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Record W1863841928 · doi:10.7202/019582ar

Les composantes de l’entraînement à l’improvisation actives dans la gestion des imprévus en salle de classe du niveau secondaire

2008· article· fr· W1863841928 on OpenAlexaffvenue
Jean‐Pierre Pelletier, France Jutras

Bibliographic record

VenueMcGill Journal of Education / Revue des sciences de l éducation de McGill · 2008
Typearticle
Languagefr
FieldPsychology
TopicSocial Representations and Identity
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsHumanitiesPsychologyPhilosophy

Abstract

fetched live from OpenAlex

La gestion de classe est l’une des principales difficultés éprouvées par les enseignantes et enseignants novices. Cependant, avec le temps, ils développent une certaine assurance devant les imprévus, notamment en raison de leur capacité à improviser. La présente étude vise à identifier certaines composantes de l’entraînement à l’improvisation actives dans la gestion des imprévus en classe du secondaire. Les résultats montrent qu’un tel entraînement peut développer la vigilance et la rapidité d’exécution devant une situation non planifiée.

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
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 head0.273
GPT teacher head0.443
Teacher spread0.170 · 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 designQualitative
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

Citations11
Published2008
Admission routes2
Has abstractyes

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