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Record W4412442151 · doi:10.7202/1118738ar

Examen de l’influence de l’indice de milieu socioéconomique sur les exigences du travail et le bien-être des directions et des directions adjointes au Québec

2025· article· fr· W4412442151 on OpenAlexaffvenueabout
Marie-Christine Rivest, Louise Clément, Emmanuel Poirel

Bibliographic record

VenueCanadian Journal of Educational Administration and Policy · 2025
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsUniversité de MontréalUniversité LavalUniversité du Québec en Outaouais
Fundersnot available
KeywordsHumanitiesPhilosophyPolitical science

Abstract

fetched live from OpenAlex

30% des directions et des directions adjointes travaillent en milieu socioéconomique défavorisé au Québec (MEQ, 2024). Si la nature de leur travail est essentielle, les exigences de leur quotidien sont un déterminant important de leur bien-être au travail (Leithwood et al., 2017; Marsh et al., 2023; Poirel et al., 2020). Cette étude vise à examiner de manière comparative la perception des exigences du travail ainsi que le bien-être des directions et des directions adjointes (n = 864) d’établissements d’enseignement du Québec avec et sans le contexte de défavorisation. Les résultats montrent que l’indice de milieu socioéconomique (IMSE) a un effet partiel sur la perception des répondants en ce qui concerne les exigences du travail et leur bien-être selon la fonction de travail et l’ordre d’enseignement. Ces résultats sont cruciaux pour mieux comprendre les dynamiques professionnelles des directions et des directions adjointes et peuvent contribuer ainsi à l’élaboration de politiques plus efficaces pour soutenir leur réalité de travail.

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)0.010
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 score0.076
Threshold uncertainty score0.153

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0030.002
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.030
GPT teacher head0.334
Teacher spread0.303 · 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

Citations0
Published2025
Admission routes3
Has abstractyes

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