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... ... @@ -19,2171 +19,17 @@
19 19  - You'll also find a download link to the original full study in pdf form at the bottom of the collapsible block.
20 20  
21 21  
22 +This page was getting too full, therefore I have created sub pages for each category. This makes it much easier to add new studies.
22 22  
23 -= Genetics =
24 24  
25 -{{expandable summary="
25 +[[Studies: Gentics>>doc:.Studies\: Genetics.WebHome]]
26 26  
27 -Study: Reconstructing Indian Population History"}}
28 -**Source:** *Nature*
29 -**Date of Publication:** *2009*
30 -**Author(s):** *David Reich, Kumarasamy Thangaraj, Nick Patterson, Alkes L. Price, Lalji Singh*
31 -**Title:** *"Reconstructing Indian Population History"*
32 -**DOI:** [10.1038/nature08365](https://doi.org/10.1038/nature08365)
33 -**Subject Matter:** *Genetics, Population History, South Asian Ancestry* 
27 +[[Studies: IQ>>doc:.Studies\: IQ.WebHome]]
34 34  
35 -{{expandable summary="📊 Key Statistics"}}
36 -1. **General Observations:**
37 - - Study analyzed **132 individuals from 25 diverse Indian groups**.
38 - - Identified two major ancestral populations: **Ancestral North Indians (ANI)** and **Ancestral South Indians (ASI)**.
29 +[[Studies: Crime and Substance Abuse>>doc:.Studies\: Crime and Substance Abuse.WebHome]]
39 39  
40 -2. **Subgroup Analysis:**
41 - - ANI ancestry is closely related to **Middle Easterners, Central Asians, and Europeans**.
42 - - ASI ancestry is **genetically distinct from ANI and East Asians**.
31 +[[Studies: Dating>>doc:.Studies\: Dating.WebHome]]
43 43  
44 -3. **Other Significant Data Points:**
45 - - ANI ancestry ranges from **39% to 71%** across Indian groups.
46 - - **Caste and linguistic differences** strongly correlate with genetic variation.
47 -{{/expandable}}
33 +[[Studies: Whiteness>>doc:.Studies\: Whiteness and White Guilt.WebHome]]
48 48  
49 -{{expandable summary="🔬 Findings"}}
50 -1. **Primary Observations:**
51 - - The genetic landscape of India has been shaped by **thousands of years of endogamy**.
52 - - Groups with **only ASI ancestry no longer exist** in mainland India.
53 -
54 -2. **Subgroup Trends:**
55 - - **Higher ANI ancestry in upper-caste and Indo-European-speaking groups**.
56 - - **Andaman Islanders** are unique in having **ASI ancestry without ANI influence**.
57 -
58 -3. **Specific Case Analysis:**
59 - - **Founder effects** have maintained allele frequency differences among Indian groups.
60 - - Predicts **higher incidence of recessive diseases** due to historical genetic isolation.
61 -{{/expandable}}
62 -
63 -{{expandable summary="📝 Critique & Observations"}}
64 -1. **Strengths of the Study:**
65 - - **First large-scale genetic analysis** of Indian population history.
66 - - Introduces **new methods for ancestry estimation without direct ancestral reference groups**.
67 -
68 -2. **Limitations of the Study:**
69 - - Limited **sample size relative to India's population diversity**.
70 - - Does not include **recent admixture events** post-colonial era.
71 -
72 -3. **Suggestions for Improvement:**
73 - - Future research should **expand sampling across more Indian tribal groups**.
74 - - Use **whole-genome sequencing** for finer resolution of ancestry.
75 -{{/expandable}}
76 -
77 -{{expandable summary="📌 Relevance to Subproject"}}
78 -- Provides a **genetic basis for caste and linguistic diversity** in India.
79 -- Highlights **founder effects and genetic drift** shaping South Asian populations.
80 -- Supports research on **medical genetics and disease risk prediction** in Indian populations.
81 -{{/expandable}}
82 -
83 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
84 -1. Examine **genetic markers linked to disease susceptibility** in Indian subpopulations.
85 -2. Investigate the impact of **recent migration patterns on ANI-ASI ancestry distribution**.
86 -3. Study **gene flow between Indian populations and other global groups**.
87 -{{/expandable}}
88 -
89 -{{expandable summary="📄 Download Full Study"}}
90 -[[Download Full Study>>attach:10.1038_nature08365.pdf]]
91 -{{/expandable}}
92 -{{/expandable}}
93 -
94 -{{expandable summary="Study: The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations"}}
95 -**Source:** *Nature*
96 -**Date of Publication:** *2016*
97 -**Author(s):** *David Reich, Swapan Mallick, Heng Li, Mark Lipson, and others*
98 -**Title:** *"The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations"*
99 -**DOI:** [10.1038/nature18964](https://doi.org/10.1038/nature18964)
100 -**Subject Matter:** *Human Genetic Diversity, Population History, Evolutionary Genomics*
101 -
102 -{{expandable summary="📊 Key Statistics"}}
103 -1. **General Observations:**
104 - - Analyzed **high-coverage genome sequences of 300 individuals from 142 populations**.
105 - - Included **many underrepresented and indigenous groups** from Africa, Asia, Europe, and the Americas.
106 -
107 -2. **Subgroup Analysis:**
108 - - Found **higher genetic diversity within African populations** compared to non-African groups.
109 - - Showed **Neanderthal and Denisovan ancestry in non-African populations**, particularly in Oceania.
110 -
111 -3. **Other Significant Data Points:**
112 - - Identified **5.8 million base pairs absent from the human reference genome**.
113 - - Estimated that **mutations have accumulated 5% faster in non-Africans than in Africans**.
114 -{{/expandable}}
115 -
116 -{{expandable summary="🔬 Findings"}}
117 -1. **Primary Observations:**
118 - - **African populations harbor the greatest genetic diversity**, confirming an out-of-Africa dispersal model.
119 - - Indigenous Australians and New Guineans **share a common ancestral population with other non-Africans**.
120 -
121 -2. **Subgroup Trends:**
122 - - **Lower heterozygosity in non-Africans** due to founder effects from migration bottlenecks.
123 - - **Denisovan ancestry in South Asians is higher than previously thought**.
124 -
125 -3. **Specific Case Analysis:**
126 - - **Neanderthal ancestry is higher in East Asians than in Europeans**.
127 - - African hunter-gatherer groups show **deep population splits over 100,000 years ago**.
128 -{{/expandable}}
129 -
130 -{{expandable summary="📝 Critique & Observations"}}
131 -1. **Strengths of the Study:**
132 - - **Largest global genetic dataset** outside of the 1000 Genomes Project.
133 - - High sequencing depth allows **more accurate identification of genetic variants**.
134 -
135 -2. **Limitations of the Study:**
136 - - **Limited sample sizes for some populations**, restricting generalizability.
137 - - Lacks ancient DNA comparisons, making it difficult to reconstruct deep ancestry fully.
138 -
139 -3. **Suggestions for Improvement:**
140 - - Future studies should include **ancient genomes** to improve demographic modeling.
141 - - Expand research into **how genetic variation affects health outcomes** across populations.
142 -{{/expandable}}
143 -
144 -{{expandable summary="📌 Relevance to Subproject"}}
145 -- Provides **comprehensive data on human genetic diversity**, useful for **evolutionary studies**.
146 -- Supports research on **Neanderthal and Denisovan introgression** in modern human populations.
147 -- Enhances understanding of **genetic adaptation and disease susceptibility across groups**.
148 -{{/expandable}}
149 -
150 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
151 -1. Investigate **functional consequences of genetic variation in underrepresented populations**.
152 -2. Study **how selection pressures shaped genetic diversity across different environments**.
153 -3. Explore **medical applications of population-specific genetic markers**.
154 -{{/expandable}}
155 -
156 -{{expandable summary="📄 Download Full Study"}}
157 -[[Download Full Study>>attach:10.1038_nature18964.pdf]]
158 -{{/expandable}}
159 -{{/expandable}}
160 -
161 -{{expandable summary="
162 -
163 -Study: Meta-analysis of the heritability of human traits based on fifty years of twin studies"}}
164 -**Source:** *Nature Genetics*
165 -**Date of Publication:** *2015*
166 -**Author(s):** *Tinca J. C. Polderman, Beben Benyamin, Christiaan A. de Leeuw, Patrick F. Sullivan, Arjen van Bochoven, Peter M. Visscher, Danielle Posthuma*
167 -**Title:** *"Meta-analysis of the heritability of human traits based on fifty years of twin studies"*
168 -**DOI:** [10.1038/ng.328](https://doi.org/10.1038/ng.328)
169 -**Subject Matter:** *Genetics, Heritability, Twin Studies, Behavioral Science*
170 -
171 -{{expandable summary="📊 Key Statistics"}}
172 -1. **General Observations:**
173 - - Analyzed **17,804 traits from 2,748 twin studies** published between **1958 and 2012**.
174 - - Included data from **14,558,903 twin pairs**, making it the largest meta-analysis on human heritability.
175 -
176 -2. **Subgroup Analysis:**
177 - - Found **49% average heritability** across all traits.
178 - - **69% of traits follow a simple additive genetic model**, meaning most variance is due to genes, not environment.
179 -
180 -3. **Other Significant Data Points:**
181 - - **Neurological, metabolic, and psychiatric traits** showed the highest heritability estimates.
182 - - Traits related to **social values and environmental interactions** had lower heritability estimates.
183 -{{/expandable}}
184 -
185 -{{expandable summary="🔬 Findings"}}
186 -1. **Primary Observations:**
187 - - Across all traits, genetic factors play a significant role in individual differences.
188 - - The study contradicts models that **overestimate environmental effects in behavioral and cognitive traits**.
189 -
190 -2. **Subgroup Trends:**
191 - - **Eye and brain-related traits showed the highest heritability (70-80%)**.
192 - - **Shared environmental effects were negligible (<10%) for most traits**.
193 -
194 -3. **Specific Case Analysis:**
195 - - Twin correlations suggest **limited evidence for strong non-additive genetic influences**.
196 - - The study highlights **missing heritability in complex traits**, which genome-wide association studies (GWAS) have yet to fully explain.
197 -{{/expandable}}
198 -
199 -{{expandable summary="📝 Critique & Observations"}}
200 -1. **Strengths of the Study:**
201 - - **Largest-ever heritability meta-analysis**, covering nearly all published twin studies.
202 - - Provides a **comprehensive framework for understanding gene-environment contributions**.
203 -
204 -2. **Limitations of the Study:**
205 - - **Underrepresentation of African, South American, and Asian twin cohorts**, limiting global generalizability.
206 - - Cannot **fully separate genetic influences from potential cultural/environmental confounders**.
207 -
208 -3. **Suggestions for Improvement:**
209 - - Future research should use **whole-genome sequencing** for finer-grained heritability estimates.
210 - - **Incorporate non-Western populations** to assess global heritability trends.
211 -{{/expandable}}
212 -
213 -{{expandable summary="📌 Relevance to Subproject"}}
214 -- Establishes a **quantitative benchmark for heritability across human traits**.
215 -- Reinforces **genetic influence on cognitive, behavioral, and physical traits**.
216 -- Highlights the need for **genome-wide studies to identify missing heritability**.
217 -{{/expandable}}
218 -
219 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
220 -1. Investigate how **heritability estimates compare across different socioeconomic backgrounds**.
221 -2. Examine **gene-environment interactions in cognitive and psychiatric traits**.
222 -3. Explore **non-additive genetic effects on human traits using newer statistical models**.
223 -{{/expandable}}
224 -
225 -{{expandable summary="📄 Download Full Study"}}
226 -[[Download Full Study>>attach:10.1038_ng.328.pdf]]
227 -{{/expandable}}
228 -{{/expandable}}
229 -
230 -{{expandable summary="
231 -
232 -Study: Genetic Analysis of African Populations: Human Evolution and Complex Disease"}}
233 -**Source:** *Nature Reviews Genetics*
234 -**Date of Publication:** *2002*
235 -**Author(s):** *Sarah A. Tishkoff, Scott M. Williams*
236 -**Title:** *"Genetic Analysis of African Populations: Human Evolution and Complex Disease"*
237 -**DOI:** [10.1038/nrg865](https://doi.org/10.1038/nrg865)
238 -**Subject Matter:** *Population Genetics, Human Evolution, Complex Diseases* 
239 -
240 -{{expandable summary="📊 Key Statistics"}}
241 -1. **General Observations:**
242 - - Africa harbors **the highest genetic diversity** of any region, making it key to understanding human evolution.
243 - - The study analyzes **genetic variation and linkage disequilibrium (LD) in African populations**.
244 -
245 -2. **Subgroup Analysis:**
246 - - African populations exhibit **greater genetic differentiation compared to non-Africans**.
247 - - **Migration and admixture** have shaped modern African genomes over the past **100,000 years**.
248 -
249 -3. **Other Significant Data Points:**
250 - - The **effective population size (Ne) of Africans** is higher than that of non-African populations.
251 - - LD blocks are **shorter in African genomes**, suggesting more historical recombination events.
252 -{{/expandable}}
253 -
254 -{{expandable summary="🔬 Findings"}}
255 -1. **Primary Observations:**
256 - - African populations are the **most genetically diverse**, supporting the *Recent African Origin* hypothesis.
257 - - Genetic variation in African populations can **help fine-map complex disease genes**.
258 -
259 -2. **Subgroup Trends:**
260 - - **West Africans exhibit higher genetic diversity** than East Africans due to differing migration patterns.
261 - - Populations such as **San hunter-gatherers show deep genetic divergence**.
262 -
263 -3. **Specific Case Analysis:**
264 - - Admixture in African Americans includes **West African and European genetic contributions**.
265 - - SNP (single nucleotide polymorphism) diversity in African genomes **exceeds that of non-African groups**.
266 -{{/expandable}}
267 -
268 -{{expandable summary="📝 Critique & Observations"}}
269 -1. **Strengths of the Study:**
270 - - Provides **comprehensive genetic analysis** of diverse African populations.
271 - - Highlights **how genetic diversity impacts health disparities and disease risks**.
272 -
273 -2. **Limitations of the Study:**
274 - - Many **African populations remain understudied**, limiting full understanding of diversity.
275 - - Focuses more on genetic variation than on **specific disease mechanisms**.
276 -
277 -3. **Suggestions for Improvement:**
278 - - Expand research into **underrepresented African populations**.
279 - - Integrate **whole-genome sequencing for a more detailed evolutionary timeline**.
280 -{{/expandable}}
281 -
282 -{{expandable summary="📌 Relevance to Subproject"}}
283 -- Supports **genetic models of human evolution** and the **out-of-Africa hypothesis**.
284 -- Reinforces **Africa’s key role in disease gene mapping and precision medicine**.
285 -- Provides insight into **historical migration patterns and their genetic impact**.
286 -{{/expandable}}
287 -
288 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
289 -1. Investigate **genetic adaptations to local environments within Africa**.
290 -2. Study **the role of African genetic diversity in disease resistance**.
291 -3. Expand research on **how ancient migration patterns shaped modern genetic structure**.
292 -{{/expandable}}
293 -
294 -{{expandable summary="📄 Download Full Study"}}
295 -[[Download Full Study>>attach:10.1038_nrg865MODERN.pdf]]
296 -{{/expandable}}
297 -{{/expandable}}
298 -
299 -{{expandable summary="
300 -
301 -Study: Pervasive Findings of Directional Selection in Ancient DNA"}}
302 -**Source:** *bioRxiv Preprint*
303 -**Date of Publication:** *September 15, 2024*
304 -**Author(s):** *Ali Akbari, Alison R. Barton, Steven Gazal, Zheng Li, Mohammadreza Kariminejad, et al.*
305 -**Title:** *"Pervasive findings of directional selection realize the promise of ancient DNA to elucidate human adaptation"*
306 -**DOI:** [10.1101/2024.09.14.613021](https://doi.org/10.1101/2024.09.14.613021)
307 -**Subject Matter:** *Genomics, Evolutionary Biology, Natural Selection*
308 -
309 -{{expandable summary="📊 Key Statistics"}}
310 -1. **General Observations:**
311 - - Study analyzes **8,433 ancient individuals** from the past **14,000 years**.
312 - - Identifies **347 genome-wide significant loci** showing strong selection.
313 -
314 -2. **Subgroup Analysis:**
315 - - Examines **West Eurasian populations** and their genetic evolution.
316 - - Tracks **changes in allele frequencies over millennia**.
317 -
318 -3. **Other Significant Data Points:**
319 - - **10,000 years of directional selection** affected metabolic, immune, and cognitive traits.
320 - - **Strong selection signals** found for traits like **skin pigmentation, cognitive function, and immunity**.
321 -{{/expandable}}
322 -
323 -{{expandable summary="🔬 Findings"}}
324 -1. **Primary Observations:**
325 - - **Hundreds of alleles have been subject to directional selection** over recent millennia.
326 - - Traits like **immune function, metabolism, and cognitive performance** show strong selection.
327 -
328 -2. **Subgroup Trends:**
329 - - Selection pressure on **energy storage genes** supports the **Thrifty Gene Hypothesis**.
330 - - **Cognitive performance-related alleles** have undergone selection, but their historical advantages remain unclear.
331 -
332 -3. **Specific Case Analysis:**
333 - - **Celiac disease risk allele** increased from **0% to 20%** in 4,000 years.
334 - - **Blood type B frequency rose from 0% to 8% in 6,000 years**.
335 - - **Tuberculosis risk allele** fluctuated from **2% to 9% over 3,000 years before declining**.
336 -{{/expandable}}
337 -
338 -{{expandable summary="📝 Critique & Observations"}}
339 -1. **Strengths of the Study:**
340 - - **Largest dataset to date** on natural selection in human ancient DNA.
341 - - Uses **direct allele frequency tracking instead of indirect measures**.
342 -
343 -2. **Limitations of the Study:**
344 - - Findings **may not translate directly** to modern populations.
345 - - **Unclear whether observed selection pressures persist today**.
346 -
347 -3. **Suggestions for Improvement:**
348 - - Expanding research to **other global populations** to assess universal trends.
349 - - Investigating **long-term evolutionary trade-offs of selected alleles**.
350 -{{/expandable}}
351 -
352 -{{expandable summary="📌 Relevance to Subproject"}}
353 -- Provides **direct evidence of long-term genetic adaptation** in human populations.
354 -- Supports theories on **polygenic selection shaping human cognition, metabolism, and immunity**.
355 -- Highlights **how past selection pressures may still influence modern health and disease prevalence**.
356 -{{/expandable}}
357 -
358 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
359 -1. Examine **selection patterns in non-European populations** for comparison.
360 -2. Investigate **how environmental and cultural shifts influenced genetic selection**.
361 -3. Explore **the genetic basis of traits linked to past and present-day human survival**.
362 -{{/expandable}}
363 -
364 -{{expandable summary="📄 Download Full Study"}}
365 -[[Download Full Study>>attach:10.1101_2024.09.14.613021doi_.pdf]]
366 -{{/expandable}}
367 -{{/expandable}}
368 -
369 -{{expandable summary="Study: The Wilson Effect: The Increase in Heritability of IQ With Age"}}
370 -**Source:** *Twin Research and Human Genetics (Cambridge University Press)*
371 -**Date of Publication:** *2013*
372 -**Author(s):** *Thomas J. Bouchard Jr.*
373 -**Title:** *"The Wilson Effect: The Increase in Heritability of IQ With Age"*
374 -**DOI:** [10.1017/thg.2013.54](https://doi.org/10.1017/thg.2013.54)
375 -**Subject Matter:** *Intelligence, Heritability, Developmental Psychology*
376 -
377 -{{expandable summary="📊 Key Statistics"}}
378 -1. **General Observations:**
379 - - The study documents how the **heritability of IQ increases with age**, reaching an asymptote at **0.80 by adulthood**.
380 - - Analysis is based on **longitudinal twin and adoption studies**.
381 -
382 -2. **Subgroup Analysis:**
383 - - Shared environmental influence on IQ **declines with age**, reaching **0.10 in adulthood**.
384 - - Monozygotic twins show **increasing genetic similarity in IQ over time**, while dizygotic twins become **less concordant**.
385 -
386 -3. **Other Significant Data Points:**
387 - - Data from the **Louisville Longitudinal Twin Study and cross-national twin samples** support findings.
388 - - IQ stability over time is **influenced more by genetics than by shared environmental factors**.
389 -{{/expandable}}
390 -
391 -{{expandable summary="🔬 Findings"}}
392 -1. **Primary Observations:**
393 - - Intelligence heritability **strengthens throughout development**, contrary to early environmental models.
394 - - Shared environmental effects **decrease by late adolescence**, emphasizing **genetic influence in adulthood**.
395 -
396 -2. **Subgroup Trends:**
397 - - Studies from **Scotland, Netherlands, and the US** show **consistent patterns of increasing heritability with age**.
398 - - Findings hold across **varied socio-economic and educational backgrounds**.
399 -
400 -3. **Specific Case Analysis:**
401 - - Longitudinal adoption studies show **declining impact of adoptive parental influence on IQ** as children age.
402 - - Cross-sectional twin data confirm **higher IQ correlations for monozygotic twins in adulthood**.
403 -{{/expandable}}
404 -
405 -{{expandable summary="📝 Critique & Observations"}}
406 -1. **Strengths of the Study:**
407 - - **Robust dataset covering multiple twin and adoption studies over decades**.
408 - - **Clear, replicable trend** demonstrating the increasing role of genetics in intelligence.
409 -
410 -2. **Limitations of the Study:**
411 - - Findings apply primarily to **Western industrialized nations**, limiting generalizability.
412 - - **Lack of neurobiological mechanisms** explaining how genes express their influence over time.
413 -
414 -3. **Suggestions for Improvement:**
415 - - Future research should investigate **gene-environment interactions in cognitive aging**.
416 - - Examine **heritability trends in non-Western populations** to determine cross-cultural consistency.
417 -{{/expandable}}
418 -
419 -{{expandable summary="📌 Relevance to Subproject"}}
420 -- Provides **strong evidence for the genetic basis of intelligence**.
421 -- Highlights the **diminishing role of shared environment in cognitive development**.
422 -- Supports research on **cognitive aging and heritability across the lifespan**.
423 -{{/expandable}}
424 -
425 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
426 -1. Investigate **neurogenetic pathways underlying IQ development**.
427 -2. Examine **how education and socioeconomic factors interact with genetic IQ influences**.
428 -3. Study **heritability trends in aging populations and cognitive decline**.
429 -{{/expandable}}
430 -
431 -{{expandable summary="📄 Download Full Study"}}
432 -[[Download Full Study>>attach:10.1017_thg.2013.54.pdf]]
433 -{{/expandable}}
434 -{{/expandable}}
435 -
436 -{{expandable summary="Study: Is Homo sapiens polytypic? Human taxonomic diversity and its implications"}}
437 -**Source:** *Medical Hypotheses (Elsevier)*
438 -**Date of Publication:** *2010*
439 -**Author(s):** *Michael A. Woodley*
440 -**Title:** *"Is Homo sapiens polytypic? Human taxonomic diversity and its implications"*
441 -**DOI:** [10.1016/j.mehy.2009.07.046](https://doi.org/10.1016/j.mehy.2009.07.046)
442 -**Subject Matter:** *Human Taxonomy, Evolutionary Biology, Anthropology*
443 -
444 -{{expandable summary="📊 Key Statistics"}}
445 -1. **General Observations:**
446 - - The study argues that **Homo sapiens is polytypic**, meaning it consists of multiple subspecies rather than a single monotypic species.
447 - - Examines **genetic diversity, morphological variation, and evolutionary lineage** in humans.
448 -
449 -2. **Subgroup Analysis:**
450 - - Discusses **four primary definitions of race/subspecies**: Essentialist, Taxonomic, Population-based, and Lineage-based.
451 - - Suggests that **human heterozygosity levels are comparable to species that are classified as polytypic**.
452 -
453 -3. **Other Significant Data Points:**
454 - - The study evaluates **FST values (genetic differentiation measure)** and argues that human genetic differentiation is comparable to that of recognized subspecies in other species.
455 - - Considers **phylogenetic species concepts** in defining human variation.
456 -{{/expandable}}
457 -
458 -{{expandable summary="🔬 Findings"}}
459 -1. **Primary Observations:**
460 - - Proposes that **modern human populations meet biological criteria for subspecies classification**.
461 - - Highlights **medical and evolutionary implications** of human taxonomic diversity.
462 -
463 -2. **Subgroup Trends:**
464 - - Discusses **how race concepts evolved over time** in biological sciences.
465 - - Compares **human diversity with that of other primates** such as chimpanzees and gorillas.
466 -
467 -3. **Specific Case Analysis:**
468 - - Evaluates how **genetic markers correlate with population structure**.
469 - - Addresses the **controversy over race classification in modern anthropology**.
470 -{{/expandable}}
471 -
472 -{{expandable summary="📝 Critique & Observations"}}
473 -1. **Strengths of the Study:**
474 - - Uses **comparative species analysis** to assess human classification.
475 - - Provides a **biological perspective** on the race concept, moving beyond social constructivism arguments.
476 -
477 -2. **Limitations of the Study:**
478 - - Controversial topic with **strong opposing views in anthropology and genetics**.
479 - - **Relies on broad genetic trends**, but does not analyze individual-level genetic variation in depth.
480 -
481 -3. **Suggestions for Improvement:**
482 - - Further research should **incorporate whole-genome studies** to refine subspecies classifications.
483 - - Investigate **how admixture affects taxonomic classification over time**.
484 -{{/expandable}}
485 -
486 -{{expandable summary="📌 Relevance to Subproject"}}
487 -- Contributes to discussions on **evolutionary taxonomy and species classification**.
488 -- Provides evidence on **genetic differentiation among human populations**.
489 -- Highlights **historical and contemporary scientific debates on race and human variation**.
490 -{{/expandable}}
491 -
492 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
493 -1. Examine **FST values in modern and ancient human populations**.
494 -2. Investigate how **adaptive evolution influences population differentiation**.
495 -3. Explore **the impact of genetic diversity on medical treatments and disease susceptibility**.
496 -{{/expandable}}
497 -
498 -{{expandable summary="📄 Download Full Study"}}
499 -[[Download Full Study>>attach:10.1016_j.mehy.2009.07.046.pdf]]
500 -{{/expandable}}
501 -{{/expandable}}
502 -
503 -= IQ =
504 -
505 -{{expandable summary="Study: Survey of Expert Opinion on Intelligence: Intelligence Research, Experts' Background, Controversial Issues, and the Media"}}
506 -**Source:** *Intelligence (Elsevier)*
507 -**Date of Publication:** *2019*
508 -**Author(s):** *Heiner Rindermann, David Becker, Thomas R. Coyle*
509 -**Title:** *"Survey of Expert Opinion on Intelligence: Intelligence Research, Experts' Background, Controversial Issues, and the Media"*
510 -**DOI:** [10.1016/j.intell.2019.101406](https://doi.org/10.1016/j.intell.2019.101406)
511 -**Subject Matter:** *Psychology, Intelligence Research, Expert Analysis*
512 -
513 -{{expandable summary="📊 Key Statistics"}}
514 -1. **General Observations:**
515 - - Survey of **102 experts** on intelligence research and public discourse.
516 - - Evaluated experts' backgrounds, political affiliations, and views on controversial topics in intelligence research.
517 -
518 -2. **Subgroup Analysis:**
519 - - **90% of experts were from Western countries**, and **83% were male**.
520 - - Political spectrum ranged from **54% left-liberal, 24% conservative**, with significant ideological influences on views.
521 -
522 -3. **Other Significant Data Points:**
523 - - Experts rated media coverage of intelligence research as **poor (avg. 3.1 on a 9-point scale)**.
524 - - **50% of experts attributed US Black-White IQ differences to genetic factors, 50% to environmental factors**.
525 -{{/expandable}}
526 -
527 -{{expandable summary="🔬 Findings"}}
528 -1. **Primary Observations:**
529 - - Experts overwhelmingly support **the g-factor theory of intelligence**.
530 - - **Heritability of intelligence** was widely accepted, though views differed on race and group differences.
531 -
532 -2. **Subgroup Trends:**
533 - - **Left-leaning experts were more likely to reject genetic explanations for group IQ differences**.
534 - - **Right-leaning experts tended to favor a stronger role for genetic factors** in intelligence disparities.
535 -
536 -3. **Specific Case Analysis:**
537 - - The study compared **media coverage of intelligence research** with expert opinions.
538 - - Found a **disconnect between journalists and intelligence researchers**, especially regarding politically sensitive issues.
539 -{{/expandable}}
540 -
541 -{{expandable summary="📝 Critique & Observations"}}
542 -1. **Strengths of the Study:**
543 - - **Largest expert survey on intelligence research** to date.
544 - - Provides insight into **how political orientation influences scientific perspectives**.
545 -
546 -2. **Limitations of the Study:**
547 - - **Sample primarily from Western countries**, limiting global perspectives.
548 - - Self-selection bias may skew responses toward **those more willing to engage with controversial topics**.
549 -
550 -3. **Suggestions for Improvement:**
551 - - Future studies should include **a broader range of global experts**.
552 - - Additional research needed on **media biases and misrepresentation of intelligence research**.
553 -{{/expandable}}
554 -
555 -{{expandable summary="📌 Relevance to Subproject"}}
556 -- Provides insight into **expert consensus and division on intelligence research**.
557 -- Highlights the **role of media bias** in shaping public perception of intelligence science.
558 -- Useful for understanding **the intersection of science, politics, and public discourse** on intelligence research.
559 -{{/expandable}}
560 -
561 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
562 -1. Examine **cross-national differences** in expert opinions on intelligence.
563 -2. Investigate how **media bias impacts public understanding of intelligence research**.
564 -3. Conduct follow-up studies with **a more diverse expert pool** to test findings.
565 -{{/expandable}}
566 -
567 -{{expandable summary="📄 Download Full Study"}}
568 -[[Download Full Study>>attach:10.1016_j.intell.2019.101406.pdf]]
569 -{{/expandable}}
570 -{{/expandable}}
571 -
572 -{{expandable summary="Study: A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation"}}
573 -**Source:** *Intelligence (Elsevier)*
574 -**Date of Publication:** *2015*
575 -**Author(s):** *Davide Piffer*
576 -**Title:** *"A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation"*
577 -**DOI:** [10.1016/j.intell.2015.08.008](https://doi.org/10.1016/j.intell.2015.08.008)
578 -**Subject Matter:** *Genetics, Intelligence, GWAS, Population Differences*
579 -
580 -{{expandable summary="📊 Key Statistics"}}
581 -1. **General Observations:**
582 - - Study analyzed **genome-wide association studies (GWAS) hits** linked to intelligence.
583 - - Found a **strong correlation (r = .91) between polygenic intelligence scores and national IQ levels**.
584 -
585 -2. **Subgroup Analysis:**
586 - - Factor analysis of **9 intelligence-associated alleles** revealed a metagene correlated with **country IQ (r = .86)**.
587 - - **Allele frequencies varied significantly by continent**, aligning with observed population differences in cognitive ability.
588 -
589 -3. **Other Significant Data Points:**
590 - - GWAS intelligence SNPs predicted **IQ levels more strongly than random genetic markers**.
591 - - Genetic differentiation (Fst values) showed that **selection pressure, rather than drift, influenced intelligence-related allele distributions**.
592 -{{/expandable}}
593 -
594 -{{expandable summary="🔬 Findings"}}
595 -1. **Primary Observations:**
596 - - Intelligence-associated SNP frequencies correlate **highly with national IQ levels**.
597 - - Genetic selection for intelligence appears **stronger than selection for height-related genes**.
598 -
599 -2. **Subgroup Trends:**
600 - - **East Asian populations** exhibited the **highest frequencies of intelligence-associated alleles**.
601 - - **African populations** showed lower frequencies compared to European and East Asian populations.
602 -
603 -3. **Specific Case Analysis:**
604 - - Polygenic scores using **intelligence-related alleles significantly outperformed random SNPs** in predicting IQ.
605 - - Selection pressures **may explain differences in global intelligence distribution** beyond genetic drift effects.
606 -{{/expandable}}
607 -
608 -{{expandable summary="📝 Critique & Observations"}}
609 -1. **Strengths of the Study:**
610 - - **Comprehensive genetic analysis** of intelligence-linked SNPs.
611 - - Uses **multiple statistical methods (factor analysis, Fst analysis) to confirm results**.
612 -
613 -2. **Limitations of the Study:**
614 - - **Correlation does not imply causation**; factors beyond genetics influence intelligence.
615 - - **Limited number of GWAS-identified intelligence alleles**—future studies may identify more.
616 -
617 -3. **Suggestions for Improvement:**
618 - - Larger **cross-population GWAS studies** needed to validate findings.
619 - - Investigate **non-genetic contributors to IQ variance** in addition to genetic factors.
620 -{{/expandable}}
621 -
622 -{{expandable summary="📌 Relevance to Subproject"}}
623 -- Supports research on **genetic influences on intelligence at a population level**.
624 -- Aligns with broader discussions on **cognitive genetics and natural selection effects**.
625 -- Provides a **quantitative framework for analyzing polygenic selection in intelligence studies**.
626 -{{/expandable}}
627 -
628 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
629 -1. Conduct **expanded GWAS studies** including diverse populations.
630 -2. Investigate **gene-environment interactions influencing intelligence**.
631 -3. Explore **historical selection pressures shaping intelligence-related alleles**.
632 -{{/expandable}}
633 -
634 -{{expandable summary="📄 Download Full Study"}}
635 -[[Download Full Study>>attach:10.1016_j.intell.2015.08.008.pdf]]
636 -{{/expandable}}
637 -{{/expandable}}
638 -
639 -{{expandable summary="Study: Genetic Structure, Self-Identified Race/Ethnicity, and Confounding"}}
640 -**Source:** Journal of Genetic Epidemiology
641 -**Date of Publication:** 2024-01-15
642 -**Author(s):** Smith et al.
643 -**Title:** "Genetic Structure, Self-Identified Race/Ethnicity, and Confounding in Case-Control Association Studies"
644 -**DOI:** [https://doi.org/10.1037/1076-8971.11.2.235](https://doi.org/10.1037/1076-8971.11.2.235)
645 -**Subject Matter:** Genetics, Social Science
646 -{{/expandable}}
647 -
648 -= Dating =
649 -
650 -{{expandable summary="Study: Positioning Multiraciality in Cyberspace – Treatment of Multiracial Daters in an Online Dating Website"}}
651 -**Source:** *Social Forces*
652 -**Date of Publication:** *2016*
653 -**Author(s):** *Stephanie M. Curington, Kevin K. Anderson, and Jennifer Glass*
654 -**Title:** *"Positioning Multiraciality in Cyberspace: Treatment of Multiracial Daters in an Online Dating Website"*
655 -**DOI:** [https://doi.org/10.1093/sf/sow007](https://doi.org/10.1093/sf/sow007)
656 -**Subject Matter:** *Race and Dating, Multiracial Identity, Online Behavior*
657 -
658 -{{expandable summary="📊 Key Statistics"}}
659 -1. **General Observations:**
660 - - Data drawn from **over 1 million messaging records** from an online dating site.
661 - - Focused on how **monoracial users** (especially Whites) interact with **multiracial daters**.
662 -
663 -2. **Subgroup Analysis:**
664 - - **Multiracial Black/White and Asian/White women** received **fewer responses from White men** than their monoracial counterparts.
665 - - White daters showed **stronger preferences for monoracial identities**, particularly **own-race pairings**.
666 -
667 -3. **Other Significant Data Points:**
668 - - **Multiracial men** fared worse than multiracial women across most pairings.
669 - - **Latina/White and Asian/White multiracial women** were **more positively received by Black and Hispanic men**.
670 -{{/expandable}}
671 -
672 -{{expandable summary="🔬 Findings"}}
673 -1. **Primary Observations:**
674 - - White users demonstrated a clear pattern of **in-group preference**, preferring other White users (monoracial or partially White) over more ambiguous multiracial identities.
675 - - Authors suggest this reflects **"boundary-maintaining behavior"** and **"latent racial bias"**.
676 -
677 -2. **Subgroup Trends:**
678 - - **Multiracial women with partial minority backgrounds** were more acceptable to non-White men than White men.
679 - - Multiracial daters were **often treated as ambiguous or “less desirable”** in ways the authors frame as **resistance to racial integration**.
680 -
681 -3. **Specific Case Analysis:**
682 - - The most rejected group? **Black/White multiracial men**, especially by **White women**, which the authors do not frame as bias in the same way.
683 - - The study shows **asymmetrical concern** — when Whites select inwardly, it's seen as racial boundary policing; when minorities do it, it's not pathologized.
684 -{{/expandable}}
685 -
686 -{{expandable summary="📝 Critique & Observations"}}
687 -1. **Strengths of the Study:**
688 - - Large, real-world dataset gives useful behavioral insight into **racial preferences in dating**.
689 - - Raises legitimate questions about **how race, desire, and group identity intersect**.
690 -
691 -2. **Limitations of the Study:**
692 - - Frames **normal in-group preference among Whites as "resistance to multiraciality"**, rather than neutral human patterning.
693 - - Ignores **similar or stronger in-group preference among Black and Asian users**, which could indicate *universal patterns*, not White exceptionalism.
694 - - Uses CRT framing to subtly **morally indict Whites for preferring Whites**, while exempting other groups.
695 -
696 -3. **Suggestions for Improvement:**
697 - - Treat all in-group preference equally across racial groups — not just when Whites do it.
698 - - Disaggregate by age, education, and regional variation to control for confounds.
699 - - Consider whether **multiracial identity is ambiguous** by nature and if that ambiguity reduces clarity of signals in dating.
700 -{{/expandable}}
701 -
702 -{{expandable summary="📌 Relevance to Subproject"}}
703 -- Provides a data point in the **ongoing academic effort to pathologize White selectiveness**, even in private, personal domains like dating.
704 -- Demonstrates how **racial preferences are only considered “problematic” when they preserve White group boundaries**.
705 -- Supports analysis of **how DEI-aligned narratives seek to dissolve in-group loyalty under the guise of openness and inclusion**.
706 -{{/expandable}}
707 -
708 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
709 -1. Investigate how **media and dating platforms reinforce multiracialism as normative** despite evidence of natural in-group selection.
710 -2. Study the **psychological effects of being told your preferences are morally wrong if you're White**.
711 -3. Explore how **multiracial identities are strategically framed** depending on political or cultural goals — exoticization, integration, or guilt projection.
712 -{{/expandable}}
713 -
714 -{{expandable summary="📄 Download Full Study"}}
715 -[[Download Full Study>>attach:Curington et al. - Positioning Multiraciality in Cyberspace Treatment of Multiracial Daters in an Online Dating Websit.pdf]]
716 -{{/expandable}}
717 -{{/expandable}}
718 -
719 -
720 -{{expandable summary="Study: The White Man’s Burden: Gonzo Pornography and the Construction of Black Masculinity"}}
721 -**Source:** *Porn Studies*
722 -**Date of Publication:** *2015*
723 -**Author(s):** *Noah Tsika*
724 -**Title:** *"The White Man’s Burden: Gonzo Pornography and the Construction of Black Masculinity"*
725 -**DOI:** [10.1080/23268743.2015.1025389](https://doi.org/10.1080/23268743.2015.1025389)
726 -**Subject Matter:** *Pornography Studies, Race and Sexuality, Cultural Critique*
727 -
728 -{{expandable summary="📊 Key Statistics"}}
729 -1. **General Observations:**
730 - - This is a **qualitative content analysis** of gonzo pornography, particularly interracial porn involving Black men and White women.
731 - - The author reviews **select films, not a dataset**, using them to extrapolate broad cultural claims about race and sexuality.
732 -
733 -2. **Subgroup Analysis:**
734 - - Claims that **interracial porn “others” and dehumanizes Black men**, yet selectively **frames Black male sexual aggression as liberatory**.
735 - - The author accuses White male consumers of **fetishizing Black men** as both threats and tools for their own “colonial guilt.”
736 -
737 -3. **Other Significant Data Points:**
738 - - No empirical evidence, just interpretive readings of scenes and film dialogue.
739 - - Repeatedly criticizes **White directors and actors** as complicit in perpetuating “White supremacy through porn.”
740 -{{/expandable}}
741 -
742 -{{expandable summary="🔬 Findings"}}
743 -1. **Primary Observations:**
744 - - Argues that **gonzo interracial porn functions as racial propaganda**, reinforcing White guilt while commodifying Black masculinity.
745 - - Portrays White women as willing participants in a fantasy of racial domination that allegedly “liberates” Black men.
746 -
747 -2. **Subgroup Trends:**
748 - - White male viewers are pathologized as both sexually repressed and voyeuristically complicit in anti-Black racism.
749 - - Black male performers are framed as both victims of racial commodification and **agents of resistance through hypersexuality**.
750 -
751 -3. **Specific Case Analysis:**
752 - - Cites scenes where Black male actors degrade or dominate White women as **“transgressive acts” that destabilize White power**, rather than examples of racial hostility or objectification.
753 - - The narrative treats **racially charged sexual violence as deconstructive**, only when it reverses traditional racial dynamics.
754 -{{/expandable}}
755 -
756 -{{expandable summary="📝 Critique & Observations"}}
757 -1. **Strengths of the Study:**
758 - - Useful in showcasing how **critical race theory invades even the most apolitical domains** (porn consumption) and turns them into race war battlegrounds.
759 - - Offers insight into how **White heterosexuality is recoded as colonialism** in activist academia.
760 -
761 -2. **Limitations of the Study:**
762 - - **No statistical basis**, relies entirely on biased interpretive analysis of fringe media.
763 - - Presumes **intent and audience motivation** without surveys, viewership data, or cross-cultural comparison.
764 - - Treats Black aggression as empowering and White sexuality as inherently oppressive — a double standard.
765 -
766 -3. **Suggestions for Improvement:**
767 - - Include comparative data on how different racial groups are portrayed in pornography across genres.
768 - - Analyze how **minority-run porn studios frame interracial themes** — not just White-directed media.
769 - - Address how racial fetishization **harms all groups**, not just Black men.
770 -{{/expandable}}
771 -
772 -{{expandable summary="📌 Relevance to Subproject"}}
773 -- Exemplifies how **racialized sexual narratives are reinterpreted to indict White identity**, even in consumer entertainment.
774 -- Shows how **DEI and CRT frameworks are applied to pornographic material** to pathologize White maleness while sanctifying non-White hypermasculinity.
775 -- Highlights the **academic bias that treats transgressive content as empowering when it serves anti-White narratives**.
776 -{{/expandable}}
777 -
778 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
779 -1. Study how **interracial porn narratives differ when produced by non-White vs. White directors**.
780 -2. Examine **how racial power is portrayed in same-sex vs. heterosexual interracial porn**.
781 -3. Investigate whether the **fetishization of Black masculinity fuels unrealistic expectations and destructive stereotypes** for both Black and White men.
782 -{{/expandable}}
783 -
784 -{{expandable summary="📄 Download Full Study"}}
785 -[[Download Full Study>>attach:Dinest - The White Man's Burden Gonzo Pornography and the Construction of Black Masculinity.pdf]]
786 -{{/expandable}}
787 -{{/expandable}}
788 -
789 -
790 -{{expandable summary="Study: Gendered Racial Exclusion Among White Internet Daters"}}
791 -**Source:** *Social Science Research*
792 -**Date of Publication:** *2009*
793 -**Author(s):** *Cynthia Feliciano, Belinda Robnett, Golnaz Komaie*
794 -**Title:** *"Gendered Racial Exclusion Among White Internet Daters"*
795 -**DOI:** [10.1016/j.ssresearch.2009.04.004](https://doi.org/10.1016/j.ssresearch.2009.04.004)
796 -**Subject Matter:** *Online Dating, Racial Preferences, CRT Framing of White Intimacy*
797 -
798 -{{expandable summary="📊 Key Statistics"}}
799 -1. **General Observations:**
800 - - Based on data from **Love@aol.com**, analyzing **over 6,000 profiles** from California.
801 - - The study investigated **racial preferences listed explicitly** in dating profiles.
802 -
803 -2. **Subgroup Analysis:**
804 - - **White women were least likely to express openness to interracial dating**, particularly with Black and Asian men.
805 - - **White men also showed exclusion**, but were more open than White women.
806 -
807 -3. **Other Significant Data Points:**
808 - - The authors labeled preference for one’s own race as **“racial exclusion”**.
809 - - Profiles by non-White users expressing same-race preferences were **not similarly problematized**.
810 -{{/expandable}}
811 -
812 -{{expandable summary="🔬 Findings"}}
813 -1. **Primary Observations:**
814 - - **White in-group preference was framed as discriminatory**, regardless of intent or context.
815 - - Dating preferences were interpreted as a **“reinforcement of racial hierarchies”**.
816 -
817 -2. **Subgroup Trends:**
818 - - The study suggested **White women’s selectivity** stemmed from **cultural and structural advantages**, implying racial gatekeeping.
819 - - Did not critically examine **non-White preferences** for their own race.
820 -
821 -3. **Specific Case Analysis:**
822 - - Highlighted that **Latina and Asian women were more open to White men** than to men of their own ethnicity, which was not treated as exclusionary.
823 - - **No racial preference was criticized except when it protected White boundaries.**
824 -{{/expandable}}
825 -
826 -{{expandable summary="📝 Critique & Observations"}}
827 -1. **Strengths of the Study:**
828 - - Large dataset from real-world dating profiles.
829 - - Provides rare insight into **gendered patterns of racial preference**.
830 -
831 -2. **Limitations of the Study:**
832 - - **Frames personal preference as political discrimination** when expressed by White users.
833 - - **Fails to control for cultural compatibility, attraction patterns, or religious values.**
834 - - **Double standard** in analysis — **non-White selectivity is ignored or justified.**
835 -
836 -3. **Suggestions for Improvement:**
837 - - Should distinguish **racial animus from in-group preference**.
838 - - Include **psychological, aesthetic, and cultural compatibility data**.
839 - - Apply **equal critical lens to all racial groups**, not just Whites.
840 -{{/expandable}}
841 -
842 -{{expandable summary="📌 Relevance to Subproject"}}
843 -- Reinforces how CRT-aligned research pathologizes **White in-group dating preferences**.
844 -- Supports the claim that **White intimacy boundaries are uniquely scrutinized** and politicized.
845 -- Demonstrates how even non-political behavior (e.g., dating) is racialized when it involves Whites.
846 -{{/expandable}}
847 -
848 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
849 -1. Study how **dating preferences vary by upbringing, media influence, and culture**, not just race.
850 -2. Analyze **racial preferences across all groups** with equal rigor and skepticism.
851 -3. Examine the **mental health impact of stigmatizing in-group preference** among Whites.
852 -{{/expandable}}
853 -
854 -{{expandable summary="📄 Download Full Study"}}
855 -[[Download Full Study>>attach:10.1016_j.ssresearch.2009.04.004.pdf]]
856 -{{/expandable}}
857 -{{/expandable}}
858 -
859 -
860 -{{expandable summary="Study: Black Penis and the Demoralization of the Western World"}}
861 -**Source:** *Journal of European Psychoanalysis*
862 -**Date of Publication:** *2009*
863 -**Author(s):** *Kristen Fink* *Jewish*))
864 -**Title:** *"Black Penis and the Demoralization of the Western World: Sexual relationships between black men and white women as a cause of decline"*
865 -**DOI:** *Unavailable – Psychoanalytic essay publication*
866 -**Subject Matter:** *Race and Sexuality, Psychoanalysis, Cultural Demoralization*
867 -
868 -{{expandable summary="📊 Key Statistics"}}
869 -1. **General Observations:**
870 - - This is a **psychoanalytic essay**, not an empirical study.
871 - - Uses **Freudian and Lacanian theory** to explore symbolic meanings of interracial sex.
872 - - Frames **Black male–White female pairings** as psychologically disruptive to the White male ego and Western civilization.
873 -
874 -2. **Subgroup Analysis:**
875 - - Positions **Black men as symbolic rivals** to emasculated Western (White) men.
876 - - **White women’s interracial attraction** is framed as rebellion or rejection of Western order.
877 -
878 -3. **Other Significant Data Points:**
879 - - The essay proposes that **sexual representation in media** is demoralizing to White culture.
880 - - Uses **high theory language** to justify what is ultimately an anti-White cultural narrative.
881 -{{/expandable}}
882 -
883 -{{expandable summary="🔬 Findings"}}
884 -1. **Primary Observations:**
885 - - **Interracial sexual dynamics** are framed as central to **Western decline**.
886 - - **White masculinity is portrayed as passive, obsolete, or neurotic** in contrast to hypermasculinized Blackness.
887 -
888 -2. **Subgroup Trends:**
889 - - Suggests White men internalize emasculation through exposure to interracial symbolism.
890 - - Sees **cultural loss of confidence** in White society as stemming from racial-sexual symbolism.
891 -
892 -3. **Specific Case Analysis:**
893 - - Analyzes media tropes (e.g., interracial porn, pop culture) through the lens of psychoanalytic guilt and transgression.
894 - - Never critiques the **ideological project of glorifying Blackness at the expense of White identity**.
895 -{{/expandable}}
896 -
897 -{{expandable summary="📝 Critique & Observations"}}
898 -1. **Strengths of the Study:**
899 - - Reveals how **elite academic disciplines like psychoanalysis** are used to mask anti-White narratives in esoteric jargon.
900 - - Serves as **ideological evidence** of demoralization tactics embedded in cultural theory.
901 -
902 -2. **Limitations of the Study:**
903 - - No empirical data, surveys, or statistical analysis — purely speculative.
904 - - **Does not critique hypersexualization of Black men** or the dehumanizing aspects of the fetish.
905 - - Assumes **White masculinity must passively accept its symbolic erasure** as psychoanalytically “natural.”
906 -
907 -3. **Suggestions for Improvement:**
908 - - Include **perspectives from White men and women** on how these portrayals affect their psychological well-being.
909 - - Disentangle psychoanalytic theory from **racial guilt ideology**.
910 - - Explore **mutual respect-based frameworks** for interracial dynamics rather than ones rooted in humiliation or power symbolism.
911 -{{/expandable}}
912 -
913 -{{expandable summary="📌 Relevance to Subproject"}}
914 -- Illustrates how **race, sex, and culture are manipulated to undermine White self-perception**.
915 -- Demonstrates how **academic elites frame White decline as psychologically necessary or deserved**.
916 -- Provides ideological background for modern media trends that eroticize racial power imbalance.
917 -{{/expandable}}
918 -
919 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
920 -1. Analyze how psychoanalytic language is used to **justify racial inversion in cultural dominance**.
921 -2. Examine the **role of pornography in demoralization campaigns** targeting White men.
922 -3. Explore how elite journals create **ideological cover for overt anti-White sentiment**.
923 -{{/expandable}}
924 -
925 -{{expandable summary="📄 Download Full Study"}}
926 -[[Download Full Study>>attach:10.Fink_Black_Penis_Demoralization.pdf]]
927 -{{/expandable}}
928 -{{/expandable}}
929 -
930 -
931 -{{expandable summary="Study: Trends in Frequency of Sexual Activity and Number of Sexual Partners Among Adults Aged 18 to 44 Years in the US, 2000-2018"}}
932 -**Source:** *JAMA Network Open*
933 -**Date of Publication:** *2020*
934 -**Author(s):** *Ueda P, Mercer CH, Ghaznavi C, Herbenick D.*
935 -**Title:** *"Trends in Frequency of Sexual Activity and Number of Sexual Partners Among Adults Aged 18 to 44 Years in the US, 2000-2018"*
936 -**DOI:** [10.1001/jamanetworkopen.2020.3833](https://doi.org/10.1001/jamanetworkopen.2020.3833)
937 -**Subject Matter:** *Public Health, Sexual Behavior, Demography* 
938 -
939 -{{expandable summary="📊 Key Statistics"}}
940 -1. **General Observations:**
941 - - Study analyzed **General Social Survey (2000-2018)** data.
942 - - Found **declining trends in sexual activity** among young adults.
943 -
944 -2. **Subgroup Analysis:**
945 - - Decreases in sexual activity were most prominent among **men aged 18-34**.
946 - - Factors like **marital status, employment, and psychological well-being** were associated with changes in sexual frequency.
947 -
948 -3. **Other Significant Data Points:**
949 - - Frequency of sexual activity decreased by **8-10%** over the studied period.
950 - - Number of sexual partners remained **relatively stable** despite declining activity rates.
951 -{{/expandable}}
952 -
953 -{{expandable summary="🔬 Findings"}}
954 -1. **Primary Observations:**
955 - - A significant decline in sexual frequency, especially among **younger men**.
956 - - Shifts in relationship dynamics and economic stressors may contribute to the trend.
957 -
958 -2. **Subgroup Trends:**
959 - - More pronounced decline among **unmarried individuals**.
960 - - No major change observed for **married adults** over time.
961 -
962 -3. **Specific Case Analysis:**
963 - - **Mental health and employment status** were correlated with decreased activity.
964 - - Social factors such as **screen time and digital entertainment consumption** are potential contributors.
965 -{{/expandable}}
966 -
967 -{{expandable summary="📝 Critique & Observations"}}
968 -1. **Strengths of the Study:**
969 - - **Large sample size** from a nationally representative dataset.
970 - - **Longitudinal design** enables trend analysis over time.
971 -
972 -2. **Limitations of the Study:**
973 - - Self-reported data may introduce **response bias**.
974 - - No direct causal mechanisms tested for the decline in sexual activity.
975 -
976 -3. **Suggestions for Improvement:**
977 - - Further studies should incorporate **qualitative data** on behavioral shifts.
978 - - Additional factors such as **economic shifts and social media usage** need exploration.
979 -{{/expandable}}
980 -
981 -{{expandable summary="📌 Relevance to Subproject"}}
982 -- Provides evidence on **changing demographic behaviors** in relation to relationships and social interactions.
983 -- Highlights the role of **mental health, employment, and societal changes** in personal behaviors.
984 -{{/expandable}}
985 -
986 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
987 -1. Investigate the **impact of digital media consumption** on relationship dynamics.
988 -2. Examine **regional and cultural differences** in sexual activity trends.
989 -{{/expandable}}
990 -
991 -{{expandable summary="📄 Download Full Study"}}
992 -
993 -{{/expandable}}
994 -{{/expandable}}
995 -
996 -{{expandable summary="Study: Biracial Couples and Adverse Birth Outcomes – A Systematic Review and Meta-Analysis"}}
997 -**Source:** *Acta Obstetricia et Gynecologica Scandinavica*
998 -**Date of Publication:** *2012*
999 -**Author(s):** *Ravisha M. Srinivasjois, Shreya Shah, Prakesh S. Shah, Knowledge Synthesis Group on Determinants of Preterm/LBW Births*
1000 -**Title:** *"Biracial Couples and Adverse Birth Outcomes: A Systematic Review and Meta-Analysis"*
1001 -**DOI:** [10.1111/j.1600-0412.2012.01501.x](https://doi.org/10.1111/j.1600-0412.2012.01501.x)
1002 -**Subject Matter:** *Neonatal Health, Maternal-Fetal Medicine, Racial Disparities*
1003 -
1004 -{{expandable summary="📊 Key Statistics"}}
1005 -1. **General Observations:**
1006 - - Meta-analysis of **26,335,596 singleton births** from eight studies.
1007 - - **Higher risk of adverse birth outcomes in biracial couples** than White couples, but lower than Black couples.
1008 -
1009 -2. **Subgroup Analysis:**
1010 - - **Maternal race had a stronger influence than paternal race** on birth outcomes.
1011 - - **Black mother–White father (BMWF) couples** had a higher risk than **White mother–Black father (WMBF) couples**.
1012 -
1013 -3. **Other Significant Data Points:**
1014 - - **Adjusted Odds Ratios (aORs) for key outcomes:**
1015 - - **Low birthweight (LBW):** WMBF (1.21), BMWF (1.75), Black mother–Black father (BMBF) (2.08).
1016 - - **Preterm births (PTB):** WMBF (1.17), BMWF (1.37), BMBF (1.78).
1017 - - **Stillbirths:** WMBF (1.43), BMWF (1.51), BMBF (1.85).
1018 -{{/expandable}}
1019 -
1020 -{{expandable summary="🔬 Findings"}}
1021 -1. **Primary Observations:**
1022 - - **Biracial couples face a gradient of risk**: higher than White couples but lower than Black couples.
1023 - - **Maternal race plays a more significant role** in pregnancy outcomes.
1024 -
1025 -2. **Subgroup Trends:**
1026 - - **Black mothers (regardless of paternal race) had the highest risk of LBW and PTB**.
1027 - - **White mothers with Black fathers had a lower risk** than Black mothers with White fathers.
1028 -
1029 -3. **Specific Case Analysis:**
1030 - - The **weathering hypothesis** suggests that **long-term stress exposure** contributes to higher adverse birth risks in Black mothers.
1031 - - **Genetic and environmental factors** may interact to influence birth outcomes.
1032 -{{/expandable}}
1033 -
1034 -{{expandable summary="📝 Critique & Observations"}}
1035 -1. **Strengths of the Study:**
1036 - - **Largest meta-analysis** on racial disparities in birth outcomes.
1037 - - Uses **adjusted statistical models** to account for confounding variables.
1038 -
1039 -2. **Limitations of the Study:**
1040 - - Data limited to **Black-White biracial couples**, excluding other racial groups.
1041 - - **Socioeconomic and healthcare access factors** not fully explored.
1042 -
1043 -3. **Suggestions for Improvement:**
1044 - - Future studies should examine **Asian, Hispanic, and Indigenous biracial couples**.
1045 - - Investigate **long-term health effects on infants from biracial pregnancies**.
1046 -{{/expandable}}
1047 -
1048 -{{expandable summary="📌 Relevance to Subproject"}}
1049 -- Provides **critical insights into racial disparities** in maternal and infant health.
1050 -- Supports **research on genetic and environmental influences on neonatal health**.
1051 -- Highlights **how maternal race plays a more significant role than paternal race** in birth outcomes.
1052 -{{/expandable}}
1053 -
1054 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
1055 -1. Investigate **the role of prenatal care quality in mitigating racial disparities**.
1056 -2. Examine **how social determinants of health impact biracial pregnancy outcomes**.
1057 -3. Explore **gene-environment interactions influencing birthweight and prematurity risks**.
1058 -{{/expandable}}
1059 -
1060 -{{expandable summary="📄 Download Full Study"}}
1061 -[[Download Full Study>>attach:10.1111_j.1600-0412.2012.01501.xAbstract.pdf]]
1062 -{{/expandable}}
1063 -{{/expandable}}
1064 -
1065 -{{expandable summary="Study: One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness"}}
1066 -**Source:** *Current Psychology*
1067 -**Date of Publication:** *2024*
1068 -**Author(s):** *Brandon Sparks, Alexandra M. Zidenberg, Mark E. Olver*
1069 -**Title:** *"One is the Loneliest Number: Involuntary Celibacy (Incel), Mental Health, and Loneliness"*
1070 -**DOI:** [10.1007/s12144-023-04275-z](https://doi.org/10.1007/s12144-023-04275-z)
1071 -**Subject Matter:** *Psychology, Mental Health, Social Isolation*
1072 -
1073 -{{expandable summary="📊 Key Statistics"}}
1074 -1. **General Observations:**
1075 - - Study analyzed **67 self-identified incels** and **103 non-incel men**.
1076 - - Incels reported **higher loneliness and lower social support** compared to non-incels.
1077 -
1078 -2. **Subgroup Analysis:**
1079 - - Incels exhibited **higher levels of depression, anxiety, and self-critical rumination**.
1080 - - **Social isolation was a key factor** differentiating incels from non-incels.
1081 -
1082 -3. **Other Significant Data Points:**
1083 - - 95% of incels in the study reported **having depression**, with 38% receiving a formal diagnosis.
1084 - - **Higher externalization of blame** was linked to stronger incel identification.
1085 -{{/expandable}}
1086 -
1087 -{{expandable summary="🔬 Findings"}}
1088 -1. **Primary Observations:**
1089 - - Incels experience **heightened rejection sensitivity and loneliness**.
1090 - - Lack of social support correlates with **worse mental health outcomes**.
1091 -
1092 -2. **Subgroup Trends:**
1093 - - **Avoidant attachment styles** were a strong predictor of incel identity.
1094 - - **Mate value perceptions** significantly differed between incels and non-incels.
1095 -
1096 -3. **Specific Case Analysis:**
1097 - - Incels **engaged in fewer positive coping mechanisms** such as emotional support or positive reframing.
1098 - - Instead, they relied on **solitary coping strategies**, worsening their isolation.
1099 -{{/expandable}}
1100 -
1101 -{{expandable summary="📝 Critique & Observations"}}
1102 -1. **Strengths of the Study:**
1103 - - **First quantitative study** on incels’ social isolation and mental health.
1104 - - **Robust sample size** and validated psychological measures.
1105 -
1106 -2. **Limitations of the Study:**
1107 - - Sample drawn from **Reddit communities**, which may not represent all incels.
1108 - - **No causal conclusions**—correlations between isolation and inceldom need further research.
1109 -
1110 -3. **Suggestions for Improvement:**
1111 - - Future studies should **compare incel forum users vs. non-users**.
1112 - - Investigate **potential intervention strategies** for social integration.
1113 -{{/expandable}}
1114 -
1115 -{{expandable summary="📌 Relevance to Subproject"}}
1116 -- Highlights **mental health vulnerabilities** within the incel community.
1117 -- Supports research on **loneliness, attachment styles, and social dominance orientation**.
1118 -- Examines how **peer rejection influences self-perceived mate value**.
1119 -{{/expandable}}
1120 -
1121 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
1122 -1. Explore how **online community participation** affects incel mental health.
1123 -2. Investigate **cognitive biases** influencing self-perceived rejection among incels.
1124 -3. Assess **therapeutic interventions** to address incel social isolation.
1125 -{{/expandable}}
1126 -
1127 -{{expandable summary="📄 Download Full Study"}}
1128 -[[Download Full Study>>attach:10.1007_s12144-023-04275-z.pdf]]
1129 -{{/expandable}}
1130 -{{/expandable}}
1131 -
1132 -= Crime and Substance Abuse =
1133 -
1134 -{{expandable summary="Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program"}}
1135 -**Source:** *Substance Use & Misuse*
1136 -**Date of Publication:** *2002*
1137 -**Author(s):** *Clifford A. Butzin, Christine A. Saum, Frank R. Scarpitti*
1138 -**Title:** *"Factors Associated with Completion of a Drug Treatment Court Diversion Program"*
1139 -**DOI:** [10.1081/JA-120014424](https://doi.org/10.1081/JA-120014424)
1140 -**Subject Matter:** *Substance Use, Criminal Justice, Drug Courts*
1141 -
1142 -{{expandable summary="📊 Key Statistics"}}
1143 -1. **General Observations:**
1144 - - Study examined **drug treatment court success rates** among first-time offenders.
1145 - - Strongest predictors of **successful completion were employment status and race**.
1146 -
1147 -2. **Subgroup Analysis:**
1148 - - Individuals with **stable jobs were more likely to complete the program**.
1149 - - **Black participants had lower success rates**, suggesting potential systemic disparities.
1150 -
1151 -3. **Other Significant Data Points:**
1152 - - **Education level was positively correlated** with program completion.
1153 - - Frequency of **drug use before enrollment affected treatment outcomes**.
1154 -{{/expandable}}
1155 -
1156 -{{expandable summary="🔬 Findings"}}
1157 -1. **Primary Observations:**
1158 - - **Social stability factors** (employment, education) were key to treatment success.
1159 - - **Race and pre-existing substance use patterns** influenced completion rates.
1160 -
1161 -2. **Subgroup Trends:**
1162 - - White offenders had **higher completion rates** than Black offenders.
1163 - - Drug court success was **higher for those with lower initial drug use frequency**.
1164 -
1165 -3. **Specific Case Analysis:**
1166 - - **Individuals with strong social ties were more likely to finish the program**.
1167 - - Success rates were **significantly higher for participants with case management support**.
1168 -{{/expandable}}
1169 -
1170 -{{expandable summary="📝 Critique & Observations"}}
1171 -1. **Strengths of the Study:**
1172 - - **First empirical study on drug court program success factors**.
1173 - - Uses **longitudinal data** for post-treatment analysis.
1174 -
1175 -2. **Limitations of the Study:**
1176 - - Lacks **qualitative data on personal motivation and treatment engagement**.
1177 - - Focuses on **short-term program success** without tracking **long-term relapse rates**.
1178 -
1179 -3. **Suggestions for Improvement:**
1180 - - Future research should examine **racial disparities in drug court outcomes**.
1181 - - Study **how community resources impact long-term recovery**.
1182 -{{/expandable}}
1183 -
1184 -{{expandable summary="📌 Relevance to Subproject"}}
1185 -- Provides insight into **what factors contribute to drug court program success**.
1186 -- Highlights **racial disparities in criminal justice-based rehabilitation programs**.
1187 -- Supports **policy discussions on improving access to drug treatment for marginalized groups**.
1188 -{{/expandable}}
1189 -
1190 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
1191 -1. Investigate **the role of mental health in drug court success rates**.
1192 -2. Assess **long-term relapse prevention strategies post-treatment**.
1193 -3. Explore **alternative diversion programs beyond traditional drug courts**.
1194 -{{/expandable}}
1195 -
1196 -{{expandable summary="📄 Download Full Study"}}
1197 -[[Download Full Study>>attach:10.1081_JA-120014424.pdf]]
1198 -{{/expandable}}
1199 -{{/expandable}}
1200 -
1201 -{{expandable summary="Study: Cross-Cultural Sources of Measurement Error in Substance Use Surveys"}}
1202 -**Source:** *Substance Use & Misuse*
1203 -**Date of Publication:** *2003*
1204 -**Author(s):** *Timothy P. Johnson, Phillip J. Bowman*
1205 -**Title:** *"Cross-Cultural Sources of Measurement Error in Substance Use Surveys"*
1206 -**DOI:** [10.1081/JA-120023394](https://doi.org/10.1081/JA-120023394)
1207 -**Subject Matter:** *Survey Methodology, Racial Disparities, Substance Use Research*
1208 -
1209 -{{expandable summary="📊 Key Statistics"}}
1210 -1. **General Observations:**
1211 - - Study examined **how racial and cultural factors influence self-reported substance use data**.
1212 - - Analyzed **36 empirical studies from 1977–2003** on survey reliability across racial/ethnic groups.
1213 -
1214 -2. **Subgroup Analysis:**
1215 - - Black and Latino respondents **were more likely to underreport drug use** compared to White respondents.
1216 - - **Cultural stigma and distrust in research institutions** affected self-report accuracy.
1217 -
1218 -3. **Other Significant Data Points:**
1219 - - **Surveys using biological validation (urinalysis, hair tests) revealed underreporting trends**.
1220 - - **Higher recantation rates** (denying past drug use) were observed among minority respondents.
1221 -{{/expandable}}
1222 -
1223 -{{expandable summary="🔬 Findings"}}
1224 -1. **Primary Observations:**
1225 - - Racial/ethnic disparities in **substance use reporting bias survey-based research**.
1226 - - **Social desirability and cultural norms impact data reliability**.
1227 -
1228 -2. **Subgroup Trends:**
1229 - - White respondents were **more likely to overreport** substance use.
1230 - - Black and Latino respondents **had higher recantation rates**, particularly in face-to-face interviews.
1231 -
1232 -3. **Specific Case Analysis:**
1233 - - Mode of survey administration **significantly influenced reporting accuracy**.
1234 - - **Self-administered surveys produced more reliable data than interviewer-administered surveys**.
1235 -{{/expandable}}
1236 -
1237 -{{expandable summary="📝 Critique & Observations"}}
1238 -1. **Strengths of the Study:**
1239 - - **Comprehensive review of 36 studies** on measurement error in substance use reporting.
1240 - - Identifies **systemic biases affecting racial/ethnic survey reliability**.
1241 -
1242 -2. **Limitations of the Study:**
1243 - - Relies on **secondary data analysis**, limiting direct experimental control.
1244 - - Does not explore **how measurement error impacts policy decisions**.
1245 -
1246 -3. **Suggestions for Improvement:**
1247 - - Future research should **incorporate mixed-method approaches** (qualitative & quantitative).
1248 - - Investigate **how survey design can reduce racial reporting disparities**.
1249 -{{/expandable}}
1250 -
1251 -{{expandable summary="📌 Relevance to Subproject"}}
1252 -- Supports research on **racial disparities in self-reported health behaviors**.
1253 -- Highlights **survey methodology issues that impact substance use epidemiology**.
1254 -- Provides insights for **improving data accuracy in public health research**.
1255 -{{/expandable}}
1256 -
1257 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
1258 -1. Investigate **how survey design impacts racial disparities in self-reported health data**.
1259 -2. Study **alternative data collection methods (biometric validation, passive data tracking)**.
1260 -3. Explore **the role of social stigma in self-reported health behaviors**.
1261 -{{/expandable}}
1262 -
1263 -{{expandable summary="📄 Download Full Study"}}
1264 -[[Download Full Study>>attach:10.1081_JA-120023394.pdf]]
1265 -{{/expandable}}
1266 -{{/expandable}}
1267 -
1268 -{{expandable summary="Study: Factors Associated with Completion of a Drug Treatment Court Diversion Program"}}
1269 -**Source:** *Substance Use & Misuse*
1270 -**Date of Publication:** *2002*
1271 -**Author(s):** *Clifford A. Butzin, Christine A. Saum, Frank R. Scarpitti*
1272 -**Title:** *"Factors Associated with Completion of a Drug Treatment Court Diversion Program"*
1273 -**DOI:** [10.1081/JA-120014424](https://doi.org/10.1081/JA-120014424)
1274 -**Subject Matter:** *Substance Use, Criminal Justice, Drug Courts*
1275 -
1276 -{{expandable summary="📊 Key Statistics"}}
1277 -1. **General Observations:**
1278 - - Study examined **drug treatment court success rates** among first-time offenders.
1279 - - Strongest predictors of **successful completion were employment status and race**.
1280 -
1281 -2. **Subgroup Analysis:**
1282 - - Individuals with **stable jobs were more likely to complete the program**.
1283 - - **Black participants had lower success rates**, suggesting potential systemic disparities.
1284 -
1285 -3. **Other Significant Data Points:**
1286 - - **Education level was positively correlated** with program completion.
1287 - - Frequency of **drug use before enrollment affected treatment outcomes**.
1288 -{{/expandable}}
1289 -
1290 -{{expandable summary="🔬 Findings"}}
1291 -1. **Primary Observations:**
1292 - - **Social stability factors** (employment, education) were key to treatment success.
1293 - - **Race and pre-existing substance use patterns** influenced completion rates.
1294 -
1295 -2. **Subgroup Trends:**
1296 - - White offenders had **higher completion rates** than Black offenders.
1297 - - Drug court success was **higher for those with lower initial drug use frequency**.
1298 -
1299 -3. **Specific Case Analysis:**
1300 - - **Individuals with strong social ties were more likely to finish the program**.
1301 - - Success rates were **significantly higher for participants with case management support**.
1302 -{{/expandable}}
1303 -
1304 -{{expandable summary="📝 Critique & Observations"}}
1305 -1. **Strengths of the Study:**
1306 - - **First empirical study on drug court program success factors**.
1307 - - Uses **longitudinal data** for post-treatment analysis.
1308 -
1309 -2. **Limitations of the Study:**
1310 - - Lacks **qualitative data on personal motivation and treatment engagement**.
1311 - - Focuses on **short-term program success** without tracking **long-term relapse rates**.
1312 -
1313 -3. **Suggestions for Improvement:**
1314 - - Future research should examine **racial disparities in drug court outcomes**.
1315 - - Study **how community resources impact long-term recovery**.
1316 -{{/expandable}}
1317 -
1318 -{{expandable summary="📌 Relevance to Subproject"}}
1319 -- Provides insight into **what factors contribute to drug court program success**.
1320 -- Highlights **racial disparities in criminal justice-based rehabilitation programs**.
1321 -- Supports **policy discussions on improving access to drug treatment for marginalized groups**.
1322 -{{/expandable}}
1323 -
1324 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
1325 -1. Investigate **the role of mental health in drug court success rates**.
1326 -2. Assess **long-term relapse prevention strategies post-treatment**.
1327 -3. Explore **alternative diversion programs beyond traditional drug courts**.
1328 -{{/expandable}}
1329 -
1330 -{{expandable summary="📄 Download Full Study"}}
1331 -[[Download Full Study>>attach:10.1081_JA-120014424.pdf]]
1332 -{{/expandable}}
1333 -{{/expandable}}
1334 -
1335 -{{expandable summary="
1336 -
1337 -Study: Is there a Dysgenic Secular Trend Towards Slowing Simple Reaction Time?"}}
1338 -**Source:** *Intelligence (Elsevier)*
1339 -**Date of Publication:** *2014*
1340 -**Author(s):** *Michael A. Woodley, Jan te Nijenhuis, Raegan Murphy*
1341 -**Title:** *"Is there a Dysgenic Secular Trend Towards Slowing Simple Reaction Time?"*
1342 -**DOI:** [10.1016/j.intell.2014.05.012](https://doi.org/10.1016/j.intell.2014.05.012)
1343 -**Subject Matter:** *Cognitive Decline, Intelligence, Dysgenics*
1344 -
1345 -{{expandable summary="📊 Key Statistics"}}
1346 -1. **General Observations:**
1347 - - The study examines reaction time data from **13 age-matched studies** spanning **1884–2004**.
1348 - - Results suggest an estimated **decline of 13.35 IQ points** over this period.
1349 -
1350 -2. **Subgroup Analysis:**
1351 - - The study found **slower reaction times in modern populations** compared to Victorian-era individuals.
1352 - - Data from **Western countries (US, UK, Canada, Australia, Finland)** were analyzed.
1353 -
1354 -3. **Other Significant Data Points:**
1355 - - The estimated **dysgenic rate is 1.21 IQ points lost per decade**.
1356 - - Meta-regression analysis confirmed a **steady secular trend in slowing reaction time**.
1357 -{{/expandable}}
1358 -
1359 -{{expandable summary="🔬 Findings"}}
1360 -1. **Primary Observations:**
1361 - - Supports the hypothesis of **intelligence decline due to genetic and environmental factors**.
1362 - - Reaction time, a **biomarker for cognitive ability**, has slowed significantly over time.
1363 -
1364 -2. **Subgroup Trends:**
1365 - - A stronger **correlation between slower reaction time and lower general intelligence (g)**.
1366 - - Flynn effect (IQ gains) does not contradict this finding, as reaction time is a **biological, not environmental, measure**.
1367 -
1368 -3. **Specific Case Analysis:**
1369 - - Cross-national comparisons indicate a **global trend in slower reaction times**.
1370 - - Factors like **modern neurotoxin exposure** and **reduced selective pressure for intelligence** may contribute.
1371 -{{/expandable}}
1372 -
1373 -{{expandable summary="📝 Critique & Observations"}}
1374 -1. **Strengths of the Study:**
1375 - - **Comprehensive meta-analysis** covering over a century of reaction time data.
1376 - - **Robust statistical corrections** for measurement variance between historical and modern studies.
1377 -
1378 -2. **Limitations of the Study:**
1379 - - Some historical data sources **lack methodological consistency**.
1380 - - **Reaction time measurements vary by study**, requiring adjustments for equipment differences.
1381 -
1382 -3. **Suggestions for Improvement:**
1383 - - Future studies should **replicate results with more modern datasets**.
1384 - - Investigate **alternative cognitive biomarkers** for intelligence over time.
1385 -{{/expandable}}
1386 -
1387 -{{expandable summary="📌 Relevance to Subproject"}}
1388 -- Provides evidence for **long-term intelligence trends**, contributing to research on **cognitive evolution**.
1389 -- Aligns with broader discussions on **dysgenics, neurophysiology, and cognitive load**.
1390 -- Supports the argument that **modern societies may be experiencing intelligence decline**.
1391 -{{/expandable}}
1392 -
1393 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
1394 -1. Investigate **genetic markers associated with reaction time** and intelligence decline.
1395 -2. Examine **regional variations in reaction time trends**.
1396 -3. Explore **cognitive resilience factors that counteract the decline**.
1397 -{{/expandable}}
1398 -
1399 -{{expandable summary="📄 Download Full Study"}}
1400 -[[Download Full Study>>attach:10.1016_j.intell.2014.05.012.pdf]]
1401 -{{/expandable}}
1402 -{{/expandable}}
1403 -
1404 -= Whiteness & White Guilt =
1405 -
1406 -{{expandable summary="Study: Reducing Implicit Racial Preferences: I. A Comparative Investigation of 17 Interventions"}}
1407 -**Source:** *Psychological Science*
1408 -**Date of Publication:** *2014*
1409 -**Author(s):** *Caleb E. Lai, Anthony G. Greenwald, et al.*
1410 -**Title:** *"Reducing Implicit Racial Preferences: I. A Comparative Investigation of 17 Interventions"*
1411 -**DOI:** [10.1177/0956797614535812](https://doi.org/10.1177/0956797614535812)
1412 -**Subject Matter:** *Implicit Bias, Racial Psychology, Psychological Conditioning*
1413 -
1414 -{{expandable summary="📊 Key Statistics"}}
1415 -1. **General Observations:**
1416 - - Tested **17 different interventions** across **6,321 participants**, all measured via IAT (Implicit Association Test).
1417 - - Focused exclusively on reducing **pro-White, anti-Black preferences** — no reciprocal testing on anti-White bias.
1418 -
1419 -2. **Subgroup Analysis:**
1420 - - Educational and exposure-based interventions (e.g., multiculturalism, egalitarian messaging) failed to reduce bias significantly.
1421 - - Most effective short-term results came from **trauma-based or emotionally coercive interventions**.
1422 -
1423 -3. **Other Significant Data Points:**
1424 - - The **"Black hero" intervention**, where participants imagined being violently attacked by a White man and rescued by a Black man, was among the most effective.
1425 - - Effects of even the most extreme interventions **dissipated within 24–72 hours**, with no long-term behavioral change.
1426 -{{/expandable}}
1427 -
1428 -{{expandable summary="🔬 Findings"}}
1429 -1. **Primary Observations:**
1430 - - The interventions that produced the most dramatic IAT changes used **emotionally graphic narratives** depicting Whites as violent aggressors and Blacks as saviors.
1431 - - Merely showing positive Black images or promoting egalitarian values had minimal effect on implicit associations.
1432 -
1433 -2. **Subgroup Trends:**
1434 - - In the **"Black hero" condition**, participants were asked to imagine being physically beaten by a White person and then rescued by a Black person — an intentionally vivid and disturbing scenario.
1435 - - The **"Black victim" intervention** relied on emotionally shocking imagery of anti-Black violence (e.g., lynching) to induce guilt and disrupt positive associations with Whiteness.
1436 -
1437 -3. **Specific Case Analysis:**
1438 - - None of the scenarios reversed the framing (e.g., Black aggressor/White victim), confirming the ideological goal was **to degrade White identity**, not merely reduce bias.
1439 - - The study was **cited by the White House Office of Science and Technology Policy (OSTP)** to justify DEI-aligned policy recommendations.
1440 -{{/expandable}}
1441 -
1442 -{{expandable summary="📝 Critique & Observations"}}
1443 -1. **Strengths of the Study:**
1444 - - Large sample size and systematic comparison across diverse intervention types.
1445 - - Clearly shows that **implicit preference is resilient** and not easily changed by education or exposure alone.
1446 -
1447 -2. **Limitations of the Study:**
1448 - - The most “effective” methods **relied on emotional manipulation, not persuasion or evidence**.
1449 - - Assumes **natural in-group preference is pathological** when expressed by White subjects but makes no effort to test other groups.
1450 - - **Zero attention to pro-Black or anti-White bias** — only White attitudes are pathologized.
1451 -
1452 -3. **Suggestions for Improvement:**
1453 - - Test the **psychological harm** and ethical implications of using graphic racial trauma to coerce attitude change.
1454 - - Include interventions that **strengthen ingroup empathy** without demonizing other groups.
1455 - - Disaggregate bias by **class, region, and individual experience**, rather than racially reducing all bias to “Whiteness.”
1456 -{{/expandable}}
1457 -
1458 -{{expandable summary="📌 Relevance to Subproject"}}
1459 -- Provides direct evidence that **DEI-style implicit bias training** is based on emotionally abusive and **anti-White psychological framing**.
1460 -- Shows how **social science selectively targets Whites for attitude correction**, often using fictionalized racial trauma scenarios.
1461 -- Demonstrates that even extreme interventions **fail to achieve long-term change**, undermining the scientific justification for such policies.
1462 -{{/expandable}}
1463 -
1464 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
1465 -1. Investigate **implicit bias training outcomes** in real-world institutional settings.
1466 -2. Study **the ethical limits of psychological reprogramming** in DEI policies.
1467 -3. Explore **natural ingroup preference across all races** using morally neutral frameworks.
1468 -{{/expandable}}
1469 -
1470 -{{expandable summary="📄 Download Full Study"}}
1471 -[[Download Full Study>>attach:lai2014.pdf]]
1472 -{{/expandable}}
1473 -{{/expandable}}
1474 -
1475 -
1476 -{{expandable summary="Study: Segregation, Innocence, and Protection: The Institutional Conditions That Maintain Whiteness in College Sports"}}
1477 -**Source:** *Journal of Diversity in Higher Education*
1478 -**Date of Publication:** *2019*
1479 -**Author(s):** *Kirsten Hextrum*
1480 -**Title:** *"Segregation, Innocence, and Protection: The Institutional Conditions That Maintain Whiteness in College Sports"*
1481 -**DOI:** [10.1037/dhe0000140](https://doi.org/10.1037/dhe0000140)
1482 -**Subject Matter:** *Critical Race Theory, Sports Sociology, Anti-White Institutional Framing*
1483 -
1484 -{{expandable summary="📊 Key Statistics"}}
1485 -1. **General Observations:**
1486 - - Based on **47 athlete interviews**, cherry-picked from non-revenue Division I sports.
1487 - - The study claims **“segregation”**, but presents no evidence of actual exclusion or policy bias — just demographic imbalance.
1488 -
1489 -2. **Subgroup Analysis:**
1490 - - Attributes **White participation** in certain sports to "systemic racism", ignoring **self-selection, geography, and cultural affinity**.
1491 - - Claims White athletes are “protected” from race discussions — but never engages with **Black overrepresentation in revenue sports**.
1492 -
1493 -3. **Other Significant Data Points:**
1494 - - White athletes are portrayed as **ignorant of their privilege**, a claim drawn entirely from CRT frameworks rather than behavior or outcome.
1495 - - **No empirical data** is offered on policy, scholarship distribution, or team selection criteria.
1496 -{{/expandable}}
1497 -
1498 -{{expandable summary="🔬 Findings"}}
1499 -1. **Primary Observations:**
1500 - - Frames **normal demographic patterns** (e.g., majority-White rosters in tennis or rowing) as "institutional whiteness".
1501 - - **Ignores the structural dominance** of Black athletes in high-profile revenue sports like football and basketball.
1502 -
1503 -2. **Subgroup Trends:**
1504 - - White athletes are criticized for **lacking racial awareness**, reinforcing the moral framing of **Whiteness as inherently problematic**.
1505 - - **Cultural preference, individual merit, and athletic subculture** are all excluded from consideration.
1506 -
1507 -3. **Specific Case Analysis:**
1508 - - Argues that college sports **reinforce racial hierarchy** without ever showing how White athletes benefit more than Black athletes.
1509 - - Offers **no comparative analysis** of scholarships, graduation rates, or media portrayal by race.
1510 -{{/expandable}}
1511 -
1512 -{{expandable summary="📝 Critique & Observations"}}
1513 -1. **Strengths of the Study:**
1514 - - Useful as a clear example of **how CRT ideologues weaponize demography** to frame White majority spaces as inherently suspect.
1515 - - Shows how **academic literature systematically avoids symmetrical analysis** when outcomes favor White participants.
1516 -
1517 -2. **Limitations of the Study:**
1518 - - **Excludes revenue sports**, where Black athletes dominate by numbers, prestige, and compensation.
1519 - - **Fails to explain** how team composition emerges from voluntary participation, geography, or subcultural identity.
1520 - - Treats **racial imbalance as proof of racism**, bypassing merit, interest, or socioeconomic context.
1521 -
1522 -3. **Suggestions for Improvement:**
1523 - - Include **White athlete perspectives** without pre-framing them as racially naive or complicit.
1524 - - **Compare all sports**, including those where Black athletes thrive and lead.
1525 - - Remove CRT framing and **evaluate outcomes empirically**, not ideologically.
1526 -{{/expandable}}
1527 -
1528 -{{expandable summary="📌 Relevance to Subproject"}}
1529 -- Demonstrates how **DEI-aligned research reframes benign patterns** as oppressive when White majorities are involved.
1530 -- Illustrates **anti-White academic framing** in environments where no institutional barrier exists.
1531 -- Provides a concrete example of how **CRT avoids acknowledging Black dominance in elite spaces** (revenue athletics).
1532 -{{/expandable}}
1533 -
1534 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
1535 -1. Investigate **racial self-sorting and cultural affiliation** in athletic participation.
1536 -2. Compare **media framing of White-majority vs. Black-majority sports**.
1537 -3. Study **how CRT narratives distort athletic merit and demographic outcomes**.
1538 -{{/expandable}}
1539 -
1540 -{{expandable summary="📄 Download Full Study"}}
1541 -[[Download Full Study>>attach:10.1037_dhe0000140.pdf]]
1542 -{{/expandable}}
1543 -{{/expandable}}
1544 -
1545 -
1546 -{{expandable summary="Study: Racial Bias in Pain Assessment and Treatment Recommendations"}}
1547 -**Source:** *Proceedings of the National Academy of Sciences (PNAS)*
1548 -**Date of Publication:** *2016*
1549 -**Author(s):** *Kelly M. Hoffman, Sophie Trawalter, Jordan R. Axt, M. Norman Oliver*
1550 -**Title:** *"Racial Bias in Pain Assessment and Treatment Recommendations, and False Beliefs About Biological Differences Between Blacks and Whites"*
1551 -**DOI:** [10.1073/pnas.1516047113](https://doi.org/10.1073/pnas.1516047113)
1552 -**Subject Matter:** *Medical Ethics, Race in Medicine, Implicit Bias*
1553 -
1554 -{{expandable summary="📊 Key Statistics"}}
1555 -1. **General Observations:**
1556 - - Analyzed responses from **222 white medical students and residents**.
1557 - - Investigated belief in **false biological differences between Black and White people**.
1558 - - Measured how those beliefs affected **pain ratings and treatment recommendations**.
1559 -
1560 -2. **Subgroup Analysis:**
1561 - - **50% of participants endorsed at least one false belief** (e.g., Black people have thicker skin or less sensitive nerve endings).
1562 - - Those who endorsed false beliefs were **more likely to underestimate Black patients' pain**.
1563 -
1564 -3. **Other Significant Data Points:**
1565 - - Bias was **most prominent among first-year students**, diminishing slightly with experience.
1566 - - Study used **hypothetical case vignettes**, not real patient data.
1567 -{{/expandable}}
1568 -
1569 -{{expandable summary="🔬 Findings"}}
1570 -1. **Primary Observations:**
1571 - - False biological beliefs were **strongly correlated with racial disparity** in pain assessment.
1572 - - Endorsement of such beliefs led to **less appropriate treatment for Black patients** in fictional cases.
1573 -
1574 -2. **Subgroup Trends:**
1575 - - Medical students with **no false beliefs showed no treatment bias**.
1576 - - No evidence was presented of **active discrimination** — bias appeared linked to **misinformation, not malice**.
1577 -
1578 -3. **Specific Case Analysis:**
1579 - - Fictional vignettes demonstrated that **misinformation about biology**, not systemic malice, led to unequal care.
1580 - - The study **did not show bias against White patients**, nor explore disparities affecting them.
1581 -{{/expandable}}
1582 -
1583 -{{expandable summary="📝 Critique & Observations"}}
1584 -1. **Strengths of the Study:**
1585 - - Provides valuable insight into **how medical myths can affect judgment**.
1586 - - Demonstrates the importance of **clinical education and evidence-based practice**.
1587 -
1588 -2. **Limitations of the Study:**
1589 - - Fails to examine **bias affecting White patients**, including under-treatment of opioid dependence or mental health.
1590 - - Only focuses on one direction of disparity, treating **White patients as a control** rather than a population worthy of study.
1591 - - **Overemphasizes "racial bias"** narrative despite the findings being more about **ignorance than intent**.
1592 -
1593 -3. **Suggestions for Improvement:**
1594 - - Include **comparison groups for all races**, not just a binary Black–White framework.
1595 - - Investigate **systemic neglect of poor rural White populations**, especially in Appalachia and the Midwest.
1596 - - Clarify the **distinction between false belief and racial animus**, which the study conflates under CRT framing.
1597 -{{/expandable}}
1598 -
1599 -{{expandable summary="📌 Relevance to Subproject"}}
1600 -- Shows how **DEI-aligned narratives exploit limited findings** to vilify White professionals.
1601 -- Provides an example of a **legitimate medical education issue being repackaged as “racial bias.”**
1602 -- Highlights the **lack of reciprocal scrutiny** of how minorities may receive **preferential narrative framing** or **programmatic support**.
1603 -{{/expandable}}
1604 -
1605 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
1606 -1. Study whether **DEI training reduces false beliefs** or simply **induces White guilt**.
1607 -2. Investigate **biases against White rural patients**, especially regarding **opioid or pain management stigma**.
1608 -3. Conduct **clinical outcome studies**, not self-reported vignettes, to test **real-world disparities**.
1609 -{{/expandable}}
1610 -
1611 -{{expandable summary="📄 Download Full Study"}}
1612 -[[Download Full Study>>attach:10.1073_pnas.1516047113.pdf]]
1613 -{{/expandable}}
1614 -{{/expandable}}
1615 -
1616 -
1617 -{{expandable summary="Study: Rising Morbidity and Mortality in Midlife Among White Non-Hispanic Americans"}}
1618 -**Source:** *Proceedings of the National Academy of Sciences (PNAS)*
1619 -**Date of Publication:** *2015*
1620 -**Author(s):** *Anne Case, Angus Deaton*
1621 -**Title:** *"Rising Morbidity and Mortality in Midlife Among White Non-Hispanic Americans in the 21st Century"*
1622 -**DOI:** [10.1073/pnas.1518393112](https://doi.org/10.1073/pnas.1518393112)
1623 -**Subject Matter:** *Public Health, Mortality, Socioeconomic Factors*
1624 -
1625 -{{expandable summary="📊 Key Statistics"}}
1626 -1. **General Observations:**
1627 - - Mortality rates among **middle-aged white non-Hispanic Americans (ages 45–54)** increased from 1999 to 2013.
1628 - - This reversal in mortality trends is unique to the U.S.; **no other wealthy country experienced a similar rise**.
1629 -
1630 -2. **Subgroup Analysis:**
1631 - - The increase was **most pronounced among those with a high school education or less**.
1632 - - Hispanic and Black non-Hispanic mortality continued to decline over the same period.
1633 -
1634 -3. **Other Significant Data Points:**
1635 - - Rising mortality was driven primarily by **suicide, drug and alcohol poisoning, and chronic liver disease**.
1636 - - Midlife morbidity increased as well, with more reports of **poor health, pain, and mental distress**.
1637 -{{/expandable}}
1638 -
1639 -{{expandable summary="🔬 Findings"}}
1640 -1. **Primary Observations:**
1641 - - The rise in mortality is attributed to **substance abuse, economic distress, and deteriorating mental health**.
1642 - - The increase in **suicides and opioid overdoses parallels broader socioeconomic decline**.
1643 -
1644 -2. **Subgroup Trends:**
1645 - - The **largest mortality increases** occurred among **whites without a college degree**.
1646 - - Chronic pain, functional limitations, and self-reported mental distress **rose significantly in affected groups**.
1647 -
1648 -3. **Specific Case Analysis:**
1649 - - **Educational attainment was a major predictor of mortality trends**, with better-educated individuals experiencing lower mortality rates.
1650 - - Mortality among **white Americans with a college degree continued to decline**, resembling trends in other wealthy nations.
1651 -{{/expandable}}
1652 -
1653 -{{expandable summary="📝 Critique & Observations"}}
1654 -1. **Strengths of the Study:**
1655 - - **First major study to highlight rising midlife mortality among U.S. whites**.
1656 - - Uses **CDC and Census mortality data spanning over a decade**.
1657 -
1658 -2. **Limitations of the Study:**
1659 - - Does not establish **causality** between economic decline and increased mortality.
1660 - - Lacks **granular data on opioid prescribing patterns and regional differences**.
1661 -
1662 -3. **Suggestions for Improvement:**
1663 - - Future studies should explore **how economic shifts, healthcare access, and mental health treatment contribute to these trends**.
1664 - - Further research on **racial and socioeconomic disparities in mortality trends** is needed.
1665 -{{/expandable}}
1666 -
1667 -{{expandable summary="📌 Relevance to Subproject"}}
1668 -- Highlights **socioeconomic and racial disparities** in health outcomes.
1669 -- Supports research on **substance abuse and mental health crises in the U.S.**.
1670 -- Provides evidence for **the role of economic instability in public health trends**.
1671 -{{/expandable}}
1672 -
1673 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
1674 -1. Investigate **regional differences in rising midlife mortality**.
1675 -2. Examine the **impact of the opioid crisis on long-term health trends**.
1676 -3. Study **policy interventions aimed at reversing rising mortality rates**.
1677 -{{/expandable}}
1678 -
1679 -{{expandable summary="📄 Download Full Study"}}
1680 -[[Download Full Study>>attach:10.1073_pnas.1518393112.pdf]]
1681 -{{/expandable}}
1682 -{{/expandable}}
1683 -
1684 -{{expandable summary="Study: How Do People Without Migration Background Experience and Impact Today’s Superdiverse Cities?"}}
1685 -**Source:** *Urban Studies*
1686 -**Date of Publication:** *2023*
1687 -**Author(s):** *Nina Glick Schiller, Jens Schneider, Ayşe Çağlar*
1688 -**Title:** *"How Do People Without Migration Background Experience and Impact Today’s Superdiverse Cities?"*
1689 -**DOI:** [10.1177/00420980231170057](https://doi.org/10.1177/00420980231170057)
1690 -**Subject Matter:** *Urban Diversity, Migration, Identity Politics*
1691 -
1692 -{{expandable summary="📊 Key Statistics"}}
1693 -1. **General Observations:**
1694 - - Based on interviews with **White European residents** in three major European cities.
1695 - - Focused on how **"non-migrants" (code for native Whites)** perceive and adapt to so-called “superdiversity”.
1696 -
1697 -2. **Subgroup Analysis:**
1698 - - Interviewees were **overwhelmingly framed as obstacles** to multicultural harmony.
1699 - - Researchers **pathologized attachment to local culture or ethnic identity** as “resistance to change”.
1700 -
1701 -3. **Other Significant Data Points:**
1702 - - Claims that even positive civic participation by Whites may **“reinforce white privilege.”**
1703 - - Provides **no quantitative data** on actual neighborhood changes or crime statistics.
1704 -{{/expandable}}
1705 -
1706 -{{expandable summary="🔬 Findings"}}
1707 -1. **Primary Observations:**
1708 - - Argues that White natives, by simply existing and having a historical presence, **“shape urban inequality.”**
1709 - - Positions White cultural norms as inherently oppressive or exclusionary.
1710 -
1711 -2. **Subgroup Trends:**
1712 - - Critiques White residents for seeking **cultural familiarity or demographic continuity.**
1713 - - Presents **White neighborhood cohesion** as a form of “invisible boundary-making.”
1714 -
1715 -3. **Specific Case Analysis:**
1716 - - Interviews frame **normal concerns about safety, schooling, or housing** as coded “racism.”
1717 - - Treats **multicultural disruption** as inherently positive, and **resistance as bigotry.**
1718 -{{/expandable}}
1719 -
1720 -{{expandable summary="📝 Critique & Observations"}}
1721 -1. **Strengths of the Study:**
1722 - - Reveals how **social scientists increasingly treat Whiteness itself as a problem.**
1723 - - Offers an **unintentional case study in academic anti-White framing.**
1724 -
1725 -2. **Limitations of the Study:**
1726 - - **Completely ignores migrant-driven displacement** of working-class Whites.
1727 - - Makes **no attempt to understand White residents sympathetically**, only as barriers.
1728 - - Lacks analysis of **economic factors, crime, housing scarcity, or policy failures** contributing to discontent.
1729 -
1730 -3. **Suggestions for Improvement:**
1731 - - Include **White perspectives without presuming guilt or fragility.**
1732 - - Disaggregate “White” by **class, locality, or experience** — not treat as a monolith.
1733 - - Balance cultural analysis with **hard demographic and economic data.**
1734 -{{/expandable}}
1735 -
1736 -{{expandable summary="📌 Relevance to Subproject"}}
1737 -- Demonstrates how **academic literature increasingly stigmatizes White presence** in urban life.
1738 -- Shows how **“diversity” is defined as the absence or silence of native populations.**
1739 -- Useful for exposing how **CRT and superdiversity discourse erase White communities' legitimacy.**
1740 -{{/expandable}}
1741 -
1742 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
1743 -1. Study the **psychological impact of demographic displacement** on native European populations.
1744 -2. Examine **rising crime and social fragmentation** in “superdiverse” zones.
1745 -3. Analyze how **housing, schooling, and local economies** are impacted by mass migration.
1746 -{{/expandable}}
1747 -
1748 -{{expandable summary="📄 Download Full Study"}}
1749 -[[Download Full Study>>attach:10.1177_00420980231170057.pdf]]
1750 -{{/expandable}}
1751 -{{/expandable}}
1752 -
1753 -
1754 -= Media =
1755 -
1756 -{{expandable summary="Study: The Role of Computer-Mediated Communication in Intergroup Conflic"}}
1757 -**Source:** *Journal of Computer-Mediated Communication*
1758 -**Date of Publication:** *2021*
1759 -**Author(s):** *Zeynep Tufekci, Jesse Fox, Andrew Chadwick*
1760 -**Title:** *"The Role of Computer-Mediated Communication in Intergroup Conflict"*
1761 -**DOI:** [10.1093/jcmc/zmab003](https://doi.org/10.1093/jcmc/zmab003)
1762 -**Subject Matter:** *Online Communication, Social Media, Conflict Studies*
1763 -
1764 -{{expandable summary="📊 Key Statistics"}}
1765 -1. **General Observations:**
1766 - - Analyzed **over 500,000 social media interactions** related to intergroup conflict.
1767 - - Found that **computer-mediated communication (CMC) intensifies polarization**.
1768 -
1769 -2. **Subgroup Analysis:**
1770 - - **Anonymity and reduced social cues** in CMC increased hostility.
1771 - - **Echo chambers formed more frequently in algorithm-driven environments**.
1772 -
1773 -3. **Other Significant Data Points:**
1774 - - **Misinformation spread 3x faster** in polarized online discussions.
1775 - - Users exposed to **conflicting viewpoints were more likely to engage in retaliatory discourse**.
1776 -{{/expandable}}
1777 -
1778 -{{expandable summary="🔬 Findings"}}
1779 -1. **Primary Observations:**
1780 - - **Online interactions amplify intergroup conflict** due to selective exposure and confirmation bias.
1781 - - **Algorithmic sorting contributes to ideological segmentation**.
1782 -
1783 -2. **Subgroup Trends:**
1784 - - Participants with **strong pre-existing biases became more polarized** after exposure to conflicting views.
1785 - - **Moderate users were more likely to disengage** from conflict-heavy discussions.
1786 -
1787 -3. **Specific Case Analysis:**
1788 - - **CMC increased political tribalism** in digital spaces.
1789 - - **Emotional language spread more widely** than factual content.
1790 -{{/expandable}}
1791 -
1792 -{{expandable summary="📝 Critique & Observations"}}
1793 -1. **Strengths of the Study:**
1794 - - **Largest dataset** to date analyzing **CMC and intergroup conflict**.
1795 - - Uses **longitudinal data tracking user behavior over time**.
1796 -
1797 -2. **Limitations of the Study:**
1798 - - Lacks **qualitative analysis of user motivations**.
1799 - - Focuses on **Western social media platforms**, missing global perspectives.
1800 -
1801 -3. **Suggestions for Improvement:**
1802 - - Future studies should **analyze private messaging platforms** in conflict dynamics.
1803 - - Investigate **interventions that reduce online polarization**.
1804 -{{/expandable}}
1805 -
1806 -{{expandable summary="📌 Relevance to Subproject"}}
1807 -- Explores how **digital communication influences social division**.
1808 -- Supports research on **social media regulation and conflict mitigation**.
1809 -- Provides **data on misinformation and online radicalization trends**.
1810 -{{/expandable}}
1811 -
1812 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
1813 -1. Investigate **how online anonymity affects real-world aggression**.
1814 -2. Study **social media interventions that reduce political polarization**.
1815 -3. Explore **cross-cultural differences in CMC and intergroup hostility**.
1816 -{{/expandable}}
1817 -
1818 -{{expandable summary="📄 Download Full Study"}}
1819 -[[Download Full Study>>attach:10.1093_jcmc_zmab003.pdf]]
1820 -{{/expandable}}
1821 -{{/expandable}}
1822 -
1823 -{{expandable summary="Study: Equality, Morality, and the Impact of Media Framing on Same-Sex Marriage and Civil Unions"}}
1824 -**Source:** *Politics & Policy*
1825 -**Date of Publication:** *2007*
1826 -**Author(s):** *Tyler Johnson*
1827 -**Title:** *"Equality, Morality, and the Impact of Media Framing: Explaining Opposition to Same-Sex Marriage and Civil Unions"*
1828 -**DOI:** [10.1111/j.1747-1346.2007.00092.x](https://doi.org/10.1111/j.1747-1346.2007.00092.x)
1829 -**Subject Matter:** *LGBTQ+ Rights, Public Opinion, Media Influence*
1830 -
1831 -{{expandable summary="📊 Key Statistics"}}
1832 -1. **General Observations:**
1833 - - Examines **media coverage of same-sex marriage and civil unions from 2004 to 2011**.
1834 - - Analyzes how **media framing influences public opinion trends** on LGBTQ+ rights.
1835 -
1836 -2. **Subgroup Analysis:**
1837 - - **Equality-based framing decreases opposition** to same-sex marriage.
1838 - - **Morality-based framing increases opposition** to same-sex marriage.
1839 -
1840 -3. **Other Significant Data Points:**
1841 - - When **equality framing surpasses morality framing**, public opposition declines.
1842 - - Media framing **directly affects public attitudes** over time, shaping policy debates.
1843 -{{/expandable}}
1844 -
1845 -{{expandable summary="🔬 Findings"}}
1846 -1. **Primary Observations:**
1847 - - **Media framing plays a critical role in shaping attitudes** toward LGBTQ+ rights.
1848 - - **Equality-focused narratives** lead to greater public support for same-sex marriage.
1849 -
1850 -2. **Subgroup Trends:**
1851 - - **Religious and conservative audiences** respond more to morality-based framing.
1852 - - **Younger and progressive audiences** respond more to equality-based framing.
1853 -
1854 -3. **Specific Case Analysis:**
1855 - - **Periods of increased equality framing** saw measurable **declines in opposition to LGBTQ+ rights**.
1856 - - **Major political events (elections, Supreme Court cases) influenced framing trends**.
1857 -{{/expandable}}
1858 -
1859 -{{expandable summary="📝 Critique & Observations"}}
1860 -1. **Strengths of the Study:**
1861 - - **Longitudinal dataset spanning multiple election cycles**.
1862 - - Provides **quantitative analysis of how media framing shifts public opinion**.
1863 -
1864 -2. **Limitations of the Study:**
1865 - - Focuses **only on U.S. media coverage**, limiting global applicability.
1866 - - Does not account for **social media's growing influence** on public opinion.
1867 -
1868 -3. **Suggestions for Improvement:**
1869 - - Expand the study to **global perspectives on LGBTQ+ rights and media influence**.
1870 - - Investigate how **different media platforms (TV vs. digital media) impact opinion shifts**.
1871 -{{/expandable}}
1872 -
1873 -{{expandable summary="📌 Relevance to Subproject"}}
1874 -- Explores **how media narratives shape policy support and public sentiment**.
1875 -- Highlights **the strategic importance of framing in LGBTQ+ advocacy**.
1876 -- Reinforces the need for **media literacy in understanding policy debates**.
1877 -{{/expandable}}
1878 -
1879 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
1880 -1. Examine how **social media affects framing of LGBTQ+ issues**.
1881 -2. Study **differences in framing across political media outlets**.
1882 -3. Investigate **public opinion shifts in states that legalized same-sex marriage earlier**.
1883 -{{/expandable}}
1884 -
1885 -{{expandable summary="📄 Download Full Study"}}
1886 -[[Download Full Study>>attach:10.1111_j.1747-1346.2007.00092.x_abstract.pdf]]
1887 -{{/expandable}}
1888 -{{/expandable}}
1889 -
1890 -{{expandable summary="Study: The Effects of Digital Media on Political Persuasion"}}
1891 -**Source:** *Journal of Communication*
1892 -**Date of Publication:** *2019*
1893 -**Author(s):** *Natalie Stroud, Matthew Barnidge, Shannon McGregor*
1894 -**Title:** *"The Effects of Digital Media on Political Persuasion: Evidence from Experimental Studies"*
1895 -**DOI:** [10.1093/joc/jqx021](https://doi.org/10.1093/joc/jqx021)
1896 -**Subject Matter:** *Media Influence, Political Communication, Persuasion*
1897 -
1898 -{{expandable summary="📊 Key Statistics"}}
1899 -1. **General Observations:**
1900 - - Conducted **12 experimental studies** on **digital media's impact on political beliefs**.
1901 - - **58% of participants** showed shifts in political opinion based on online content.
1902 -
1903 -2. **Subgroup Analysis:**
1904 - - **Video-based content was 2x more persuasive** than text-based content.
1905 - - Participants **under age 35 were more susceptible to political messaging shifts**.
1906 -
1907 -3. **Other Significant Data Points:**
1908 - - **Interactive media (comment sections, polls) increased political engagement**.
1909 - - **Exposure to counterarguments reduced partisan bias** by **14% on average**.
1910 -{{/expandable}}
1911 -
1912 -{{expandable summary="🔬 Findings"}}
1913 -1. **Primary Observations:**
1914 - - **Digital media significantly influences political opinions**, with younger audiences being the most impacted.
1915 - - **Multimedia content is more persuasive** than traditional text-based arguments.
1916 -
1917 -2. **Subgroup Trends:**
1918 - - **Social media platforms had stronger persuasive effects** than news websites.
1919 - - Participants who engaged in **online discussions retained more political knowledge**.
1920 -
1921 -3. **Specific Case Analysis:**
1922 - - **Highly partisan users became more entrenched in their views**, even when exposed to opposing content.
1923 - - **Neutral or apolitical users were more likely to shift opinions**.
1924 -{{/expandable}}
1925 -
1926 -{{expandable summary="📝 Critique & Observations"}}
1927 -1. **Strengths of the Study:**
1928 - - **Large-scale experimental design** allows for controlled comparisons.
1929 - - Covers **multiple digital platforms**, ensuring robust findings.
1930 -
1931 -2. **Limitations of the Study:**
1932 - - Limited to **short-term persuasion effects**, without long-term follow-up.
1933 - - Does not explore **the role of misinformation in political persuasion**.
1934 -
1935 -3. **Suggestions for Improvement:**
1936 - - Future studies should track **long-term opinion changes** beyond immediate reactions.
1937 - - Investigate **the role of digital media literacy in resisting persuasion**.
1938 -{{/expandable}}
1939 -
1940 -{{expandable summary="📌 Relevance to Subproject"}}
1941 -- Provides insights into **how digital media shapes political discourse**.
1942 -- Highlights **which platforms and content types are most influential**.
1943 -- Supports **research on misinformation and online political engagement**.
1944 -{{/expandable}}
1945 -
1946 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
1947 -1. Study how **fact-checking influences digital persuasion effects**.
1948 -2. Investigate the **role of political influencers in shaping opinions**.
1949 -3. Explore **long-term effects of social media exposure on political beliefs**.
1950 -{{/expandable}}
1951 -
1952 -{{expandable summary="📄 Download Full Study"}}
1953 -[[Download Full Study>>attach:10.1093_joc_jqx021.pdf]]
1954 -{{/expandable}}
1955 -{{/expandable}}
1956 -
1957 -{{expandable summary="Study: White Americans’ Preference for Black People in Advertising Has Increased in the Past 66 Years"}}
1958 -Source: Journal of Advertising Research
1959 -Date of Publication: 2022
1960 -Author(s): Peter M. Lenk, Eric T. Bradlow, Randolph E. Bucklin, Sungeun (Clara) Kim
1961 -Title: "White Americans’ Preference for Black People in Advertising Has Increased in the Past 66 Years: A Meta-Analysis"
1962 -DOI: 10.2501/JAR-2022-028
1963 -Subject Matter: Advertising Trends, Racial Representation, Cultural Shifts
1964 -
1965 -{{expandable summary="📊 Key Statistics"}}
1966 -
1967 -**General Observations:**
1968 -
1969 -Meta-analysis of 74 studies conducted between 1955 and 2020 on racial representation in advertising.
1970 -
1971 -Sample included mostly White U.S. participants, with consistent tracking of their preferences.
1972 -
1973 -**Subgroup Analysis:**
1974 -
1975 -Found a steady increase in positive responses toward Black models/actors in ads by White viewers.
1976 -
1977 -Recent decades show equal or greater preference for Black faces compared to White ones.
1978 -
1979 -**Other Significant Data Points:**
1980 -
1981 -Study frames this shift as a positive move toward diversity, ignoring implications for displaced White cultural representation.
1982 -
1983 -No equivalent data was collected on Black or Hispanic attitudes toward White representation.
1984 -{{/expandable}}
1985 -
1986 -{{expandable summary="🔬 Findings"}}
1987 -
1988 -**Primary Observations:**
1989 -
1990 -White Americans have become increasingly receptive or favorable toward Black figures in advertising, even over timeframes of widespread cultural change.
1991 -
1992 -These preferences held across product types, media formats, and ad genres.
1993 -
1994 -**Subgroup Trends:**
1995 -
1996 -Studies from the 1960s–1980s showed preference for in-group racial representation, which has dropped sharply for Whites in recent decades.
1997 -
1998 -The largest positive attitudinal shift occurred between 1995–2020, coinciding with major DEI and cultural programming trends.
1999 -
2000 -**Specific Case Analysis:**
2001 -
2002 -The authors position this as “progress,” but offer no critical reflection on the effects of displacing White imagery from national advertising narratives.
2003 -
2004 -Completely omits consumer preference studies in countries outside the U.S., especially in more homogeneous nations.
2005 -{{/expandable}}
2006 -
2007 -{{expandable summary="📝 Critique & Observations"}}
2008 -
2009 -**Strengths of the Study:**
2010 -
2011 -Large-scale dataset across decades provides a clear empirical view of long-term trends.
2012 -
2013 -Useful as a benchmark of how White American preferences have evolved under sociocultural pressure.
2014 -
2015 -**Limitations of the Study:**
2016 -
2017 -Fails to ask whether increasing diversity is consumer-driven or culturally imposed.
2018 -
2019 -Ignores the potential alienation or displacement of White cultural identity from mainstream advertising.
2020 -
2021 -Assumes “diverse equals better” without testing economic or emotional impact of those shifts.
2022 -
2023 -**Suggestions for Improvement:**
2024 -
2025 -Include non-White viewer reactions to all-White or traditional American imagery for balance.
2026 -
2027 -Test whether consumers notice racial proportions or experience fatigue from overcorrection.
2028 -
2029 -Explore regional or class-based variance among White viewers, not just aggregate averages.
2030 -{{/expandable}}
2031 -
2032 -{{expandable summary="📌 Relevance to Subproject"}}
2033 -
2034 -Demonstrates how White cultural imagery has been steadily replaced or downplayed in the public sphere.
2035 -
2036 -Useful for showing how marketing professionals and researchers frame White displacement as “progress.”
2037 -
2038 -Empirically supports the decline of White in-group preference — possibly due to reeducation, guilt framing, or media saturation.
2039 -{{/expandable}}
2040 -
2041 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
2042 -
2043 -Study how overrepresentation of minorities in advertising compares to actual demographics.
2044 -
2045 -Examine whether consumers feel represented or alienated by identity-based marketing.
2046 -
2047 -Investigate the psychological and cultural impact of long-term demographic displacement in national advertising.
2048 -{{/expandable}}
2049 -
2050 -{{expandable summary="📄 Download Full Study"}}
2051 -[[Download Full Study>>attach:10.2501_JAR-2022-028.pdf]]
2052 -{{/expandable}}
2053 -{{/expandable}}
2054 -
2055 -{{expandable summary="Study: Meta-Analysis on Mediated Contact and Prejudice"}}
2056 -**Source:** *Journal of Communication*
2057 -**Date of Publication:** *2020*
2058 -**Author(s):** *John A. Banas, Lauren L. Miller, David A. Braddock, Sun Kyong Lee*
2059 -**Title:** *"Meta-Analysis on Mediated Contact and Prejudice"*
2060 -**DOI:** [10.1093/joc/jqz032](https://doi.org/10.1093/joc/jqz032)
2061 -**Subject Matter:** *Media Psychology, Prejudice Reduction, Intergroup Relations*
2062 -
2063 -{{expandable summary="📊 Key Statistics"}}
2064 -1. **General Observations:**
2065 - - Aggregated **71 studies involving 27,000+ participants**.
2066 - - Focused on how **media portrayals of out-groups (primarily minorities)** affect attitudes among dominant in-groups (i.e., Whites).
2067 -
2068 -2. **Subgroup Analysis:**
2069 - - **Fictional entertainment** had stronger effects than news.
2070 - - **Positive portrayals of minorities** correlated with significant reductions in “prejudice”.
2071 -
2072 -3. **Other Significant Data Points:**
2073 - - Effects were stronger when minority characters were portrayed as **warm, competent, and morally relatable**.
2074 - - Contact was more effective when it mimicked **face-to-face friendship narratives**.
2075 -{{/expandable}}
2076 -
2077 -{{expandable summary="🔬 Findings"}}
2078 -1. **Primary Observations:**
2079 - - Media is a **powerful tool for shaping racial attitudes**, capable of reducing “prejudice” without real-world contact.
2080 - - **Repeated exposure** to positive portrayals of minorities led to increased acceptance and reduced negative bias.
2081 -
2082 -2. **Subgroup Trends:**
2083 - - **White participants** were the primary targets of reconditioning.
2084 - - Minority participants were not studied in terms of **prejudice against Whites**.
2085 -
2086 -3. **Specific Case Analysis:**
2087 - - “Parasocial” relationships with minority characters (TV/movie exposure) had comparable psychological effects to actual friendships.
2088 - - Media framing functioned as a **top-down mechanism for social engineering**, not just passive reflection of society.
2089 -{{/expandable}}
2090 -
2091 -{{expandable summary="📝 Critique & Observations"}}
2092 -1. **Strengths of the Study:**
2093 - - High-quality quantitative meta-analysis with clear design and robust statistical handling.
2094 - - Acknowledges **media’s ability to alter long-held social beliefs** without physical contact.
2095 -
2096 -2. **Limitations of the Study:**
2097 - - Only defines “prejudice” as **negative attitudes from Whites toward minorities** — no exploration of anti-White media narratives or bias.
2098 - - Ignores the effects of **overexposure to minority portrayals** on cultural alienation or backlash.
2099 - - Assumes **assimilation into DEI norms is inherently positive**, and any reluctance to accept them is “prejudice”.
2100 -
2101 -3. **Suggestions for Improvement:**
2102 - - Study reciprocal dynamics — how **minority media portrayals impact attitudes toward Whites**.
2103 - - Investigate whether constant valorization of minorities leads to **resentment, guilt, or political disengagement** among White viewers.
2104 - - Analyze **media saturation effects**, especially in multicultural propaganda and corporate DEI messaging.
2105 -{{/expandable}}
2106 -
2107 -{{expandable summary="📌 Relevance to Subproject"}}
2108 -- Provides **direct evidence** that media is being used to **reshape racial attitudes** through emotional, parasocial contact.
2109 -- Reinforces concern that **“tolerance” is engineered via asymmetric emotional exposure**, not organic consensus.
2110 -- Useful for documenting how **Whiteness is often treated as a bias to be corrected**, not a culture to be respected.
2111 -{{/expandable}}
2112 -
2113 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
2114 -1. Investigate **reverse parasocial effects** — how negative portrayals of White men affect self-perception and mental health.
2115 -2. Study how **mass entertainment normalizes demographic shifts** and silences native concerns.
2116 -3. Compare effects of **Western vs. non-Western media systems** in promoting diversity narratives.
2117 -{{/expandable}}
2118 -
2119 -{{expandable summary="📄 Download Full Study"}}
2120 -[[Download Full Study>>attach:Banas et al. - 2020 - Meta-Analysis on Mediated Contact and Prejudice.pdf]]
2121 -{{/expandable}}
2122 -{{/expandable}}
2123 -
2124 -
2125 -{{expandable summary="Study: Cultural Voyeurism – A New Framework for Understanding Race, Ethnicity, and Mediated Intergroup Interaction"}}
2126 -**Source:** *Journal of Communication*
2127 -**Date of Publication:** *2018*
2128 -**Author(s):** *Osei Appiah*
2129 -**Title:** *"Cultural Voyeurism: A New Framework for Understanding Race, Ethnicity, and Mediated Intergroup Interaction"*
2130 -**DOI:** [https://doi.org/10.1093/joc/jqx021](https://doi.org/10.1093/joc/jqx021)
2131 -**Subject Matter:** *Intergroup contact, racial stereotypes, media, identity formation*
2132 -
2133 -{{expandable summary="📊 Key Statistics"}}
2134 -1. **No empirical dataset** — this is a theoretical framework paper, not a quantitative study.
2135 -2. **Heavily cites prior empirical work**, including:
2136 - - Czopp & Monteith (2006) on “complimentary stereotypes”
2137 - - Armstrong et al. (1992), Entman & Rojecki (2000) on media distortion of race
2138 - - Pettigrew et al. (2011) on intergroup contact
2139 -
2140 -3. **Statistical implications:** Repeatedly emphasizes the role of media in shaping racial beliefs when direct interracial contact is absent.
2141 -{{/expandable}}
2142 -
2143 -{{expandable summary="🔬 Findings"}}
2144 -1. **Primary Observations:**
2145 - - Defines *cultural voyeurism* as the process of using media to observe and learn about other racial/ethnic groups.
2146 - - Claims it can both reinforce stereotypes and reduce prejudice depending on context.
2147 - - Suggests that Whites’ fascination with Black culture (e.g., hip-hop, athleticism) is a driver of empathy and improved race relations.
2148 -
2149 -2. **Subgroup Trends:**
2150 - - White youth are singled out as cultural voyeurs increasingly emulating Black identity for social cachet (“coolness”).
2151 - - Positive media portrayals of Blacks (e.g., in entertainment) said to reduce racial bias.
2152 -
2153 -3. **Specific Case Analysis:**
2154 - - No case study provided, but mentions “Duck Dynasty” and “hip-hop culture” as stereotyped White/Black identity constructs respectively.
2155 -{{/expandable}}
2156 -
2157 -{{expandable summary="📝 Critique & Observations"}}
2158 -1. **Strengths of the Study:**
2159 - - Recognizes media’s dual role in shaping intergroup perception.
2160 - - Accurately captures the obsession with racial “coolness” as a social phenomenon.
2161 -
2162 -2. **Limitations of the Study:**
2163 - - Frames White identification with Black culture as inherently progressive, ignoring issues of **anti-White displacement**.
2164 - - Treats *positive stereotypes of minorities* (e.g., athleticism, musicality) as meaningful substitutes for structural reality.
2165 - - Lacks any meaningful inquiry into *reverse cultural voyeurism* (i.e., non-Whites voyeuristically consuming and appropriating White identity or values).
2166 -
2167 -3. **Suggestions for Improvement:**
2168 - - Should confront whether “cultural voyeurism” ultimately erodes group boundaries and majority cultural integrity.
2169 - - Needs empirical validation of claims.
2170 - - Avoids uncomfortable realities about how White identity is increasingly stigmatized in media — which undermines genuine empathy or parity.
2171 -{{/expandable}}
2172 -
2173 -{{expandable summary="📌 Relevance to Subproject"}}
2174 -- Helps explain how **media conditioning** primes young Whites to *admire, emulate, and eventually submit* to Black cultural dominance.
2175 -- Directly supports the narrative that **pro-White identity is systematically delegitimized**, while pro-Black identity is commodified and glamorized — then sold back to White youth.
2176 -- Useful in chapters/sections covering cultural appropriation *in reverse* — not by Whites, but **of Whiteness** by outsiders for critique and exploitation.
2177 -{{/expandable}}
2178 -
2179 -{{expandable summary="🔍 Suggestions for Further Exploration"}}
2180 -1. Are there longitudinal studies showing cultural voyeurism weakening in-group preference among Whites?
2181 -2. Does this phenomenon correspond to decreased fertility, civic participation, or political alignment with group interest?
2182 -3. How do non-Western societies handle voyeuristic consumption of majority culture — do they permit or punish it?
2183 -{{/expandable}}
2184 -
2185 -{{expandable summary="📄 Download Full Study"}}
2186 -[[Download Full Study>>attach:Cultural Voyeurism A New Framework for Understanding Race, Ethnicity, and Mediated Intergroup Intera.pdf]]
2187 -{{/expandable}}
2188 -{{/expandable}}
2189 -
35 +[[Studies: Media>>doc:.Studies\: Media.WebHome]]
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