MétaCan
Menu
Back to cohort
Record W2145368831 · doi:10.1177/0013164404267286

Items in Context: Assessing the Dimensionality of Raven’s Advanced Progressive Matrices

2004· article· en· W2145368831 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.

Bibliographic record

VenueEducational and Psychological Measurement · 2004
Typearticle
Languageen
FieldPsychology
TopicCognitive Abilities and Testing
Canadian institutionsThe Scarborough HospitalUniversity of TorontoUniversité de Moncton
Fundersnot available
KeywordsRasch modelPrincipal component analysisRaven's Progressive MatricesCurse of dimensionalityContext (archaeology)Set (abstract data type)PsychologyTest (biology)Artificial intelligenceCognitive psychologyMathematicsStatisticsComputer scienceCognition

Abstract

fetched live from OpenAlex

The problem of dimensionality with respect to Raven’s Advanced Progressive Matrices (APM) specifically and, more generally, g or fluid intelligence, has been a long-standing issue. The present article reports two studies examining the dimensionality of both the original Set II of the APM ( n = 506) and a short form ( n = 644), using principal component analysis and Rasch analysis. Although the results from the principal component analysis were equivocal, results from the Rasch analyses more strongly suggested that both forms of the test are best described as being multidimensional. Furthermore, comparison of items common to both forms indicated a context effect, thus making adaptive testing versions of this test difficult.

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 score0.547
Threshold uncertainty score0.591

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)0.0010.000

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 head0.156
GPT teacher head0.416
Teacher spread0.260 · 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