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Record W4312360533 · doi:10.7202/1092959ar

Equity, Diversity, and Inclusion (EDI) Case Study: Where Does the Ombuds Fit?

2022· article· en· W4312360533 on OpenAlex
Julie Boncompain, Heather McGhee Peggs, Brent Epperson

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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Journal of Bioethics · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsEquity (law)Political scienceInclusion (mineral)HumanitiesDiversity (politics)SociologyLawPhilosophySocial science

Abstract

fetched live from OpenAlex

Comment un ombudsman pourrait-il répondre à un problème d’équité? À l’aide d’une étude de cas réelle portant sur un conflit entre un étudiant et un membre du corps professoral soumis à un ombudsman universitaire, nous examinons la valeur d’une lentille d’équité qu’un ombudsman peut apporter aux discussions éthiques sur l’EDI.

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)0.014
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Open science, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.417
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0400.000
Scholarly communication0.0000.000
Open science0.0000.009
Research integrity0.0000.003
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 head0.342
GPT teacher head0.514
Teacher spread0.172 · 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