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Wiki source code of Research at a Glance

Version 84.1 by Ryan C on 2025/03/16 07:11

version	line-number	content
2.1	1	= Research at a Glance =
	2
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2.1	4
83.1	5	Welcome to the Research at a Glance repository. This section serves as a centralized reference hub for key academic studies related to various important Racial themes. Each study is categorized for easy navigation and presented in a collapsible format to maintain a clean layout. I wanted to make this for a couple of reasons. Number one is organization. There are a ton of useful studies out there that expose the truth, sometimes inadvertently. You'll notice that in this initial draft the summaries are often woke and reflect the bias of the AI writing them as well as the researchers politically correct conclusions in most cases. That's because I havent gotten to going through and pointing out the reasons I put all of them in here. There is often an underlying hypocrisy or double standar, saying the quiet part out loud, or conclusions that are so much of an antithesis to what the data shows that made me want to include it. At least, thats the idea for once its polished. I have about 150 more studies to upload, so it will be a few weeks before I get through it all. Until such time, feel free to search for them yourself and edit in what you find, or add your own studies. If you like you can do it manually, or if you'd rather go the route I did, just feed the study into an AI and tell them to summarize the study using the following format:
4.1	6
84.1	7	{{example}}
	8	~{~{expand title="Study: [Study Title] (Click to Expand)" expanded="false"}}
	9	~~Source:~~ [Journal/Institution Name]
	10	~~Date of Publication:~~ [Publication Date]
	11	~~Author (s):~~ [Author (s) Name (s)]
	12	~~Title:~~ "[Study Title]"
	13	~~DOI:~~ [DOI or Link]
	14	~~Subject Matter:~~ [Broad Research Area, e.g., Social Psychology, Public Policy, Behavioral Economics]
83.1	15
84.1	16	~-~--
	17
	18	~#~# ~~Key Statistics~~
	19	~1. ~~General Observations:~~
	20	- [Statistical finding or observation]
	21	- [Statistical finding or observation]
	22
	23	2. ~~Subgroup Analysis:~~
	24	- [Breakdown of findings by gender, race, or other subgroups]
	25
	26	3. ~~Other Significant Data Points:~~
	27	- [Any additional findings or significant statistics]
	28
	29	~-~--
	30
	31	~#~# ~~Findings~~
	32	~1. ~~Primary Observations:~~
	33	- [High-level findings or trends in the study]
	34
	35	2. ~~Subgroup Trends:~~
	36	- [Disparities or differences highlighted in the study]
	37
	38	3. ~~Specific Case Analysis:~~
	39	- [Detailed explanation of any notable specific findings]
	40
	41	~-~--
	42
	43	~#~# ~~Critique and Observations~~
	44	~1. ~~Strengths of the Study:~~
	45	- [Examples: strong methodology, large dataset, etc.]
	46
	47	2. ~~Limitations of the Study:~~
	48	- [Examples: data gaps, lack of upstream analysis, etc.]
	49
	50	3. ~~Suggestions for Improvement:~~
	51	- [Ideas for further research or addressing limitations]
	52
	53	~-~--
	54
	55	~#~# ~~Relevance to Subproject~~
	56	- [Explanation of how this study contributes to your subproject goals.]
	57	- [Any key arguments or findings that support or challenge your views.]
	58
	59	~-~--
	60
	61	~#~# ~~Suggestions for Further Exploration~~
	62	~1. [Research questions or areas to investigate further.]
	63	2. [Potential studies or sources to complement this analysis.]
	64
	65	~-~--
	66
	67	~#~# ~~Summary of Research Study~~
	68	This study examines ~~[core research question or focus]~~, providing insights into ~~[main subject area]~~. The research utilized ~~[sample size and methodology]~~ to assess ~~[key variables or measured outcomes]~~.
	69	{{/example}}
	70
2.1	71	- Click on a category in the Table of Contents to browse studies related to that topic.
	72	- Click on a study title to expand its details, including key findings, critique, and relevance.
	73	- Use the search function (Ctrl + F or XWiki's built-in search) to quickly find specific topics or authors.
	74	- If needed, you can export this page as PDF or print-friendly format, and all studies will automatically expand for readability.
83.1	75	- You'll also find a download link to the original full study in pdf form at the bottom of the collapsible block.
2.1	76
	77
81.1	78	{{toc/}}
76.1	79
80.1	80
2.1	81
79.1	82
83.1	83
77.1	84	= Genetics =
3.1	85
79.1	86
77.1	87	== Study: Reconstructing Indian Population History ==
78.1	88
	89	{{expand expanded="false" title="Study: Reconstructing Indian Population History"}}
77.1	90	Source: Nature
	91	Date of Publication: 2009
	92	Author(s): David Reich, Kumarasamy Thangaraj, Nick Patterson, Alkes L. Price, Lalji Singh
	93	Title: "Reconstructing Indian Population History"
	94	DOI: [10.1038/nature08365](https://doi.org/10.1038/nature08365)
78.1	95	Subject Matter: Genetics, Population History, South Asian Ancestry
3.1	96
81.1	97	----
64.1	98
78.1	99	## Key Statistics##
	100
64.1	101	1. General Observations:
77.1	102	- Study analyzed 132 individuals from 25 diverse Indian groups.
	103	- Identified two major ancestral populations: Ancestral North Indians (ANI) and Ancestral South Indians (ASI).
64.1	104
	105	2. Subgroup Analysis:
77.1	106	- ANI ancestry is closely related to Middle Easterners, Central Asians, and Europeans.
	107	- ASI ancestry is genetically distinct from ANI and East Asians.
64.1	108
	109	3. Other Significant Data Points:
77.1	110	- ANI ancestry ranges from 39% to 71% across Indian groups.
	111	- Caste and linguistic differences strongly correlate with genetic variation.
64.1	112
81.1	113	----
64.1	114
78.1	115	## Findings##
	116
64.1	117	1. Primary Observations:
77.1	118	- The genetic landscape of India has been shaped by thousands of years of endogamy.
	119	- Groups with only ASI ancestry no longer exist in mainland India.
64.1	120
	121	2. Subgroup Trends:
77.1	122	- Higher ANI ancestry in upper-caste and Indo-European-speaking groups.
	123	- Andaman Islanders are unique in having ASI ancestry without ANI influence.
64.1	124
	125	3. Specific Case Analysis:
77.1	126	- Founder effects have maintained allele frequency differences among Indian groups.
	127	- Predicts higher incidence of recessive diseases due to historical genetic isolation.
64.1	128
81.1	129	----
64.1	130
78.1	131	## Critique and Observations##
	132
64.1	133	1. Strengths of the Study:
77.1	134	- First large-scale genetic analysis of Indian population history.
	135	- Introduces new methods for ancestry estimation without direct ancestral reference groups.
64.1	136
	137	2. Limitations of the Study:
77.1	138	- Limited sample size relative to India's population diversity.
	139	- Does not include recent admixture events post-colonial era.
64.1	140
	141	3. Suggestions for Improvement:
77.1	142	- Future research should expand sampling across more Indian tribal groups.
	143	- Use whole-genome sequencing for finer resolution of ancestry.
64.1	144
81.1	145	----
64.1	146
	147	## Relevance to Subproject
77.1	148	- Provides a genetic basis for caste and linguistic diversity in India.
	149	- Highlights founder effects and genetic drift shaping South Asian populations.
78.1	150	- Supports research on medical genetics and disease risk prediction in Indian populations.##
64.1	151
81.1	152	----
64.1	153
78.1	154	## Suggestions for Further Exploration##
	155
77.1	156	1. Examine genetic markers linked to disease susceptibility in Indian subpopulations.
	157	2. Investigate the impact of recent migration patterns on ANI-ASI ancestry distribution.
	158	3. Study gene flow between Indian populations and other global groups.
64.1	159
81.1	160	----
64.1	161
	162	## Summary of Research Study
78.1	163	This study reconstructs the genetic history of India, revealing two ancestral populations—ANI (related to West Eurasians) and ASI (distinctly South Asian). By analyzing 25 diverse Indian groups, the researchers demonstrate how historical endogamy and founder effects have maintained genetic differentiation. The findings have implications for medical genetics, population history, and the study of South Asian ancestry.##
64.1	164
77.1	165	This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
64.1	166
81.1	167	----
64.1	168
	169	## 📄 Download Full Study
78.1	170	[[Download Full Study>>attach:10.1038_nature08365.pdf]]##
65.1	171	{{/expand}}
64.1	172
	173
77.1	174	== Study: The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations ==
78.1	175
	176	{{expand expanded="false" title="Study: The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations"}}
77.1	177	Source: Nature
	178	Date of Publication: 2016
	179	Author(s): David Reich, Swapan Mallick, Heng Li, Mark Lipson, and others
	180	Title: "The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations"
	181	DOI: [10.1038/nature18964](https://doi.org/10.1038/nature18964)
78.1	182	Subject Matter: Human Genetic Diversity, Population History, Evolutionary Genomics
64.1	183
81.1	184	----
66.1	185
78.1	186	## Key Statistics##
	187
66.1	188	1. General Observations:
77.1	189	- Analyzed high-coverage genome sequences of 300 individuals from 142 populations.
	190	- Included many underrepresented and indigenous groups from Africa, Asia, Europe, and the Americas.
66.1	191
	192	2. Subgroup Analysis:
77.1	193	- Found higher genetic diversity within African populations compared to non-African groups.
	194	- Showed Neanderthal and Denisovan ancestry in non-African populations, particularly in Oceania.
66.1	195
	196	3. Other Significant Data Points:
77.1	197	- Identified 5.8 million base pairs absent from the human reference genome.
	198	- Estimated that mutations have accumulated 5% faster in non-Africans than in Africans.
66.1	199
81.1	200	----
66.1	201
78.1	202	## Findings##
	203
66.1	204	1. Primary Observations:
77.1	205	- African populations harbor the greatest genetic diversity, confirming an out-of-Africa dispersal model.
	206	- Indigenous Australians and New Guineans share a common ancestral population with other non-Africans.
66.1	207
	208	2. Subgroup Trends:
77.1	209	- Lower heterozygosity in non-Africans due to founder effects from migration bottlenecks.
	210	- Denisovan ancestry in South Asians is higher than previously thought.
66.1	211
	212	3. Specific Case Analysis:
77.1	213	- Neanderthal ancestry is higher in East Asians than in Europeans.
	214	- African hunter-gatherer groups show deep population splits over 100,000 years ago.
66.1	215
81.1	216	----
66.1	217
78.1	218	## Critique and Observations##
	219
66.1	220	1. Strengths of the Study:
77.1	221	- Largest global genetic dataset outside of the 1000 Genomes Project.
	222	- High sequencing depth allows more accurate identification of genetic variants.
66.1	223
	224	2. Limitations of the Study:
77.1	225	- Limited sample sizes for some populations, restricting generalizability.
	226	- Lacks ancient DNA comparisons, making it difficult to reconstruct deep ancestry fully.
66.1	227
	228	3. Suggestions for Improvement:
77.1	229	- Future studies should include ancient genomes to improve demographic modeling.
	230	- Expand research into how genetic variation affects health outcomes across populations.
66.1	231
81.1	232	----
66.1	233
	234	## Relevance to Subproject
77.1	235	- Provides comprehensive data on human genetic diversity, useful for evolutionary studies.
	236	- Supports research on Neanderthal and Denisovan introgression in modern human populations.
78.1	237	- Enhances understanding of genetic adaptation and disease susceptibility across groups.##
66.1	238
81.1	239	----
66.1	240
78.1	241	## Suggestions for Further Exploration##
	242
77.1	243	1. Investigate functional consequences of genetic variation in underrepresented populations.
	244	2. Study how selection pressures shaped genetic diversity across different environments.
	245	3. Explore medical applications of population-specific genetic markers.
66.1	246
81.1	247	----
66.1	248
	249	## Summary of Research Study
78.1	250	This study presents high-coverage genome sequences from 300 individuals across 142 populations, offering new insights into global genetic diversity and human evolution. The findings highlight deep African population splits, widespread archaic ancestry in non-Africans, and unique variants absent from the human reference genome. The research enhances our understanding of migration patterns, adaptation, and evolutionary history.##
66.1	251
77.1	252	This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
66.1	253
81.1	254	----
66.1	255
	256	## 📄 Download Full Study
78.1	257	[[Download Full Study>>attach:10.1038_nature18964.pdf]]##
66.1	258	{{/expand}}
	259
	260
77.1	261	== Study: Meta-analysis of the heritability of human traits based on fifty years of twin studies ==
78.1	262
	263	{{expand expanded="false" title="Study: Meta-analysis of the heritability of human traits based on fifty years of twin studies"}}
77.1	264	Source: Nature Genetics
	265	Date of Publication: 2015
	266	Author(s): Tinca J. C. Polderman, Beben Benyamin, Christiaan A. de Leeuw, Patrick F. Sullivan, Arjen van Bochoven, Peter M. Visscher, Danielle Posthuma
	267	Title: "Meta-analysis of the heritability of human traits based on fifty years of twin studies"
	268	DOI: [10.1038/ng.328](https://doi.org/10.1038/ng.328)
78.1	269	Subject Matter: Genetics, Heritability, Twin Studies, Behavioral Science
67.1	270
81.1	271	----
67.1	272
78.1	273	## Key Statistics##
	274
67.1	275	1. General Observations:
77.1	276	- Analyzed 17,804 traits from 2,748 twin studies published between 1958 and 2012.
	277	- Included data from 14,558,903 twin pairs, making it the largest meta-analysis on human heritability.
67.1	278
	279	2. Subgroup Analysis:
77.1	280	- Found 49% average heritability across all traits.
	281	- 69% of traits follow a simple additive genetic model, meaning most variance is due to genes, not environment.
67.1	282
	283	3. Other Significant Data Points:
77.1	284	- Neurological, metabolic, and psychiatric traits showed the highest heritability estimates.
	285	- Traits related to social values and environmental interactions had lower heritability estimates.
67.1	286
81.1	287	----
67.1	288
78.1	289	## Findings##
	290
67.1	291	1. Primary Observations:
77.1	292	- Across all traits, genetic factors play a significant role in individual differences.
	293	- The study contradicts models that overestimate environmental effects in behavioral and cognitive traits.
67.1	294
	295	2. Subgroup Trends:
78.1	296	- Eye and brain-related traits showed the highest heritability (70-80%).
77.1	297	- Shared environmental effects were negligible (<10%) for most traits.
67.1	298
	299	3. Specific Case Analysis:
77.1	300	- Twin correlations suggest limited evidence for strong non-additive genetic influences.
	301	- The study highlights missing heritability in complex traits, which genome-wide association studies (GWAS) have yet to fully explain.
67.1	302
81.1	303	----
67.1	304
78.1	305	## Critique and Observations##
	306
67.1	307	1. Strengths of the Study:
77.1	308	- Largest-ever heritability meta-analysis, covering nearly all published twin studies.
	309	- Provides a comprehensive framework for understanding gene-environment contributions.
67.1	310
	311	2. Limitations of the Study:
77.1	312	- Underrepresentation of African, South American, and Asian twin cohorts, limiting global generalizability.
	313	- Cannot fully separate genetic influences from potential cultural/environmental confounders.
67.1	314
	315	3. Suggestions for Improvement:
77.1	316	- Future research should use whole-genome sequencing for finer-grained heritability estimates.
	317	- Incorporate non-Western populations to assess global heritability trends.
67.1	318
81.1	319	----
67.1	320
	321	## Relevance to Subproject
77.1	322	- Establishes a quantitative benchmark for heritability across human traits.
	323	- Reinforces genetic influence on cognitive, behavioral, and physical traits.
78.1	324	- Highlights the need for genome-wide studies to identify missing heritability.##
67.1	325
81.1	326	----
67.1	327
78.1	328	## Suggestions for Further Exploration##
	329
77.1	330	1. Investigate how heritability estimates compare across different socioeconomic backgrounds.
	331	2. Examine gene-environment interactions in cognitive and psychiatric traits.
	332	3. Explore non-additive genetic effects on human traits using newer statistical models.
67.1	333
81.1	334	----
67.1	335
	336	## Summary of Research Study
78.1	337	This study presents a comprehensive meta-analysis of human trait heritability, covering over 50 years of twin research. The findings confirm genes play a predominant role in shaping human traits, with an average heritability of 49% across all measured characteristics. The research offers valuable insights into genetic and environmental influences, guiding future gene-mapping efforts and behavioral genetics studies.##
67.1	338
	339	This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
	340
81.1	341	----
67.1	342
	343	## 📄 Download Full Study
78.1	344	[[Download Full Study>>attach:10.1038_ng.328.pdf]]##
67.1	345	{{/expand}}
	346
	347
77.1	348	== Study: Genetic Analysis of African Populations: Human Evolution and Complex Disease ==
78.1	349
	350	{{expand expanded="false" title="Study: Genetic Analysis of African Populations: Human Evolution and Complex Disease"}}
77.1	351	Source: Nature Reviews Genetics
	352	Date of Publication: 2002
	353	Author(s): Sarah A. Tishkoff, Scott M. Williams
	354	Title: "Genetic Analysis of African Populations: Human Evolution and Complex Disease"
	355	DOI: [10.1038/nrg865](https://doi.org/10.1038/nrg865)
78.1	356	Subject Matter: Population Genetics, Human Evolution, Complex Diseases
67.1	357
81.1	358	----
68.1	359
78.1	360	## Key Statistics##
	361
68.1	362	1. General Observations:
77.1	363	- Africa harbors the highest genetic diversity of any region, making it key to understanding human evolution.
	364	- The study analyzes genetic variation and linkage disequilibrium (LD) in African populations.
68.1	365
	366	2. Subgroup Analysis:
77.1	367	- African populations exhibit greater genetic differentiation compared to non-Africans.
	368	- Migration and admixture have shaped modern African genomes over the past 100,000 years.
68.1	369
	370	3. Other Significant Data Points:
77.1	371	- The effective population size (Ne) of Africans is higher than that of non-African populations.
	372	- LD blocks are shorter in African genomes, suggesting more historical recombination events.
68.1	373
81.1	374	----
68.1	375
78.1	376	## Findings##
	377
68.1	378	1. Primary Observations:
77.1	379	- African populations are the most genetically diverse, supporting the Recent African Origin hypothesis.
	380	- Genetic variation in African populations can help fine-map complex disease genes.
68.1	381
	382	2. Subgroup Trends:
77.1	383	- West Africans exhibit higher genetic diversity than East Africans due to differing migration patterns.
	384	- Populations such as San hunter-gatherers show deep genetic divergence.
68.1	385
	386	3. Specific Case Analysis:
77.1	387	- Admixture in African Americans includes West African and European genetic contributions.
	388	- SNP (single nucleotide polymorphism) diversity in African genomes exceeds that of non-African groups.
68.1	389
81.1	390	----
68.1	391
78.1	392	## Critique and Observations##
	393
68.1	394	1. Strengths of the Study:
77.1	395	- Provides comprehensive genetic analysis of diverse African populations.
	396	- Highlights how genetic diversity impacts health disparities and disease risks.
68.1	397
	398	2. Limitations of the Study:
77.1	399	- Many African populations remain understudied, limiting full understanding of diversity.
	400	- Focuses more on genetic variation than on specific disease mechanisms.
68.1	401
	402	3. Suggestions for Improvement:
77.1	403	- Expand research into underrepresented African populations.
	404	- Integrate whole-genome sequencing for a more detailed evolutionary timeline.
68.1	405
81.1	406	----
68.1	407
	408	## Relevance to Subproject
77.1	409	- Supports genetic models of human evolution and the out-of-Africa hypothesis.
	410	- Reinforces Africa’s key role in disease gene mapping and precision medicine.
78.1	411	- Provides insight into historical migration patterns and their genetic impact.##
68.1	412
81.1	413	----
68.1	414
78.1	415	## Suggestions for Further Exploration##
	416
77.1	417	1. Investigate genetic adaptations to local environments within Africa.
	418	2. Study the role of African genetic diversity in disease resistance.
	419	3. Expand research on how ancient migration patterns shaped modern genetic structure.
68.1	420
81.1	421	----
68.1	422
	423	## Summary of Research Study
78.1	424	This study explores the genetic diversity of African populations, analyzing their role in human evolution and complex disease research. The findings highlight Africa’s unique genetic landscape, confirming it as the most genetically diverse continent. The research provides valuable insights into how genetic variation influences disease susceptibility, evolution, and population structure.##
68.1	425
	426	This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
	427
81.1	428	----
68.1	429
	430	## 📄 Download Full Study
78.1	431	[[Download Full Study>>attach:10.1038_nrg865MODERN.pdf]]##
68.1	432	{{/expand}}
	433
	434
77.1	435	== Study: Pervasive Findings of Directional Selection in Ancient DNA ==
78.1	436
	437	{{expand expanded="false" title="Study: Pervasive Findings of Directional Selection in Ancient DNA"}}
77.1	438	Source: bioRxiv Preprint
	439	Date of Publication: September 15, 2024
	440	Author(s): Ali Akbari, Alison R. Barton, Steven Gazal, Zheng Li, Mohammadreza Kariminejad, et al.
	441	Title: "Pervasive findings of directional selection realize the promise of ancient DNA to elucidate human adaptation"
	442	DOI: [10.1101/2024.09.14.613021](https://doi.org/10.1101/2024.09.14.613021)
78.1	443	Subject Matter: Genomics, Evolutionary Biology, Natural Selection
68.1	444
81.1	445	----
69.1	446
78.1	447	## Key Statistics##
	448
69.1	449	1. General Observations:
77.1	450	- Study analyzes 8,433 ancient individuals from the past 14,000 years.
	451	- Identifies 347 genome-wide significant loci showing strong selection.
69.1	452
	453	2. Subgroup Analysis:
77.1	454	- Examines West Eurasian populations and their genetic evolution.
	455	- Tracks changes in allele frequencies over millennia.
69.1	456
	457	3. Other Significant Data Points:
77.1	458	- 10,000 years of directional selection affected metabolic, immune, and cognitive traits.
	459	- Strong selection signals found for traits like skin pigmentation, cognitive function, and immunity.
69.1	460
81.1	461	----
69.1	462
78.1	463	## Findings##
	464
69.1	465	1. Primary Observations:
77.1	466	- Hundreds of alleles have been subject to directional selection over recent millennia.
	467	- Traits like immune function, metabolism, and cognitive performance show strong selection.
69.1	468
	469	2. Subgroup Trends:
77.1	470	- Selection pressure on energy storage genes supports the Thrifty Gene Hypothesis.
	471	- Cognitive performance-related alleles have undergone selection, but their historical advantages remain unclear.
69.1	472
	473	3. Specific Case Analysis:
77.1	474	- Celiac disease risk allele increased from 0% to 20% in 4,000 years.
	475	- Blood type B frequency rose from 0% to 8% in 6,000 years.
	476	- Tuberculosis risk allele fluctuated from 2% to 9% over 3,000 years before declining.
69.1	477
81.1	478	----
69.1	479
78.1	480	## Critique and Observations##
	481
69.1	482	1. Strengths of the Study:
77.1	483	- Largest dataset to date on natural selection in human ancient DNA.
	484	- Uses direct allele frequency tracking instead of indirect measures.
69.1	485
	486	2. Limitations of the Study:
77.1	487	- Findings may not translate directly to modern populations.
	488	- Unclear whether observed selection pressures persist today.
69.1	489
	490	3. Suggestions for Improvement:
77.1	491	- Expanding research to other global populations to assess universal trends.
	492	- Investigating long-term evolutionary trade-offs of selected alleles.
69.1	493
81.1	494	----
69.1	495
	496	## Relevance to Subproject
77.1	497	- Provides direct evidence of long-term genetic adaptation in human populations.
	498	- Supports theories on polygenic selection shaping human cognition, metabolism, and immunity.
78.1	499	- Highlights how past selection pressures may still influence modern health and disease prevalence.##
69.1	500
81.1	501	----
69.1	502
78.1	503	## Suggestions for Further Exploration##
	504
77.1	505	1. Examine selection patterns in non-European populations for comparison.
	506	2. Investigate how environmental and cultural shifts influenced genetic selection.
	507	3. Explore the genetic basis of traits linked to past and present-day human survival.
69.1	508
81.1	509	----
69.1	510
	511	## Summary of Research Study
78.1	512	This study examines how human genetic adaptation has unfolded over 14,000 years, using a large dataset of ancient DNA. It highlights strong selection on immune function, metabolism, and cognitive traits, revealing hundreds of loci affected by directional selection. The findings emphasize the power of ancient DNA in tracking human evolution and adaptation.##
69.1	513
81.1	514	----
69.1	515
	516	## 📄 Download Full Study
78.1	517	[[Download Full Study>>attach:10.1101_2024.09.14.613021doi_.pdf]]##
69.1	518	{{/expand}}
	519
79.1	520
77.1	521	== Study: The Wilson Effect: The Increase in Heritability of IQ With Age ==
78.1	522
	523	{{expand expanded="false" title="Study: The Wilson Effect: The Increase in Heritability of IQ With Age"}}
77.1	524	Source: Twin Research and Human Genetics (Cambridge University Press)
	525	Date of Publication: 2013
	526	Author(s): Thomas J. Bouchard Jr.
	527	Title: "The Wilson Effect: The Increase in Heritability of IQ With Age"
	528	DOI: [10.1017/thg.2013.54](https://doi.org/10.1017/thg.2013.54)
78.1	529	Subject Matter: Intelligence, Heritability, Developmental Psychology
69.1	530
81.1	531	----
69.1	532
78.1	533	## Key Statistics##
	534
69.1	535	1. General Observations:
77.1	536	- The study documents how the heritability of IQ increases with age, reaching an asymptote at 0.80 by adulthood.
	537	- Analysis is based on longitudinal twin and adoption studies.
69.1	538
	539	2. Subgroup Analysis:
77.1	540	- Shared environmental influence on IQ declines with age, reaching 0.10 in adulthood.
	541	- Monozygotic twins show increasing genetic similarity in IQ over time, while dizygotic twins become less concordant.
69.1	542
	543	3. Other Significant Data Points:
77.1	544	- Data from the Louisville Longitudinal Twin Study and cross-national twin samples support findings.
	545	- IQ stability over time is influenced more by genetics than by shared environmental factors.
69.1	546
81.1	547	----
69.1	548
78.1	549	## Findings##
	550
69.1	551	1. Primary Observations:
77.1	552	- Intelligence heritability strengthens throughout development, contrary to early environmental models.
	553	- Shared environmental effects decrease by late adolescence, emphasizing genetic influence in adulthood.
69.1	554
	555	2. Subgroup Trends:
77.1	556	- Studies from Scotland, Netherlands, and the US show consistent patterns of increasing heritability with age.
	557	- Findings hold across varied socio-economic and educational backgrounds.
69.1	558
	559	3. Specific Case Analysis:
77.1	560	- Longitudinal adoption studies show declining impact of adoptive parental influence on IQ as children age.
	561	- Cross-sectional twin data confirm higher IQ correlations for monozygotic twins in adulthood.
69.1	562
81.1	563	----
69.1	564
78.1	565	## Critique and Observations##
	566
69.1	567	1. Strengths of the Study:
77.1	568	- Robust dataset covering multiple twin and adoption studies over decades.
	569	- Clear, replicable trend demonstrating the increasing role of genetics in intelligence.
69.1	570
	571	2. Limitations of the Study:
77.1	572	- Findings apply primarily to Western industrialized nations, limiting generalizability.
	573	- Lack of neurobiological mechanisms explaining how genes express their influence over time.
69.1	574
	575	3. Suggestions for Improvement:
77.1	576	- Future research should investigate gene-environment interactions in cognitive aging.
	577	- Examine heritability trends in non-Western populations to determine cross-cultural consistency.
69.1	578
81.1	579	----
69.1	580
	581	## Relevance to Subproject
77.1	582	- Provides strong evidence for the genetic basis of intelligence.
	583	- Highlights the diminishing role of shared environment in cognitive development.
78.1	584	- Supports research on cognitive aging and heritability across the lifespan.##
69.1	585
81.1	586	----
69.1	587
78.1	588	## Suggestions for Further Exploration##
	589
77.1	590	1. Investigate neurogenetic pathways underlying IQ development.
	591	2. Examine how education and socioeconomic factors interact with genetic IQ influences.
	592	3. Study heritability trends in aging populations and cognitive decline.
69.1	593
81.1	594	----
69.1	595
	596	## Summary of Research Study
78.1	597	This study documents The Wilson Effect, demonstrating how the heritability of IQ increases throughout development, reaching a plateau of 0.80 by adulthood. The findings indicate that shared environmental effects diminish with age, while genetic influences on intelligence strengthen. Using longitudinal twin and adoption data, the research provides strong empirical support for the increasing role of genetics in cognitive ability over time.##
69.1	598
	599	This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
	600
81.1	601	----
69.1	602
	603	## 📄 Download Full Study
78.1	604	[[Download Full Study>>attach:10.1017_thg.2013.54.pdf]]##
69.1	605	{{/expand}}
	606
79.1	607
77.1	608	== Study: Is Homo sapiens polytypic? Human taxonomic diversity and its implications ==
78.1	609
	610	{{expand expanded="false" title="Study: Is Homo sapiens polytypic? Human taxonomic diversity and its implications"}}
69.1	611	Source: Medical Hypotheses (Elsevier)
	612	Date of Publication: 2010
	613	Author(s): Michael A. Woodley
	614	Title: "Is Homo sapiens polytypic? Human taxonomic diversity and its implications"
	615	DOI: [10.1016/j.mehy.2009.07.046](https://doi.org/10.1016/j.mehy.2009.07.046)
78.1	616	Subject Matter: Human Taxonomy, Evolutionary Biology, Anthropology
69.1	617
81.1	618	----
69.1	619
78.1	620	## Key Statistics##
	621
69.1	622	1. General Observations:
	623	- The study argues that Homo sapiens is polytypic, meaning it consists of multiple subspecies rather than a single monotypic species.
	624	- Examines genetic diversity, morphological variation, and evolutionary lineage in humans.
	625
	626	2. Subgroup Analysis:
	627	- Discusses four primary definitions of race/subspecies: Essentialist, Taxonomic, Population-based, and Lineage-based.
	628	- Suggests that human heterozygosity levels are comparable to species that are classified as polytypic.
	629
	630	3. Other Significant Data Points:
	631	- The study evaluates FST values (genetic differentiation measure) and argues that human genetic differentiation is comparable to that of recognized subspecies in other species.
	632	- Considers phylogenetic species concepts in defining human variation.
	633
81.1	634	----
69.1	635
78.1	636	## Findings##
	637
69.1	638	1. Primary Observations:
	639	- Proposes that modern human populations meet biological criteria for subspecies classification.
	640	- Highlights medical and evolutionary implications of human taxonomic diversity.
	641
	642	2. Subgroup Trends:
	643	- Discusses how race concepts evolved over time in biological sciences.
	644	- Compares human diversity with that of other primates such as chimpanzees and gorillas.
	645
	646	3. Specific Case Analysis:
	647	- Evaluates how genetic markers correlate with population structure.
	648	- Addresses the controversy over race classification in modern anthropology.
	649
81.1	650	----
69.1	651
78.1	652	## Critique and Observations##
	653
69.1	654	1. Strengths of the Study:
	655	- Uses comparative species analysis to assess human classification.
	656	- Provides a biological perspective on the race concept, moving beyond social constructivism arguments.
	657
	658	2. Limitations of the Study:
	659	- Controversial topic with strong opposing views in anthropology and genetics.
	660	- Relies on broad genetic trends, but does not analyze individual-level genetic variation in depth.
	661
	662	3. Suggestions for Improvement:
	663	- Further research should incorporate whole-genome studies to refine subspecies classifications.
	664	- Investigate how admixture affects taxonomic classification over time.
	665
81.1	666	----
69.1	667
	668	## Relevance to Subproject
	669	- Contributes to discussions on evolutionary taxonomy and species classification.
	670	- Provides evidence on genetic differentiation among human populations.
78.1	671	- Highlights historical and contemporary scientific debates on race and human variation.##
69.1	672
81.1	673	----
69.1	674
78.1	675	## Suggestions for Further Exploration##
	676
69.1	677	1. Examine FST values in modern and ancient human populations.
	678	2. Investigate how adaptive evolution influences population differentiation.
	679	3. Explore the impact of genetic diversity on medical treatments and disease susceptibility.
	680
81.1	681	----
69.1	682
	683	## Summary of Research Study
78.1	684	This study evaluates whether Homo sapiens should be classified as a polytypic species, analyzing genetic diversity, evolutionary lineage, and morphological variation. Using comparative analysis with other primates and mammals, the research suggests that human populations meet biological criteria for subspecies classification, with implications for evolutionary biology, anthropology, and medicine.##
69.1	685
	686	This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
	687
81.1	688	----
69.1	689
	690	## 📄 Download Full Study
78.1	691	[[Download Full Study>>attach:10.1016_j.mehy.2009.07.046.pdf]]##
69.1	692	{{/expand}}
	693
	694
77.1	695	== Study: Survey of Expert Opinion on Intelligence: Intelligence Research, Experts' Background, Controversial Issues, and the Media ==
78.1	696
	697	{{expand expanded="false" title="Study: Survey of Expert Opinion on Intelligence: Intelligence Research, Experts' Background, Controversial Issues, and the Media"}}
77.1	698	Source: Intelligence (Elsevier)
	699	Date of Publication: 2019
	700	Author(s): Heiner Rindermann, David Becker, Thomas R. Coyle
	701	Title: "Survey of Expert Opinion on Intelligence: Intelligence Research, Experts' Background, Controversial Issues, and the Media"
	702	DOI: [10.1016/j.intell.2019.101406](https://doi.org/10.1016/j.intell.2019.101406)
78.1	703	Subject Matter: Psychology, Intelligence Research, Expert Analysis
69.1	704
81.1	705	----
69.1	706
78.1	707	## Key Statistics##
	708
69.1	709	1. General Observations:
77.1	710	- Survey of 102 experts on intelligence research and public discourse.
	711	- Evaluated experts' backgrounds, political affiliations, and views on controversial topics in intelligence research.
69.1	712
	713	2. Subgroup Analysis:
77.1	714	- 90% of experts were from Western countries, and 83% were male.
	715	- Political spectrum ranged from 54% left-liberal, 24% conservative, with significant ideological influences on views.
69.1	716
	717	3. Other Significant Data Points:
77.1	718	- Experts rated media coverage of intelligence research as poor (avg. 3.1 on a 9-point scale).
	719	- 50% of experts attributed US Black-White IQ differences to genetic factors, 50% to environmental factors.
69.1	720
81.1	721	----
69.1	722
78.1	723	## Findings##
	724
69.1	725	1. Primary Observations:
77.1	726	- Experts overwhelmingly support the g-factor theory of intelligence.
	727	- Heritability of intelligence was widely accepted, though views differed on race and group differences.
69.1	728
	729	2. Subgroup Trends:
77.1	730	- Left-leaning experts were more likely to reject genetic explanations for group IQ differences.
	731	- Right-leaning experts tended to favor a stronger role for genetic factors in intelligence disparities.
69.1	732
	733	3. Specific Case Analysis:
77.1	734	- The study compared media coverage of intelligence research with expert opinions.
	735	- Found a disconnect between journalists and intelligence researchers, especially regarding politically sensitive issues.
69.1	736
81.1	737	----
69.1	738
78.1	739	## Critique and Observations##
	740
69.1	741	1. Strengths of the Study:
77.1	742	- Largest expert survey on intelligence research to date.
	743	- Provides insight into how political orientation influences scientific perspectives.
69.1	744
	745	2. Limitations of the Study:
77.1	746	- Sample primarily from Western countries, limiting global perspectives.
	747	- Self-selection bias may skew responses toward those more willing to engage with controversial topics.
69.1	748
	749	3. Suggestions for Improvement:
77.1	750	- Future studies should include a broader range of global experts.
	751	- Additional research needed on media biases and misrepresentation of intelligence research.
69.1	752
81.1	753	----
69.1	754
	755	## Relevance to Subproject
77.1	756	- Provides insight into expert consensus and division on intelligence research.
	757	- Highlights the role of media bias in shaping public perception of intelligence science.
78.1	758	- Useful for understanding the intersection of science, politics, and public discourse on intelligence research.##
69.1	759
81.1	760	----
69.1	761
78.1	762	## Suggestions for Further Exploration##
	763
77.1	764	1. Examine cross-national differences in expert opinions on intelligence.
	765	2. Investigate how media bias impacts public understanding of intelligence research.
	766	3. Conduct follow-up studies with a more diverse expert pool to test findings.
69.1	767
81.1	768	----
69.1	769
	770	## Summary of Research Study
78.1	771	This study surveys expert opinions on intelligence research, analyzing how backgrounds, political ideologies, and media representation influence perspectives on intelligence. The findings highlight divisions in scientific consensus, particularly on genetic vs. environmental causes of IQ disparities. Additionally, the research uncovers widespread dissatisfaction with media portrayals of intelligence research, pointing to the impact of ideological biases on public discourse.##
69.1	772
	773	This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
	774
81.1	775	----
69.1	776
	777	## 📄 Download Full Study
78.1	778	[[Download Full Study>>attach:10.1016_j.intell.2019.101406.pdf]]##
69.1	779	{{/expand}}
	780
70.1	781
77.1	782	== Study: A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation ==
78.1	783
	784	{{expand expanded="false" title="Study: A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation"}}
77.1	785	Source: Intelligence (Elsevier)
	786	Date of Publication: 2015
	787	Author(s): Davide Piffer
	788	Title: "A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation"
	789	DOI: [10.1016/j.intell.2015.08.008](https://doi.org/10.1016/j.intell.2015.08.008)
78.1	790	Subject Matter: Genetics, Intelligence, GWAS, Population Differences
70.1	791
81.1	792	----
70.1	793
78.1	794	## Key Statistics##
	795
70.1	796	1. General Observations:
77.1	797	- Study analyzed genome-wide association studies (GWAS) hits linked to intelligence.
	798	- Found a strong correlation (r = .91) between polygenic intelligence scores and national IQ levels.
70.1	799
	800	2. Subgroup Analysis:
77.1	801	- Factor analysis of 9 intelligence-associated alleles revealed a metagene correlated with country IQ (r = .86).
	802	- Allele frequencies varied significantly by continent, aligning with observed population differences in cognitive ability.
70.1	803
	804	3. Other Significant Data Points:
77.1	805	- GWAS intelligence SNPs predicted IQ levels more strongly than random genetic markers.
	806	- Genetic differentiation (Fst values) showed that selection pressure, rather than drift, influenced intelligence-related allele distributions.
70.1	807
81.1	808	----
70.1	809
78.1	810	## Findings##
	811
70.1	812	1. Primary Observations:
77.1	813	- Intelligence-associated SNP frequencies correlate highly with national IQ levels.
	814	- Genetic selection for intelligence appears stronger than selection for height-related genes.
70.1	815
	816	2. Subgroup Trends:
77.1	817	- East Asian populations exhibited the highest frequencies of intelligence-associated alleles.
	818	- African populations showed lower frequencies compared to European and East Asian populations.
70.1	819
	820	3. Specific Case Analysis:
77.1	821	- Polygenic scores using intelligence-related alleles significantly outperformed random SNPs in predicting IQ.
	822	- Selection pressures may explain differences in global intelligence distribution beyond genetic drift effects.
70.1	823
81.1	824	----
70.1	825
78.1	826	## Critique and Observations##
	827
70.1	828	1. Strengths of the Study:
77.1	829	- Comprehensive genetic analysis of intelligence-linked SNPs.
	830	- Uses multiple statistical methods (factor analysis, Fst analysis) to confirm results.
70.1	831
	832	2. Limitations of the Study:
77.1	833	- Correlation does not imply causation; factors beyond genetics influence intelligence.
	834	- Limited number of GWAS-identified intelligence alleles—future studies may identify more.
70.1	835
	836	3. Suggestions for Improvement:
77.1	837	- Larger cross-population GWAS studies needed to validate findings.
	838	- Investigate non-genetic contributors to IQ variance in addition to genetic factors.
70.1	839
81.1	840	----
70.1	841
	842	## Relevance to Subproject
77.1	843	- Supports research on genetic influences on intelligence at a population level.
	844	- Aligns with broader discussions on cognitive genetics and natural selection effects.
78.1	845	- Provides a quantitative framework for analyzing polygenic selection in intelligence studies.##
70.1	846
81.1	847	----
70.1	848
78.1	849	## Suggestions for Further Exploration##
	850
77.1	851	1. Conduct expanded GWAS studies including diverse populations.
	852	2. Investigate gene-environment interactions influencing intelligence.
	853	3. Explore historical selection pressures shaping intelligence-related alleles.
70.1	854
81.1	855	----
70.1	856
	857	## Summary of Research Study
78.1	858	This study reviews genome-wide association study (GWAS) findings on intelligence, demonstrating a strong correlation between polygenic intelligence scores and national IQ levels. The research highlights how genetic selection may explain population-level cognitive differences beyond genetic drift effects. Intelligence-linked alleles showed higher variability across populations than height-related alleles, suggesting stronger selection pressures. ##
70.1	859
	860	This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
	861
81.1	862	----
70.1	863
	864	## 📄 Download Full Study
78.1	865	[[Download Full Study>>attach:10.1016_j.intell.2015.08.008.pdf]]##
70.1	866	{{/expand}}
	867
79.1	868
77.1	869	== Study: Genetic Structure, Self-Identified Race/Ethnicity, and Confounding ==
78.1	870
77.1	871	{{expand expanded="false" title="Click here to expand details"}}
	872	Source: Journal of Genetic Epidemiology
	873	Date of Publication: 2024-01-15
	874	Author(s): Smith et al.
	875	Title: "Genetic Structure, Self-Identified Race/Ethnicity, and Confounding in Case-Control Association Studies"
	876	DOI: [https://doi.org/10.1037/1076-8971.11.2.235](https://doi.org/10.1037/1076-8971.11.2.235)
78.1	877	Subject Matter: Genetics, Social Science
70.1	878
77.1	879	Tags: `Genetics` `Race & Ethnicity` `Biomedical Research`
70.1	880
82.1	881	Key Statistics
70.1	882
	883	1. General Observations:
77.1	884	- A near-perfect alignment between self-identified race/ethnicity (SIRE) and genetic ancestry was observed.
	885	- Misclassification rate: 0.14%.
70.1	886
	887	2. Subgroup Analysis:
77.1	888	- Four groups analyzed: White, African American, East Asian, and Hispanic.
	889	- Hispanic genetic clusters showed significant European and Native American lineage.
70.1	890
82.1	891	Findings
70.1	892
77.1	893	- Self-identified race strongly aligns with genetic ancestry.
	894	- Minor discrepancies exist but do not significantly impact classification.
70.1	895
82.1	896	Relevance to Subproject
70.1	897
77.1	898	- Reinforces the reliability of self-reported racial identity in genetic research.
	899	- Highlights policy considerations in biomedical studies.
	900	{{/expand}}
70.1	901
	902
81.1	903	----
70.1	904
77.1	905	= Dating and Interpersonal Relationships =
70.1	906
79.1	907
77.1	908	== Study: Trends in Frequency of Sexual Activity and Number of Sexual Partners Among Adults Aged 18 to 44 Years in the US, 2000-2018 ==
78.1	909
	910	{{expand expanded="false" title="Study: Trends in Frequency of Sexual Activity and Number of Sexual Partners Among Adults Aged 18 to 44 Years in the US, 2000-2018"}}
77.1	911	Source: JAMA Network Open
	912	Date of Publication: 2020
	913	Author(s): Ueda P, Mercer CH, Ghaznavi C, Herbenick D.
	914	Title: "Trends in Frequency of Sexual Activity and Number of Sexual Partners Among Adults Aged 18 to 44 Years in the US, 2000-2018"
	915	DOI: [10.1001/jamanetworkopen.2020.3833](https://doi.org/10.1001/jamanetworkopen.2020.3833)
78.1	916	Subject Matter: Public Health, Sexual Behavior, Demography
70.1	917
81.1	918	----
70.1	919
78.1	920	## Key Statistics##
	921
70.1	922	1. General Observations:
77.1	923	- Study analyzed General Social Survey (2000-2018) data.
	924	- Found declining trends in sexual activity among young adults.
70.1	925
	926	2. Subgroup Analysis:
77.1	927	- Decreases in sexual activity were most prominent among men aged 18-34.
	928	- Factors like marital status, employment, and psychological well-being were associated with changes in sexual frequency.
70.1	929
	930	3. Other Significant Data Points:
77.1	931	- Frequency of sexual activity decreased by 8-10% over the studied period.
	932	- Number of sexual partners remained relatively stable despite declining activity rates.
70.1	933
81.1	934	----
70.1	935
78.1	936	## Findings##
	937
70.1	938	1. Primary Observations:
77.1	939	- A significant decline in sexual frequency, especially among younger men.
	940	- Shifts in relationship dynamics and economic stressors may contribute to the trend.
70.1	941
	942	2. Subgroup Trends:
77.1	943	- More pronounced decline among unmarried individuals.
	944	- No major change observed for married adults over time.
70.1	945
	946	3. Specific Case Analysis:
77.1	947	- Mental health and employment status were correlated with decreased activity.
	948	- Social factors such as screen time and digital entertainment consumption are potential contributors.
70.1	949
81.1	950	----
70.1	951
78.1	952	## Critique and Observations##
	953
70.1	954	1. Strengths of the Study:
77.1	955	- Large sample size from a nationally representative dataset.
	956	- Longitudinal design enables trend analysis over time.
70.1	957
	958	2. Limitations of the Study:
77.1	959	- Self-reported data may introduce response bias.
	960	- No direct causal mechanisms tested for the decline in sexual activity.
70.1	961
	962	3. Suggestions for Improvement:
77.1	963	- Further studies should incorporate qualitative data on behavioral shifts.
	964	- Additional factors such as economic shifts and social media usage need exploration.
70.1	965
81.1	966	----
70.1	967
	968	## Relevance to Subproject
77.1	969	- Provides evidence on changing demographic behaviors in relation to relationships and social interactions.
78.1	970	- Highlights the role of mental health, employment, and societal changes in personal behaviors.##
70.1	971
81.1	972	----
70.1	973
78.1	974	## Suggestions for Further Exploration##
	975
77.1	976	1. Investigate the impact of digital media consumption on relationship dynamics.
	977	2. Examine regional and cultural differences in sexual activity trends.
70.1	978
81.1	979	----
70.1	980
	981	## Summary of Research Study
78.1	982	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. ##
70.1	983
77.1	984	This summary provides an accessible, at-a-glance overview of the study's contributions. Please refer to the full paper for in-depth analysis.
70.1	985
81.1	986	----
70.1	987
	988	## 📄 Download Full Study
77.1	989	{{velocity}}
	990	#set($doi = "10.1001_jamanetworkopen.2020.3833")
	991	#set($filename = "${doi}.pdf")
	992	#if($xwiki.exists("attach:$filename"))
	993	[[Download>>attach:$filename]]
	994	#else
	995	{{html}}<span style="color: red; font-weight: bold;">🚨 PDF Not Available 🚨</span>{{/html}}
78.1	996	#end {{/velocity}}##
70.1	997	{{/expand}}
	998
	999
77.1	1000	== Study: Biracial Couples and Adverse Birth Outcomes – A Systematic Review and Meta-Analysis ==
78.1	1001
	1002	{{expand expanded="false" title="Study: Biracial Couples and Adverse Birth Outcomes – A Systematic Review and Meta-Analysis"}}
77.1	1003	Source: Acta Obstetricia et Gynecologica Scandinavica
	1004	Date of Publication: 2012
	1005	Author(s): Ravisha M. Srinivasjois, Shreya Shah, Prakesh S. Shah, Knowledge Synthesis Group on Determinants of Preterm/LBW Births
	1006	Title: "Biracial Couples and Adverse Birth Outcomes: A Systematic Review and Meta-Analysis"
	1007	DOI: [10.1111/j.1600-0412.2012.01501.x](https://doi.org/10.1111/j.1600-0412.2012.01501.x)
78.1	1008	Subject Matter: Neonatal Health, Maternal-Fetal Medicine, Racial Disparities
70.1	1009
81.1	1010	----
70.1	1011
78.1	1012	## Key Statistics##
	1013
70.1	1014	1. General Observations:
77.1	1015	- Meta-analysis of 26,335,596 singleton births from eight studies.
	1016	- Higher risk of adverse birth outcomes in biracial couples than White couples, but lower than Black couples.
70.1	1017
	1018	2. Subgroup Analysis:
77.1	1019	- Maternal race had a stronger influence than paternal race on birth outcomes.
	1020	- Black mother–White father (BMWF) couples had a higher risk than White mother–Black father (WMBF) couples.
70.1	1021
	1022	3. Other Significant Data Points:
77.1	1023	- Adjusted Odds Ratios (aORs) for key outcomes:
	1024	- Low birthweight (LBW): WMBF (1.21), BMWF (1.75), Black mother–Black father (BMBF) (2.08).
	1025	- Preterm births (PTB): WMBF (1.17), BMWF (1.37), BMBF (1.78).
	1026	- Stillbirths: WMBF (1.43), BMWF (1.51), BMBF (1.85).
70.1	1027
81.1	1028	----
70.1	1029
78.1	1030	## Findings##
	1031
70.1	1032	1. Primary Observations:
77.1	1033	- Biracial couples face a gradient of risk: higher than White couples but lower than Black couples.
	1034	- Maternal race plays a more significant role in pregnancy outcomes.
70.1	1035
	1036	2. Subgroup Trends:
77.1	1037	- Black mothers (regardless of paternal race) had the highest risk of LBW and PTB.
	1038	- White mothers with Black fathers had a lower risk than Black mothers with White fathers.
70.1	1039
	1040	3. Specific Case Analysis:
77.1	1041	- The weathering hypothesis suggests that long-term stress exposure contributes to higher adverse birth risks in Black mothers.
	1042	- Genetic and environmental factors may interact to influence birth outcomes.
70.1	1043
81.1	1044	----
70.1	1045
78.1	1046	## Critique and Observations##
	1047
70.1	1048	1. Strengths of the Study:
77.1	1049	- Largest meta-analysis on racial disparities in birth outcomes.
	1050	- Uses adjusted statistical models to account for confounding variables.
70.1	1051
	1052	2. Limitations of the Study:
77.1	1053	- Data limited to Black-White biracial couples, excluding other racial groups.
	1054	- Socioeconomic and healthcare access factors not fully explored.
70.1	1055
	1056	3. Suggestions for Improvement:
77.1	1057	- Future studies should examine Asian, Hispanic, and Indigenous biracial couples.
	1058	- Investigate long-term health effects on infants from biracial pregnancies.
70.1	1059
81.1	1060	----
70.1	1061
	1062	## Relevance to Subproject
77.1	1063	- Provides critical insights into racial disparities in maternal and infant health.
	1064	- Supports research on genetic and environmental influences on neonatal health.
78.1	1065	- Highlights how maternal race plays a more significant role than paternal race in birth outcomes.##
70.1	1066
81.1	1067	----
70.1	1068
78.1	1069	## Suggestions for Further Exploration##
	1070
77.1	1071	1. Investigate the role of prenatal care quality in mitigating racial disparities.
	1072	2. Examine how social determinants of health impact biracial pregnancy outcomes.
	1073	3. Explore gene-environment interactions influencing birthweight and prematurity risks.
70.1	1074
81.1	1075	----
70.1	1076
	1077	## Summary of Research Study
78.1	1078	This meta-analysis examines the impact of biracial parentage on birth outcomes, showing that biracial couples face a higher risk of adverse pregnancy outcomes than White couples but lower than Black couples. The findings emphasize maternal race as a key factor in birth risks, with Black mothers having the highest rates of preterm birth and low birthweight, regardless of paternal race.##
70.1	1079
81.1	1080	----
70.1	1081
	1082	## 📄 Download Full Study
78.1	1083	[[Download Full Study>>attach:10.1111_j.1600-0412.2012.01501.xAbstract.pdf]]##
70.1	1084	{{/expand}}
	1085
	1086
77.1	1087	== Study: One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness ==
78.1	1088
	1089	{{expand expanded="false" title="Study: One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness"}}
77.1	1090	Source: Current Psychology
	1091	Date of Publication: 2024
	1092	Author(s): Brandon Sparks, Alexandra M. Zidenberg, Mark E. Olver
	1093	Title: "One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness"
	1094	DOI: [10.1007/s12144-023-04275-z](https://doi.org/10.1007/s12144-023-04275-z)
78.1	1095	Subject Matter: Psychology, Mental Health, Social Isolation
70.1	1096
81.1	1097	----
70.1	1098
78.1	1099	## Key Statistics##
	1100
70.1	1101	1. General Observations:
77.1	1102	- Study analyzed 67 self-identified incels and 103 non-incel men.
	1103	- Incels reported higher loneliness and lower social support compared to non-incels.
70.1	1104
	1105	2. Subgroup Analysis:
77.1	1106	- Incels exhibited higher levels of depression, anxiety, and self-critical rumination.
	1107	- Social isolation was a key factor differentiating incels from non-incels.
70.1	1108
	1109	3. Other Significant Data Points:
77.1	1110	- 95% of incels in the study reported having depression, with 38% receiving a formal diagnosis.
	1111	- Higher externalization of blame was linked to stronger incel identification.
70.1	1112
81.1	1113	----
70.1	1114
78.1	1115	## Findings##
	1116
70.1	1117	1. Primary Observations:
77.1	1118	- Incels experience heightened rejection sensitivity and loneliness.
	1119	- Lack of social support correlates with worse mental health outcomes.
70.1	1120
	1121	2. Subgroup Trends:
77.1	1122	- Avoidant attachment styles were a strong predictor of incel identity.
	1123	- Mate value perceptions significantly differed between incels and non-incels.
70.1	1124
	1125	3. Specific Case Analysis:
77.1	1126	- Incels engaged in fewer positive coping mechanisms such as emotional support or positive reframing.
	1127	- Instead, they relied on solitary coping strategies, worsening their isolation.
70.1	1128
81.1	1129	----
70.1	1130
78.1	1131	## Critique and Observations##
	1132
70.1	1133	1. Strengths of the Study:
77.1	1134	- First quantitative study on incels’ social isolation and mental health.
	1135	- Robust sample size and validated psychological measures.
70.1	1136
	1137	2. Limitations of the Study:
77.1	1138	- Sample drawn from Reddit communities, which may not represent all incels.
	1139	- No causal conclusions—correlations between isolation and inceldom need further research.
70.1	1140
	1141	3. Suggestions for Improvement:
77.1	1142	- Future studies should compare incel forum users vs. non-users.
	1143	- Investigate potential intervention strategies for social integration.
70.1	1144
81.1	1145	----
70.1	1146
	1147	## Relevance to Subproject
77.1	1148	- Highlights mental health vulnerabilities within the incel community.
	1149	- Supports research on loneliness, attachment styles, and social dominance orientation.
78.1	1150	- Examines how peer rejection influences self-perceived mate value.##
70.1	1151
81.1	1152	----
70.1	1153
78.1	1154	## Suggestions for Further Exploration##
	1155
77.1	1156	1. Explore how online community participation affects incel mental health.
	1157	2. Investigate cognitive biases influencing self-perceived rejection among incels.
	1158	3. Assess therapeutic interventions to address incel social isolation.
70.1	1159
81.1	1160	----
70.1	1161
	1162	## Summary of Research Study
78.1	1163	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.##
70.1	1164
	1165	This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
	1166
81.1	1167	----
70.1	1168
	1169	## 📄 Download Full Study
78.1	1170	[[Download Full Study>>attach:10.1007_s12144-023-04275-z.pdf]]##
70.1	1171	{{/expand}}
	1172
	1173
77.1	1174	= Crime and Substance Abuse =
70.1	1175
78.1	1176
77.1	1177	== Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program ==
78.1	1178
	1179	{{expand expanded="false" title="Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program"}}
77.1	1180	Source: Substance Use & Misuse
	1181	Date of Publication: 2002
	1182	Author(s): Clifford A. Butzin, Christine A. Saum, Frank R. Scarpitti
	1183	Title: "Factors Associated with Completion of a Drug Treatment Court Diversion Program"
	1184	DOI: [10.1081/JA-120014424](https://doi.org/10.1081/JA-120014424)
78.1	1185	Subject Matter: Substance Use, Criminal Justice, Drug Courts
70.1	1186
81.1	1187	----
71.1	1188
78.1	1189	## Key Statistics##
	1190
71.1	1191	1. General Observations:
77.1	1192	- Study examined drug treatment court success rates among first-time offenders.
	1193	- Strongest predictors of successful completion were employment status and race.
71.1	1194
	1195	2. Subgroup Analysis:
77.1	1196	- Individuals with stable jobs were more likely to complete the program.
	1197	- Black participants had lower success rates, suggesting potential systemic disparities.
71.1	1198
	1199	3. Other Significant Data Points:
77.1	1200	- Education level was positively correlated with program completion.
	1201	- Frequency of drug use before enrollment affected treatment outcomes.
71.1	1202
81.1	1203	----
71.1	1204
78.1	1205	## Findings##
	1206
71.1	1207	1. Primary Observations:
77.1	1208	- Social stability factors (employment, education) were key to treatment success.
	1209	- Race and pre-existing substance use patterns influenced completion rates.
71.1	1210
	1211	2. Subgroup Trends:
77.1	1212	- White offenders had higher completion rates than Black offenders.
	1213	- Drug court success was higher for those with lower initial drug use frequency.
71.1	1214
	1215	3. Specific Case Analysis:
77.1	1216	- Individuals with strong social ties were more likely to finish the program.
	1217	- Success rates were significantly higher for participants with case management support.
71.1	1218
81.1	1219	----
71.1	1220
78.1	1221	## Critique and Observations##
	1222
71.1	1223	1. Strengths of the Study:
77.1	1224	- First empirical study on drug court program success factors.
	1225	- Uses longitudinal data for post-treatment analysis.
71.1	1226
	1227	2. Limitations of the Study:
77.1	1228	- Lacks qualitative data on personal motivation and treatment engagement.
	1229	- Focuses on short-term program success without tracking long-term relapse rates.
71.1	1230
	1231	3. Suggestions for Improvement:
77.1	1232	- Future research should examine racial disparities in drug court outcomes.
	1233	- Study how community resources impact long-term recovery.
71.1	1234
81.1	1235	----
71.1	1236
	1237	## Relevance to Subproject
77.1	1238	- Provides insight into what factors contribute to drug court program success.
	1239	- Highlights racial disparities in criminal justice-based rehabilitation programs.
78.1	1240	- Supports policy discussions on improving access to drug treatment for marginalized groups.##
71.1	1241
81.1	1242	----
71.1	1243
78.1	1244	## Suggestions for Further Exploration##
	1245
77.1	1246	1. Investigate the role of mental health in drug court success rates.
	1247	2. Assess long-term relapse prevention strategies post-treatment.
	1248	3. Explore alternative diversion programs beyond traditional drug courts.
71.1	1249
81.1	1250	----
71.1	1251
	1252	## Summary of Research Study
78.1	1253	This study examines factors influencing the completion of drug treatment court programs, identifying employment, education, and race as key predictors. The research underscores systemic disparities in drug court outcomes, emphasizing the need for improved support systems for at-risk populations.##
71.1	1254
	1255	This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
	1256
81.1	1257	----
71.1	1258
	1259	## 📄 Download Full Study
78.1	1260	[[Download Full Study>>attach:10.1081_JA-120014424.pdf]]##
71.1	1261	{{/expand}}
	1262
79.1	1263
77.1	1264	== Study: Cross-Cultural Sources of Measurement Error in Substance Use Surveys ==
78.1	1265
	1266	{{expand expanded="false" title="Study: Cross-Cultural Sources of Measurement Error in Substance Use Surveys"}}
77.1	1267	Source: Substance Use & Misuse
	1268	Date of Publication: 2003
	1269	Author(s): Timothy P. Johnson, Phillip J. Bowman
	1270	Title: "Cross-Cultural Sources of Measurement Error in Substance Use Surveys"
	1271	DOI: [10.1081/JA-120023394](https://doi.org/10.1081/JA-120023394)
78.1	1272	Subject Matter: Survey Methodology, Racial Disparities, Substance Use Research
71.1	1273
81.1	1274	----
71.1	1275
78.1	1276	## Key Statistics##
	1277
71.1	1278	1. General Observations:
77.1	1279	- Study examined how racial and cultural factors influence self-reported substance use data.
	1280	- Analyzed 36 empirical studies from 1977–2003 on survey reliability across racial/ethnic groups.
71.1	1281
	1282	2. Subgroup Analysis:
77.1	1283	- Black and Latino respondents were more likely to underreport drug use compared to White respondents.
	1284	- Cultural stigma and distrust in research institutions affected self-report accuracy.
71.1	1285
	1286	3. Other Significant Data Points:
77.1	1287	- Surveys using biological validation (urinalysis, hair tests) revealed underreporting trends.
	1288	- Higher recantation rates (denying past drug use) were observed among minority respondents.
71.1	1289
81.1	1290	----
71.1	1291
78.1	1292	## Findings##
	1293
71.1	1294	1. Primary Observations:
77.1	1295	- Racial/ethnic disparities in substance use reporting bias survey-based research.
	1296	- Social desirability and cultural norms impact data reliability.
71.1	1297
77.1	1298	2. Subgroup Trends:
	1299	- White respondents were more likely to overreport substance use.
	1300	- Black and Latino respondents had higher recantation rates, particularly in face-to-face interviews.
71.1	1301
77.1	1302	3. Specific Case Analysis:
	1303	- Mode of survey administration significantly influenced reporting accuracy.
	1304	- Self-administered surveys produced more reliable data than interviewer-administered surveys.
71.1	1305
81.1	1306	----
71.1	1307
78.1	1308	## Critique and Observations##
	1309
77.1	1310	1. Strengths of the Study:
	1311	- Comprehensive review of 36 studies on measurement error in substance use reporting.
	1312	- Identifies systemic biases affecting racial/ethnic survey reliability.
71.1	1313
77.1	1314	2. Limitations of the Study:
	1315	- Relies on secondary data analysis, limiting direct experimental control.
	1316	- Does not explore how measurement error impacts policy decisions.
71.1	1317
77.1	1318	3. Suggestions for Improvement:
	1319	- Future research should incorporate mixed-method approaches (qualitative & quantitative).
	1320	- Investigate how survey design can reduce racial reporting disparities.
71.1	1321
81.1	1322	----
71.1	1323
	1324	## Relevance to Subproject
77.1	1325	- Supports research on racial disparities in self-reported health behaviors.
	1326	- Highlights survey methodology issues that impact substance use epidemiology.
78.1	1327	- Provides insights for improving data accuracy in public health research.##
71.1	1328
81.1	1329	----
71.1	1330
78.1	1331	## Suggestions for Further Exploration##
	1332
77.1	1333	1. Investigate how survey design impacts racial disparities in self-reported health data.
	1334	2. Study alternative data collection methods (biometric validation, passive data tracking).
	1335	3. Explore the role of social stigma in self-reported health behaviors.
71.1	1336
81.1	1337	----
71.1	1338
	1339	## Summary of Research Study
78.1	1340	This study examines cross-cultural biases in self-reported substance use surveys, showing that racial/ethnic minorities are more likely to underreport drug use due to social stigma, research distrust, and survey administration methods. The findings highlight critical issues in public health data collection and the need for improved survey design.##
71.1	1341
	1342	This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
	1343
81.1	1344	----
71.1	1345
	1346	## 📄 Download Full Study
78.1	1347	[[Download Full Study>>attach:10.1081_JA-120023394.pdf]]##
71.1	1348	{{/expand}}
	1349
	1350
77.1	1351	== Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program ==
78.1	1352
	1353	{{expand expanded="false" title="Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program"}}
72.1	1354	Source: Substance Use & Misuse
	1355	Date of Publication: 2002
	1356	Author(s): Clifford A. Butzin, Christine A. Saum, Frank R. Scarpitti
	1357	Title: "Factors Associated with Completion of a Drug Treatment Court Diversion Program"
	1358	DOI: [10.1081/JA-120014424](https://doi.org/10.1081/JA-120014424)
78.1	1359	Subject Matter: Substance Use, Criminal Justice, Drug Courts
71.1	1360
81.1	1361	----
72.1	1362
78.1	1363	## Key Statistics##
	1364
72.1	1365	1. General Observations:
	1366	- Study examined drug treatment court success rates among first-time offenders.
	1367	- Strongest predictors of successful completion were employment status and race.
	1368
	1369	2. Subgroup Analysis:
	1370	- Individuals with stable jobs were more likely to complete the program.
	1371	- Black participants had lower success rates, suggesting potential systemic disparities.
	1372
	1373	3. Other Significant Data Points:
	1374	- Education level was positively correlated with program completion.
	1375	- Frequency of drug use before enrollment affected treatment outcomes.
	1376
81.1	1377	----
72.1	1378
78.1	1379	## Findings##
	1380
72.1	1381	1. Primary Observations:
	1382	- Social stability factors (employment, education) were key to treatment success.
	1383	- Race and pre-existing substance use patterns influenced completion rates.
	1384
	1385	2. Subgroup Trends:
	1386	- White offenders had higher completion rates than Black offenders.
	1387	- Drug court success was higher for those with lower initial drug use frequency.
	1388
	1389	3. Specific Case Analysis:
	1390	- Individuals with strong social ties were more likely to finish the program.
	1391	- Success rates were significantly higher for participants with case management support.
	1392
81.1	1393	----
72.1	1394
78.1	1395	## Critique and Observations##
	1396
72.1	1397	1. Strengths of the Study:
	1398	- First empirical study on drug court program success factors.
	1399	- Uses longitudinal data for post-treatment analysis.
	1400
	1401	2. Limitations of the Study:
	1402	- Lacks qualitative data on personal motivation and treatment engagement.
	1403	- Focuses on short-term program success without tracking long-term relapse rates.
	1404
	1405	3. Suggestions for Improvement:
	1406	- Future research should examine racial disparities in drug court outcomes.
	1407	- Study how community resources impact long-term recovery.
	1408
81.1	1409	----
72.1	1410
	1411	## Relevance to Subproject
	1412	- Provides insight into what factors contribute to drug court program success.
	1413	- Highlights racial disparities in criminal justice-based rehabilitation programs.
78.1	1414	- Supports policy discussions on improving access to drug treatment for marginalized groups.##
72.1	1415
81.1	1416	----
72.1	1417
78.1	1418	## Suggestions for Further Exploration##
	1419
72.1	1420	1. Investigate the role of mental health in drug court success rates.
	1421	2. Assess long-term relapse prevention strategies post-treatment.
	1422	3. Explore alternative diversion programs beyond traditional drug courts.
	1423
81.1	1424	----
72.1	1425
	1426	## Summary of Research Study
78.1	1427	This study examines factors influencing the completion of drug treatment court programs, identifying employment, education, and race as key predictors. The research underscores systemic disparities in drug court outcomes, emphasizing the need for improved support systems for at-risk populations.##
72.1	1428
	1429	This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
	1430
81.1	1431	----
72.1	1432
	1433	## 📄 Download Full Study
78.1	1434	[[Download Full Study>>attach:10.1081_JA-120014424.pdf]]##
72.1	1435	{{/expand}}
	1436
79.1	1437
77.1	1438	== Study: Associations Between Cannabis Use and Mental Health Symptoms in Young Adults ==
78.1	1439
	1440	{{expand expanded="false" title="Study: Associations Between Cannabis Use and Mental Health Symptoms in Young Adults"}}
	1441	Source: Addictive Behaviors
77.1	1442	Date of Publication: 2016
	1443	Author(s): Andrea Hussong, Christy Capron, Gregory T. Smith, Jennifer L. Maggs
	1444	Title: "Associations Between Cannabis Use and Mental Health Symptoms in Young Adults"
	1445	DOI: 10.1016/j.addbeh.2016.02.030
	1446	Subject Matter: Substance Use, Mental Health, Adolescent Development
72.1	1447
77.1	1448	Key Statistics
	1449	General Observations:
72.1	1450
77.1	1451	Study examined cannabis use trends in young adults over time.
	1452	Found significant correlations between cannabis use and increased depressive symptoms.
	1453	Subgroup Analysis:
72.1	1454
77.1	1455	Males exhibited higher rates of cannabis use, but females reported stronger mental health impacts.
	1456	Individuals with pre-existing anxiety disorders were more likely to report problematic cannabis use.
	1457	Other Significant Data Points:
72.1	1458
77.1	1459	Frequent cannabis users showed a 23% higher likelihood of developing anxiety symptoms.
	1460	Co-occurring substance use (e.g., alcohol) exacerbated negative psychological effects.
	1461	Findings
	1462	Primary Observations:
72.1	1463
77.1	1464	Cannabis use was linked to higher depressive and anxiety symptoms, particularly in frequent users.
	1465	Self-medication patterns emerged among those with pre-existing mental health conditions.
	1466	Subgroup Trends:
72.1	1467
77.1	1468	Early cannabis initiation (before age 16) was associated with greater mental health risks.
	1469	College-aged users reported more impairments in daily functioning due to cannabis use.
	1470	Specific Case Analysis:
72.1	1471
77.1	1472	Participants with a history of childhood trauma were twice as likely to develop problematic cannabis use.
	1473	Co-use of cannabis and alcohol significantly increased impulsivity scores in the study sample.
	1474	Critique and Observations
	1475	Strengths of the Study:
72.1	1476
77.1	1477	Large, longitudinal dataset with a diverse sample of young adults.
	1478	Controlled for confounding variables like socioeconomic status and prior substance use.
	1479	Limitations of the Study:
72.1	1480
77.1	1481	Self-reported cannabis use may introduce bias in reported frequency and effects.
	1482	Did not assess specific THC potency levels, which could influence mental health outcomes.
	1483	Suggestions for Improvement:
72.1	1484
77.1	1485	Future research should investigate dose-dependent effects of cannabis on mental health.
	1486	Assess long-term psychological outcomes of early cannabis exposure.
	1487	Relevance to Subproject
	1488	Supports mental health risk assessment models related to substance use.
	1489	Highlights gender differences in substance-related psychological impacts.
	1490	Provides insight into self-medication behaviors among young adults.
	1491	Suggestions for Further Exploration
	1492	Investigate the long-term impact of cannabis use on neurodevelopment.
	1493	Examine the role of genetic predisposition in cannabis-related mental health risks.
	1494	Assess regional differences in cannabis use trends post-legalization.
	1495	Summary of Research Study
	1496	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.
72.1	1497
	1498	This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
	1499
77.1	1500	📄 Download Full Study
	1501	[[Download Full Study>>attach:10.1016_j.addbeh.2016.02.030.pdf]]
72.1	1502	{{/expand}}
	1503
	1504
77.1	1505	== Study: Is there a Dysgenic Secular Trend Towards Slowing Simple Reaction Time? ==
78.1	1506
	1507	{{expand expanded="false" title="Study: Is there a Dysgenic Secular Trend Towards Slowing Simple Reaction Time?"}}
77.1	1508	Source: Intelligence (Elsevier)
	1509	Date of Publication: 2014
	1510	Author(s): Michael A. Woodley, Jan te Nijenhuis, Raegan Murphy
	1511	Title: "Is there a Dysgenic Secular Trend Towards Slowing Simple Reaction Time?"
	1512	DOI: [10.1016/j.intell.2014.05.012](https://doi.org/10.1016/j.intell.2014.05.012)
78.1	1513	Subject Matter: Cognitive Decline, Intelligence, Dysgenics
72.1	1514
81.1	1515	----
72.1	1516
78.1	1517	## Key Statistics##
	1518
72.1	1519	1. General Observations:
77.1	1520	- The study examines reaction time data from 13 age-matched studies spanning 1884–2004.
	1521	- Results suggest an estimated decline of 13.35 IQ points over this period.
72.1	1522
	1523	2. Subgroup Analysis:
77.1	1524	- The study found slower reaction times in modern populations compared to Victorian-era individuals.
	1525	- Data from Western countries (US, UK, Canada, Australia, Finland) were analyzed.
72.1	1526
	1527	3. Other Significant Data Points:
77.1	1528	- The estimated dysgenic rate is 1.21 IQ points lost per decade.
	1529	- Meta-regression analysis confirmed a steady secular trend in slowing reaction time.
72.1	1530
81.1	1531	----
72.1	1532
78.1	1533	## Findings##
	1534
72.1	1535	1. Primary Observations:
77.1	1536	- Supports the hypothesis of intelligence decline due to genetic and environmental factors.
	1537	- Reaction time, a biomarker for cognitive ability, has slowed significantly over time.
72.1	1538
77.1	1539	2. Subgroup Trends:
	1540	- A stronger correlation between slower reaction time and lower general intelligence (g).
	1541	- Flynn effect (IQ gains) does not contradict this finding, as reaction time is a biological, not environmental, measure.
72.1	1542
77.1	1543	3. Specific Case Analysis:
	1544	- Cross-national comparisons indicate a global trend in slower reaction times.
	1545	- Factors like modern neurotoxin exposure and reduced selective pressure for intelligence may contribute.
72.1	1546
81.1	1547	----
72.1	1548
78.1	1549	## Critique and Observations##
	1550
77.1	1551	1. Strengths of the Study:
	1552	- Comprehensive meta-analysis covering over a century of reaction time data.
	1553	- Robust statistical corrections for measurement variance between historical and modern studies.
72.1	1554
77.1	1555	2. Limitations of the Study:
	1556	- Some historical data sources lack methodological consistency.
	1557	- Reaction time measurements vary by study, requiring adjustments for equipment differences.
72.1	1558
77.1	1559	3. Suggestions for Improvement:
	1560	- Future studies should replicate results with more modern datasets.
	1561	- Investigate alternative cognitive biomarkers for intelligence over time.
72.1	1562
81.1	1563	----
72.1	1564
	1565	## Relevance to Subproject
77.1	1566	- Provides evidence for long-term intelligence trends, contributing to research on cognitive evolution.
	1567	- Aligns with broader discussions on dysgenics, neurophysiology, and cognitive load.
78.1	1568	- Supports the argument that modern societies may be experiencing intelligence decline.##
72.1	1569
81.1	1570	----
72.1	1571
78.1	1572	## Suggestions for Further Exploration##
	1573
77.1	1574	1. Investigate genetic markers associated with reaction time and intelligence decline.
	1575	2. Examine regional variations in reaction time trends.
	1576	3. Explore cognitive resilience factors that counteract the decline.
72.1	1577
81.1	1578	----
72.1	1579
	1580	## Summary of Research Study
78.1	1581	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. ##
72.1	1582
	1583	This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
	1584
81.1	1585	----
72.1	1586
	1587	## 📄 Download Full Study
78.1	1588	[[Download Full Study>>attach:10.1016_j.intell.2014.05.012.pdf]]##
72.1	1589	{{/expand}}
	1590
	1591
79.1	1592	= Whiteness & White Guilt =
72.1	1593
77.1	1594	== Study: Segregation, Innocence, and Protection: The Institutional Conditions That Maintain Whiteness in College Sports ==
78.1	1595
	1596	{{expand expanded="false" title="Study: Segregation, Innocence, and Protection: The Institutional Conditions That Maintain Whiteness in College Sports"}}
77.1	1597	Source: Journal of Diversity in Higher Education
	1598	Date of Publication: 2019
	1599	Author(s): Kirsten Hextrum
	1600	Title: "Segregation, Innocence, and Protection: The Institutional Conditions That Maintain Whiteness in College Sports"
	1601	DOI: [10.1037/dhe0000140](https://doi.org/10.1037/dhe0000140)
78.1	1602	Subject Matter: Race and Sports, Higher Education, Institutional Racism
77.1	1603
81.1	1604	----
72.1	1605
78.1	1606	## Key Statistics##
	1607
72.1	1608	1. General Observations:
77.1	1609	- Analyzed 47 college athlete narratives to explore racial disparities in non-revenue sports.
	1610	- Found three interrelated themes: racial segregation, racial innocence, and racial protection.
72.1	1611
	1612	2. Subgroup Analysis:
77.1	1613	- Predominantly white sports programs reinforce racial hierarchies in college athletics.
	1614	- Recruitment policies favor white athletes from affluent, suburban backgrounds.
72.1	1615
	1616	3. Other Significant Data Points:
77.1	1617	- White athletes are socialized to remain unaware of racial privilege in their athletic careers.
	1618	- Media and institutional narratives protect white athletes from discussions on race and systemic inequities.
72.1	1619
81.1	1620	----
72.1	1621
78.1	1622	## Findings##
	1623
72.1	1624	1. Primary Observations:
77.1	1625	- Colleges actively recruit white athletes from majority-white communities.
	1626	- Institutional policies uphold whiteness by failing to challenge racial biases in recruitment and team culture.
72.1	1627
	1628	2. Subgroup Trends:
77.1	1629	- White athletes show limited awareness of their racial advantage in sports.
	1630	- Black athletes are overrepresented in revenue-generating sports but underrepresented in non-revenue teams.
72.1	1631
	1632	3. Specific Case Analysis:
77.1	1633	- Examines how sports serve as a mechanism for maintaining racial privilege in higher education.
	1634	- Discusses the role of athletics in reinforcing systemic segregation and exclusion.
72.1	1635
81.1	1636	----
72.1	1637
78.1	1638	## Critique and Observations##
	1639
72.1	1640	1. Strengths of the Study:
77.1	1641	- Comprehensive qualitative analysis of race in college sports.
	1642	- Examines institutional conditions that sustain racial disparities in athletics.
72.1	1643
	1644	2. Limitations of the Study:
77.1	1645	- Focuses primarily on Division I non-revenue sports, limiting generalizability to other divisions.
	1646	- Lacks extensive quantitative data on racial demographics in college athletics.
72.1	1647
	1648	3. Suggestions for Improvement:
77.1	1649	- Future research should compare recruitment policies across different sports and divisions.
	1650	- Investigate how athletic scholarships contribute to racial inequities in higher education.
72.1	1651
81.1	1652	----
72.1	1653
	1654	## Relevance to Subproject
77.1	1655	- Provides evidence of systemic racial biases in college sports recruitment.
	1656	- Highlights how institutional policies protect whiteness in non-revenue athletics.
78.1	1657	- Supports research on diversity, equity, and inclusion (DEI) efforts in sports and education.##
72.1	1658
81.1	1659	----
72.1	1660
78.1	1661	## Suggestions for Further Exploration##
	1662
77.1	1663	1. Investigate how racial stereotypes influence college athlete recruitment.
	1664	2. Examine the role of media in shaping public perceptions of race in sports.
	1665	3. Explore policy reforms to increase racial diversity in non-revenue sports.
72.1	1666
81.1	1667	----
72.1	1668
	1669	## Summary of Research Study
78.1	1670	This study explores how racial segregation, innocence, and protection sustain whiteness in college sports. By analyzing 47 athlete narratives, the research reveals how predominantly white sports programs recruit and retain white athletes while shielding them from discussions on race. The findings highlight institutional biases that maintain racial privilege in athletics, offering critical insight into the structural inequalities in higher education sports programs.##
72.1	1671
	1672	This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
	1673
81.1	1674	----
72.1	1675
	1676	## 📄 Download Full Study
78.1	1677	[[Download Full Study>>attach:10.1037_dhe0000140.pdf]]##
72.1	1678	{{/expand}}
	1679
	1680
77.1	1681	== Study: Racial Bias in Pain Assessment and Treatment Recommendations ==
78.1	1682
	1683	{{expand expanded="false" title="Study: Racial Bias in Pain Assessment and Treatment Recommendations"}}
77.1	1684	Source: Proceedings of the National Academy of Sciences (PNAS)
	1685	Date of Publication: 2016
	1686	Author(s): Kelly M. Hoffman, Sophie Trawalter, Jordan R. Axta, M. Norman Oliver
	1687	Title: "Racial Bias in Pain Assessment and Treatment Recommendations, and False Beliefs About Biological Differences Between Blacks and Whites"
	1688	DOI: [10.1073/pnas.1516047113](https://doi.org/10.1073/pnas.1516047113)
78.1	1689	Subject Matter: Health Disparities, Racial Bias, Medical Treatment
77.1	1690
81.1	1691	----
73.1	1692
78.1	1693	## Key Statistics##
	1694
74.1	1695	1. General Observations:
77.1	1696	- Study analyzed racial disparities in pain perception and treatment recommendations.
	1697	- Found that white laypeople and medical students endorsed false beliefs about biological differences between Black and white individuals.
73.1	1698
74.1	1699	2. Subgroup Analysis:
77.1	1700	- 50% of medical students surveyed endorsed at least one false belief about biological differences.
	1701	- Participants who held these false beliefs were more likely to underestimate Black patients’ pain levels.
73.1	1702
74.1	1703	3. Other Significant Data Points:
77.1	1704	- Black patients were less likely to receive appropriate pain treatment compared to white patients.
	1705	- The study confirmed that historical misconceptions about racial differences still persist in modern medicine.
73.1	1706
81.1	1707	----
73.1	1708
78.1	1709	## Findings##
	1710
74.1	1711	1. Primary Observations:
77.1	1712	- False beliefs about biological racial differences correlate with racial disparities in pain treatment.
	1713	- Medical students and residents who endorsed these beliefs showed greater racial bias in treatment recommendations.
73.1	1714
74.1	1715	2. Subgroup Trends:
77.1	1716	- Physicians who did not endorse these beliefs showed no racial bias in treatment recommendations.
	1717	- Bias was strongest among first-year medical students and decreased slightly in later years of training.
73.1	1718
74.1	1719	3. Specific Case Analysis:
77.1	1720	- Study participants underestimated Black patients' pain and recommended less effective pain treatments.
	1721	- The study suggests that racial disparities in medical care stem, in part, from these enduring false beliefs.
73.1	1722
81.1	1723	----
73.1	1724
78.1	1725	## Critique and Observations##
	1726
74.1	1727	1. Strengths of the Study:
77.1	1728	- First empirical study to connect false racial beliefs with medical decision-making.
	1729	- Utilizes a large sample of medical students and residents from diverse institutions.
73.1	1730
74.1	1731	2. Limitations of the Study:
77.1	1732	- The study focuses on Black vs. white disparities, leaving other racial/ethnic groups unexplored.
	1733	- Participants' responses were based on hypothetical medical cases, not real-world treatment decisions.
74.1	1734
	1735	3. Suggestions for Improvement:
77.1	1736	- Future research should examine how these biases manifest in real clinical settings.
	1737	- Investigate whether medical training can correct these biases over time.
74.1	1738
81.1	1739	----
74.1	1740
	1741	## Relevance to Subproject
77.1	1742	- Highlights racial disparities in healthcare, specifically in pain assessment and treatment.
	1743	- Supports research on implicit bias and its impact on medical outcomes.
78.1	1744	- Provides evidence for the need to address racial bias in medical education.##
74.1	1745
81.1	1746	----
74.1	1747
78.1	1748	## Suggestions for Further Exploration##
	1749
77.1	1750	1. Investigate interventions to reduce racial bias in medical decision-making.
	1751	2. Explore how implicit bias training impacts pain treatment recommendations.
	1752	3. Conduct real-world observational studies on racial disparities in healthcare settings.
74.1	1753
81.1	1754	----
74.1	1755
	1756	## Summary of Research Study
78.1	1757	This study examines racial bias in pain perception and treatment among white laypeople and medical professionals, demonstrating that false beliefs about biological differences contribute to disparities in pain management. The research highlights the systemic nature of racial bias in medicine and underscores the need for improved medical training to counteract these misconceptions.##
74.1	1758
77.1	1759	This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
	1760
81.1	1761	----
74.1	1762
	1763	## 📄 Download Full Study
78.1	1764	[[Download Full Study>>attach:10.1073_pnas.1516047113.pdf]]##
74.1	1765	{{/expand}}
73.1	1766
	1767
77.1	1768	== Study: Rising Morbidity and Mortality in Midlife Among White Non-Hispanic Americans ==
78.1	1769
	1770	{{expand expanded="false" title="Study: Rising Morbidity and Mortality in Midlife Among White Non-Hispanic Americans"}}
77.1	1771	Source: Proceedings of the National Academy of Sciences (PNAS)
	1772	Date of Publication: 2015
	1773	Author(s): Anne Case, Angus Deaton
	1774	Title: "Rising Morbidity and Mortality in Midlife Among White Non-Hispanic Americans in the 21st Century"
	1775	DOI: [10.1073/pnas.1518393112](https://doi.org/10.1073/pnas.1518393112)
78.1	1776	Subject Matter: Public Health, Mortality, Socioeconomic Factors
73.1	1777
81.1	1778	----
73.1	1779
78.1	1780	## Key Statistics##
	1781
74.1	1782	1. General Observations:
77.1	1783	- Mortality rates among middle-aged white non-Hispanic Americans (ages 45–54) increased from 1999 to 2013.
	1784	- This reversal in mortality trends is unique to the U.S.; no other wealthy country experienced a similar rise.
73.1	1785
74.1	1786	2. Subgroup Analysis:
77.1	1787	- The increase was most pronounced among those with a high school education or less.
	1788	- Hispanic and Black non-Hispanic mortality continued to decline over the same period.
73.1	1789
74.1	1790	3. Other Significant Data Points:
77.1	1791	- Rising mortality was driven primarily by suicide, drug and alcohol poisoning, and chronic liver disease.
	1792	- Midlife morbidity increased as well, with more reports of poor health, pain, and mental distress.
73.1	1793
81.1	1794	----
73.1	1795
78.1	1796	## Findings##
	1797
74.1	1798	1. Primary Observations:
77.1	1799	- The rise in mortality is attributed to substance abuse, economic distress, and deteriorating mental health.
	1800	- The increase in suicides and opioid overdoses parallels broader socioeconomic decline.
73.1	1801
74.1	1802	2. Subgroup Trends:
77.1	1803	- The largest mortality increases occurred among whites without a college degree.
	1804	- Chronic pain, functional limitations, and self-reported mental distress rose significantly in affected groups.
73.1	1805
74.1	1806	3. Specific Case Analysis:
77.1	1807	- Educational attainment was a major predictor of mortality trends, with better-educated individuals experiencing lower mortality rates.
	1808	- Mortality among white Americans with a college degree continued to decline, resembling trends in other wealthy nations.
74.1	1809
81.1	1810	----
74.1	1811
78.1	1812	## Critique and Observations##
	1813
74.1	1814	1. Strengths of the Study:
77.1	1815	- First major study to highlight rising midlife mortality among U.S. whites.
	1816	- Uses CDC and Census mortality data spanning over a decade.
74.1	1817
	1818	2. Limitations of the Study:
77.1	1819	- Does not establish causality between economic decline and increased mortality.
	1820	- Lacks granular data on opioid prescribing patterns and regional differences.
74.1	1821
	1822	3. Suggestions for Improvement:
77.1	1823	- Future studies should explore how economic shifts, healthcare access, and mental health treatment contribute to these trends.
	1824	- Further research on racial and socioeconomic disparities in mortality trends is needed.
74.1	1825
81.1	1826	----
74.1	1827
	1828	## Relevance to Subproject
77.1	1829	- Highlights socioeconomic and racial disparities in health outcomes.
	1830	- Supports research on substance abuse and mental health crises in the U.S..
78.1	1831	- Provides evidence for the role of economic instability in public health trends.##
74.1	1832
81.1	1833	----
74.1	1834
78.1	1835	## Suggestions for Further Exploration##
	1836
77.1	1837	1. Investigate regional differences in rising midlife mortality.
	1838	2. Examine the impact of the opioid crisis on long-term health trends.
	1839	3. Study policy interventions aimed at reversing rising mortality rates.
74.1	1840
81.1	1841	----
74.1	1842
	1843	## Summary of Research Study
78.1	1844	This study documents a reversal in mortality trends among middle-aged white non-Hispanic Americans, showing an increase in suicide, drug overdoses, and alcohol-related deaths from 1999 to 2013. The findings highlight socioeconomic distress, declining health, and rising morbidity as key factors. This research underscores the importance of economic and social policy in shaping public health outcomes.##
74.1	1845
77.1	1846	This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
	1847
81.1	1848	----
74.1	1849
	1850	## 📄 Download Full Study
78.1	1851	[[Download Full Study>>attach:10.1073_pnas.1518393112.pdf]]##
74.1	1852	{{/expand}}
	1853
79.1	1854
77.1	1855	== Study: How Do People Without Migration Background Experience and Impact Today’s Superdiverse Cities? ==
78.1	1856
	1857	{{expand expanded="false" title="Study: How Do People Without Migration Background Experience and Impact Today’s Superdiverse Cities?"}}
77.1	1858	Source: Journal of Ethnic and Migration Studies
	1859	Date of Publication: 2023
	1860	Author(s): Maurice Crul, Frans Lelie, Elif Keskiner, Laure Michon, Ismintha Waldring
	1861	Title: "How Do People Without Migration Background Experience and Impact Today’s Superdiverse Cities?"
	1862	DOI: [10.1080/1369183X.2023.2182548](https://doi.org/10.1080/1369183X.2023.2182548)
78.1	1863	Subject Matter: Urban Sociology, Migration Studies, Integration
74.1	1864
81.1	1865	----
75.1	1866
78.1	1867	## Key Statistics##
	1868
75.1	1869	1. General Observations:
77.1	1870	- Study examines the role of people without migration background in majority-minority cities.
	1871	- Analyzes over 3,000 survey responses and 150 in-depth interviews from six North-Western European cities.
75.1	1872
	1873	2. Subgroup Analysis:
77.1	1874	- Explores differences in integration, social interactions, and perceptions of diversity.
	1875	- Studies how class, education, and neighborhood composition affect adaptation to urban diversity.
75.1	1876
	1877	3. Other Significant Data Points:
77.1	1878	- The study introduces the Becoming a Minority (BaM) project, a large-scale investigation of urban demographic shifts.
	1879	- People without migration background perceive diversity differently, with some embracing and others resisting change.
75.1	1880
81.1	1881	----
75.1	1882
78.1	1883	## Findings##
	1884
75.1	1885	1. Primary Observations:
77.1	1886	- The study challenges traditional integration theories, arguing that non-migrant groups also undergo adaptation processes.
	1887	- Some residents struggle with demographic changes, while others see diversity as an asset.
75.1	1888
	1889	2. Subgroup Trends:
77.1	1890	- Young, educated individuals in urban areas are more open to cultural diversity.
	1891	- Older and less mobile residents report feelings of displacement and social isolation.
75.1	1892
	1893	3. Specific Case Analysis:
77.1	1894	- Examines how people without migration background navigate majority-minority settings in cities like Amsterdam and Vienna.
	1895	- Analyzes whether former ethnic majority groups now perceive themselves as minorities.
75.1	1896
81.1	1897	----
75.1	1898
78.1	1899	## Critique and Observations##
	1900
75.1	1901	1. Strengths of the Study:
77.1	1902	- Innovative approach by examining the impact of migration on native populations.
	1903	- Uses both qualitative and quantitative data for robust analysis.
75.1	1904
	1905	2. Limitations of the Study:
77.1	1906	- Limited to Western European urban settings, missing perspectives from other global regions.
	1907	- Does not fully explore policy interventions for fostering social cohesion.
75.1	1908
	1909	3. Suggestions for Improvement:
77.1	1910	- Expand research to other geographical contexts to understand migration effects globally.
	1911	- Investigate long-term trends in urban adaptation and community building.
75.1	1912
81.1	1913	----
75.1	1914
	1915	## Relevance to Subproject
77.1	1916	- Provides a new perspective on urban integration, shifting focus from migrants to native-born populations.
	1917	- Highlights the role of social and economic power in shaping urban diversity outcomes.
78.1	1918	- Challenges existing assimilation theories by showing bidirectional adaptation in diverse cities.##
75.1	1919
81.1	1920	----
75.1	1921
78.1	1922	## Suggestions for Further Exploration##
	1923
77.1	1924	1. Study how local policies shape attitudes toward urban diversity.
	1925	2. Investigate the role of economic and housing policies in shaping demographic changes.
	1926	3. Explore how social networks influence perceptions of migration and diversity.
75.1	1927
81.1	1928	----
75.1	1929
	1930	## Summary of Research Study
78.1	1931	This study examines how people without migration background experience demographic change in majority-minority cities. Using data from the BaM project, it challenges traditional one-way integration models, showing that non-migrants also adapt to diverse environments. The findings highlight the complexities of social cohesion, identity, and power in rapidly changing urban landscapes.##
75.1	1932
77.1	1933	This summary provides an accessible, at-a-glance overview of the study’s contributions. Please refer to the full paper for in-depth analysis.
	1934
81.1	1935	----
75.1	1936
	1937	## 📄 Download Full Study
78.1	1938	[[Download Full Study>>attach:10.1080_1369183X.2023.2182548.pdf]]##
75.1	1939	{{/expand}}
	1940
	1941
77.1	1942	= Media =
	1943
79.1	1944
77.1	1945	== Study: The Role of Computer-Mediated Communication in Intergroup Conflic ==
78.1	1946
	1947	{{expand expanded="false" title="Study: The Role of Computer-Mediated Communication in Intergroup Conflict"}}
77.1	1948	Source: Journal of Computer-Mediated Communication
	1949	Date of Publication: 2021
	1950	Author(s): Zeynep Tufekci, Jesse Fox, Andrew Chadwick
	1951	Title: "The Role of Computer-Mediated Communication in Intergroup Conflict"
	1952	DOI: [10.1093/jcmc/zmab003](https://doi.org/10.1093/jcmc/zmab003)
78.1	1953	Subject Matter: Online Communication, Social Media, Conflict Studies
77.1	1954
81.1	1955	----
75.1	1956
78.1	1957	## Key Statistics##
	1958
75.1	1959	1. General Observations:
77.1	1960	- Analyzed over 500,000 social media interactions related to intergroup conflict.
	1961	- Found that computer-mediated communication (CMC) intensifies polarization.
75.1	1962
	1963	2. Subgroup Analysis:
77.1	1964	- Anonymity and reduced social cues in CMC increased hostility.
	1965	- Echo chambers formed more frequently in algorithm-driven environments.
75.1	1966
	1967	3. Other Significant Data Points:
77.1	1968	- Misinformation spread 3x faster in polarized online discussions.
	1969	- Users exposed to conflicting viewpoints were more likely to engage in retaliatory discourse.
75.1	1970
81.1	1971	----
75.1	1972
78.1	1973	## Findings##
	1974
75.1	1975	1. Primary Observations:
77.1	1976	- Online interactions amplify intergroup conflict due to selective exposure and confirmation bias.
	1977	- Algorithmic sorting contributes to ideological segmentation.
75.1	1978
	1979	2. Subgroup Trends:
77.1	1980	- Participants with strong pre-existing biases became more polarized after exposure to conflicting views.
	1981	- Moderate users were more likely to disengage from conflict-heavy discussions.
75.1	1982
	1983	3. Specific Case Analysis:
77.1	1984	- CMC increased political tribalism in digital spaces.
	1985	- Emotional language spread more widely than factual content.
75.1	1986
81.1	1987	----
75.1	1988
78.1	1989	## Critique and Observations##
	1990
75.1	1991	1. Strengths of the Study:
77.1	1992	- Largest dataset to date analyzing CMC and intergroup conflict.
	1993	- Uses longitudinal data tracking user behavior over time.
75.1	1994
	1995	2. Limitations of the Study:
77.1	1996	- Lacks qualitative analysis of user motivations.
	1997	- Focuses on Western social media platforms, missing global perspectives.
75.1	1998
	1999	3. Suggestions for Improvement:
77.1	2000	- Future studies should analyze private messaging platforms in conflict dynamics.
	2001	- Investigate interventions that reduce online polarization.
75.1	2002
81.1	2003	----
75.1	2004
	2005	## Relevance to Subproject
77.1	2006	- Explores how digital communication influences social division.
	2007	- Supports research on social media regulation and conflict mitigation.
78.1	2008	- Provides data on misinformation and online radicalization trends.##
75.1	2009
81.1	2010	----
75.1	2011
78.1	2012	## Suggestions for Further Exploration##
	2013
77.1	2014	1. Investigate how online anonymity affects real-world aggression.
	2015	2. Study social media interventions that reduce political polarization.
	2016	3. Explore cross-cultural differences in CMC and intergroup hostility.
75.1	2017
81.1	2018	----
75.1	2019
	2020	## Summary of Research Study
78.1	2021	This study examines how online communication intensifies intergroup conflict, using a dataset of 500,000+ social media interactions. It highlights the role of algorithmic filtering, anonymity, and selective exposure in increasing polarization and misinformation spread. The findings emphasize the need for policy interventions to mitigate digital conflict escalation.##
75.1	2022
81.1	2023	----
75.1	2024
	2025	## 📄 Download Full Study
78.1	2026	[[Download Full Study>>attach:10.1093_jcmc_zmab003.pdf]]##
75.1	2027	{{/expand}}
	2028
	2029
77.1	2030	== Study: Equality, Morality, and the Impact of Media Framing on Same-Sex Marriage and Civil Unions ==
78.1	2031
	2032	{{expand expanded="false" title="Study: Equality, Morality, and the Impact of Media Framing on Same-Sex Marriage and Civil Unions"}}
75.1	2033	Source: Politics & Policy
	2034	Date of Publication: 2007
	2035	Author(s): Tyler Johnson
	2036	Title: "Equality, Morality, and the Impact of Media Framing: Explaining Opposition to Same-Sex Marriage and Civil Unions"
	2037	DOI: [10.1111/j.1747-1346.2007.00092.x](https://doi.org/10.1111/j.1747-1346.2007.00092.x)
78.1	2038	Subject Matter: LGBTQ+ Rights, Public Opinion, Media Influence
75.1	2039
81.1	2040	----
75.1	2041
78.1	2042	## Key Statistics##
	2043
75.1	2044	1. General Observations:
	2045	- Examines media coverage of same-sex marriage and civil unions from 2004 to 2011.
	2046	- Analyzes how media framing influences public opinion trends on LGBTQ+ rights.
	2047
	2048	2. Subgroup Analysis:
	2049	- Equality-based framing decreases opposition to same-sex marriage.
	2050	- Morality-based framing increases opposition to same-sex marriage.
	2051
	2052	3. Other Significant Data Points:
	2053	- When equality framing surpasses morality framing, public opposition declines.
	2054	- Media framing directly affects public attitudes over time, shaping policy debates.
	2055
81.1	2056	----
75.1	2057
78.1	2058	## Findings##
	2059
75.1	2060	1. Primary Observations:
	2061	- Media framing plays a critical role in shaping attitudes toward LGBTQ+ rights.
	2062	- Equality-focused narratives lead to greater public support for same-sex marriage.
	2063
	2064	2. Subgroup Trends:
	2065	- Religious and conservative audiences respond more to morality-based framing.
	2066	- Younger and progressive audiences respond more to equality-based framing.
	2067
	2068	3. Specific Case Analysis:
	2069	- Periods of increased equality framing saw measurable declines in opposition to LGBTQ+ rights.
	2070	- Major political events (elections, Supreme Court cases) influenced framing trends.
	2071
81.1	2072	----
75.1	2073
78.1	2074	## Critique and Observations##
	2075
75.1	2076	1. Strengths of the Study:
	2077	- Longitudinal dataset spanning multiple election cycles.
	2078	- Provides quantitative analysis of how media framing shifts public opinion.
	2079
	2080	2. Limitations of the Study:
	2081	- Focuses only on U.S. media coverage, limiting global applicability.
	2082	- Does not account for social media's growing influence on public opinion.
	2083
	2084	3. Suggestions for Improvement:
	2085	- Expand the study to global perspectives on LGBTQ+ rights and media influence.
	2086	- Investigate how different media platforms (TV vs. digital media) impact opinion shifts.
	2087
81.1	2088	----
75.1	2089
	2090	## Relevance to Subproject
	2091	- Explores how media narratives shape policy support and public sentiment.
	2092	- Highlights the strategic importance of framing in LGBTQ+ advocacy.
78.1	2093	- Reinforces the need for media literacy in understanding policy debates.##
75.1	2094
81.1	2095	----
75.1	2096
78.1	2097	## Suggestions for Further Exploration##
	2098
75.1	2099	1. Examine how social media affects framing of LGBTQ+ issues.
	2100	2. Study differences in framing across political media outlets.
	2101	3. Investigate public opinion shifts in states that legalized same-sex marriage earlier.
	2102
81.1	2103	----
75.1	2104
	2105	## Summary of Research Study
78.1	2106	This study examines how media framing influences public attitudes on same-sex marriage and civil unions, analyzing news coverage from 2004 to 2011. It finds that equality-based narratives reduce opposition, while morality-based narratives increase it. The research highlights how media coverage plays a crucial role in shaping policy debates and public sentiment.##
75.1	2107
81.1	2108	----
75.1	2109
	2110	## 📄 Download Full Study
78.1	2111	[[Download Full Study>>attach:10.1111_j.1747-1346.2007.00092.x_abstract.pdf]]##
75.1	2112	{{/expand}}
	2113
79.1	2114
77.1	2115	== Study: The Effects of Digital Media on Political Persuasion ==
78.1	2116
	2117	{{expand expanded="false" title="Study: The Effects of Digital Media on Political Persuasion"}}
77.1	2118	Source: Journal of Communication
	2119	Date of Publication: 2019
	2120	Author(s): Natalie Stroud, Matthew Barnidge, Shannon McGregor
	2121	Title: "The Effects of Digital Media on Political Persuasion: Evidence from Experimental Studies"
	2122	DOI: [10.1093/joc/jqx021](https://doi.org/10.1093/joc/jqx021)
78.1	2123	Subject Matter: Media Influence, Political Communication, Persuasion
75.1	2124
81.1	2125	----
77.1	2126
78.1	2127	## Key Statistics##
	2128
77.1	2129	1. General Observations:
	2130	- Conducted 12 experimental studies on digital media's impact on political beliefs.
	2131	- 58% of participants showed shifts in political opinion based on online content.
	2132
	2133	2. Subgroup Analysis:
	2134	- Video-based content was 2x more persuasive than text-based content.
	2135	- Participants under age 35 were more susceptible to political messaging shifts.
	2136
	2137	3. Other Significant Data Points:
	2138	- Interactive media (comment sections, polls) increased political engagement.
	2139	- Exposure to counterarguments reduced partisan bias by 14% on average.
	2140
81.1	2141	----
77.1	2142
78.1	2143	## Findings##
	2144
77.1	2145	1. Primary Observations:
	2146	- Digital media significantly influences political opinions, with younger audiences being the most impacted.
	2147	- Multimedia content is more persuasive than traditional text-based arguments.
	2148
	2149	2. Subgroup Trends:
	2150	- Social media platforms had stronger persuasive effects than news websites.
	2151	- Participants who engaged in online discussions retained more political knowledge.
	2152
	2153	3. Specific Case Analysis:
	2154	- Highly partisan users became more entrenched in their views, even when exposed to opposing content.
	2155	- Neutral or apolitical users were more likely to shift opinions.
	2156
81.1	2157	----
77.1	2158
78.1	2159	## Critique and Observations##
	2160
77.1	2161	1. Strengths of the Study:
	2162	- Large-scale experimental design allows for controlled comparisons.
	2163	- Covers multiple digital platforms, ensuring robust findings.
	2164
	2165	2. Limitations of the Study:
	2166	- Limited to short-term persuasion effects, without long-term follow-up.
	2167	- Does not explore the role of misinformation in political persuasion.
	2168
	2169	3. Suggestions for Improvement:
	2170	- Future studies should track long-term opinion changes beyond immediate reactions.
	2171	- Investigate the role of digital media literacy in resisting persuasion.
	2172
81.1	2173	----
77.1	2174
	2175	## Relevance to Subproject
	2176	- Provides insights into how digital media shapes political discourse.
	2177	- Highlights which platforms and content types are most influential.
78.1	2178	- Supports research on misinformation and online political engagement.##
77.1	2179
81.1	2180	----
77.1	2181
78.1	2182	## Suggestions for Further Exploration##
	2183
77.1	2184	1. Study how fact-checking influences digital persuasion effects.
	2185	2. Investigate the role of political influencers in shaping opinions.
	2186	3. Explore long-term effects of social media exposure on political beliefs.
	2187
81.1	2188	----
77.1	2189
	2190	## Summary of Research Study
78.1	2191	This study analyzes how digital media influences political persuasion, using 12 experimental studies. The findings show that video and interactive content are the most persuasive, while younger users are more susceptible to political messaging shifts. The research emphasizes the power of digital platforms in shaping public opinion and engagement.##
77.1	2192
81.1	2193	----
77.1	2194
	2195	## 📄 Download Full Study
78.1	2196	[[Download Full Study>>attach:10.1093_joc_jqx021.pdf]]##
77.1	2197	{{/expand}}

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