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Record W3150974753 · doi:10.7202/1077970ar

Quelles compétences pour accompagner des enseignants débutants? Étude multicas

2021· article· fr· W3150974753 on OpenAlex
Isabelle Vivegnis

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueMcGill Journal of Education / Revue des sciences de l éducation de McGill · 2021
Typearticle
Languagefr
FieldSocial Sciences
TopicPsychodrama and Leishmaniasis Studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesSociologyPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

De nombreuses études dans le monde font état d’une insertion professionnelle particulièrement critique, menant souvent à un décrochage chez les enseignants débutants. L’accompagnement, tel que le mentorat, occupe une place de première ligne parmi les moyens pouvant soutenir l’enseignant qui débute dans la profession. Mais, pour assurer un soutien fécond en termes de développement professionnel chez le débutant, l’accompagnateur se devra d’agir avec précaution et aura à mobiliser plusieurs compétences d’accompagnement. C’est un des aspects documentés dans notre recherche doctorale menée sous la forme d’une étude multicas et selon une approche qualitative/interprétative auprès de quatre dyades accompagnateurs-enseignants débutants de l’enseignement secondaire au Québec.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.474
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0050.004
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
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 head0.481
GPT teacher head0.455
Teacher spread0.027 · 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