1. General Observations:
      - Survey of 102 experts on intelligence research and public discourse.
      - Evaluated experts' backgrounds, political affiliations, and views on controversial topics in intelligence research.

2. Subgroup Analysis:
   - 90% of experts were from Western countries, and 83% were male.
   - Political spectrum ranged from 54% left-liberal, 24% conservative, with significant ideological influences on views.

3. Other Significant Data Points:
   - Experts rated media coverage of intelligence research as poor (avg. 3.1 on a 9-point scale).
   - 50% of experts attributed US Black-White IQ differences to genetic factors, 50% to environmental factors.

1. Primary Observations:
      - Experts overwhelmingly support the g-factor theory of intelligence.
      - Heritability of intelligence was widely accepted, though views differed on race and group differences.

2. Subgroup Trends:
   - Left-leaning experts were more likely to reject genetic explanations for group IQ differences.
   - Right-leaning experts tended to favor a stronger role for genetic factors in intelligence disparities.

3. Specific Case Analysis:
   - The study compared media coverage of intelligence research with expert opinions.
   - Found a disconnect between journalists and intelligence researchers, especially regarding politically sensitive issues.

1. Strengths of the Study:
      - Largest expert survey on intelligence research to date.
      - Provides insight into how political orientation influences scientific perspectives.

2. Limitations of the Study:
   - Sample primarily from Western countries, limiting global perspectives.
   - Self-selection bias may skew responses toward those more willing to engage with controversial topics.

3. Suggestions for Improvement:
   - Future studies should include a broader range of global experts.
   - Additional research needed on media biases and misrepresentation of intelligence research.

- Provides insight into expert consensus and division on intelligence research.
- Highlights the role of media bias in shaping public perception of intelligence science.
- Useful for understanding the intersection of science, politics, and public discourse on intelligence research.

1. Examine cross-national differences in expert opinions on intelligence.
   2. Investigate how media bias impacts public understanding of intelligence research.
   3. Conduct follow-up studies with a more diverse expert pool to test findings.

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1. General Observations:
      - Study analyzed genome-wide association studies (GWAS) hits linked to intelligence.
      - Found a strong correlation (r = .91) between polygenic intelligence scores and national IQ levels.

2. Subgroup Analysis:
   - Factor analysis of 9 intelligence-associated alleles revealed a metagene correlated with country IQ (r = .86).
   - Allele frequencies varied significantly by continent, aligning with observed population differences in cognitive ability.

3. Other Significant Data Points:
   - GWAS intelligence SNPs predicted IQ levels more strongly than random genetic markers.
   - Genetic differentiation (Fst values) showed that selection pressure, rather than drift, influenced intelligence-related allele distributions.

1. Primary Observations:
      - Intelligence-associated SNP frequencies correlate highly with national IQ levels.
      - Genetic selection for intelligence appears stronger than selection for height-related genes.

2. Subgroup Trends:
   - East Asian populations exhibited the highest frequencies of intelligence-associated alleles.
   - African populations showed lower frequencies compared to European and East Asian populations.

3. Specific Case Analysis:
   - Polygenic scores using intelligence-related alleles significantly outperformed random SNPs in predicting IQ.
   - Selection pressures may explain differences in global intelligence distribution beyond genetic drift effects.

1. Strengths of the Study:
      - Comprehensive genetic analysis of intelligence-linked SNPs.
      - Uses multiple statistical methods (factor analysis, Fst analysis) to confirm results.

2. Limitations of the Study:
   - Correlation does not imply causation; factors beyond genetics influence intelligence.
   - Limited number of GWAS-identified intelligence alleles—future studies may identify more.

3. Suggestions for Improvement:
   - Larger cross-population GWAS studies needed to validate findings.
   - Investigate non-genetic contributors to IQ variance in addition to genetic factors.

- Supports research on genetic influences on intelligence at a population level.
- Aligns with broader discussions on cognitive genetics and natural selection effects.
- Provides a quantitative framework for analyzing polygenic selection in intelligence studies.

1. Conduct expanded GWAS studies including diverse populations.
   2. Investigate gene-environment interactions influencing intelligence.
   3. Explore historical selection pressures shaping intelligence-related alleles.

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1. General Observations:
      - Mean IQ gap between Blacks and Whites in the U.S.: 15 points.
      - Heritability estimates for IQ: 0.5 to 0.8 (moderate to high).
      - Brain volume differences align with IQ differences: 50 cm³ difference on average.

2. Subgroup Analysis:
   - Black Americans consistently score about 1 SD below White Americans across age groups.
   - East Asians tend to score slightly higher than Whites on non-verbal IQ tests.

3. Other Significant Data Points:
   - Between-group differences are found on culture-free, g-loaded tests.
   - Adoption studies: Black children raised in White households still show IQ closer to Black population mean.

1. Primary Observations:
      - The Black–White IQ gap is persistent, replicable, and appears early in life.
      - g factor (general intelligence) underlies the racial IQ gap across diverse cognitive tasks.

2. Subgroup Trends:
   - Differences are larger on more g-loaded tests, suggesting the gap is not a test artifact.
   - Socioeconomic status does not eliminate the gap, though it can influence expression.

3. Specific Case Analysis:
   - Minnesota Transracial Adoption Study: Black children adopted into affluent White homes scored lower than White adoptees.
   - U.S. military data (e.g. AFQT scores) showed consistent racial stratification in cognitive performance.

1. Strengths of the Study:
      - Synthesizes hundreds of studies spanning psychometrics, neuroscience, and genetics.
      - Applies rigorous meta-analytic and test-construction logic.
      - Challenges purely environmental or cultural explanations with empirical evidence.

2. Limitations of the Study:
   - The review is intensely controversial, particularly due to assumptions about race as a valid biological category.
   - Heritability within groups does not automatically justify between-group heritability claims — critics argue this is misused.
   - Critics allege selective reporting or bias in study inclusion (e.g. underrepresenting null results).

3. Suggestions for Improvement:
   - Further work could benefit from modern genomic tools (e.g. polygenic risk scoring) to isolate population-level traits.
   - Greater inclusion of cross-cultural replications would help test universality vs. U.S.-specific effects.

- This is one of the most comprehensive defenses of biological origins of racial cognitive differences.
- Supports the view that racial gaps in academic or occupational outcomes are not purely environmental.
- Challenges dominant narratives in education policy, DEI programming, and social justice frameworks.

1. How have genetic studies (e.g. GWAS) since 2005 confirmed or contradicted Rushton & Jensen’s findings?  
   2. What are the policy implications of acknowledging cognitive group differences — in education, immigration, or welfare?  
   3. To what extent do cultural suppression and academic censorship affect open discussion of these results?

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1. Average Brain Volumes (cc):
      - Blacks: 1267 cm³  
      - Whites: 1347 cm³  
      - East Asians: 1364 cm³  

2. IQ Averages:
   - Blacks: 85  
   - Whites: 100  
   - East Asians: 106  

3. Correlation Between Brain Size & Morphological Traits:
   - Across 37 skeletal variables, mean correlation with brain size: r = 0.94

4. Sample Basis:
   - Study synthesizes cranial and postcranial anatomical data from global populations.

1. Primary Conclusion:
      - Brain size differences among races are robust, biologically grounded, and closely track IQ differences.

2. Skeletal Evidence:
   - Morphological traits (jaw shape, tooth structure, thigh curvature, pelvis width) correlate with brain volume across groups.

3. Interpretation:
   - These consistent anatomical differences support the theory that evolved brain size variation underlies racial IQ gaps.

1. Strengths of the Study:
      - High ecological correlations (r = 0.94) across diverse skeletal metrics.
      - Integrates anthropometry with cognitive data for holistic biological analysis.

2. Limitations:
   - Relies on preexisting datasets rather than new measurements.
   - Assumes uniformity within broad racial categories without finer intra-group distinctions.

3. Suggestions for Improvement:
   - Add neuroimaging evidence (MRI/CT) to confirm volume estimates.
   - Include modern genomic ancestry estimates for greater precision.

- Provides hard anatomical evidence reinforcing racial differences in cognitive ability.
- Links IQ differences to physiological, not social factors—countering CRT narratives.
- Strong empirical foundation for hereditarian interpretations of race and intelligence.

1. Cross-validate musculoskeletal trait correlations using modern 3D skeletal databases.  
   2. Explore how sexual dimorphism interacts with racial brain size differences.  
   3. Investigate similar correlations in other species to support evolutionary reasoning.

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