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Record W2189093594 · doi:10.65030/idr.01014

Neuropsychological Performance, IQ, Personality, and Grades in a Longitudinal Grade-School Male Sample

2003· article· en· W2189093594 on OpenAlexaff
Jordan B. Peterson, Robert O. Pihl, Daniel M. Higgins, Jean R. Séguin, Richard E. Tremblay

Bibliographic record

VenueIndividual Differences Research · 2003
Typearticle
Languageen
FieldPsychology
TopicCognitive Abilities and Testing
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychologyBoston Naming TestNeuropsychologyNeuropsychological testIntelligence quotientDevelopmental psychologyLateralityClinical psychologyCognitionPsychiatry

Abstract

fetched live from OpenAlex

This study assessed the statistical relationship between neuropsychological performance, IQ and personality test results and school grades in a longitudinal sample of adolescent males. One-hundred and forty-eight boys completed six years of WISC-R short forms (Block Design and Vocabulary) and provided six years of math and language grades and grade failure data while in elementary school. In junior high school, the same boys completed an extensive neuropsychological test battery and the NEO-PI-R, a standard big five personality trait measure. Neuropsychological test scores were more powerfully associated with grades than were IQ scores, despite their later and single administration. In addition, hierarchical regression analysis demonstrated that three of four neuropsychological test score factors (Verbal Learning, Executive Function, and Tactile Laterality improved the statistical association with six-year averaged failure-weighted grades over and above IQ (averaged Vocabulary and Block Design). NEO-PI-R Agreeableness was significantly and positively related to grades, over and above both IQ and neuropsychological function.

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.

How this classification was reachedexpand

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.334
GPT teacher head0.436
Teacher spread0.102 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2003
Admission routes1
Has abstractyes

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