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In Defense of a Disputed Study of Construct Validity from South Africa

2006· article· en· W1505097313 on OpenAlexaff
J. Philippe Rushton

Bibliographic record

VenueInternational Journal of Selection and Assessment · 2006
Typearticle
Languageen
FieldPsychology
TopicCognitive Abilities and Testing
Canadian institutionsWestern University
Fundersnot available
KeywordsGeneralizability theoryPsychologyConfirmatory factor analysisConstruct (python library)Construct validitySocial psychologyCross-culturalBlack africanWhite (mutation)Developmental psychologyPsychometricsAnthropologyStatisticsSociologyEthnologyStructural equation modeling

Abstract

fetched live from OpenAlex

This analysis of a critique finds that the original study accurately showed that the items found easy or difficult by Black South African undergraduates were those found easy or difficult by their White and South Asian counterparts (r's=.90). There was no evidence of any culture‐specific effect. Instead, African/non‐African differences were found to be most pronounced on g. This was shown by item‐total correlations (estimates of the item's g loading), which predicted the magnitude of African/non‐African differences on those same items, and by a confirmatory factor analysis. The tests were equally predictive for Blacks and non‐Blacks on external criteria such as course grades. The results indicate the remarkable cross‐cultural generalizability of item properties across sub‐Saharan Africans, South Asians, and Europeans and that these reflect g more than culturally specific ways of thinking.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.039
metaresearch head score (Gemma)0.103
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.999
Threshold uncertainty score0.204

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0390.103
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0030.012
Scholarly communication0.0040.005
Open science0.0020.006
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.049
GPT teacher head0.363
Teacher spread0.314 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
DomainMethods
GenreCommentary

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

Citations0
Published2006
Admission routes1
Has abstractyes

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