Document ID: T_1_10
Section: T_Psychology_Social
Keywords: psychometrics, intelligence, IQ, g factor, Spearman, fluid intelligence, crystallized intelligence, Cattell, multiple intelligences, Gardner, emotional intelligence, Sternberg, Wechsler, Stanford-Binet, Flynn effect, stereotype threat, measurement, reliability, validity, factor analysis, item response theory, bias, cultural fairness
Category Tags: psychology, social, art-culture
Cross-References: T_1_08 · ZC_1_12 · T_3_06 · T_1_09 · T_3_05
Reliability Tier: Tier 1 (g factor among the most replicated findings in differential psychology)
Last Updated: Mar 07, 2026 | Source Count: 20 | Weighted Score: 45 | Source Confidence: [5/5] | Confidence: Very High

QUICK SUMMARY

Intelligence testing is among the oldest and most psychometrically robust enterprises in psychology. Spearman's g factor (1904) — a general mental ability extracted through factor analysis — remains one of the strongest predictors of academic achievement, job performance (r ≈ .51; Schmidt & Hunter, 1998), health outcomes, and longevity. Despite controversy over what intelligence "is," the predictive validity of cognitive ability tests is among the most replicated findings in differential psychology.

Modern intelligence theory recognizes a hierarchical structure: the Cattell-Horn-Carroll (CHC) model posits a general factor (g) at the apex, broad abilities (fluid reasoning [Gf], crystallized ability [Gc], processing speed [Gs], working memory [Gwm], etc.) at the second stratum, and narrow abilities at the first. The Flynn effect — rising IQ scores across generations (≈3 points per decade) — demonstrates environmental contributions but complicates comparisons across cohorts. Stereotype threat (Steele & Aronson, 1995) showed situational factors can depress test performance, though recent meta-analyses have found smaller and more situationally specific effects than originally reported.

1. VERIFIED CLAIMS (Tier 1 — Peer-Reviewed / Archaeological Record)

1.1 The g factor and hierarchical structure

• Spearman (1904): Factor analysis of cognitive tests reveals a dominant general factor (g) — performance on diverse cognitive tasks is positively correlated (the "positive manifold"); g accounts for 40–50% of variance in large test batteries.
• Cattell-Horn-Carroll (CHC) model: Three-stratum hierarchy — (1) narrow abilities (~70), (2) broad abilities (~10: Gf, Gc, Gs, Gwm, Gv, Ga, Glr, Gsm), (3) g at the apex; most comprehensive empirically-derived model; basis of modern test construction (WJ-IV, KABC-II).
• Fluid (Gf) vs. Crystallized (Gc) intelligence (Cattell, 1963): Gf — reasoning with novel problems, pattern detection, declines from ~25 years; Gc — accumulated knowledge and vocabulary, stable or increasing into 60s–70s; double dissociation supports the distinction.
• Neural correlates: g is correlated with total brain volume (r ≈ .25–.30; McDaniel, 2005 meta-analysis), white matter integrity, cortical thickness, and neural efficiency (more intelligent individuals show less prefrontal activation during moderate-difficulty tasks — neural efficiency hypothesis; Neubauer & Fink, 2009).

1.2 Predictive validity of intelligence tests

• Academic achievement: IQ correlates r ≈ .50–.60 with grades and educational attainment (Strenze, 2007 meta-analysis; N = 70,000+).
• Job performance: General mental ability is the strongest single predictor of job performance across all occupations (r ≈ .51 for medium-complexity jobs; Schmidt & Hunter, 1998 meta-analysis); validity increases with job complexity; incremental validity above experience, education, and personality.
• Health and longevity: Higher childhood IQ predicts lower mortality risk (Deary et al., 2004 — Scottish Mental Survey 1932; HR ≈ 0.79 per 1 SD increase); mechanisms include health literacy, socioeconomic pathways, and system integrity.
• G is not the whole story: Specific abilities predict outcomes beyond g; conscientiousness adds incremental validity for job performance (ρ ≈ .22–.27; Barrick & Mount, 1991); domain knowledge, creativity, and practical skills matter for real-world success.

1.3 Major intelligence tests

• Wechsler Adult Intelligence Scale (WAIS-IV): Full-Scale IQ (FSIQ) with four index scores: Verbal Comprehension (VCI), Perceptual Reasoning (PRI), Working Memory (WMI), Processing Speed (PSI); mean = 100, SD = 15; most widely used adult IQ test.
• Stanford-Binet Intelligence Scales, 5th Edition (SB5): Five factors: Fluid Reasoning, Knowledge, Quantitative Reasoning, Visual-Spatial Processing, Working Memory; strong CHC alignment; extends to age 2.
• Wechsler Intelligence Scale for Children (WISC-V): Dominant child intelligence test; five factor indexes aligned with CHC.
• Raven's Progressive Matrices: Non-verbal, culture-reduced measure of fluid intelligence (Gf); widely used cross-culturally; requires pattern completion with increasing difficulty.
• Psychometric properties: Internal consistency reliabilities ≥ .90 for FSIQ; test-retest stability ≥ .85. These are among the most reliable psychological measures.

1.4 The Flynn effect

• Flynn (1984, 1987): IQ scores have risen ~3 points per decade throughout the 20th century in industrialized nations — a massive effect (≈15 points over 50 years); gains are largest on fluid intelligence measures (Raven's), smaller on crystallized measures; discovered by James Flynn and named by Herrnstein & Murray.
• Proposed mechanisms: Improved nutrition, reduced infectious disease, greater schooling, increased environmental complexity, cognitive stimulation from technology; the effect is almost certainly environmental since genetic change cannot occur this rapidly.
• Reversal: Some Scandinavian countries show declining IQ scores since the 1990s (Dutton & Lynn, 2013; Bratsberg & Rogeberg, 2018 — within-family design rules out immigration/compositional effects); cause debated (environmental factors, ceiling effects, changing item content).
• Implication: IQ norms must be regularly restandardized; using outdated norms inflates scores (critical for clinical/legal decisions, e.g., intellectual disability diagnosis for death penalty eligibility).

2. CREDIBLE BUT DEBATED CLAIMS (Tier 2 — Academic / Debated)

2.1 Heritability of intelligence

• Twin studies: Heritability of IQ is ~50% in childhood, rising to ~70–80% in adulthood (Bouchard & McGue, 1981; Plomin & Deary, 2015 — "Wilson effect"); shared environment matters substantially in childhood but diminishes by adulthood; non-shared environment accounts for ~20%.
• GWAS findings: Individual SNPs have tiny effects; polygenic scores (GPS/PGS) explain ~10–15% of IQ variance as of 2023 (Savage et al., 2018 — N > 269,000); thousands of genetic variants each contribute minimally.
• Debate: Heritability is a population statistic, not an individual one; it does not mean traits are immutable; heritability estimates vary by socioeconomic context (lower in deprived environments, higher in enriched ones — the Scarr-Rowe interaction, replicated in some but not all studies).

2.2 Stereotype threat

• Steele & Aronson (1995): African American students performed worse on a verbal test when it was presented as diagnostic of ability vs. a lab exercise; interpreted as showing that awareness of negative stereotypes impairs performance through anxiety, reduced working memory, and self-monitoring.
• Meta-analyses (Nguyen & Ryan, 2008; Flore & Wicherts, 2015): Effects are smaller than original studies suggested (d ≈ 0.26 for minorities, smaller for gender-math); significant publication bias detected; effects depend on the degree of threat activation and whether the test is truly high-stakes.
• Status: Stereotype threat is a real but more modest and context-dependent phenomenon than the original literature suggested; it does not fully account for group differences in test scores.

2.3 Test bias and cultural fairness

• Predictive bias: Major IQ tests generally predict academic and job outcomes equally well across racial/ethnic groups — they do not systematically overpredict or underpredict for minority groups (Jensen, 1980; Hartigan & Wigdor, 1989 NRC report); in some cases, they slightly overpredict minority performance.
• Measurement invariance: Factor structure of intelligence tests is largely invariant across groups (same g, same broad factors; Wicherts, 2007); however, some specific items may show differential item functioning (DIF).
• Debate: Absence of predictive bias does not mean tests are "fair" in a broader social sense — test scores reflect accumulated environmental (dis)advantage; construct bias vs. predictive bias are different questions.

2.4 Multiple intelligences and emotional intelligence

• Gardner's Multiple Intelligences (1983): Proposed 8 intelligences (linguistic, logical-mathematical, spatial, musical, bodily-kinesthetic, interpersonal, intrapersonal, naturalist); influential in education but lacking psychometric support — no reliable independent measures; the proposed intelligences tend to correlate (suggesting g); not empirically distinguishable from talents/abilities.
• Emotional Intelligence (Mayer & Salovey, 1997 vs. Goleman, 1995): Ability model (perceiving, using, understanding, managing emotions) — measured by MSCEIT, correlates modestly with g (r ≈ .20–.30); adds small incremental prediction of life outcomes beyond g and personality (ΔR² ≈ .01–.04; Joseph & Newman, 2010). Trait EI (self-report) — substantially overlaps with personality traits (especially agreeableness and emotional stability).
• Sternberg's Triarchic Theory: Analytical, creative, practical intelligence; weak psychometric support; factor analyses suggest the three components are not clearly separable from g.

3. SPECULATIVE CLAIMS (Tier 3 — Possible but Unverified)

3.1 Intelligence augmentation through neurostimulation

• tDCS (transcranial direct current stimulation) over the DLPFC has been proposed to enhance fluid intelligence and working memory; Jaeggi et al. (2008) dual n-back training showed initial transfer to fluid intelligence, but meta-analyses (Melby-Lervåg & Hulme, 2013) found no convincing evidence for far transfer from working memory training to fluid intelligence; tDCS effects are small and inconsistent.

3.2 Group differences in IQ: environmental vs. genetic contributions

• Mean IQ score differences between racial/ethnic groups are documented (e.g., ~15 points between Black and White Americans, narrowing over time); experts overwhelmingly agree that environmental factors (socioeconomic disadvantage, educational access, health, stereotype threat, test exposure) play a major role; the heritability of IQ within groups does not logically entail genetic contributions to between-group differences (Lewontin, 1972); rigorous causal studies (adoption, admixture) remain inconclusive.

4. DUBIOUS OR FRINGE CLAIMS (Tier 4 — No Credible Source / Contradicted by Evidence)

4.1 IQ tests measure innate, fixed intelligence

IQ tests measure current cognitive performance — not a fixed quantity. IQ scores can change with education, intervention, nutrition, and environmental enrichment; the Flynn effect alone demonstrates massive malleability within genetically stable populations.

4.2 Brain Training games substantially raise intelligence

Commercial brain training programs (Lumosity, BrainAge) claim to boost IQ or general cognitive ability; the FTC fined Lumosity $2 million (2016) for deceptive advertising; meta-analyses show training improves performance on trained tasks but does not transfer to general intelligence or real-world cognitive functioning (Simons et al., 2016 — comprehensive review).

4.3 Single IQ score captures all of human intelligence

Intelligence is multidimensional (CHC model identifies ~10 broad abilities); a single FSIQ score is a useful summary statistic but obscures meaningful profile variability; practical, creative, social, and emotional competencies are not fully captured.

COUNTER-ARGUMENTS & CRITICISMS

IMAGES

BIBLIOGRAPHY

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Document T_1_10 · Created Mar 07, 2026 · TheoriesOfAnything Knowledge Base

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