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Wiki source code of Studies: IQ

Version 10.1 by Ryan C on 2025/06/21 06:06
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1 = IQ =
2
3 {{expandable summary="Study: Survey of Expert Opinion on Intelligence: Intelligence Research, Experts' Background, Controversial Issues, and the Media"}}
4 **Source:** *Intelligence (Elsevier)*
5 **Date of Publication:** *2019*
6 **Author(s):** *Heiner Rindermann, David Becker, Thomas R. Coyle*
7 **Title:** *"Survey of Expert Opinion on Intelligence: Intelligence Research, Experts' Background, Controversial Issues, and the Media"*
8 **DOI:** [10.1016/j.intell.2019.101406](https://doi.org/10.1016/j.intell.2019.101406)
9 **Subject Matter:** *Psychology, Intelligence Research, Expert Analysis*
10
11 {{expandable summary="📊 Key Statistics"}}
12 1. **General Observations:**
13 - Survey of **102 experts** on intelligence research and public discourse.
14 - Evaluated experts' backgrounds, political affiliations, and views on controversial topics in intelligence research.
15
16 2. **Subgroup Analysis:**
17 - **90% of experts were from Western countries**, and **83% were male**.
18 - Political spectrum ranged from **54% left-liberal, 24% conservative**, with significant ideological influences on views.
19
20 3. **Other Significant Data Points:**
21 - Experts rated media coverage of intelligence research as **poor (avg. 3.1 on a 9-point scale)**.
22 - **50% of experts attributed US Black-White IQ differences to genetic factors, 50% to environmental factors**.
23 {{/expandable}}
24
25 {{expandable summary="🔬 Findings"}}
26 1. **Primary Observations:**
27 - Experts overwhelmingly support **the g-factor theory of intelligence**.
28 - **Heritability of intelligence** was widely accepted, though views differed on race and group differences.
29
30 2. **Subgroup Trends:**
31 - **Left-leaning experts were more likely to reject genetic explanations for group IQ differences**.
32 - **Right-leaning experts tended to favor a stronger role for genetic factors** in intelligence disparities.
33
34 3. **Specific Case Analysis:**
35 - The study compared **media coverage of intelligence research** with expert opinions.
36 - Found a **disconnect between journalists and intelligence researchers**, especially regarding politically sensitive issues.
37 {{/expandable}}
38
39 {{expandable summary="📝 Critique & Observations"}}
40 1. **Strengths of the Study:**
41 - **Largest expert survey on intelligence research** to date.
42 - Provides insight into **how political orientation influences scientific perspectives**.
43
44 2. **Limitations of the Study:**
45 - **Sample primarily from Western countries**, limiting global perspectives.
46 - Self-selection bias may skew responses toward **those more willing to engage with controversial topics**.
47
48 3. **Suggestions for Improvement:**
49 - Future studies should include **a broader range of global experts**.
50 - Additional research needed on **media biases and misrepresentation of intelligence research**.
51 {{/expandable}}
52
53 {{expandable summary="📌 Relevance to Subproject"}}
54 - Provides insight into **expert consensus and division on intelligence research**.
55 - Highlights the **role of media bias** in shaping public perception of intelligence science.
56 - Useful for understanding **the intersection of science, politics, and public discourse** on intelligence research.
57 {{/expandable}}
58
59 {{expandable summary="🔍 Suggestions for Further Exploration"}}
60 1. Examine **cross-national differences** in expert opinions on intelligence.
61 2. Investigate how **media bias impacts public understanding of intelligence research**.
62 3. Conduct follow-up studies with **a more diverse expert pool** to test findings.
63 {{/expandable}}
64
65 {{expandable summary="📄 Download Full Study"}}
66 [[Download Full Study>>attach:Rindermann et al. - 2020 - Survey of expert opinion on intelligence Intelligence research, experts' background, controversial.pdf]]
67 {{/expandable}}
68 {{/expandable}}
69
70 {{expandable summary="Study: A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation"}}
71 **Source:** *Intelligence (Elsevier)*
72 **Date of Publication:** *2015*
73 **Author(s):** *Davide Piffer*
74 **Title:** *"A Review of Intelligence GWAS Hits: Their Relationship to Country IQ and the Issue of Spatial Autocorrelation"*
75 **DOI:** [10.1016/j.intell.2015.08.008](https://doi.org/10.1016/j.intell.2015.08.008)
76 **Subject Matter:** *Genetics, Intelligence, GWAS, Population Differences*
77
78 {{expandable summary="📊 Key Statistics"}}
79 1. **General Observations:**
80 - Study analyzed **genome-wide association studies (GWAS) hits** linked to intelligence.
81 - Found a **strong correlation (r = .91) between polygenic intelligence scores and national IQ levels**.
82
83 2. **Subgroup Analysis:**
84 - Factor analysis of **9 intelligence-associated alleles** revealed a metagene correlated with **country IQ (r = .86)**.
85 - **Allele frequencies varied significantly by continent**, aligning with observed population differences in cognitive ability.
86
87 3. **Other Significant Data Points:**
88 - GWAS intelligence SNPs predicted **IQ levels more strongly than random genetic markers**.
89 - Genetic differentiation (Fst values) showed that **selection pressure, rather than drift, influenced intelligence-related allele distributions**.
90 {{/expandable}}
91
92 {{expandable summary="🔬 Findings"}}
93 1. **Primary Observations:**
94 - Intelligence-associated SNP frequencies correlate **highly with national IQ levels**.
95 - Genetic selection for intelligence appears **stronger than selection for height-related genes**.
96
97 2. **Subgroup Trends:**
98 - **East Asian populations** exhibited the **highest frequencies of intelligence-associated alleles**.
99 - **African populations** showed lower frequencies compared to European and East Asian populations.
100
101 3. **Specific Case Analysis:**
102 - Polygenic scores using **intelligence-related alleles significantly outperformed random SNPs** in predicting IQ.
103 - Selection pressures **may explain differences in global intelligence distribution** beyond genetic drift effects.
104 {{/expandable}}
105
106 {{expandable summary="📝 Critique & Observations"}}
107 1. **Strengths of the Study:**
108 - **Comprehensive genetic analysis** of intelligence-linked SNPs.
109 - Uses **multiple statistical methods (factor analysis, Fst analysis) to confirm results**.
110
111 2. **Limitations of the Study:**
112 - **Correlation does not imply causation**; factors beyond genetics influence intelligence.
113 - **Limited number of GWAS-identified intelligence alleles**—future studies may identify more.
114
115 3. **Suggestions for Improvement:**
116 - Larger **cross-population GWAS studies** needed to validate findings.
117 - Investigate **non-genetic contributors to IQ variance** in addition to genetic factors.
118 {{/expandable}}
119
120 {{expandable summary="📌 Relevance to Subproject"}}
121 - Supports research on **genetic influences on intelligence at a population level**.
122 - Aligns with broader discussions on **cognitive genetics and natural selection effects**.
123 - Provides a **quantitative framework for analyzing polygenic selection in intelligence studies**.
124 {{/expandable}}
125
126 {{expandable summary="🔍 Suggestions for Further Exploration"}}
127 1. Conduct **expanded GWAS studies** including diverse populations.
128 2. Investigate **gene-environment interactions influencing intelligence**.
129 3. Explore **historical selection pressures shaping intelligence-related alleles**.
130 {{/expandable}}
131
132 {{expandable summary="📄 Download Full Study"}}
133 [[Download Full Study>>attach:Piffer - 2015 - A review of intelligence GWAS hits Their relationship to country IQ and the issue of spatial autoco.pdf]]
134 {{/expandable}}
135 {{/expandable}}
136
137 {{expandable summary="Study: Genetic Structure, Self-Identified Race/Ethnicity, and Confounding in Case-Control Association Studies"}}
138 **Source:** *Genetic Epidemiology*
139 **Date of Publication:** *2001*
140 **Author(s):** *Neil Risch, Esteban Burchard, Elisa Ziv, Hua Tang*
141 **Title:** *"Genetic Structure, Self-Identified Race/Ethnicity, and Confounding in Case-Control Association Studies"*
142 **DOI:** [10.1038/ng1199-355](https://doi.org/10.1038/ng1199-355)
143 **Subject Matter:** *Population Genetics, Biomedical Research, Race & Ancestry*
144
145 {{expandable summary="📊 Key Statistics"}}
146 1. **General Observations:**
147 - Sample: 3,636 individuals from **White, African-American, East Asian, and Hispanic** groups.
148 - Genotyped for **326 microsatellite markers**.
149
150 2. **Subgroup Analysis:**
151 - **Self-identified race matched genetic clusters 99.86% of the time**.
152 - Each group formed **distinct, non-overlapping clusters** in genetic space.
153
154 3. **Other Significant Data Points:**
155 - Genetic structure correlated strongly with **continental ancestry**, not geography of residence.
156 - Demonstrated minimal overlap between populations, affirming **biological distinctiveness** of racial groupings.
157 {{/expandable}}
158
159 {{expandable summary="🔬 Findings"}}
160 1. **Primary Observations:**
161 - **Self-identified race is a valid proxy for genetic ancestry** in medical and population studies.
162 - Racial classification is not merely “socially constructed,” but **reflects deep ancestral population structure**.
163
164 2. **Subgroup Trends:**
165 - East Asians, Africans, and Europeans formed **clear, separable genetic clusters**.
166 - Hispanics showed **admixture**, but still clustered distinguishably.
167
168 3. **Specific Case Analysis:**
169 - The paper challenged the **PC dogma** that race is biologically meaningless.
170 - Warned that **ignoring race in genetic studies can introduce confounding**, especially in disease association research.
171 {{/expandable}}
172
173 {{expandable summary="📝 Critique & Observations"}}
174 1. **Strengths of the Study:**
175 - Robust dataset across multiple racial/ethnic groups.
176 - Clear empirical demonstration of the **biological reality of race**.
177
178 2. **Limitations of the Study:**
179 - Did not account for intra-population stratification or recent admixture in fine detail.
180 - Based on microsatellite markers — less resolution than full-genome sequencing.
181
182 3. **Suggestions for Improvement:**
183 - Update with modern SNP or WGS data.
184 - Include more populations (e.g., Middle Easterners, South Asians) for global structure.
185 {{/expandable}}
186
187 {{expandable summary="📌 Relevance to Subproject"}}
188 - Provides foundational genetic evidence **supporting the coherence of racial classifications**.
189 - Useful in refuting the claim that race is merely a sociological artifact.
190 - Directly applicable to the **race realism** and **genetic confounding** discussion in medical ethics and social sciences.
191 {{/expandable}}
192
193 {{expandable summary="🔍 Suggestions for Further Exploration"}}
194 1. Analyze how racial identity correlates with **disease risk and treatment outcomes**.
195 2. Compare modern SNP datasets to validate or refine the 2001 conclusions.
196 3. Investigate how **DEI-driven research** suppresses or distorts findings on genetic ancestry.
197 {{/expandable}}
198
199 {{expandable summary="📄 Download Full Study"}}
200 [[Download Full Study>>https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1196372/]]
201 {{/expandable}}
202 {{/expandable}}
203
204 {{expandable summary="Study: Brain Size, IQ, and Racial-Group Differences"}}
205 **Source:** *Intelligence (Elsevier)*
206 **Date of Publication:** *2003*
207 **Author(s):** *J. Philippe Rushton, Elizabeth W. Rushton*
208 **Title:** *"Brain size, IQ, and racial-group differences: Evidence from musculoskeletal traits"*
209 **DOI:** [10.1016/S0160-2896(02)00137-X](https://doi.org/10.1016/S0160-2896(02)00137-X)
210 **Subject Matter:** *Neuroanatomy, Intelligence, Evolutionary Anthropology, Racial Differences*
211
212 {{expandable summary="📊 Key Statistics"}}
213 1. **Average Brain Volumes (cc):**
214 - Blacks: ~1267 cm³
215 - Whites: ~1347 cm³
216 - East Asians: ~1364 cm³
217
218 2. **IQ Averages:**
219 - Blacks: ~85
220 - Whites: 100
221 - East Asians: ~106
222
223 3. **Correlation Between Brain Size & Morphological Traits:**
224 - Across 37 skeletal variables, mean correlation with brain size: **r = 0.94**
225
226 4. **Sample Basis:**
227 - Study synthesizes cranial and postcranial anatomical data from global populations.
228 {{/expandable}}
229
230 {{expandable summary="🔬 Findings"}}
231 1. **Primary Conclusion:**
232 - Brain size differences among races are robust, **biologically grounded**, and closely track IQ differences.
233
234 2. **Skeletal Evidence:**
235 - Morphological traits (jaw shape, tooth structure, thigh curvature, pelvis width) correlate with brain volume across groups.
236
237 3. **Interpretation:**
238 - These consistent anatomical differences support the theory that **evolved brain size variation underlies racial IQ gaps**.
239 {{/expandable}}
240
241 {{expandable summary="📝 Critique & Observations"}}
242 1. **Strengths of the Study:**
243 - High ecological correlations (r = 0.94) across diverse skeletal metrics.
244 - Integrates anthropometry with cognitive data for holistic biological analysis.
245
246 2. **Limitations:**
247 - Relies on preexisting datasets rather than new measurements.
248 - Assumes uniformity within broad racial categories without finer intra-group distinctions.
249
250 3. **Suggestions for Improvement:**
251 - Add neuroimaging evidence (MRI/CT) to confirm volume estimates.
252 - Include modern genomic ancestry estimates for greater precision.
253 {{/expandable}}
254
255 {{expandable summary="📌 Relevance to Subproject"}}
256 - Provides **hard anatomical evidence** reinforcing racial differences in cognitive ability.
257 - Links IQ differences to **physiological, not social** factors—countering CRT narratives.
258 - Strong empirical foundation for hereditarian interpretations of race and intelligence.
259 {{/expandable}}
260
261 {{expandable summary="🔍 Suggestions for Further Exploration"}}
262 1. Cross-validate musculoskeletal trait correlations using modern 3D skeletal databases.
263 2. Explore how sexual dimorphism interacts with racial brain size differences.
264 3. Investigate similar correlations in other species to support evolutionary reasoning.
265 {{/expandable}}
266
267 {{expandable summary="📄 Download Full Study"}}
268 [[Download Full Study>>attach:rushton2003.pdf]]
269 {{/expandable}}
270 {{/expandable}}

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