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Mesurer les facteurs psychosociaux en milieu de travail au sein du gouvernement fédéral

2022· article· fr· W6907896660 on OpenAlexaboutno aff

Bibliographic record

VenueStatistics Canada Dissemination · 2022
Typearticle
Languagefr
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsnot available
Fundersnot available
KeywordsCivil servantsResearch methodologyWork environment

Abstract

fetched live from OpenAlex

La Norme nationale du Canada sur la santé et la sécurité psychologiques en milieu de travail (la Norme) identifie 13 facteurs de risque psychosociaux qui ont une incidence sur la santé et la sécurité psychologiques en milieu de travail, et que les employeurs devraient mesurer et surveiller en vue de prendre des mesures à l’égard des aspects à améliorer. Cette étude vise à déterminer si le Sondage auprès des fonctionnaires fédéraux (SAFF) peut servir d’outil pour évaluer ces facteurs chez les fonctionnaires fédéraux. Elle cherche également à examiner, de façon préliminaire, les prédicteurs de la satisfaction au travail de ces employés. Les données du SAFF de 2017 et de 2019 ont été analysées à ces fins. Plus précisément, la modélisation structurale exploratoire et les essais de l’invariance des mesures ont été utilisés pour déterminer un modèle de mesure qui rendrait compte des facteurs de risque psychosociaux décrits dans la Norme et pour évaluer l’équivalence de ce modèle entre les deux cycles du SAFF.

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)0.015
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 score0.027
Threshold uncertainty score0.194

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.005
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.339
Teacher spread0.324 · 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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