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Record W2091057870 · doi:10.1027/1614-0001.29.2.57

Spearman's Law of Diminishing Returns in Normative Samples for the WISC-IV and WAIS-III

2008· article· en· W2091057870 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Individual Differences · 2008
Typearticle
Languageen
FieldPsychology
TopicCognitive Abilities and Testing
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsNormativeWechsler Adult Intelligence ScalePsychologyWechsler Intelligence Scale for ChildrenDevelopmental psychologyCognitionIntelligence quotientLawPsychiatryPolitical science

Abstract

fetched live from OpenAlex

In order to explain observed variations in intelligence test scores, Spearman (1927 ) proposed the “law of diminishing returns” (SLODR). It states that the g saturation of cognitive ability tests decreases as a function of ability or age. Published studies have shown mixed results. However, a recent review ( Hartmann & Nyborg, 2004 ) suggests that there is evidence for differences in g saturation by ability level, but that observed age effects on g saturation are most likely to be a consequence of the ability effect. The current study analyzed the standardization data of the most recent Wechsler scales for both children and adults from several different countries. This study did not find evidence to support either the ability or age version of SLODR by using large normative samples for the WISC-IV from the United States, Canada, and Australia, and for the WAIS-III from the same three countries and also from The Netherlands.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.229
Threshold uncertainty score0.262

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.136
GPT teacher head0.330
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it