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Record W4377004880 · doi:10.7202/1095889ar

État des lieux sur les usages du test de jugement situationnel en formation

2023· article· fr· W4377004880 on OpenAlexaff
Anne-Michèle Delobbe, Martin Lauzier, Chantale Jeanrie

Bibliographic record

VenueHumain et Organisation · 2023
Typearticle
Languagefr
FieldMedicine
TopicMedical Education and Admissions
Canadian institutionsInstitut du Savoir MontfortUniversité LavalUniversité du Québec en OutaouaisUniversité du Québec à Rimouski
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Le test de jugement situationnel (TJS) est un outil composé de descriptions de situations auxquelles le répondant doit réagir. Bien que plusieurs études portent sur son développement et ses propriétés psychométriques en sélection, peu étudient la possibilité d’utiliser cet outil en formation. Cet article dresse un portrait des utilisations possibles du TJS en formation. Une recension a été réalisée dans des bases de données reconnues au moyen de mots-clés liés au domaine de la formation. Les résultats indiquent que peu d’études ont testé un usage du TJS en formation. Lorsqu’utilisé, celui-ci a surtout servi à faciliter l’enseignement des contenus pendant la formation ou à évaluer certaines retombées après celle-ci. Sur la base des constats établis, un agenda de recherche est proposé.

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)0.039
metaresearch head score (Gemma)0.150
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.039
Threshold uncertainty score0.207

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0390.150
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0020.004
Scholarly communication0.0050.004
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.072
GPT teacher head0.342
Teacher spread0.269 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations0
Published2023
Admission routes1
Has abstractyes

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