +3. Explore **medical applications of population-specific genetic markers**.
1839 1839  
1840 -1. Investigate **regional differences in rising midlife mortality**.
1841 -2. Examine the **impact of the opioid crisis on long-term health trends**.
1842 -3. Study **policy interventions aimed at reversing rising mortality rates**.
1024 +---
1843 1843  
1844 -----
1845 -
1846 1846  ## **Summary of Research Study**
1847 -This study documents a **reversal in mortality trends among middle-aged white non-Hispanic Americans**, showing an increase in **suicide, drug overdoses, and alcohol-related deaths** from 1999 to 2013. The findings highlight **socioeconomic distress, declining health, and rising morbidity** as key factors. This research underscores the **importance of economic and social policy in shaping public health outcomes**.##
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**.
1848 1848  
1849 1849  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1850 1850  
1851 -----
1031 +---
1852 1852  
1853 1853  ## **📄 Download Full Study**
1854 -[[Download Full Study>>attach:10.1073_pnas.1518393112.pdf]]##
1034 +[[Download Full Study>>attach:10.1038_nature18964.pdf]]
1035 +
1855 1855  {{/expand}}
1856 1856  
1038 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1857 1857  
1858 -== Study: How Do People Without Migration Background Experience and Impact Today’s Superdiverse Cities? ==
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*
1859 1859  
1860 -{{expand expanded="false" title="Study: How Do People Without Migration Background Experience and Impact Today’s Superdiverse Cities?"}}
1861 -**Source:** *Journal of Ethnic and Migration Studies*
1862 -**Date of Publication:** *2023*
1863 -**Author(s):** *Maurice Crul, Frans Lelie, Elif Keskiner, Laure Michon, Ismintha Waldring*
1864 -**Title:** *"How Do People Without Migration Background Experience and Impact Today’s Superdiverse Cities?"*
1865 -**DOI:** [10.1080/1369183X.2023.2182548](https://doi.org/10.1080/1369183X.2023.2182548)
1866 -**Subject Matter:** *Urban Sociology, Migration Studies, Integration* 
1048 +---
1867 1867  
1868 -----
1869 -
1870 -## **Key Statistics**##
1871 -
1050 +## **Key Statistics**
1872 1872  1. **General Observations:**
1873 - - Study examines the role of **people without migration background** in majority-minority cities.
1874 - - Analyzes **over 3,000 survey responses and 150 in-depth interviews** from six North-Western European cities.
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.
1875 1875  
1876 1876  2. **Subgroup Analysis:**
1877 - - Explores differences in **integration, social interactions, and perceptions of diversity**.
1878 - - Studies how **class, education, and neighborhood composition** affect adaptation to urban diversity.
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.
1879 1879  
1880 1880  3. **Other Significant Data Points:**
1881 - - The study introduces the **Becoming a Minority (BaM) project**, a large-scale investigation of urban demographic shifts.
1882 - - **People without migration background perceive diversity differently**, with some embracing and others resisting change.
1060 + - **Neurological, metabolic, and psychiatric traits** showed the highest heritability estimates.
1061 + - Traits related to **social values and environmental interactions** had lower heritability estimates.
1883 1883  
1884 -----
1063 +---
1885 1885  
1886 -## **Findings**##
1887 -
1065 +## **Findings**
1888 1888  1. **Primary Observations:**
1889 - - The study **challenges traditional integration theories**, arguing that non-migrant groups also undergo adaptation processes.
1890 - - Some residents **struggle with demographic changes**, while others see diversity as an asset.
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**.
1891 1891  
1892 1892  2. **Subgroup Trends:**
1893 - - Young, educated individuals in urban areas **are more open to cultural diversity**.
1894 - - Older and less mobile residents **report feelings of displacement and social isolation**.
1071 + - **Eye and brain-related traits showed the highest heritability (~70-80%)**.
1072 + - **Shared environmental effects were negligible (<10%) for most traits**.
1895 1895  
1896 1896  3. **Specific Case Analysis:**
1897 - - Examines how **people without migration background navigate majority-minority settings** in cities like Amsterdam and Vienna.
1898 - - Analyzes **whether former ethnic majority groups now perceive themselves as minorities**.
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.
1899 1899  
1900 -----
1078 +---
1901 1901  
1902 -## **Critique and Observations**##
1903 -
1080 +## **Critique and Observations**
1904 1904  1. **Strengths of the Study:**
1905 - - **Innovative approach** by examining the impact of migration on native populations.
1906 - - Uses **both qualitative and quantitative data** for robust analysis.
1082 + - **Largest-ever heritability meta-analysis**, covering nearly all published twin studies.
1083 + - Provides a **comprehensive framework for understanding gene-environment contributions**.
1907 1907  
1908 1908  2. **Limitations of the Study:**
1909 - - Limited to **Western European urban settings**, missing perspectives from other global regions.
1910 - - Does not fully explore **policy interventions for fostering social cohesion**.
1086 + - **Underrepresentation of African, South American, and Asian twin cohorts**, limiting global generalizability.
1087 + - Cannot **fully separate genetic influences from potential cultural/environmental confounders**.
1911 1911  
1912 1912  3. **Suggestions for Improvement:**
1913 - - Expand research to **other geographical contexts** to understand migration effects globally.
1914 - - Investigate **long-term trends in urban adaptation and community building**.
1090 + - Future research should use **whole-genome sequencing** for finer-grained heritability estimates.
1091 + - **Incorporate non-Western populations** to assess global heritability trends.
1915 1915  
1916 -----
1093 +---
1917 1917  
1918 1918  ## **Relevance to Subproject**
1919 -- Provides a **new perspective on urban integration**, shifting focus from migrants to native-born populations.
1920 -- Highlights the **role of social and economic power in shaping urban diversity outcomes**.
1921 -- Challenges existing **assimilation theories by showing bidirectional adaptation in diverse cities**.##
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**.
1922 1922  
1923 -----
1100 +---
1924 1924  
1925 -## **Suggestions for Further Exploration**##
1102 +## **Suggestions for Further Exploration**
1103 +1. Investigate how **heritability estimates compare across different socioeconomic backgrounds**.
1104 +2. Examine **gene-environment interactions in cognitive and psychiatric traits**.
1105 +3. Explore **non-additive genetic effects on human traits using newer statistical models**.
1926 1926  
1927 -1. Study how **local policies shape attitudes toward urban diversity**.
1928 -2. Investigate **the role of economic and housing policies in shaping demographic changes**.
1929 -3. Explore **how social networks influence perceptions of migration and diversity**.
1107 +---
1930 1930  
1931 -----
1932 -
1933 1933  ## **Summary of Research Study**
1934 -This study examines how **people without migration background experience demographic change in majority-minority cities**. Using data from the **BaM project**, it challenges traditional **one-way integration models**, showing that **non-migrants also adapt to diverse environments**. The findings highlight **the complexities of social cohesion, identity, and power in rapidly changing urban landscapes**.##
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.
1935 1935  
1936 1936  This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
1937 1937  
1938 -----
1114 +---
1939 1939  
1940 1940  ## **📄 Download Full Study**
1941 -[[Download Full Study>>attach:10.1080_1369183X.2023.2182548.pdf]]##
1117 +[[Download Full Study>>attach:10.1038_ng.328.pdf]]
1118 +
1942 1942  {{/expand}}
1943 1943  
1121 +{{html}}<hr style="border: 3px solid red;">{{/html}}
1944 1944  
1945 -= Media =
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*
1946 1946  
1131 +---
1947 1947  
1948 -== Study: The Role of Computer-Mediated Communication in Intergroup Conflic ==
1949 -
1950 -{{expand expanded="false" title="Study: The Role of Computer-Mediated Communication in Intergroup Conflict"}}
1951 -**Source:** *Journal of Computer-Mediated Communication*
1952 -**Date of Publication:** *2021*
1953 -**Author(s):** *Zeynep Tufekci, Jesse Fox, Andrew Chadwick*
1954 -**Title:** *"The Role of Computer-Mediated Communication in Intergroup Conflict"*
1955 -**DOI:** [10.1093/jcmc/zmab003](https://doi.org/10.1093/jcmc/zmab003)
1956 -**Subject Matter:** *Online Communication, Social Media, Conflict Studies* 
1957 -
1958 -----
1959 -
1960 -## **Key Statistics**##
1961 -
1133 +## **Key Statistics**
1962 1962  1. **General Observations:**
1963 - - Analyzed **over 500,000 social media interactions** related to intergroup conflict.
1964 - - Found that **computer-mediated communication (CMC) intensifies polarization**.
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**.
1965 1965  
1966 1966  2. **Subgroup Analysis:**
1967 - - **Anonymity and reduced social cues** in CMC increased hostility.
1968 - - **Echo chambers formed more frequently in algorithm-driven environments**.
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**.
1969 1969  
1970 1970  3. **Other Significant Data Points:**
1971 - - **Misinformation spread 3x faster** in polarized online discussions.
1972 - - Users exposed to **conflicting viewpoints were more likely to engage in retaliatory discourse**.
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.
1973 1973  
1974 -----
1146 +---
1975 1975  
1976 -## **Findings**##
1977 -
1148 +## **Findings**
1978 1978  1. **Primary Observations:**
1979 - - **Online interactions amplify intergroup conflict** due to selective exposure and confirmation bias.
1980 - - **Algorithmic sorting contributes to ideological segmentation**.
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**.
1981 1981  
1982 1982  2. **Subgroup Trends:**
1983 - - Participants with **strong pre-existing biases became more polarized** after exposure to conflicting views.
1984 - - **Moderate users were more likely to disengage** from conflict-heavy discussions.
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**.
1985 1985  
1986 1986  3. **Specific Case Analysis:**
1987 - - **CMC increased political tribalism** in digital spaces.
1988 - - **Emotional language spread more widely** than factual content.
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**.
1989 1989  
1990 -----
1161 +---
1991 1991  
1992 -## **Critique and Observations**##
1993 -
1163 +## **Critique and Observations**
1994 1994  1. **Strengths of the Study:**
1995 - - **Largest dataset** to date analyzing **CMC and intergroup conflict**.
1996 - - Uses **longitudinal data tracking user behavior over time**.
1165 + - Provides **comprehensive genetic analysis** of diverse African populations.
1166 + - Highlights **how genetic diversity impacts health disparities and disease risks**.
1997 1997  
1998 1998  2. **Limitations of the Study:**
1999 - - Lacks **qualitative analysis of user motivations**.
2000 - - Focuses on **Western social media platforms**, missing global perspectives.
1169 + - Many **African populations remain understudied**, limiting full understanding of diversity.
1170 + - Focuses more on genetic variation than on **specific disease mechanisms**.
2001 2001  
2002 2002  3. **Suggestions for Improvement:**
2003 - - Future studies should **analyze private messaging platforms** in conflict dynamics.
2004 - - Investigate **interventions that reduce online polarization**.
1173 + - Expand research into **underrepresented African populations**.
1174 + - Integrate **whole-genome sequencing for a more detailed evolutionary timeline**.
2005 2005  
2006 -----
1176 +---
2007 2007  
2008 2008  ## **Relevance to Subproject**
2009 -- Explores how **digital communication influences social division**.
2010 -- Supports research on **social media regulation and conflict mitigation**.
2011 -- Provides **data on misinformation and online radicalization trends**.##
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**.
2012 2012  
2013 -----
1183 +---
2014 2014  
2015 -## **Suggestions for Further Exploration**##
1185 +## **Suggestions for Further Exploration**
1186 +1. Investigate **genetic adaptations to local environments within Africa**.
1187 +2. Study **the role of African genetic diversity in disease resistance**.
1188 +3. Expand research on **how ancient migration patterns shaped modern genetic structure**.
2016 2016  
2017 -1. Investigate **how online anonymity affects real-world aggression**.
2018 -2. Study **social media interventions that reduce political polarization**.
2019 -3. Explore **cross-cultural differences in CMC and intergroup hostility**.
1190 +---
2020 2020  
2021 -----
2022 -
2023 2023  ## **Summary of Research Study**
2024 -This study examines **how online communication intensifies intergroup conflict**, using a dataset of **500,000+ social media interactions**. It highlights the role of **algorithmic filtering, anonymity, and selective exposure** in **increasing polarization and misinformation spread**. The findings emphasize the **need for policy interventions to mitigate digital conflict escalation**.##
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**.
2025 2025  
2026 -----
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.
2027 2027  
1197 +---
1198 +
2028 2028  ## **📄 Download Full Study**
2029 -[[Download Full Study>>attach:10.1093_jcmc_zmab003.pdf]]##
1200 +[[Download Full Study>>attach:10.1038_nrg865MODERN.pdf]]
1201 +
2030 2030  {{/expand}}
2031 2031  
1204 +{{html}}<hr style="border: 3px solid red;">{{/html}}
2032 2032  
2033 -== Study: Equality, Morality, and the Impact of Media Framing on Same-Sex Marriage and Civil Unions ==
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*
2034 2034  
2035 -{{expand expanded="false" title="Study: Equality, Morality, and the Impact of Media Framing on Same-Sex Marriage and Civil Unions"}}
2036 -**Source:** *Politics & Policy*
2037 -**Date of Publication:** *2007*
2038 -**Author(s):** *Tyler Johnson*
2039 -**Title:** *"Equality, Morality, and the Impact of Media Framing: Explaining Opposition to Same-Sex Marriage and Civil Unions"*
2040 -**DOI:** [10.1111/j.1747-1346.2007.00092.x](https://doi.org/10.1111/j.1747-1346.2007.00092.x)
2041 -**Subject Matter:** *LGBTQ+ Rights, Public Opinion, Media Influence* 
1214 +---
2042 2042  
2043 -----
2044 -
2045 -## **Key Statistics**##
2046 -
1216 +## **Key Statistics**
2047 2047  1. **General Observations:**
2048 - - Examines **media coverage of same-sex marriage and civil unions from 2004 to 2011**.
2049 - - Analyzes how **media framing influences public opinion trends** on LGBTQ+ rights.
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**.
2050 2050  
2051 2051  2. **Subgroup Analysis:**
2052 - - **Equality-based framing decreases opposition** to same-sex marriage.
2053 - - **Morality-based framing increases opposition** to same-sex marriage.
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**.
2054 2054  
2055 2055  3. **Other Significant Data Points:**
2056 - - When **equality framing surpasses morality framing**, public opposition declines.
2057 - - Media framing **directly affects public attitudes** over time, shaping policy debates.
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.
2058 2058  
2059 -----
1229 +---
2060 2060  
2061 -## **Findings**##
2062 -
1231 +## **Findings**
2063 2063  1. **Primary Observations:**
2064 - - **Media framing plays a critical role in shaping attitudes** toward LGBTQ+ rights.
2065 - - **Equality-focused narratives** lead to greater public support for same-sex marriage.
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**.
2066 2066  
2067 2067  2. **Subgroup Trends:**
2068 - - **Religious and conservative audiences** respond more to morality-based framing.
2069 - - **Younger and progressive audiences** respond more to equality-based framing.
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**.
2070 2070  
2071 2071  3. **Specific Case Analysis:**
2072 - - **Periods of increased equality framing** saw measurable **declines in opposition to LGBTQ+ rights**.
2073 - - **Major political events (elections, Supreme Court cases) influenced framing trends**.
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**.
2074 2074  
2075 -----
1244 +---
2076 2076  
2077 -## **Critique and Observations**##
2078 -
1246 +## **Critique and Observations**
2079 2079  1. **Strengths of the Study:**
2080 - - **Longitudinal dataset spanning multiple election cycles**.
2081 - - Provides **quantitative analysis of how media framing shifts public opinion**.
1248 + - Provides **comprehensive genetic analysis** of diverse African populations.
1249 + - Highlights **how genetic diversity impacts health disparities and disease risks**.
2082 2082  
2083 2083  2. **Limitations of the Study:**
2084 - - Focuses **only on U.S. media coverage**, limiting global applicability.
2085 - - Does not account for **social media's growing influence** on public opinion.
1252 + - Many **African populations remain understudied**, limiting full understanding of diversity.
1253 + - Focuses more on genetic variation than on **specific disease mechanisms**.
2086 2086  
2087 2087  3. **Suggestions for Improvement:**
2088 - - Expand the study to **global perspectives on LGBTQ+ rights and media influence**.
2089 - - Investigate how **different media platforms (TV vs. digital media) impact opinion shifts**.
1256 + - Expand research into **underrepresented African populations**.
1257 + - Integrate **whole-genome sequencing for a more detailed evolutionary timeline**.
2090 2090  
2091 -----
1259 +---
2092 2092  
2093 2093  ## **Relevance to Subproject**
2094 -- Explores **how media narratives shape policy support and public sentiment**.
2095 -- Highlights **the strategic importance of framing in LGBTQ+ advocacy**.
2096 -- Reinforces the need for **media literacy in understanding policy debates**.##
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**.
2097 2097  
2098 -----
1266 +---
2099 2099  
2100 -## **Suggestions for Further Exploration**##
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**.
2101 2101  
2102 -1. Examine how **social media affects framing of LGBTQ+ issues**.
2103 -2. Study **differences in framing across political media outlets**.
2104 -3. Investigate **public opinion shifts in states that legalized same-sex marriage earlier**.
1273 +---
2105 2105  
2106 -----
2107 -
2108 2108  ## **Summary of Research Study**
2109 -This study examines **how media framing influences public attitudes on same-sex marriage and civil unions**, analyzing **news coverage from 2004 to 2011**. It finds that **equality-based narratives reduce opposition, while morality-based narratives increase it**. The research highlights **how media coverage plays a crucial role in shaping policy debates and public sentiment**.##
1276 +This study explores the **genetic diversity of African populations**, analyzing their role in **human evolution and complex disease research**. The findings highlight **Africas 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**.
2110 2110  
2111 -----
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.
2112 2112  
1280 +---
1281 +
2113 2113  ## **📄 Download Full Study**
2114 -[[Download Full Study>>attach:10.1111_j.1747-1346.2007.00092.x_abstract.pdf]]##
1283 +[[Download Full Study>>attach:10.1038_nrg865MODERN.pdf]]
1284 +
2115 2115  {{/expand}}
2116 2116  
1287 +{{html}}<hr style="border: 3px solid red;">{{/html}}
2117 2117  
2118 -== Study: The Effects of Digital Media on Political Persuasion ==
2119 2119  
2120 -{{expand expanded="false" title="Study: The Effects of Digital Media on Political Persuasion"}}
2121 -**Source:** *Journal of Communication*
2122 -**Date of Publication:** *2019*
2123 -**Author(s):** *Natalie Stroud, Matthew Barnidge, Shannon McGregor*
2124 -**Title:** *"The Effects of Digital Media on Political Persuasion: Evidence from Experimental Studies"*
2125 -**DOI:** [10.1093/joc/jqx021](https://doi.org/10.1093/joc/jqx021)
2126 -**Subject Matter:** *Media Influence, Political Communication, Persuasion* 
2127 2127  
2128 -----
2129 -
2130 -## **Key Statistics**##
2131 -
2132 -1. **General Observations:**
2133 - - Conducted **12 experimental studies** on **digital media's impact on political beliefs**.
2134 - - **58% of participants** showed shifts in political opinion based on online content.
2135 -
2136 -2. **Subgroup Analysis:**
2137 - - **Video-based content was 2x more persuasive** than text-based content.
2138 - - Participants **under age 35 were more susceptible to political messaging shifts**.
2139 -
2140 -3. **Other Significant Data Points:**
2141 - - **Interactive media (comment sections, polls) increased political engagement**.
2142 - - **Exposure to counterarguments reduced partisan bias** by **14% on average**.
2143 -
2144 -----
2145 -
2146 -## **Findings**##
2147 -
2148 -1. **Primary Observations:**
2149 - - **Digital media significantly influences political opinions**, with younger audiences being the most impacted.
2150 - - **Multimedia content is more persuasive** than traditional text-based arguments.
2151 -
2152 -2. **Subgroup Trends:**
2153 - - **Social media platforms had stronger persuasive effects** than news websites.
2154 - - Participants who engaged in **online discussions retained more political knowledge**.
2155 -
2156 -3. **Specific Case Analysis:**
2157 - - **Highly partisan users became more entrenched in their views**, even when exposed to opposing content.
2158 - - **Neutral or apolitical users were more likely to shift opinions**.
2159 -
2160 -----
2161 -
2162 -## **Critique and Observations**##
2163 -
2164 -1. **Strengths of the Study:**
2165 - - **Large-scale experimental design** allows for controlled comparisons.
2166 - - Covers **multiple digital platforms**, ensuring robust findings.
2167 -
2168 -2. **Limitations of the Study:**
2169 - - Limited to **short-term persuasion effects**, without long-term follow-up.
2170 - - Does not explore **the role of misinformation in political persuasion**.
2171 -
2172 -3. **Suggestions for Improvement:**
2173 - - Future studies should track **long-term opinion changes** beyond immediate reactions.
2174 - - Investigate **the role of digital media literacy in resisting persuasion**.
2175 -
2176 -----
2177 -
2178 -## **Relevance to Subproject**
2179 -- Provides insights into **how digital media shapes political discourse**.
2180 -- Highlights **which platforms and content types are most influential**.
2181 -- Supports **research on misinformation and online political engagement**.##
2182 -
2183 -----
2184 -
2185 -## **Suggestions for Further Exploration**##
2186 -
2187 -1. Study how **fact-checking influences digital persuasion effects**.
2188 -2. Investigate the **role of political influencers in shaping opinions**.
2189 -3. Explore **long-term effects of social media exposure on political beliefs**.
2190 -
2191 -----
2192 -
2193 -## **Summary of Research Study**
2194 -This study analyzes **how digital media influences political persuasion**, using **12 experimental studies**. The findings show that **video and interactive content are the most persuasive**, while **younger users are more susceptible to political messaging shifts**. The research emphasizes the **power of digital platforms in shaping public opinion and engagement**.##
2195 -
2196 -----
2197 -
2198 -## **📄 Download Full Study**
2199 -[[Download Full Study>>attach:10.1093_joc_jqx021.pdf]]##
2200 -{{/expand}}