MétaCan
Menu
Back to cohort
Record W2592574207 · doi:10.1177/1948550617693063

Construct Validation in Social and Personality Research

2017· article· en· W2592574207 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSocial Psychological and Personality Science · 2017
Typearticle
Languageen
FieldPsychology
TopicCognitive and psychological constructs research
Canadian institutionsToronto Metropolitan UniversityYork University
FundersOntario Ministry of Research and Innovation
KeywordsConstruct (python library)Construct validityPsychologyPersonalitySocial psychologySample (material)PsychometricsApplied psychologyDevelopmental psychologyComputer science

Abstract

fetched live from OpenAlex

The verity of results about a psychological construct hinges on the validity of its measurement, making construct validation a fundamental methodology to the scientific process. We reviewed a representative sample of articles published in the Journal of Personality and Social Psychology for construct validity evidence. We report that latent variable measurement, in which responses to items are used to represent a construct, is pervasive in social and personality research. However, the field does not appear to be engaged in best practices for ongoing construct validation. We found that validity evidence of existing and author-developed scales was lacking, with coefficient α often being the only psychometric evidence reported. We provide a discussion of why the construct validation framework is important for social and personality researchers and recommendations for improving practice.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.339
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.016
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.519
GPT teacher head0.588
Teacher spread0.069 · 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