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Record W2149521665 · doi:10.1093/her/cyl088

Introducing equating methodologies to compare test scores from two different self-regulation scales

2006· article· en· W2149521665 on OpenAlexaff
Louise C. Mâsse, Diane D. Allen, Mark Wilson, Geoffrey C. Williams

Bibliographic record

VenueHealth Education Research · 2006
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsBritish Columbia Centre of Excellence for Women's HealthUniversity of British Columbia
FundersNational Cancer InstituteU.S. Public Health Service
KeywordsEquatingConstruct (python library)Psychological interventionReliability (semiconductor)Rating scaleScale (ratio)PsychologyApplied psychologyConstruct validityMeasure (data warehouse)Test (biology)Affect (linguistics)StandardizationItem response theoryPsychometricsClinical psychologyComputer scienceRasch modelData miningDevelopmental psychology

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.298
metaresearch head score (Gemma)0.608
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.702
Threshold uncertainty score0.866

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2980.608
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.006
Bibliometrics0.0120.010
Science and technology studies0.0010.005
Scholarly communication0.0040.005
Open science0.0050.007
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0050.002

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 head0.415
GPT teacher head0.618
Teacher spread0.202 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designTheoretical or conceptual
DomainMethods
GenreMethods

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

Citations18
Published2006
Admission routes1
Has abstractyes

Explore more

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