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Record W7128693309 · doi:10.7202/1123119ar

La santé mentale et le bien-être des directions d’établissement au Québec à l’épreuve de la période pandémique (COVID-19)

2025· article· fr· W7128693309 on OpenAlexaffvenueabout
Rana Naimi, Emmanuel Poirel

Bibliographic record

VenueNouveaux cahiers de la recherche en éducation · 2025
Typearticle
Languagefr
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsFace (sociological concept)Social impactSocial environmentSocial risk

Abstract

fetched live from OpenAlex

La COVID-19 a profondément bouleversé le rôle des directions d’établissement d’enseignement (DEE) exposées à des directives fluctuantes, des attentes accrues et des risques pour leur santé mentale. Dans cette recherche, des entretiens ont été menés auprès de 20 DEE afin de rendre compte des risques psychosociaux (RPS) auxquelles elles ont été confrontées ainsi que de leur bien-être au travail durant la pandémie. La majorité des personnes participantes ont rapporté une exacerbation des risques psychosociaux, ce qui a contribué à accentuer la dégradation de leur bien-être au travail déjà fragilisé avant la pandémie en raison des exigences de la fonction. Les résultats montrent aussi que les DEE ont vécu une surcharge émotionnelle et cognitive importante. Toutefois, un soutien social a permis à certains de mieux faire face à cette surcharge. Cette étude met en évidence la nécessité de donner du pouvoir d’agir sur l’organisation du travail pour réduire les risques et préserver la santé mentale des DEE face à de futures crises.

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)0.006
metaresearch head score (Gemma)0.014
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 score0.097
Threshold uncertainty score0.210

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0060.002
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0120.001

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 head0.164
GPT teacher head0.513
Teacher spread0.350 · 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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