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Record W4375936292 · doi:10.7202/1098362ar

[ Sans Titre - No Title ]Raîche, G. et Talbot, N. (dir.). (2020). Des mécanismes pour assurer la validité de l’interprétation de la mesure en éducation. Volume 4 – Interdisciplinarité de la mesure et de l’évaluation. Presses de l’Université du Québec

2022· article· fr· W4375936292 on OpenAlexaffvenueabout
Jesse Schnobb

Bibliographic record

VenueRevue des sciences de l éducation · 2022
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsUniversité du Québec en Outaouais
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Raîche, G. et Talbot, N. (dir.). (2020). Des mécanismes pour assurer la validité de l’interprétation de la mesure en éducation. Volume 4 – Interdisciplinarité de la mesure et de l’évaluation. Presses de l’Université du Québec. Un article de la revue Revue des sciences de l’éducation (Enjeux et tension autour de la notion ou du concept d’approche par compétences et autour des pratiques que cette approche inspire) diffusée par la plateforme Érudit.

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)0.004
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.996
Threshold uncertainty score0.596

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.022
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.008
Science and technology studies0.0040.003
Scholarly communication0.0080.008
Open science0.0040.003
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.1780.152

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 head0.149
GPT teacher head0.448
Teacher spread0.299 · 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.

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

Citations0
Published2022
Admission routes3
Has abstractyes

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