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Record W2465480805 · doi:10.7202/1036763ar

Validation de la version française de la Behavior and Instructional Management Scale

2016· article· fr· W2465480805 on OpenAlexvenueno aff
Philippe Wanlin, Malika Revilloud

Bibliographic record

VenueMesure et évaluation en éducation · 2016
Typearticle
Languagefr
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsnot available
Fundersnot available
KeywordsSassHumanitiesPhilosophyComputer science

Abstract

fetched live from OpenAlex

La Behavior and Instructional Management Scale (BIMS) développée par Martin et Sass (2010) permet de mesurer les pratiques et les croyances des enseignants en gestion de la classe. Elle est composée de deux dimensions théoriques : la gestion de l’enseignement et la gestion du comportement des élèves. Martin et Sass (2010) ont validé la version anglaise de cet instrument de mesure. L’objectif de cet article est de présenter la chronologie de son évolution, puis de valider sa version française auprès de 338 enseignants qui se forment à l’enseignement au primaire et au secondaire. Les résultats, qui sont discutés en termes de perspectives de recherche, montrent que la traduction française de la BIMS obtient des indicateurs de qualités psychométriques proches de ceux rapportés par Martin et Sass (2010).

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)0.024
metaresearch head score (Gemma)0.040
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 score0.024
Threshold uncertainty score0.126

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.040
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.024
GPT teacher head0.361
Teacher spread0.338 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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