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Record W4396520795 · doi:10.1027/2698-1866/a000061

Structural Validity Evidence for the Oxford Utilitarianism Scale Across 15 Languages

2024· article· en· W4396520795 on OpenAlexaff
Briana Oshiro, William H.B. McAuliffe, Raymond Luong, Anabela Caetano Santos, Andrej Findor, A Kuźmińska, Anthony Lantian, Asil Ali Özdoğru, Balázs Aczél, Bojana M. Dinić, Christopher R. Chartier, Jasper Hidding, Job de Grefte, John Protzko, Mairead Shaw, Maximilian Primbs, Nicholas A. Coles, Patrí­cia Arriaga, Patrick S. Forscher, Savannah C Lewis, Tamás Nagy, Wieteke C. de Vries, William Jiménez‐Leal, Yansong Li, Jessica Kay Flake

Bibliographic record

VenuePsychological Test Adaptation and Development · 2024
Typearticle
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsMcGill University
Fundersnot available
KeywordsScale (ratio)UtilitarianismGeographyPhilosophyEpistemologyCartography

Abstract

fetched live from OpenAlex

Abstract: Background: The Psychological Science Accelerator (PSA) recently completed a large-scale moral psychology study using translated versions of the Oxford Utilitarianism Scale (OUS). However, the translated versions have no validity evidence. Objective: The study investigated the structural validity evidence of the OUS across 15 translated versions and produced version-specific validity reports. Methods: We analyzed OUS data from the PSA, which was collected internationally on a centralized online questionnaire . We also collected qualitative feedback from experts for each translated version. Results: For each version, we produced version-specific psychometric reports which include the following: (1) descriptive item and demographics analyses, (2) factor structure evidence using confirmatory factor analyses, (3) measurement invariance testing across languages using multiple-group confirmatory factor analyses and alignment optimization, and (4) reliability analyses using coefficients α and ω.

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)0.027
metaresearch head score (Gemma)0.061
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.027
Threshold uncertainty score0.142

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.061
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.003
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0000.001
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 head0.473
GPT teacher head0.426
Teacher spread0.047 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations10
Published2024
Admission routes1
Has abstractyes

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