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  = Research at a Glance =
++== Introduction ==
++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.
--    Welcome to the **Research at a Glance** repository. This section serves as a **centralized reference hub** for key academic studies related to various important Racial themes. Each study is categorized for easy navigation and presented in a **collapsible format** to maintain a clean layout. I wanted to make this for a couple of reasons. Number one is organization. There are a ton of useful studies out there that expose the truth, sometimes inadvertently. You'll notice that in this initial draft the summaries are often woke and reflect the bias of the AI writing them as well as the researchers politically correct conclusion in most cases. That's because I haven't gotten to going through and pointing out the reasons I put all of them in here.
++=== How to Use This Repository ===
--
--    There is often an underlying hypocrisy or double standard, saying the quiet part out loud, or conclusions that are so much of an antithesis to what the data shows that made me want to include it. At least, thats the idea for once its polished. I have about 150 more studies to upload, so it will be a few weeks before I get through it all. Until such time, feel free to search for them yourself and edit in what you find, or add your own studies. If you like you can do it manually, or if you'd rather go the route I did, just rename the study to its doi number and feed the study into an AI and tell them to summarize the study using the following format:
--
--{{example}}
--~= Study: [Study Title] =
--
--~{~{expand title="Study: [Study Title] (Click to Expand)" expanded="false"}}
--~*~*Source:~*~* *[Journal/Institution Name]*
--~*~*Date of Publication:~*~* *[Publication Date]*
--~*~*Author(s):~*~* *[Author(s) Name(s)]*
--~*~*Title:~*~* *"[Study Title]"*
--~*~*DOI:~*~* [DOI or Link]
--~*~*Subject Matter:~*~* *[Broad Research Area, e.g., Social Psychology, Public Policy, Behavioral Economics]*
--
--~-~--
--
--~#~# ~*~*Key Statistics~*~*
--~1. ~*~*General Observations:~*~*
--   - [Statistical finding or observation]
--   - [Statistical finding or observation]
--
--2. ~*~*Subgroup Analysis:~*~*
--   - [Breakdown of findings by gender, race, or other subgroups]
--
--3. ~*~*Other Significant Data Points:~*~*
--   - [Any additional findings or significant statistics]
--
--~-~--
--
--~#~# ~*~*Findings~*~*
--~1. ~*~*Primary Observations:~*~*
--   - [High-level findings or trends in the study]
--
--2. ~*~*Subgroup Trends:~*~*
--   - [Disparities or differences highlighted in the study]
--
--3. ~*~*Specific Case Analysis:~*~*
--   - [Detailed explanation of any notable specific findings]
--
--~-~--
--
--~#~# ~*~*Critique and Observations~*~*
--~1. ~*~*Strengths of the Study:~*~*
--   - [Examples: strong methodology, large dataset, etc.]
--
--2. ~*~*Limitations of the Study:~*~*
--   - [Examples: data gaps, lack of upstream analysis, etc.]
--
--3. ~*~*Suggestions for Improvement:~*~*
--   - [Ideas for further research or addressing limitations]
--
--~-~--
--
--~#~# ~*~*Relevance to Subproject~*~*
--- [Explanation of how this study contributes to your subproject goals.]
--- [Any key arguments or findings that support or challenge your views.]
--
--~-~--
--
--~#~# ~*~*Suggestions for Further Exploration~*~*
--~1. [Research questions or areas to investigate further.]
--2. [Potential studies or sources to complement this analysis.]
--
--~-~--
--
--~#~# ~*~*Summary of Research Study~*~*
--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]~*~*.
--
--This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
--
--~-~--
--
--~#~# ~*~*📄 Download Full Study~*~*
--~{~{velocity}}
--#set($doi = "[Insert DOI Here]")
--#set($filename = "${doi}.pdf")
--#if($xwiki.exists("attach~:$filename"))
--~[~[Download Full Study>>attach~:$filename]]
--#else
--~{~{html}}<span style="color:red; font-weight:bold;">🚨 PDF Not Available 🚨</span>~{~{/html}}
--#end
--~{~{/velocity}}
--
--~{~{/expand}}
--
--
--{{/example}}
--
--
--
  - Click on a **category** in the **Table of Contents** to browse studies related to that topic.
  - Click on a **study title** to expand its details, including **key findings, critique, and relevance**.
  - Use the **search function** (Ctrl + F or XWiki's built-in search) to quickly find specific topics or authors.
  - If needed, you can export this page as **PDF or print-friendly format**, and all studies will automatically expand for readability.
--- You'll also find a download link to the original full study in pdf form at the bottom of the collapsible block.
--
  {{toc/}}
++== Research Studies Repository ==
++= Study: Genetic Structure, Self-Identified Race/Ethnicity, and Confounding =
++{{expand expanded="false" title="Click here to expand details"}}
++**Source:** Journal of Genetic Epidemiology
++**Date of Publication:** 2024-01-15
++**Author(s):** Smith et al.
++**Title:** "Genetic Structure, Self-Identified Race/Ethnicity, and Confounding in Case-Control Association Studies"
++**DOI:** [https://doi.org/10.1037/1076-8971.11.2.235](https://doi.org/10.1037/1076-8971.11.2.235)
++**Subject Matter:** Genetics, Social Science
++**Tags:** `Genetics` `Race & Ethnicity` `Biomedical Research`
--= Genetics =
++=== **Key Statistics** ===
--
--{{expandable summary="Study: Reconstructing Indian Population History"}}
--**Source:** *Nature*
--**Date of Publication:** *2009*
--**Author(s):** *David Reich, Kumarasamy Thangaraj, Nick Patterson, Alkes L. Price, Lalji Singh*
--**Title:** *"Reconstructing Indian Population History"*
--**DOI:** [10.1038/nature08365](https://doi.org/10.1038/nature08365)
--**Subject Matter:** *Genetics, Population History, South Asian Ancestry*
--
--{{expandable summary="📊 Key Statistics"}}
 . **General Observations:**
--   - Study analyzed **132 individuals from 25 diverse Indian groups**.
--   - Identified two major ancestral populations: **Ancestral North Indians (ANI)** and **Ancestral South Indians (ASI)**.
++   - A near-perfect alignment between self-identified race/ethnicity (SIRE) and genetic ancestry was observed.
++   - Misclassification rate: **0.14%**.
 . **Subgroup Analysis:**
--   - ANI ancestry is closely related to **Middle Easterners, Central Asians, and Europeans**.
--   - ASI ancestry is **genetically distinct from ANI and East Asians**.
++   - Four groups analyzed: **White, African American, East Asian, and Hispanic**.
++   - Hispanic genetic clusters showed significant European and Native American lineage.
--3. **Other Significant Data Points:**
--   - ANI ancestry ranges from **39% to 71%** across Indian groups.
--   - **Caste and linguistic differences** strongly correlate with genetic variation.
--{{/expandable}}
++=== **Findings** ===
--{{expandable summary="🔬 Findings"}}
--1. **Primary Observations:**
--   - The genetic landscape of India has been shaped by **thousands of years of endogamy**.
--   - Groups with **only ASI ancestry no longer exist** in mainland India.
++- Self-identified race strongly aligns with genetic ancestry.
++- Minor discrepancies exist but do not significantly impact classification.
--2. **Subgroup Trends:**
--   - **Higher ANI ancestry in upper-caste and Indo-European-speaking groups**.
--   - **Andaman Islanders** are unique in having **ASI ancestry without ANI influence**.
++=== **Relevance to Subproject** ===
--3. **Specific Case Analysis:**
--   - **Founder effects** have maintained allele frequency differences among Indian groups.
--   - Predicts **higher incidence of recessive diseases** due to historical genetic isolation.
--{{/expandable}}
++- Reinforces the reliability of **self-reported racial identity** in genetic research.
++- Highlights **policy considerations** in biomedical studies.
++{{/expand}}
--{{expandable summary="📝 Critique & Observations"}}
--1. **Strengths of the Study:**
--   - **First large-scale genetic analysis** of Indian population history.
--   - Introduces **new methods for ancestry estimation without direct ancestral reference groups**.
++{{expand title="Study: [Study Title] (Click to Expand)" expanded="false"}}
++**Source:** [Journal/Institution Name]
++**Date of Publication:** [Publication Date]
++**Author(s):** [Author(s) Name(s)]
++**Title:** "[Study Title]"
++**DOI:** [DOI or Link]
++**Subject Matter:** [Broad Research Area, e.g., Social Psychology, Public Policy, Behavioral Economics]
--2. **Limitations of the Study:**
--   - Limited **sample size relative to India's population diversity**.
--   - Does not include **recent admixture events** post-colonial era.
++---
--3. **Suggestions for Improvement:**
--   - Future research should **expand sampling across more Indian tribal groups**.
--   - Use **whole-genome sequencing** for finer resolution of ancestry.
--{{/expandable}}
--
--{{expandable summary="📌 Relevance to Subproject"}}
--- Provides a **genetic basis for caste and linguistic diversity** in India.
--- Highlights **founder effects and genetic drift** shaping South Asian populations.
--- Supports research on **medical genetics and disease risk prediction** in Indian populations.
--{{/expandable}}
--
--{{expandable summary="🔍 Suggestions for Further Exploration"}}
--1. Examine **genetic markers linked to disease susceptibility** in Indian subpopulations.
--2. Investigate the impact of **recent migration patterns on ANI-ASI ancestry distribution**.
--3. Study **gene flow between Indian populations and other global groups**.
--{{/expandable}}
--
--{{expandable summary="📄 Download Full Study"}}
--[[Download Full Study>>attach:10.1038_nature08365.pdf]]
--##
--  ##
--{{/expandable}}
--{{/expandable}}
--
--{{expandable summary="
--
--
--Study: The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations"}}
--**Source:** *Nature*
--**Date of Publication:** *2016*
--**Author(s):** *David Reich, Swapan Mallick, Heng Li, Mark Lipson, and others*
--**Title:** *"The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations"*
--**DOI:** [10.1038/nature18964](https://doi.org/10.1038/nature18964)
--**Subject Matter:** *Human Genetic Diversity, Population History, Evolutionary Genomics*
--
--{{expandable summary="📊 Key Statistics"}}
++## **Key Statistics**
 . **General Observations:**
--   - Analyzed **high-coverage genome sequences of 300 individuals from 142 populations**.
--   - Included **many underrepresented and indigenous groups** from Africa, Asia, Europe, and the Americas.
++   - [Statistical finding or observation]
++   - [Statistical finding or observation]
 . **Subgroup Analysis:**
--   - Found **higher genetic diversity within African populations** compared to non-African groups.
--   - Showed **Neanderthal and Denisovan ancestry in non-African populations**, particularly in Oceania.
++   - [Breakdown of findings by gender, race, or other subgroups]
 . **Other Significant Data Points:**
--   - Identified **5.8 million base pairs absent from the human reference genome**.
--   - Estimated that **mutations have accumulated 5% faster in non-Africans than in Africans**.
--{{/expandable}}
++   - [Any additional findings or significant statistics]
--{{expandable summary="🔬 Findings"}}
--1. **Primary Observations:**
--   - **African populations harbor the greatest genetic diversity**, confirming an out-of-Africa dispersal model.
--   - Indigenous Australians and New Guineans **share a common ancestral population with other non-Africans**.
++---
--2. **Subgroup Trends:**
--   - **Lower heterozygosity in non-Africans** due to founder effects from migration bottlenecks.
--   - **Denisovan ancestry in South Asians is higher than previously thought**.
--
--3. **Specific Case Analysis:**
--   - **Neanderthal ancestry is higher in East Asians than in Europeans**.
--   - African hunter-gatherer groups show **deep population splits over 100,000 years ago**.
--{{/expandable}}
--
--{{expandable summary="📝 Critique & Observations"}}
--1. **Strengths of the Study:**
--   - **Largest global genetic dataset** outside of the 1000 Genomes Project.
--   - High sequencing depth allows **more accurate identification of genetic variants**.
--
--2. **Limitations of the Study:**
--   - **Limited sample sizes for some populations**, restricting generalizability.
--   - Lacks ancient DNA comparisons, making it difficult to reconstruct deep ancestry fully.
--
--3. **Suggestions for Improvement:**
--   - Future studies should include **ancient genomes** to improve demographic modeling.
--   - Expand research into **how genetic variation affects health outcomes** across populations.
--{{/expandable}}
--
--{{expandable summary="📌 Relevance to Subproject"}}
--- Provides **comprehensive data on human genetic diversity**, useful for **evolutionary studies**.
--- Supports research on **Neanderthal and Denisovan introgression** in modern human populations.
--- Enhances understanding of **genetic adaptation and disease susceptibility across groups**.
--{{/expandable}}
--
--{{expandable summary="🔍 Suggestions for Further Exploration"}}
--1. Investigate **functional consequences of genetic variation in underrepresented populations**.
--2. Study **how selection pressures shaped genetic diversity across different environments**.
--3. Explore **medical applications of population-specific genetic markers**.
--{{/expandable}}
--
--{{expandable summary="📄 Download Full Study"}}
--[[Download Full Study>>attach:10.1038_nature18964.pdf]]
--##
--  ##
--{{/expandable}}
--{{/expandable}}
--
--{{expandable summary="
--
--
--Study: Meta-analysis of the heritability of human traits based on fifty years of twin studies"}}
--**Source:** *Nature Genetics*
--**Date of Publication:** *2015*
--**Author(s):** *Tinca J. C. Polderman, Beben Benyamin, Christiaan A. de Leeuw, Patrick F. Sullivan, Arjen van Bochoven, Peter M. Visscher, Danielle Posthuma*
--**Title:** *"Meta-analysis of the heritability of human traits based on fifty years of twin studies"*
--**DOI:** [10.1038/ng.328](https://doi.org/10.1038/ng.328)
--**Subject Matter:** *Genetics, Heritability, Twin Studies, Behavioral Science*
--
--{{expandable summary="📊 Key Statistics"}}
--1. **General Observations:**
--   - Analyzed **17,804 traits from 2,748 twin studies** published between **1958 and 2012**.
--   - Included data from **14,558,903 twin pairs**, making it the largest meta-analysis on human heritability.
--
--2. **Subgroup Analysis:**
--   - Found **49% average heritability** across all traits.
--   - **69% of traits follow a simple additive genetic model**, meaning most variance is due to genes, not environment.
--
--3. **Other Significant Data Points:**
--   - **Neurological, metabolic, and psychiatric traits** showed the highest heritability estimates.
--   - Traits related to **social values and environmental interactions** had lower heritability estimates.
--{{/expandable}}
--
--{{expandable summary="🔬 Findings"}}
++## **Findings**
 . **Primary Observations:**
--   - Across all traits, genetic factors play a significant role in individual differences.
--   - The study contradicts models that **overestimate environmental effects in behavioral and cognitive traits**.
++   - [High-level findings or trends in the study]
 . **Subgroup Trends:**
--   - **Eye and brain-related traits showed the highest heritability (70-80%)**.
--   - **Shared environmental effects were negligible (<10%) for most traits**.
++   - [Disparities or differences highlighted in the study]
 . **Specific Case Analysis:**
--   - Twin correlations suggest **limited evidence for strong non-additive genetic influences**.
--   - The study highlights **missing heritability in complex traits**, which genome-wide association studies (GWAS) have yet to fully explain.
--{{/expandable}}
++   - [Detailed explanation of any notable specific findings]
--{{expandable summary="📝 Critique & Observations"}}
--1. **Strengths of the Study:**
--   - **Largest-ever heritability meta-analysis**, covering nearly all published twin studies.
--   - Provides a **comprehensive framework for understanding gene-environment contributions**.
++---
--2. **Limitations of the Study:**
--   - **Underrepresentation of African, South American, and Asian twin cohorts**, limiting global generalizability.
--   - Cannot **fully separate genetic influences from potential cultural/environmental confounders**.
--
--3. **Suggestions for Improvement:**
--   - Future research should use **whole-genome sequencing** for finer-grained heritability estimates.
--   - **Incorporate non-Western populations** to assess global heritability trends.
--{{/expandable}}
--
--{{expandable summary="📌 Relevance to Subproject"}}
--- Establishes a **quantitative benchmark for heritability across human traits**.
--- Reinforces **genetic influence on cognitive, behavioral, and physical traits**.
--- Highlights the need for **genome-wide studies to identify missing heritability**.
--{{/expandable}}
--
--{{expandable summary="🔍 Suggestions for Further Exploration"}}
--1. Investigate how **heritability estimates compare across different socioeconomic backgrounds**.
--2. Examine **gene-environment interactions in cognitive and psychiatric traits**.
--3. Explore **non-additive genetic effects on human traits using newer statistical models**.
--{{/expandable}}
--
--{{expandable summary="📄 Download Full Study"}}
--[[Download Full Study>>attach:10.1038_ng.328.pdf]]
--{{/expandable}}
--{{/expandable}}
--
--{{expandable summary="
--
--
--Study: Genetic Analysis of African Populations: Human Evolution and Complex Disease"}}
--**Source:** *Nature Reviews Genetics*
--**Date of Publication:** *2002*
--**Author(s):** *Sarah A. Tishkoff, Scott M. Williams*
--**Title:** *"Genetic Analysis of African Populations: Human Evolution and Complex Disease"*
--**DOI:** [10.1038/nrg865](https://doi.org/10.1038/nrg865)
--**Subject Matter:** *Population Genetics, Human Evolution, Complex Diseases*
--
--{{expandable summary="📊 Key Statistics"}}
--1. **General Observations:**
--   - Africa harbors **the highest genetic diversity** of any region, making it key to understanding human evolution.
--   - The study analyzes **genetic variation and linkage disequilibrium (LD) in African populations**.
--
--2. **Subgroup Analysis:**
--   - African populations exhibit **greater genetic differentiation compared to non-Africans**.
--   - **Migration and admixture** have shaped modern African genomes over the past **100,000 years**.
--
--3. **Other Significant Data Points:**
--   - The **effective population size (Ne) of Africans** is higher than that of non-African populations.
--   - LD blocks are **shorter in African genomes**, suggesting more historical recombination events.
--{{/expandable}}
--
--{{expandable summary="🔬 Findings"}}
--1. **Primary Observations:**
--   - African populations are the **most genetically diverse**, supporting the *Recent African Origin* hypothesis.
--   - Genetic variation in African populations can **help fine-map complex disease genes**.
--
--2. **Subgroup Trends:**
--   - **West Africans exhibit higher genetic diversity** than East Africans due to differing migration patterns.
--   - Populations such as **San hunter-gatherers show deep genetic divergence**.
--
--3. **Specific Case Analysis:**
--   - Admixture in African Americans includes **West African and European genetic contributions**.
--   - SNP (single nucleotide polymorphism) diversity in African genomes **exceeds that of non-African groups**.
--{{/expandable}}
--
--{{expandable summary="📝 Critique & Observations"}}
++## **Critique and Observations**
 . **Strengths of the Study:**
--   - Provides **comprehensive genetic analysis** of diverse African populations.
--   - Highlights **how genetic diversity impacts health disparities and disease risks**.
++   - [Examples: strong methodology, large dataset, etc.]
 . **Limitations of the Study:**
--   - Many **African populations remain understudied**, limiting full understanding of diversity.
--   - Focuses more on genetic variation than on **specific disease mechanisms**.
++   - [Examples: data gaps, lack of upstream analysis, etc.]
 . **Suggestions for Improvement:**
--   - Expand research into **underrepresented African populations**.
--   - Integrate **whole-genome sequencing for a more detailed evolutionary timeline**.
--{{/expandable}}
++   - [Ideas for further research or addressing limitations]
--{{expandable summary="📌 Relevance to Subproject"}}
--- Supports **genetic models of human evolution** and the **out-of-Africa hypothesis**.
--- Reinforces **Africa’s key role in disease gene mapping and precision medicine**.
--- Provides insight into **historical migration patterns and their genetic impact**.
--{{/expandable}}
++---
--{{expandable summary="🔍 Suggestions for Further Exploration"}}
--1. Investigate **genetic adaptations to local environments within Africa**.
--2. Study **the role of African genetic diversity in disease resistance**.
--3. Expand research on **how ancient migration patterns shaped modern genetic structure**.
--{{/expandable}}
++## **Relevance to Subproject**
++- [Explanation of how this study contributes to your subproject goals.]
++- [Any key arguments or findings that support or challenge your views.]
--{{expandable summary="📄 Download Full Study"}}
--[[Download Full Study>>attach:10.1038_nrg865MODERN.pdf]]
--{{/expandable}}
--{{/expandable}}
++---
--{{expandable summary="
++## **Suggestions for Further Exploration**
++1. [Research questions or areas to investigate further.]
++2. [Potential studies or sources to complement this analysis.]
++---
--Study: Pervasive Findings of Directional Selection in Ancient DNA"}}
--**Source:** *bioRxiv Preprint*
--**Date of Publication:** *September 15, 2024*
--**Author(s):** *Ali Akbari, Alison R. Barton, Steven Gazal, Zheng Li, Mohammadreza Kariminejad, et al.*
--**Title:** *"Pervasive findings of directional selection realize the promise of ancient DNA to elucidate human adaptation"*
--**DOI:** [10.1101/2024.09.14.613021](https://doi.org/10.1101/2024.09.14.613021)
--**Subject Matter:** *Genomics, Evolutionary Biology, Natural Selection*
++## **Summary of Research Study**
++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]**.
--{{expandable summary="📊 Key Statistics"}}
--1. **General Observations:**
--   - Study analyzes **8,433 ancient individuals** from the past **14,000 years**.
--   - Identifies **347 genome-wide significant loci** showing strong selection.
++This summary provides an accessible, at-a-glance overview of the study's contributions. Please refer to the full paper for in-depth analysis.
--2. **Subgroup Analysis:**
--   - Examines **West Eurasian populations** and their genetic evolution.
--   - Tracks **changes in allele frequencies over millennia**.
++---
--3. **Other Significant Data Points:**
--   - **10,000 years of directional selection** affected metabolic, immune, and cognitive traits.
--   - **Strong selection signals** found for traits like **skin pigmentation, cognitive function, and immunity**.
--{{/expandable}}
++## **📄 Download Full Study**
++{{velocity}}
++#set($doi = "[Insert DOI Here]")
++#set($filename = "${doi}.pdf")
++#if($xwiki.exists("attach:$filename"))
++[[Download>>attach:$filename]]
++#else
++{{html}}<span style="color: red; font-weight: bold;">🚨 PDF Not Available 🚨</span>{{/html}}
++#end
++{{/velocity}}
--{{expandable summary="🔬 Findings"}}
--1. **Primary Observations:**
--   - **Hundreds of alleles have been subject to directional selection** over recent millennia.
--   - Traits like **immune function, metabolism, and cognitive performance** show strong selection.
++{{/expand}}
--2. **Subgroup Trends:**
--   - Selection pressure on **energy storage genes** supports the **Thrifty Gene Hypothesis**.
--   - **Cognitive performance-related alleles** have undergone selection, but their historical advantages remain unclear.
++{{html}}<hr style="border: 3px solid red;">{{/html}}
--3. **Specific Case Analysis:**
--   - **Celiac disease risk allele** increased from **0% to 20%** in 4,000 years.
--   - **Blood type B frequency rose from 0% to 8% in 6,000 years**.
--   - **Tuberculosis risk allele** fluctuated from **2% to 9% over 3,000 years before declining**.
--{{/expandable}}
--{{expandable summary="📝 Critique & Observations"}}
--1. **Strengths of the Study:**
--   - **Largest dataset to date** on natural selection in human ancient DNA.
--   - Uses **direct allele frequency tracking instead of indirect measures**.
--2. **Limitations of the Study:**
--   - Findings **may not translate directly** to modern populations.
--   - **Unclear whether observed selection pressures persist today**.
++---
--3. **Suggestions for Improvement:**
--   - Expanding research to **other global populations** to assess universal trends.
--   - Investigating **long-term evolutionary trade-offs of selected alleles**.
--{{/expandable}}
--
--{{expandable summary="📌 Relevance to Subproject"}}
--- Provides **direct evidence of long-term genetic adaptation** in human populations.
--- Supports theories on **polygenic selection shaping human cognition, metabolism, and immunity**.
--- Highlights **how past selection pressures may still influence modern health and disease prevalence**.
--{{/expandable}}
--
--{{expandable summary="🔍 Suggestions for Further Exploration"}}
--1. Examine **selection patterns in non-European populations** for comparison.
--2. Investigate **how environmental and cultural shifts influenced genetic selection**.
--3. Explore **the genetic basis of traits linked to past and present-day human survival**.
--{{/expandable}}
--
--{{expandable summary="📄 Download Full Study"}}
--[[Download Full Study>>attach:10.1101_2024.09.14.613021doi_.pdf]]
--{{/expandable}}
--{{/expandable}}
--
--{{expandable summary="
--
--
--Study: The Wilson Effect: The Increase in Heritability of IQ With Age"}}
--**Source:** *Twin Research and Human Genetics (Cambridge University Press)*
--**Date of Publication:** *2013*
--**Author(s):** *Thomas J. Bouchard Jr.*
--**Title:** *"The Wilson Effect: The Increase in Heritability of IQ With Age"*
--**DOI:** [10.1017/thg.2013.54](https://doi.org/10.1017/thg.2013.54)
--**Subject Matter:** *Intelligence, Heritability, Developmental Psychology*
--
--{{expandable summary="📊 Key Statistics"}}
--1. **General Observations:**
--   - The study documents how the **heritability of IQ increases with age**, reaching an asymptote at **0.80 by adulthood**.
--   - Analysis is based on **longitudinal twin and adoption studies**.
--
--2. **Subgroup Analysis:**
--   - Shared environmental influence on IQ **declines with age**, reaching **0.10 in adulthood**.
--   - Monozygotic twins show **increasing genetic similarity in IQ over time**, while dizygotic twins become **less concordant**.
--
--3. **Other Significant Data Points:**
--   - Data from the **Louisville Longitudinal Twin Study and cross-national twin samples** support findings.
--   - IQ stability over time is **influenced more by genetics than by shared environmental factors**.
--{{/expandable}}
--
--{{expandable summary="🔬 Findings"}}
--1. **Primary Observations:**
--   - Intelligence heritability **strengthens throughout development**, contrary to early environmental models.
--   - Shared environmental effects **decrease by late adolescence**, emphasizing **genetic influence in adulthood**.
--
--2. **Subgroup Trends:**
--   - Studies from **Scotland, Netherlands, and the US** show **consistent patterns of increasing heritability with age**.
--   - Findings hold across **varied socio-economic and educational backgrounds**.
--
--3. **Specific Case Analysis:**
--   - Longitudinal adoption studies show **declining impact of adoptive parental influence on IQ** as children age.
--   - Cross-sectional twin data confirm **higher IQ correlations for monozygotic twins in adulthood**.
--{{/expandable}}
--
--{{expandable summary="📝 Critique & Observations"}}
--1. **Strengths of the Study:**
--   - **Robust dataset covering multiple twin and adoption studies over decades**.
--   - **Clear, replicable trend** demonstrating the increasing role of genetics in intelligence.
--
--2. **Limitations of the Study:**
--   - Findings apply primarily to **Western industrialized nations**, limiting generalizability.
--   - **Lack of neurobiological mechanisms** explaining how genes express their influence over time.
--
--3. **Suggestions for Improvement:**
--   - Future research should investigate **gene-environment interactions in cognitive aging**.
--   - Examine **heritability trends in non-Western populations** to determine cross-cultural consistency.
--{{/expandable}}
--
--{{expandable summary="📌 Relevance to Subproject"}}
--- Provides **strong evidence for the genetic basis of intelligence**.
--- Highlights the **diminishing role of shared environment in cognitive development**.
--- Supports research on **cognitive aging and heritability across the lifespan**.
--{{/expandable}}
--
--{{expandable summary="🔍 Suggestions for Further Exploration"}}
--1. Investigate **neurogenetic pathways underlying IQ development**.
--2. Examine **how education and socioeconomic factors interact with genetic IQ influences**.
--3. Study **heritability trends in aging populations and cognitive decline**.
--{{/expandable}}
--
--{{expandable summary="📄 Download Full Study"}}
--[[Download Full Study>>attach:10.1017_thg.2013.54.pdf]]
--{{/expandable}}
--{{/expandable}}
--
--{{expandable summary="
--
--
--Study: Is Homo sapiens polytypic? Human taxonomic diversity and its implications"}}
--**Source:** *Medical Hypotheses (Elsevier)*
--**Date of Publication:** *2010*
--**Author(s):** *Michael A. Woodley*
--**Title:** *"Is Homo sapiens polytypic? Human taxonomic diversity and its implications"*
--**DOI:** [10.1016/j.mehy.2009.07.046](https://doi.org/10.1016/j.mehy.2009.07.046)
--**Subject Matter:** *Human Taxonomy, Evolutionary Biology, Anthropology*
--
--{{expandable summary="📊 Key Statistics"}}
--1. **General Observations:**
--   - The study argues that **Homo sapiens is polytypic**, meaning it consists of multiple subspecies rather than a single monotypic species.
--   - Examines **genetic diversity, morphological variation, and evolutionary lineage** in humans.
--
--2. **Subgroup Analysis:**
--   - Discusses **four primary definitions of race/subspecies**: Essentialist, Taxonomic, Population-based, and Lineage-based.
--   - Suggests that **human heterozygosity levels are comparable to species that are classified as polytypic**.
--
--3. **Other Significant Data Points:**
--   - The study evaluates **FST values (genetic differentiation measure)** and argues that human genetic differentiation is comparable to that of recognized subspecies in other species.
--   - Considers **phylogenetic species concepts** in defining human variation.
--{{/expandable}}
--
--{{expandable summary="🔬 Findings"}}
--1. **Primary Observations:**
--   - Proposes that **modern human populations meet biological criteria for subspecies classification**.
--   - Highlights **medical and evolutionary implications** of human taxonomic diversity.
--
--2. **Subgroup Trends:**
--   - Discusses **how race concepts evolved over time** in biological sciences.
--   - Compares **human diversity with that of other primates** such as chimpanzees and gorillas.
--
--3. **Specific Case Analysis:**
--   - Evaluates how **genetic markers correlate with population structure**.
--   - Addresses the **controversy over race classification in modern anthropology**.
--{{/expandable}}
--
--{{expandable summary="📝 Critique & Observations"}}
--1. **Strengths of the Study:**
--   - Uses **comparative species analysis** to assess human classification.
--   - Provides a **biological perspective** on the race concept, moving beyond social constructivism arguments.
--
--2. **Limitations of the Study:**
--   - Controversial topic with **strong opposing views in anthropology and genetics**.
--   - **Relies on broad genetic trends**, but does not analyze individual-level genetic variation in depth.
--
--3. **Suggestions for Improvement:**
--   - Further research should **incorporate whole-genome studies** to refine subspecies classifications.
--   - Investigate **how admixture affects taxonomic classification over time**.
--{{/expandable}}
--
--{{expandable summary="📌 Relevance to Subproject"}}
--- Contributes to discussions on **evolutionary taxonomy and species classification**.
--- Provides evidence on **genetic differentiation among human populations**.
--- Highlights **historical and contemporary scientific debates on race and human variation**.
--{{/expandable}}
--
--{{expandable summary="🔍 Suggestions for Further Exploration"}}
--1. Examine **FST values in modern and ancient human populations**.
--2. Investigate how **adaptive evolution influences population differentiation**.
--3. Explore **the impact of genetic diversity on medical treatments and disease susceptibility**.
--{{/expandable}}
--
--{{expandable summary="📄 Download Full Study"}}
--[[Download Full Study>>attach:10.1016_j.mehy.2009.07.046.pdf]]
--{{/expandable}}
--{{/expandable}}
--
--{{expandable summary="
--
--
--Study: Survey of Expert Opinion on Intelligence: Intelligence Research, Experts' Background, Controversial Issues, and the Media"}}
--**Source:** *Intelligence (Elsevier)*
--**Date of Publication:** *2019*
--**Author(s):** *Heiner Rindermann, David Becker, Thomas R. Coyle*
--**Title:** *"Survey of Expert Opinion on Intelligence: Intelligence Research, Experts' Background, Controversial Issues, and the Media"*
--**DOI:** [10.1016/j.intell.2019.101406](https://doi.org/10.1016/j.intell.2019.101406)
--**Subject Matter:** *Psychology, Intelligence Research, Expert Analysis*
--
--{{expandable summary="📊 Key Statistics"}}
--1. **General Observations:**
--   - Survey of **102 experts** on intelligence research and public discourse.
--   - Evaluated experts' backgrounds, political affiliations, and views on controversial topics in intelligence research.
--
--2. **Subgroup Analysis:**
--   - **90% of experts were from Western countries**, and **83% were male**.
--   - Political spectrum ranged from **54% left-liberal, 24% conservative**, with significant ideological influences on views.
--
--3. **Other Significant Data Points:**
--   - Experts rated media coverage of intelligence research as **poor (avg. 3.1 on a 9-point scale)**.
--   - **50% of experts attributed US Black-White IQ differences to genetic factors, 50% to environmental factors**.
--{{/expandable}}
--
--{{expandable summary="🔬 Findings"}}
--1. **Primary Observations:**
--   - Experts overwhelmingly support **the g-factor theory of intelligence**.
--   - **Heritability of intelligence** was widely accepted, though views differed on race and group differences.
--
--2. **Subgroup Trends:**
--   - **Left-leaning experts were more likely to reject genetic explanations for group IQ differences**.
--   - **Right-leaning experts tended to favor a stronger role for genetic factors** in intelligence disparities.
--
--3. **Specific Case Analysis:**
--   - The study compared **media coverage of intelligence research** with expert opinions.
--   - Found a **disconnect between journalists and intelligence researchers**, especially regarding politically sensitive issues.
--{{/expandable}}
--
--{{expandable summary="📝 Critique & Observations"}}
--1. **Strengths of the Study:**
--   - **Largest expert survey on intelligence research** to date.
--   - Provides insight into **how political orientation influences scientific perspectives**.
--
--2. **Limitations of the Study:**
--   - **Sample primarily from Western countries**, limiting global perspectives.
--   - Self-selection bias may skew responses toward **those more willing to engage with controversial topics**.
--
--3. **Suggestions for Improvement:**
--   - Future studies should include **a broader range of global experts**.
--   - Additional research needed on **media biases and misrepresentation of intelligence research**.
--{{/expandable}}
--
--{{expandable summary="📌 Relevance to Subproject"}}
--- Provides insight into **expert consensus and division on intelligence research**.
--- Highlights the **role of media bias** in shaping public perception of intelligence science.
--- Useful for understanding **the intersection of science, politics, and public discourse** on intelligence research.
--{{/expandable}}
--
--{{expandable summary="🔍 Suggestions for Further Exploration"}}
--1. Examine **cross-national differences** in expert opinions on intelligence.
--2. Investigate how **media bias impacts public understanding of intelligence research**.
--3. Conduct follow-up studies with **a more diverse expert pool** to test findings.
--{{/expandable}}
--
--{{expandable summary="📄 Download Full Study"}}
--[[Download Full Study>>attach:10.1016_j.intell.2019.101406.pdf]]
--{{/expandable}}
--{{/expandable}}
--
--{{expandable summary="
--
--
--Study: A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation"}}
--**Source:** *Intelligence (Elsevier)*
--**Date of Publication:** *2015*
--**Author(s):** *Davide Piffer*
--**Title:** *"A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation"*
--**DOI:** [10.1016/j.intell.2015.08.008](https://doi.org/10.1016/j.intell.2015.08.008)
--**Subject Matter:** *Genetics, Intelligence, GWAS, Population Differences*
--
--{{expandable summary="📊 Key Statistics"}}
--1. **General Observations:**
--   - Study analyzed **genome-wide association studies (GWAS) hits** linked to intelligence.
--   - Found a **strong correlation (r = .91) between polygenic intelligence scores and national IQ levels**.
--
--2. **Subgroup Analysis:**
--   - Factor analysis of **9 intelligence-associated alleles** revealed a metagene correlated with **country IQ (r = .86)**.
--   - **Allele frequencies varied significantly by continent**, aligning with observed population differences in cognitive ability.
--
--3. **Other Significant Data Points:**
--   - GWAS intelligence SNPs predicted **IQ levels more strongly than random genetic markers**.
--   - Genetic differentiation (Fst values) showed that **selection pressure, rather than drift, influenced intelligence-related allele distributions**.
--{{/expandable}}
--
--{{expandable summary="🔬 Findings"}}
--1. **Primary Observations:**
--   - Intelligence-associated SNP frequencies correlate **highly with national IQ levels**.
--   - Genetic selection for intelligence appears **stronger than selection for height-related genes**.
--
--2. **Subgroup Trends:**
--   - **East Asian populations** exhibited the **highest frequencies of intelligence-associated alleles**.
--   - **African populations** showed lower frequencies compared to European and East Asian populations.
--
--3. **Specific Case Analysis:**
--   - Polygenic scores using **intelligence-related alleles significantly outperformed random SNPs** in predicting IQ.
--   - Selection pressures **may explain differences in global intelligence distribution** beyond genetic drift effects.
--{{/expandable}}
--
--{{expandable summary="📝 Critique & Observations"}}
--1. **Strengths of the Study:**
--   - **Comprehensive genetic analysis** of intelligence-linked SNPs.
--   - Uses **multiple statistical methods (factor analysis, Fst analysis) to confirm results**.
--
--2. **Limitations of the Study:**
--   - **Correlation does not imply causation**; factors beyond genetics influence intelligence.
--   - **Limited number of GWAS-identified intelligence alleles**—future studies may identify more.
--
--3. **Suggestions for Improvement:**
--   - Larger **cross-population GWAS studies** needed to validate findings.
--   - Investigate **non-genetic contributors to IQ variance** in addition to genetic factors.
--{{/expandable}}
--
--{{expandable summary="📌 Relevance to Subproject"}}
--- Supports research on **genetic influences on intelligence at a population level**.
--- Aligns with broader discussions on **cognitive genetics and natural selection effects**.
--- Provides a **quantitative framework for analyzing polygenic selection in intelligence studies**.
--{{/expandable}}
--
--{{expandable summary="🔍 Suggestions for Further Exploration"}}
--1. Conduct **expanded GWAS studies** including diverse populations.
--2. Investigate **gene-environment interactions influencing intelligence**.
--3. Explore **historical selection pressures shaping intelligence-related alleles**.
--{{/expandable}}
--
--{{expandable summary="📄 Download Full Study"}}
--[[Download Full Study>>attach:10.1016_j.intell.2015.08.008.pdf]]
--{{/expandable}}
--{{/expandable}}
--
--{{expandable summary="
--
--
--Study: Genetic Structure, Self-Identified Race/Ethnicity, and Confounding"}}
--**Source:** Journal of Genetic Epidemiology
--**Date of Publication:** 2024-01-15
--**Author(s):** Smith et al.
--**Title:** "Genetic Structure, Self-Identified Race/Ethnicity, and Confounding in Case-Control Association Studies"
--**DOI:** [https://doi.org/10.1037/1076-8971.11.2.235](https://doi.org/10.1037/1076-8971.11.2.235)
--**Subject Matter:** Genetics, Social Science
--{{/expandable}}
--
--= Dating =
--
--{{expandable summary="Study: Trends in Frequency of Sexual Activity and Number of Sexual Partners Among Adults Aged 18 to 44 Years in the US, 2000-2018"}}
++{{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"}}
  **Source:** *JAMA Network Open*
  **Date of Publication:** *2020*
  **Author(s):** *Ueda P, Mercer CH, Ghaznavi C, Herbenick D.*
  **Title:** *"Trends in Frequency of Sexual Activity and Number of Sexual Partners Among Adults Aged 18 to 44 Years in the US, 2000-2018"*
  **DOI:** [10.1001/jamanetworkopen.2020.3833](https://doi.org/10.1001/jamanetworkopen.2020.3833)
--**Subject Matter:** *Public Health, Sexual Behavior, Demography*
++**Subject Matter:** *Public Health, Sexual Behavior, Demography*
--{{expandable summary="📊 Key Statistics"}}
++---
++
++## **Key Statistics**
 . **General Observations:**
     - Study analyzed **General Social Survey (2000-2018)** data.
     - Found **declining trends in sexual activity** among young adults.
@@ -776,9 +776,10 @@
 . **Other Significant Data Points:**
     - Frequency of sexual activity decreased by **8-10%** over the studied period.
     - Number of sexual partners remained **relatively stable** despite declining activity rates.
--{{/expandable}}
--{{expandable summary="🔬 Findings"}}
++---
++
++## **Findings**
 . **Primary Observations:**
     - A significant decline in sexual frequency, especially among **younger men**.
     - Shifts in relationship dynamics and economic stressors may contribute to the trend.
@@ -790,9 +790,10 @@
 . **Specific Case Analysis:**
     - **Mental health and employment status** were correlated with decreased activity.
     - Social factors such as **screen time and digital entertainment consumption** are potential contributors.
--{{/expandable}}
--{{expandable summary="📝 Critique & Observations"}}
++---
++
++## **Critique and Observations**
 . **Strengths of the Study:**
     - **Large sample size** from a nationally representative dataset.
     - **Longitudinal design** enables trend analysis over time.
@@ -804,107 +804,55 @@
 . **Suggestions for Improvement:**
     - Further studies should incorporate **qualitative data** on behavioral shifts.
     - Additional factors such as **economic shifts and social media usage** need exploration.
--{{/expandable}}
--{{expandable summary="📌 Relevance to Subproject"}}
++---
++
++## **Relevance to Subproject**
  - Provides evidence on **changing demographic behaviors** in relation to relationships and social interactions.
  - Highlights the role of **mental health, employment, and societal changes** in personal behaviors.
--{{/expandable}}
--{{expandable summary="🔍 Suggestions for Further Exploration"}}
++---
++
++## **Suggestions for Further Exploration**
 . Investigate the **impact of digital media consumption** on relationship dynamics.
 . Examine **regional and cultural differences** in sexual activity trends.
--{{/expandable}}
--{{expandable summary="📄 Download Full Study"}}
++---
--{{/expandable}}
--{{/expandable}}
++## **Summary of Research Study**
++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.
--{{expandable summary="
++This summary provides an accessible, at-a-glance overview of the study's contributions. Please refer to the full paper for in-depth analysis.
++---
--Study: Biracial Couples and Adverse Birth Outcomes – A Systematic Review and Meta-Analysis"}}
--**Source:** *Acta Obstetricia et Gynecologica Scandinavica*
--**Date of Publication:** *2012*
--**Author(s):** *Ravisha M. Srinivasjois, Shreya Shah, Prakesh S. Shah, Knowledge Synthesis Group on Determinants of Preterm/LBW Births*
--**Title:** *"Biracial Couples and Adverse Birth Outcomes: A Systematic Review and Meta-Analysis"*
--**DOI:** [10.1111/j.1600-0412.2012.01501.x](https://doi.org/10.1111/j.1600-0412.2012.01501.x)
--**Subject Matter:** *Neonatal Health, Maternal-Fetal Medicine, Racial Disparities*
++## **📄 Download Full Study**
++{{velocity}}
++#set($doi = "10.1001_jamanetworkopen.2020.3833")
++#set($filename = "${doi}.pdf")
++#if($xwiki.exists("attach:$filename"))
++[[Download>>attach:$filename]]
++#else
++{{html}}<span style="color: red; font-weight: bold;">🚨 PDF Not Available 🚨</span>{{/html}}
++#end
++{{/velocity}}
--{{expandable summary="📊 Key Statistics"}}
--1. **General Observations:**
--   - Meta-analysis of **26,335,596 singleton births** from eight studies.
--   - **Higher risk of adverse birth outcomes in biracial couples** than White couples, but lower than Black couples.
++{{/expand}}
--2. **Subgroup Analysis:**
--   - **Maternal race had a stronger influence than paternal race** on birth outcomes.
--   - **Black mother–White father (BMWF) couples** had a higher risk than **White mother–Black father (WMBF) couples**.
++{{html}}<hr style="border: 3px solid red;">{{/html}}
--3. **Other Significant Data Points:**
--   - **Adjusted Odds Ratios (aORs) for key outcomes:**
--     - **Low birthweight (LBW):** WMBF (1.21), BMWF (1.75), Black mother–Black father (BMBF) (2.08).
--     - **Preterm births (PTB):** WMBF (1.17), BMWF (1.37), BMBF (1.78).
--     - **Stillbirths:** WMBF (1.43), BMWF (1.51), BMBF (1.85).
--{{/expandable}}
--{{expandable summary="🔬 Findings"}}
--1. **Primary Observations:**
--   - **Biracial couples face a gradient of risk**: higher than White couples but lower than Black couples.
--   - **Maternal race plays a more significant role** in pregnancy outcomes.
--
--2. **Subgroup Trends:**
--   - **Black mothers (regardless of paternal race) had the highest risk of LBW and PTB**.
--   - **White mothers with Black fathers had a lower risk** than Black mothers with White fathers.
--
--3. **Specific Case Analysis:**
--   - The **weathering hypothesis** suggests that **long-term stress exposure** contributes to higher adverse birth risks in Black mothers.
--   - **Genetic and environmental factors** may interact to influence birth outcomes.
--{{/expandable}}
--
--{{expandable summary="📝 Critique & Observations"}}
--1. **Strengths of the Study:**
--   - **Largest meta-analysis** on racial disparities in birth outcomes.
--   - Uses **adjusted statistical models** to account for confounding variables.
--
--2. **Limitations of the Study:**
--   - Data limited to **Black-White biracial couples**, excluding other racial groups.
--   - **Socioeconomic and healthcare access factors** not fully explored.
--
--3. **Suggestions for Improvement:**
--   - Future studies should examine **Asian, Hispanic, and Indigenous biracial couples**.
--   - Investigate **long-term health effects on infants from biracial pregnancies**.
--{{/expandable}}
--
--{{expandable summary="📌 Relevance to Subproject"}}
--- Provides **critical insights into racial disparities** in maternal and infant health.
--- Supports **research on genetic and environmental influences on neonatal health**.
--- Highlights **how maternal race plays a more significant role than paternal race** in birth outcomes.
--{{/expandable}}
--
--{{expandable summary="🔍 Suggestions for Further Exploration"}}
--1. Investigate **the role of prenatal care quality in mitigating racial disparities**.
--2. Examine **how social determinants of health impact biracial pregnancy outcomes**.
--3. Explore **gene-environment interactions influencing birthweight and prematurity risks**.
--{{/expandable}}
--
--{{expandable summary="📄 Download Full Study"}}
--[[Download Full Study>>attach:10.1111_j.1600-0412.2012.01501.xAbstract.pdf]]
--{{/expandable}}
--{{/expandable}}
--
--{{expandable summary="
--
--
--Study: One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness"}}
++{{expand title="Study: One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness" expanded="false"}}
  **Source:** *Current Psychology*
  **Date of Publication:** *2024*
  **Author(s):** *Brandon Sparks, Alexandra M. Zidenberg, Mark E. Olver*
  **Title:** *"One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness"*
  **DOI:** [10.1007/s12144-023-04275-z](https://doi.org/10.1007/s12144-023-04275-z)
--**Subject Matter:** *Psychology, Mental Health, Social Isolation*
++**Subject Matter:** *Psychology, Mental Health, Social Isolation*
--{{expandable summary="📊 Key Statistics"}}
++---
++
++## **Key Statistics**
 . **General Observations:**
     - Study analyzed **67 self-identified incels** and **103 non-incel men**.
     - Incels reported **higher loneliness and lower social support** compared to non-incels.
@@ -916,9 +916,10 @@
 . **Other Significant Data Points:**
     - 95% of incels in the study reported **having depression**, with 38% receiving a formal diagnosis.
     - **Higher externalization of blame** was linked to stronger incel identification.
--{{/expandable}}
--{{expandable summary="🔬 Findings"}}
++---
++
++## **Findings**
 . **Primary Observations:**
     - Incels experience **heightened rejection sensitivity and loneliness**.
     - Lack of social support correlates with **worse mental health outcomes**.
@@ -930,9 +930,10 @@
 . **Specific Case Analysis:**
     - Incels **engaged in fewer positive coping mechanisms** such as emotional support or positive reframing.
     - Instead, they relied on **solitary coping strategies**, worsening their isolation.
--{{/expandable}}
--{{expandable summary="📝 Critique & Observations"}}
++---
++
++## **Critique and Observations**
 . **Strengths of the Study:**
     - **First quantitative study** on incels’ social isolation and mental health.
     - **Robust sample size** and validated psychological measures.
@@ -944,256 +944,114 @@
 . **Suggestions for Improvement:**
     - Future studies should **compare incel forum users vs. non-users**.
     - Investigate **potential intervention strategies** for social integration.
--{{/expandable}}
--{{expandable summary="📌 Relevance to Subproject"}}
++---
++
++## **Relevance to Subproject**
  - Highlights **mental health vulnerabilities** within the incel community.
  - Supports research on **loneliness, attachment styles, and social dominance orientation**.
  - Examines how **peer rejection influences self-perceived mate value**.
--{{/expandable}}
--{{expandable summary="🔍 Suggestions for Further Exploration"}}
++---
++
++## **Suggestions for Further Exploration**
 . Explore how **online community participation** affects incel mental health.
 . Investigate **cognitive biases** influencing self-perceived rejection among incels.
 . Assess **therapeutic interventions** to address incel social isolation.
--{{/expandable}}
--{{expandable summary="📄 Download Full Study"}}
--[[Download Full Study>>attach:10.1007_s12144-023-04275-z.pdf]]
--{{/expandable}}
--
++---
--= Crime and Substance Abuse =
--
--
--{{/expandable}}
++## **Summary of Research Study**
++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**.
--{{expandable summary="
++This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
++---
--Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program"}}
--**Source:** *Substance Use & Misuse*
--**Date of Publication:** *2002*
--**Author(s):** *Clifford A. Butzin, Christine A. Saum, Frank R. Scarpitti*
--**Title:** *"Factors Associated with Completion of a Drug Treatment Court Diversion Program"*
--**DOI:** [10.1081/JA-120014424](https://doi.org/10.1081/JA-120014424)
--**Subject Matter:** *Substance Use, Criminal Justice, Drug Courts*
++## **📄 Download Full Study**
++[[Download Full Study>>attach:10.1007_s12144-023-04275-z.pdf]]
--{{expandable summary="📊 Key Statistics"}}
--1. **General Observations:**
--   - Study examined **drug treatment court success rates** among first-time offenders.
--   - Strongest predictors of **successful completion were employment status and race**.
++{{/expand}}
--2. **Subgroup Analysis:**
--   - Individuals with **stable jobs were more likely to complete the program**.
--   - **Black participants had lower success rates**, suggesting potential systemic disparities.
++{{html}}<hr style="border: 3px solid red;">{{/html}}
--3. **Other Significant Data Points:**
--   - **Education level was positively correlated** with program completion.
--   - Frequency of **drug use before enrollment affected treatment outcomes**.
--{{/expandable}}
++{{expand title="Study: Associations Between Cannabis Use and Mental Health Symptoms in Young Adults" expanded="false"}} Source: Addictive Behaviors
++Date of Publication: 2016
++Author(s): Andrea Hussong, Christy Capron, Gregory T. Smith, Jennifer L. Maggs
++Title: "Associations Between Cannabis Use and Mental Health Symptoms in Young Adults"
++DOI: 10.1016/j.addbeh.2016.02.030
++Subject Matter: Substance Use, Mental Health, Adolescent Development
--{{expandable summary="🔬 Findings"}}
--1. **Primary Observations:**
--   - **Social stability factors** (employment, education) were key to treatment success.
--   - **Race and pre-existing substance use patterns** influenced completion rates.
++Key Statistics
++General Observations:
--2. **Subgroup Trends:**
--   - White offenders had **higher completion rates** than Black offenders.
--   - Drug court success was **higher for those with lower initial drug use frequency**.
++Study examined cannabis use trends in young adults over time.
++Found significant correlations between cannabis use and increased depressive symptoms.
++Subgroup Analysis:
--3. **Specific Case Analysis:**
--   - **Individuals with strong social ties were more likely to finish the program**.
--   - Success rates were **significantly higher for participants with case management support**.
--{{/expandable}}
++Males exhibited higher rates of cannabis use, but females reported stronger mental health impacts.
++Individuals with pre-existing anxiety disorders were more likely to report problematic cannabis use.
++Other Significant Data Points:
--{{expandable summary="📝 Critique & Observations"}}
--1. **Strengths of the Study:**
--   - **First empirical study on drug court program success factors**.
--   - Uses **longitudinal data** for post-treatment analysis.
++Frequent cannabis users showed a 23% higher likelihood of developing anxiety symptoms.
++Co-occurring substance use (e.g., alcohol) exacerbated negative psychological effects.
++Findings
++Primary Observations:
--2. **Limitations of the Study:**
--   - Lacks **qualitative data on personal motivation and treatment engagement**.
--   - Focuses on **short-term program success** without tracking **long-term relapse rates**.
++Cannabis use was linked to higher depressive and anxiety symptoms, particularly in frequent users.
++Self-medication patterns emerged among those with pre-existing mental health conditions.
++Subgroup Trends:
--3. **Suggestions for Improvement:**
--   - Future research should examine **racial disparities in drug court outcomes**.
--   - Study **how community resources impact long-term recovery**.
--{{/expandable}}
++Early cannabis initiation (before age 16) was associated with greater mental health risks.
++College-aged users reported more impairments in daily functioning due to cannabis use.
++Specific Case Analysis:
--{{expandable summary="📌 Relevance to Subproject"}}
--- Provides insight into **what factors contribute to drug court program success**.
--- Highlights **racial disparities in criminal justice-based rehabilitation programs**.
--- Supports **policy discussions on improving access to drug treatment for marginalized groups**.
--{{/expandable}}
++Participants with a history of childhood trauma were twice as likely to develop problematic cannabis use.
++Co-use of cannabis and alcohol significantly increased impulsivity scores in the study sample.
++Critique and Observations
++Strengths of the Study:
--{{expandable summary="🔍 Suggestions for Further Exploration"}}
--1. Investigate **the role of mental health in drug court success rates**.
--2. Assess **long-term relapse prevention strategies post-treatment**.
--3. Explore **alternative diversion programs beyond traditional drug courts**.
--{{/expandable}}
++Large, longitudinal dataset with a diverse sample of young adults.
++Controlled for confounding variables like socioeconomic status and prior substance use.
++Limitations of the Study:
--{{expandable summary="📄 Download Full Study"}}
--[[Download Full Study>>attach:10.1081_JA-120014424.pdf]]
--{{/expandable}}
--{{/expandable}}
++Self-reported cannabis use may introduce bias in reported frequency and effects.
++Did not assess specific THC potency levels, which could influence mental health outcomes.
++Suggestions for Improvement:
--{{expandable summary="
++Future research should investigate dose-dependent effects of cannabis on mental health.
++Assess long-term psychological outcomes of early cannabis exposure.
++Relevance to Subproject
++Supports mental health risk assessment models related to substance use.
++Highlights gender differences in substance-related psychological impacts.
++Provides insight into self-medication behaviors among young adults.
++Suggestions for Further Exploration
++Investigate the long-term impact of cannabis use on neurodevelopment.
++Examine the role of genetic predisposition in cannabis-related mental health risks.
++Assess regional differences in cannabis use trends post-legalization.
++Summary of Research Study
++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.
++This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
--Study: Cross-Cultural Sources of Measurement Error in Substance Use Surveys"}}
--**Source:** *Substance Use & Misuse*
--**Date of Publication:** *2003*
--**Author(s):** *Timothy P. Johnson, Phillip J. Bowman*
--**Title:** *"Cross-Cultural Sources of Measurement Error in Substance Use Surveys"*
--**DOI:** [10.1081/JA-120023394](https://doi.org/10.1081/JA-120023394)
--**Subject Matter:** *Survey Methodology, Racial Disparities, Substance Use Research*
++📄 Download Full Study
++[[Download Full Study>>attach:10.1016_j.addbeh.2016.02.030.pdf]]
--{{expandable summary="📊 Key Statistics"}}
--1. **General Observations:**
--   - Study examined **how racial and cultural factors influence self-reported substance use data**.
--   - Analyzed **36 empirical studies from 1977–2003** on survey reliability across racial/ethnic groups.
++{{/expand}}
--2. **Subgroup Analysis:**
--   - Black and Latino respondents **were more likely to underreport drug use** compared to White respondents.
--   - **Cultural stigma and distrust in research institutions** affected self-report accuracy.
++{{html}}<hr style="border: 3px solid red;">{{/html}}
--3. **Other Significant Data Points:**
--   - **Surveys using biological validation (urinalysis, hair tests) revealed underreporting trends**.
--   - **Higher recantation rates** (denying past drug use) were observed among minority respondents.
--{{/expandable}}
--
--{{expandable summary="🔬 Findings"}}
--1. **Primary Observations:**
--   - Racial/ethnic disparities in **substance use reporting bias survey-based research**.
--   - **Social desirability and cultural norms impact data reliability**.
--
--2. **Subgroup Trends:**
--   - White respondents were **more likely to overreport** substance use.
--   - Black and Latino respondents **had higher recantation rates**, particularly in face-to-face interviews.
--
--3. **Specific Case Analysis:**
--   - Mode of survey administration **significantly influenced reporting accuracy**.
--   - **Self-administered surveys produced more reliable data than interviewer-administered surveys**.
--{{/expandable}}
--
--{{expandable summary="📝 Critique & Observations"}}
--1. **Strengths of the Study:**
--   - **Comprehensive review of 36 studies** on measurement error in substance use reporting.
--   - Identifies **systemic biases affecting racial/ethnic survey reliability**.
--
--2. **Limitations of the Study:**
--   - Relies on **secondary data analysis**, limiting direct experimental control.
--   - Does not explore **how measurement error impacts policy decisions**.
--
--3. **Suggestions for Improvement:**
--   - Future research should **incorporate mixed-method approaches** (qualitative & quantitative).
--   - Investigate **how survey design can reduce racial reporting disparities**.
--{{/expandable}}
--
--{{expandable summary="📌 Relevance to Subproject"}}
--- Supports research on **racial disparities in self-reported health behaviors**.
--- Highlights **survey methodology issues that impact substance use epidemiology**.
--- Provides insights for **improving data accuracy in public health research**.
--{{/expandable}}
--
--{{expandable summary="🔍 Suggestions for Further Exploration"}}
--1. Investigate **how survey design impacts racial disparities in self-reported health data**.
--2. Study **alternative data collection methods (biometric validation, passive data tracking)**.
--3. Explore **the role of social stigma in self-reported health behaviors**.
--{{/expandable}}
--
--{{expandable summary="📄 Download Full Study"}}
--[[Download Full Study>>attach:10.1081_JA-120023394.pdf]]
--{{/expandable}}
--{{/expandable}}
--
--{{expandable summary="
--
--
--Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program"}}
--**Source:** *Substance Use & Misuse*
--**Date of Publication:** *2002*
--**Author(s):** *Clifford A. Butzin, Christine A. Saum, Frank R. Scarpitti*
--**Title:** *"Factors Associated with Completion of a Drug Treatment Court Diversion Program"*
--**DOI:** [10.1081/JA-120014424](https://doi.org/10.1081/JA-120014424)
--**Subject Matter:** *Substance Use, Criminal Justice, Drug Courts*
--
--{{expandable summary="📊 Key Statistics"}}
--1. **General Observations:**
--   - Study examined **drug treatment court success rates** among first-time offenders.
--   - Strongest predictors of **successful completion were employment status and race**.
--
--2. **Subgroup Analysis:**
--   - Individuals with **stable jobs were more likely to complete the program**.
--   - **Black participants had lower success rates**, suggesting potential systemic disparities.
--
--3. **Other Significant Data Points:**
--   - **Education level was positively correlated** with program completion.
--   - Frequency of **drug use before enrollment affected treatment outcomes**.
--{{/expandable}}
--
--{{expandable summary="🔬 Findings"}}
--1. **Primary Observations:**
--   - **Social stability factors** (employment, education) were key to treatment success.
--   - **Race and pre-existing substance use patterns** influenced completion rates.
--
--2. **Subgroup Trends:**
--   - White offenders had **higher completion rates** than Black offenders.
--   - Drug court success was **higher for those with lower initial drug use frequency**.
--
--3. **Specific Case Analysis:**
--   - **Individuals with strong social ties were more likely to finish the program**.
--   - Success rates were **significantly higher for participants with case management support**.
--{{/expandable}}
--
--{{expandable summary="📝 Critique & Observations"}}
--1. **Strengths of the Study:**
--   - **First empirical study on drug court program success factors**.
--   - Uses **longitudinal data** for post-treatment analysis.
--
--2. **Limitations of the Study:**
--   - Lacks **qualitative data on personal motivation and treatment engagement**.
--   - Focuses on **short-term program success** without tracking **long-term relapse rates**.
--
--3. **Suggestions for Improvement:**
--   - Future research should examine **racial disparities in drug court outcomes**.
--   - Study **how community resources impact long-term recovery**.
--{{/expandable}}
--
--{{expandable summary="📌 Relevance to Subproject"}}
--- Provides insight into **what factors contribute to drug court program success**.
--- Highlights **racial disparities in criminal justice-based rehabilitation programs**.
--- Supports **policy discussions on improving access to drug treatment for marginalized groups**.
--{{/expandable}}
--
--{{expandable summary="🔍 Suggestions for Further Exploration"}}
--1. Investigate **the role of mental health in drug court success rates**.
--2. Assess **long-term relapse prevention strategies post-treatment**.
--3. Explore **alternative diversion programs beyond traditional drug courts**.
--{{/expandable}}
--
--{{expandable summary="📄 Download Full Study"}}
--[[Download Full Study>>attach:10.1081_JA-120014424.pdf]]
--{{/expandable}}
--{{/expandable}}
--
--{{expandable summary="
--
--
--Study: Associations Between Cannabis Use and Mental Health Symptoms in Young Adults"}}
--
--{{/expandable}}
--
--{{expandable summary="Study: Is there a Dysgenic Secular Trend Towards Slowing Simple Reaction Time?"}}
++{{expand title="Study: Is there a Dysgenic Secular Trend Towards Slowing Simple Reaction Time?" expanded="false"}}
  **Source:** *Intelligence (Elsevier)*
  **Date of Publication:** *2014*
  **Author(s):** *Michael A. Woodley, Jan te Nijenhuis, Raegan Murphy*
  **Title:** *"Is there a Dysgenic Secular Trend Towards Slowing Simple Reaction Time?"*
  **DOI:** [10.1016/j.intell.2014.05.012](https://doi.org/10.1016/j.intell.2014.05.012)
--**Subject Matter:** *Cognitive Decline, Intelligence, Dysgenics*
++**Subject Matter:** *Cognitive Decline, Intelligence, Dysgenics*
--{{expandable summary="📊 Key Statistics"}}
++---
++
++## **Key Statistics**
 . **General Observations:**
     - The study examines reaction time data from **13 age-matched studies** spanning **1884–2004**.
     - Results suggest an estimated **decline of 13.35 IQ points** over this period.
@@ -1205,9 +1205,10 @@
 . **Other Significant Data Points:**
     - The estimated **dysgenic rate is 1.21 IQ points lost per decade**.
     - Meta-regression analysis confirmed a **steady secular trend in slowing reaction time**.
--{{/expandable}}
--{{expandable summary="🔬 Findings"}}
++---
++
++## **Findings**
 . **Primary Observations:**
     - Supports the hypothesis of **intelligence decline due to genetic and environmental factors**.
     - Reaction time, a **biomarker for cognitive ability**, has slowed significantly over time.
@@ -1219,9 +1219,10 @@
 . **Specific Case Analysis:**
     - Cross-national comparisons indicate a **global trend in slower reaction times**.
     - Factors like **modern neurotoxin exposure** and **reduced selective pressure for intelligence** may contribute.
--{{/expandable}}
--{{expandable summary="📝 Critique & Observations"}}
++---
++
++## **Critique and Observations**
 . **Strengths of the Study:**
     - **Comprehensive meta-analysis** covering over a century of reaction time data.
     - **Robust statistical corrections** for measurement variance between historical and modern studies.
@@ -1233,521 +1233,35 @@
 . **Suggestions for Improvement:**
     - Future studies should **replicate results with more modern datasets**.
     - Investigate **alternative cognitive biomarkers** for intelligence over time.
--{{/expandable}}
--{{expandable summary="📌 Relevance to Subproject"}}
++---
++
++## **Relevance to Subproject**
  - Provides evidence for **long-term intelligence trends**, contributing to research on **cognitive evolution**.
  - Aligns with broader discussions on **dysgenics, neurophysiology, and cognitive load**.
  - Supports the argument that **modern societies may be experiencing intelligence decline**.
--{{/expandable}}
--{{expandable summary="🔍 Suggestions for Further Exploration"}}
++---
++
++## **Suggestions for Further Exploration**
 . Investigate **genetic markers associated with reaction time** and intelligence decline.
 . Examine **regional variations in reaction time trends**.
 . Explore **cognitive resilience factors that counteract the decline**.
--{{/expandable}}
--{{expandable summary="📄 Download Full Study"}}
--[[Download Full Study>>attach:10.1016_j.intell.2014.05.012.pdf]]
--{{/expandable}}
--
++---
--= Whiteness & White Guilt =
--
--
--{{/expandable}}
++## **Summary of Research Study**
++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**.
--{{expandable summary="
++This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
++---
--Study: Segregation, Innocence, and Protection: The Institutional Conditions That Maintain Whiteness in College Sports"}}
--**Source:** *Journal of Diversity in Higher Education*
--**Date of Publication:** *2019*
--**Author(s):** *Kirsten Hextrum*
--**Title:** *"Segregation, Innocence, and Protection: The Institutional Conditions That Maintain Whiteness in College Sports"*
--**DOI:** [10.1037/dhe0000140](https://doi.org/10.1037/dhe0000140)
--**Subject Matter:** *Race and Sports, Higher Education, Institutional Racism*
++## **📄 Download Full Study**
++[[Download Full Study>>attach:10.1016_j.intell.2014.05.012.pdf]]
--{{expandable summary="📊 Key Statistics"}}
--1. **General Observations:**
--   - Analyzed **47 college athlete narratives** to explore racial disparities in non-revenue sports.
--   - Found three interrelated themes: **racial segregation, racial innocence, and racial protection**.
++{{/expand}}
--2. **Subgroup Analysis:**
--   - **Predominantly white sports programs** reinforce racial hierarchies in college athletics.
--   - **Recruitment policies favor white athletes** from affluent, suburban backgrounds.
++{{html}}<hr style="border: 3px solid red;">{{/html}}
--3. **Other Significant Data Points:**
--   - White athletes are **socialized to remain unaware of racial privilege** in their athletic careers.
--   - Media and institutional narratives protect white athletes from discussions on race and systemic inequities.
--{{/expandable}}
--{{expandable summary="🔬 Findings"}}
--1. **Primary Observations:**
--   - Colleges **actively recruit white athletes** from majority-white communities.
--   - Institutional policies **uphold whiteness** by failing to challenge racial biases in recruitment and team culture.
--
--2. **Subgroup Trends:**
--   - **White athletes show limited awareness** of their racial advantage in sports.
--   - **Black athletes are overrepresented** in revenue-generating sports but underrepresented in non-revenue teams.
--
--3. **Specific Case Analysis:**
--   - Examines **how sports serve as a mechanism for maintaining racial privilege** in higher education.
--   - Discusses the **role of athletics in reinforcing systemic segregation and exclusion**.
--{{/expandable}}
--
--{{expandable summary="📝 Critique & Observations"}}
--1. **Strengths of the Study:**
--   - **Comprehensive qualitative analysis** of race in college sports.
--   - Examines **institutional conditions** that sustain racial disparities in athletics.
--
--2. **Limitations of the Study:**
--   - Focuses primarily on **Division I non-revenue sports**, limiting generalizability to other divisions.
--   - Lacks extensive **quantitative data on racial demographics** in college athletics.
--
--3. **Suggestions for Improvement:**
--   - Future research should **compare recruitment policies across different sports and divisions**.
--   - Investigate **how athletic scholarships contribute to racial inequities in higher education**.
--{{/expandable}}
--
--{{expandable summary="📌 Relevance to Subproject"}}
--- Provides evidence of **systemic racial biases** in college sports recruitment.
--- Highlights **how institutional policies protect whiteness** in non-revenue athletics.
--- Supports research on **diversity, equity, and inclusion (DEI) efforts in sports and education**.
--{{/expandable}}
--
--{{expandable summary="🔍 Suggestions for Further Exploration"}}
--1. Investigate how **racial stereotypes influence college athlete recruitment**.
--2. Examine **the role of media in shaping public perceptions of race in sports**.
--3. Explore **policy reforms to increase racial diversity in non-revenue sports**.
--{{/expandable}}
--
--{{expandable summary="📄 Download Full Study"}}
--[[Download Full Study>>attach:10.1037_dhe0000140.pdf]]
--{{/expandable}}
--{{/expandable}}
--
--{{expandable summary="
--
--
--Study: Racial Bias in Pain Assessment and Treatment Recommendations"}}
--**Source:** *Proceedings of the National Academy of Sciences (PNAS)*
--**Date of Publication:** *2016*
--**Author(s):** *Kelly M. Hoffman, Sophie Trawalter, Jordan R. Axta, M. Norman Oliver*
--**Title:** *"Racial Bias in Pain Assessment and Treatment Recommendations, and False Beliefs About Biological Differences Between Blacks and Whites"*
--**DOI:** [10.1073/pnas.1516047113](https://doi.org/10.1073/pnas.1516047113)
--**Subject Matter:** *Health Disparities, Racial Bias, Medical Treatment*
--
--{{expandable summary="📊 Key Statistics"}}
--1. **General Observations:**
--   - Study analyzed **racial disparities in pain perception and treatment recommendations**.
--   - Found that **white laypeople and medical students endorsed false beliefs about biological differences** between Black and white individuals.
--
--2. **Subgroup Analysis:**
--   - **50% of medical students surveyed endorsed at least one false belief about biological differences**.
--   - Participants who held these false beliefs were **more likely to underestimate Black patients’ pain levels**.
--
--3. **Other Significant Data Points:**
--   - **Black patients were less likely to receive appropriate pain treatment** compared to white patients.
--   - The study confirmed that **historical misconceptions about racial differences still persist in modern medicine**.
--{{/expandable}}
--
--{{expandable summary="🔬 Findings"}}
--1. **Primary Observations:**
--   - False beliefs about biological racial differences **correlate with racial disparities in pain treatment**.
--   - Medical students and residents who endorsed these beliefs **showed greater racial bias in treatment recommendations**.
--
--2. **Subgroup Trends:**
--   - Physicians who **did not endorse these beliefs** showed **no racial bias** in treatment recommendations.
--   - Bias was **strongest among first-year medical students** and decreased slightly in later years of training.
--
--3. **Specific Case Analysis:**
--   - Study participants **underestimated Black patients' pain and recommended less effective pain treatments**.
--   - The study suggests that **racial disparities in medical care stem, in part, from these enduring false beliefs**.
--{{/expandable}}
--
--{{expandable summary="📝 Critique & Observations"}}
--1. **Strengths of the Study:**
--   - **First empirical study to connect false racial beliefs with medical decision-making**.
--   - Utilizes a **large sample of medical students and residents** from diverse institutions.
--
--2. **Limitations of the Study:**
--   - The study focuses on **Black vs. white disparities**, leaving other racial/ethnic groups unexplored.
--   - Participants' responses were based on **hypothetical medical cases, not real-world treatment decisions**.
--
--3. **Suggestions for Improvement:**
--   - Future research should examine **how these biases manifest in real clinical settings**.
--   - Investigate **whether medical training can correct these biases over time**.
--{{/expandable}}
--
--{{expandable summary="📌 Relevance to Subproject"}}
--- Highlights **racial disparities in healthcare**, specifically in pain assessment and treatment.
--- Supports **research on implicit bias and its impact on medical outcomes**.
--- Provides evidence for **the need to address racial bias in medical education**.
--{{/expandable}}
--
--{{expandable summary="🔍 Suggestions for Further Exploration"}}
--1. Investigate **interventions to reduce racial bias in medical decision-making**.
--2. Explore **how implicit bias training impacts pain treatment recommendations**.
--3. Conduct **real-world observational studies on racial disparities in healthcare settings**.
--{{/expandable}}
--
--{{expandable summary="📄 Download Full Study"}}
--[[Download Full Study>>attach:10.1073_pnas.1516047113.pdf]]
--{{/expandable}}
--{{/expandable}}
--
--{{expandable summary="
--
--
--Study: Rising Morbidity and Mortality in Midlife Among White Non-Hispanic Americans"}}
--**Source:** *Proceedings of the National Academy of Sciences (PNAS)*
--**Date of Publication:** *2015*
--**Author(s):** *Anne Case, Angus Deaton*
--**Title:** *"Rising Morbidity and Mortality in Midlife Among White Non-Hispanic Americans in the 21st Century"*
--**DOI:** [10.1073/pnas.1518393112](https://doi.org/10.1073/pnas.1518393112)
--**Subject Matter:** *Public Health, Mortality, Socioeconomic Factors*
--
--{{expandable summary="📊 Key Statistics"}}
--1. **General Observations:**
--   - Mortality rates among **middle-aged white non-Hispanic Americans (ages 45–54)** increased from 1999 to 2013.
--   - This reversal in mortality trends is unique to the U.S.; **no other wealthy country experienced a similar rise**.
--
--2. **Subgroup Analysis:**
--   - The increase was **most pronounced among those with a high school education or less**.
--   - Hispanic and Black non-Hispanic mortality continued to decline over the same period.
--
--3. **Other Significant Data Points:**
--   - Rising mortality was driven primarily by **suicide, drug and alcohol poisoning, and chronic liver disease**.
--   - Midlife morbidity increased as well, with more reports of **poor health, pain, and mental distress**.
--{{/expandable}}
--
--{{expandable summary="🔬 Findings"}}
--1. **Primary Observations:**
--   - The rise in mortality is attributed to **substance abuse, economic distress, and deteriorating mental health**.
--   - The increase in **suicides and opioid overdoses parallels broader socioeconomic decline**.
--
--2. **Subgroup Trends:**
--   - The **largest mortality increases** occurred among **whites without a college degree**.
--   - Chronic pain, functional limitations, and self-reported mental distress **rose significantly in affected groups**.
--
--3. **Specific Case Analysis:**
--   - **Educational attainment was a major predictor of mortality trends**, with better-educated individuals experiencing lower mortality rates.
--   - Mortality among **white Americans with a college degree continued to decline**, resembling trends in other wealthy nations.
--{{/expandable}}
--
--{{expandable summary="📝 Critique & Observations"}}
--1. **Strengths of the Study:**
--   - **First major study to highlight rising midlife mortality among U.S. whites**.
--   - Uses **CDC and Census mortality data spanning over a decade**.
--
--2. **Limitations of the Study:**
--   - Does not establish **causality** between economic decline and increased mortality.
--   - Lacks **granular data on opioid prescribing patterns and regional differences**.
--
--3. **Suggestions for Improvement:**
--   - Future studies should explore **how economic shifts, healthcare access, and mental health treatment contribute to these trends**.
--   - Further research on **racial and socioeconomic disparities in mortality trends** is needed.
--{{/expandable}}
--
--{{expandable summary="📌 Relevance to Subproject"}}
--- Highlights **socioeconomic and racial disparities** in health outcomes.
--- Supports research on **substance abuse and mental health crises in the U.S.**.
--- Provides evidence for **the role of economic instability in public health trends**.
--{{/expandable}}
--
--{{expandable summary="🔍 Suggestions for Further Exploration"}}
--1. Investigate **regional differences in rising midlife mortality**.
--2. Examine the **impact of the opioid crisis on long-term health trends**.
--3. Study **policy interventions aimed at reversing rising mortality rates**.
--{{/expandable}}
--
--{{expandable summary="📄 Download Full Study"}}
--[[Download Full Study>>attach:10.1073_pnas.1518393112.pdf]]
--{{/expandable}}
--{{/expandable}}
--
--{{expandable summary="
--
--
--Study: How Do People Without Migration Background Experience and Impact Today’s Superdiverse Cities?"}}
--**Source:** *Journal of Ethnic and Migration Studies*
--**Date of Publication:** *2023*
--**Author(s):** *Maurice Crul, Frans Lelie, Elif Keskiner, Laure Michon, Ismintha Waldring*
--**Title:** *"How Do People Without Migration Background Experience and Impact Today’s Superdiverse Cities?"*
--**DOI:** [10.1080/1369183X.2023.2182548](https://doi.org/10.1080/1369183X.2023.2182548)
--**Subject Matter:** *Urban Sociology, Migration Studies, Integration*
--
--{{expandable summary="📊 Key Statistics"}}
--1. **General Observations:**
--   - Study examines the role of **people without migration background** in majority-minority cities.
--   - Analyzes **over 3,000 survey responses and 150 in-depth interviews** from six North-Western European cities.
--
--2. **Subgroup Analysis:**
--   - Explores differences in **integration, social interactions, and perceptions of diversity**.
--   - Studies how **class, education, and neighborhood composition** affect adaptation to urban diversity.
--
--3. **Other Significant Data Points:**
--   - The study introduces the **Becoming a Minority (BaM) project**, a large-scale investigation of urban demographic shifts.
--   - **People without migration background perceive diversity differently**, with some embracing and others resisting change.
--{{/expandable}}
--
--{{expandable summary="🔬 Findings"}}
--1. **Primary Observations:**
--   - The study **challenges traditional integration theories**, arguing that non-migrant groups also undergo adaptation processes.
--   - Some residents **struggle with demographic changes**, while others see diversity as an asset.
--
--2. **Subgroup Trends:**
--   - Young, educated individuals in urban areas **are more open to cultural diversity**.
--   - Older and less mobile residents **report feelings of displacement and social isolation**.
--
--3. **Specific Case Analysis:**
--   - Examines how **people without migration background navigate majority-minority settings** in cities like Amsterdam and Vienna.
--   - Analyzes **whether former ethnic majority groups now perceive themselves as minorities**.
--{{/expandable}}
--
--{{expandable summary="📝 Critique & Observations"}}
--1. **Strengths of the Study:**
--   - **Innovative approach** by examining the impact of migration on native populations.
--   - Uses **both qualitative and quantitative data** for robust analysis.
--
--2. **Limitations of the Study:**
--   - Limited to **Western European urban settings**, missing perspectives from other global regions.
--   - Does not fully explore **policy interventions for fostering social cohesion**.
--
--3. **Suggestions for Improvement:**
--   - Expand research to **other geographical contexts** to understand migration effects globally.
--   - Investigate **long-term trends in urban adaptation and community building**.
--{{/expandable}}
--
--{{expandable summary="📌 Relevance to Subproject"}}
--- Provides a **new perspective on urban integration**, shifting focus from migrants to native-born populations.
--- Highlights the **role of social and economic power in shaping urban diversity outcomes**.
--- Challenges existing **assimilation theories by showing bidirectional adaptation in diverse cities**.
--{{/expandable}}
--
--{{expandable summary="🔍 Suggestions for Further Exploration"}}
--1. Study how **local policies shape attitudes toward urban diversity**.
--2. Investigate **the role of economic and housing policies in shaping demographic changes**.
--3. Explore **how social networks influence perceptions of migration and diversity**.
--{{/expandable}}
--
--{{expandable summary="📄 Download Full Study"}}
--[[Download Full Study>>attach:10.1080_1369183X.2023.2182548.pdf]]
--{{/expandable}}
--
--= Media =
--
--
--{{/expandable}}
--
--{{expandable summary="
--
--
--Study: The Role of Computer-Mediated Communication in Intergroup Conflic"}}
--**Source:** *Journal of Computer-Mediated Communication*
--**Date of Publication:** *2021*
--**Author(s):** *Zeynep Tufekci, Jesse Fox, Andrew Chadwick*
--**Title:** *"The Role of Computer-Mediated Communication in Intergroup Conflict"*
--**DOI:** [10.1093/jcmc/zmab003](https://doi.org/10.1093/jcmc/zmab003)
--**Subject Matter:** *Online Communication, Social Media, Conflict Studies*
--
--{{expandable summary="📊 Key Statistics"}}
--1. **General Observations:**
--   - Analyzed **over 500,000 social media interactions** related to intergroup conflict.
--   - Found that **computer-mediated communication (CMC) intensifies polarization**.
--
--2. **Subgroup Analysis:**
--   - **Anonymity and reduced social cues** in CMC increased hostility.
--   - **Echo chambers formed more frequently in algorithm-driven environments**.
--
--3. **Other Significant Data Points:**
--   - **Misinformation spread 3x faster** in polarized online discussions.
--   - Users exposed to **conflicting viewpoints were more likely to engage in retaliatory discourse**.
--{{/expandable}}
--
--{{expandable summary="🔬 Findings"}}
--1. **Primary Observations:**
--   - **Online interactions amplify intergroup conflict** due to selective exposure and confirmation bias.
--   - **Algorithmic sorting contributes to ideological segmentation**.
--
--2. **Subgroup Trends:**
--   - Participants with **strong pre-existing biases became more polarized** after exposure to conflicting views.
--   - **Moderate users were more likely to disengage** from conflict-heavy discussions.
--
--3. **Specific Case Analysis:**
--   - **CMC increased political tribalism** in digital spaces.
--   - **Emotional language spread more widely** than factual content.
--{{/expandable}}
--
--{{expandable summary="📝 Critique & Observations"}}
--1. **Strengths of the Study:**
--   - **Largest dataset** to date analyzing **CMC and intergroup conflict**.
--   - Uses **longitudinal data tracking user behavior over time**.
--
--2. **Limitations of the Study:**
--   - Lacks **qualitative analysis of user motivations**.
--   - Focuses on **Western social media platforms**, missing global perspectives.
--
--3. **Suggestions for Improvement:**
--   - Future studies should **analyze private messaging platforms** in conflict dynamics.
--   - Investigate **interventions that reduce online polarization**.
--{{/expandable}}
--
--{{expandable summary="📌 Relevance to Subproject"}}
--- Explores how **digital communication influences social division**.
--- Supports research on **social media regulation and conflict mitigation**.
--- Provides **data on misinformation and online radicalization trends**.
--{{/expandable}}
--
--{{expandable summary="🔍 Suggestions for Further Exploration"}}
--1. Investigate **how online anonymity affects real-world aggression**.
--2. Study **social media interventions that reduce political polarization**.
--3. Explore **cross-cultural differences in CMC and intergroup hostility**.
--{{/expandable}}
--
--{{expandable summary="📄 Download Full Study"}}
--[[Download Full Study>>attach:10.1093_jcmc_zmab003.pdf]]
--{{/expandable}}
--{{/expandable}}
--
--{{expandable summary="
--
--
--Study: Equality, Morality, and the Impact of Media Framing on Same-Sex Marriage and Civil Unions"}}
--**Source:** *Politics & Policy*
--**Date of Publication:** *2007*
--**Author(s):** *Tyler Johnson*
--**Title:** *"Equality, Morality, and the Impact of Media Framing: Explaining Opposition to Same-Sex Marriage and Civil Unions"*
--**DOI:** [10.1111/j.1747-1346.2007.00092.x](https://doi.org/10.1111/j.1747-1346.2007.00092.x)
--**Subject Matter:** *LGBTQ+ Rights, Public Opinion, Media Influence*
--
--{{expandable summary="📊 Key Statistics"}}
--1. **General Observations:**
--   - Examines **media coverage of same-sex marriage and civil unions from 2004 to 2011**.
--   - Analyzes how **media framing influences public opinion trends** on LGBTQ+ rights.
--
--2. **Subgroup Analysis:**
--   - **Equality-based framing decreases opposition** to same-sex marriage.
--   - **Morality-based framing increases opposition** to same-sex marriage.
--
--3. **Other Significant Data Points:**
--   - When **equality framing surpasses morality framing**, public opposition declines.
--   - Media framing **directly affects public attitudes** over time, shaping policy debates.
--{{/expandable}}
--
--{{expandable summary="🔬 Findings"}}
--1. **Primary Observations:**
--   - **Media framing plays a critical role in shaping attitudes** toward LGBTQ+ rights.
--   - **Equality-focused narratives** lead to greater public support for same-sex marriage.
--
--2. **Subgroup Trends:**
--   - **Religious and conservative audiences** respond more to morality-based framing.
--   - **Younger and progressive audiences** respond more to equality-based framing.
--
--3. **Specific Case Analysis:**
--   - **Periods of increased equality framing** saw measurable **declines in opposition to LGBTQ+ rights**.
--   - **Major political events (elections, Supreme Court cases) influenced framing trends**.
--{{/expandable}}
--
--{{expandable summary="📝 Critique & Observations"}}
--1. **Strengths of the Study:**
--   - **Longitudinal dataset spanning multiple election cycles**.
--   - Provides **quantitative analysis of how media framing shifts public opinion**.
--
--2. **Limitations of the Study:**
--   - Focuses **only on U.S. media coverage**, limiting global applicability.
--   - Does not account for **social media's growing influence** on public opinion.
--
--3. **Suggestions for Improvement:**
--   - Expand the study to **global perspectives on LGBTQ+ rights and media influence**.
--   - Investigate how **different media platforms (TV vs. digital media) impact opinion shifts**.
--{{/expandable}}
--
--{{expandable summary="📌 Relevance to Subproject"}}
--- Explores **how media narratives shape policy support and public sentiment**.
--- Highlights **the strategic importance of framing in LGBTQ+ advocacy**.
--- Reinforces the need for **media literacy in understanding policy debates**.
--{{/expandable}}
--
--{{expandable summary="🔍 Suggestions for Further Exploration"}}
--1. Examine how **social media affects framing of LGBTQ+ issues**.
--2. Study **differences in framing across political media outlets**.
--3. Investigate **public opinion shifts in states that legalized same-sex marriage earlier**.
--{{/expandable}}
--
--{{expandable summary="📄 Download Full Study"}}
--[[Download Full Study>>attach:10.1111_j.1747-1346.2007.00092.x_abstract.pdf]]
--{{/expandable}}
--{{/expandable}}
--
--{{expandable summary="
--
--
--Study: The Effects of Digital Media on Political Persuasion"}}
--**Source:** *Journal of Communication*
--**Date of Publication:** *2019*
--**Author(s):** *Natalie Stroud, Matthew Barnidge, Shannon McGregor*
--**Title:** *"The Effects of Digital Media on Political Persuasion: Evidence from Experimental Studies"*
--**DOI:** [10.1093/joc/jqx021](https://doi.org/10.1093/joc/jqx021)
--**Subject Matter:** *Media Influence, Political Communication, Persuasion*
--
--{{expandable summary="📊 Key Statistics"}}
--1. **General Observations:**
--   - Conducted **12 experimental studies** on **digital media's impact on political beliefs**.
--   - **58% of participants** showed shifts in political opinion based on online content.
--
--2. **Subgroup Analysis:**
--   - **Video-based content was 2x more persuasive** than text-based content.
--   - Participants **under age 35 were more susceptible to political messaging shifts**.
--
--3. **Other Significant Data Points:**
--   - **Interactive media (comment sections, polls) increased political engagement**.
--   - **Exposure to counterarguments reduced partisan bias** by **14% on average**.
--{{/expandable}}
--
--{{expandable summary="🔬 Findings"}}
--1. **Primary Observations:**
--   - **Digital media significantly influences political opinions**, with younger audiences being the most impacted.
--   - **Multimedia content is more persuasive** than traditional text-based arguments.
--
--2. **Subgroup Trends:**
--   - **Social media platforms had stronger persuasive effects** than news websites.
--   - Participants who engaged in **online discussions retained more political knowledge**.
--
--3. **Specific Case Analysis:**
--   - **Highly partisan users became more entrenched in their views**, even when exposed to opposing content.
--   - **Neutral or apolitical users were more likely to shift opinions**.
--{{/expandable}}
--
--{{expandable summary="📝 Critique & Observations"}}
--1. **Strengths of the Study:**
--   - **Large-scale experimental design** allows for controlled comparisons.
--   - Covers **multiple digital platforms**, ensuring robust findings.
--
--2. **Limitations of the Study:**
--   - Limited to **short-term persuasion effects**, without long-term follow-up.
--   - Does not explore **the role of misinformation in political persuasion**.
--
--3. **Suggestions for Improvement:**
--   - Future studies should track **long-term opinion changes** beyond immediate reactions.
--   - Investigate **the role of digital media literacy in resisting persuasion**.
--{{/expandable}}
--
--{{expandable summary="📌 Relevance to Subproject"}}
--- Provides insights into **how digital media shapes political discourse**.
--- Highlights **which platforms and content types are most influential**.
--- Supports **research on misinformation and online political engagement**.
--{{/expandable}}
--
--{{expandable summary="🔍 Suggestions for Further Exploration"}}
--1. Study how **fact-checking influences digital persuasion effects**.
--2. Investigate the **role of political influencers in shaping opinions**.
--3. Explore **long-term effects of social media exposure on political beliefs**.
--{{/expandable}}
--
--{{expandable summary="📄 Download Full Study"}}
--[[Download Full Study>>attach:10.1093_joc_jqx021.pdf]]
--##~{~{/expand}}##
--{{/expandable}}
--{{/expandable}}

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