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Record W2905694004 · doi:10.4000/edso.5145

Socialisation professionnelle des directions d’établissement d'enseignement au Québec : tensions entre formation et autonomie professionnelle

2018· article· fr· W2905694004 on OpenAlexaffabout
Houssine Dridi

Bibliographic record

VenueÉducation et socialisation · 2018
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsPolitical scienceHumanitiesSociologyPhilosophy

Abstract

fetched live from OpenAlex

Même si les facultés d’éducation ont tenté de résister, la professionnalisation a fini par s’imposer en 2001 avec un règlement ministériel fixant l’obligation de formation de 2e cycle en gestion scolaire. Guidée en 2008 par un « référentiel des compétences », cette formation est destinée à la socialisation professionnelle des directions d’établissement d’enseignement en les dotant de solides connaissances à la fois théoriques et pratiques et en les accompagnant dans leur insertion ou intégration professionnelle. La présente contribution se base sur une étude réalisée dans le cadre d’un partenariat université-commission scolaire. Un questionnaire et des entrevues auprès de 70 directions-adjointes d’établissement scolaire ont servi à l’analyse des données faisant ressortir une difficulté à exploiter les résultats de recherche universitaire par les milieux de pratique et révélant une remise en question de la conception de la formation, des modalités d’accompagnement et des dispositifs d’évaluation. Une réflexion est dégagée autour des défis de l’amélioration de la formation et de la socialisation professionnelle.

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)0.008
metaresearch head score (Gemma)0.013
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.490

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0110.008
Scholarly communication0.0060.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.245
GPT teacher head0.464
Teacher spread0.218 · 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

Citations0
Published2018
Admission routes2
Has abstractyes

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