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Record W3009957386 · doi:10.1522/radm.no3.1097

Vers la construction d’une culture organisationnelle de santé mentale au service des acteurs de changement dans l’économie sociale et solidaire

2020· article· fr· W3009957386 on OpenAlexaffvenue
Clarisse Broucke, Pénélope Codello

Bibliographic record

VenueAd machina l avenir de l humain au travail · 2020
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

S’engager dans une carrière à vocation sociale n’implique pas toujours une vie professionnelle et personnelle épanouie. Les acteurs de l’économie sociale et solidaire qui seront désignés ici sous le terme « acteurs de changement », peuvent eux aussi rencontrer au cours de leur carrière des enjeux de santé mentale importants les menant à des épuisements professionnels, des dépressions ou d’autres épisodes critiques de santé mentale. L’article propose une analyse des enjeux de santé mentale de ces acteurs dans une perspective psychodynamique. Les facteurs individuels, collectifs et organisationnels interagissent au sein d’un écosystème complexe qui peut produire des effets délétères en matière de santé mentale. Mais l’article conclut sur une discussion autour des leviers qui émanent de cette même dynamique. Un cercle plus vertueux peut se mettre en place si les organisations de l’économie sociale et solidaire parviennent à faire naître et entretenir une culture de santé mentale.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0060.023
Scholarly communication0.0100.006
Open science0.0010.005
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0060.001

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 head0.025
GPT teacher head0.281
Teacher spread0.256 · 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 designNot applicable
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

Citations2
Published2020
Admission routes2
Has abstractyes

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