MétaCan
Menu
Back to cohort
Record W3162982207 · doi:10.7202/1077097ar

L’admiration pour celles qui en font toujours plus que ce que leur devoir commande : quel impact pour les travailleuses sociales de l’Ontario et du Québec ?

2021· article· fr· W3162982207 on OpenAlexaffvenueabout
Roger Gervais

Bibliographic record

VenueNouvelles perspectives en sciences sociales · 2021
Typearticle
Languagefr
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsUniversité Sainte-AnneLaurentian University
Fundersnot available
KeywordsHumanitiesArtPolitical science

Abstract

fetched live from OpenAlex

Toujours animé par des analyses qui privilégient l’étude des normativités en collision dans leur propension à éclairer la relation entre l’organisation du travail et la santé des professionnelles, nous avons, pour le présent texte, isolé cet énoncé : « Je trouve admirable quelqu’un qui est capable de faire plus que ce que son devoir commande ». Tiré d’un questionnaire d’enquête utilisé en 2012-2013 auprès de 1 197 travailleuses et travailleurs sociaux du Québec de l’Ontario, cet énoncé nous permettra de savoir si ce genre de comparaison dite ascendante affectera la souffrance au travail. Nos résultats seront aussi testés en présence de deux ensembles de variables de contrôle : les conditions de travail et les facteurs structuro-organisationnels. De nombreuses études confirment déjà l’influence de ces facteurs sur le bien-être et la souffrance au travail. Cherchons donc à voir si, en plus de ces variables contrôles, le fait de se comparer aux pairs au travail qui se livrent à l’hyperactivité professionnelle affecte le bien-être en dépit des autres variables imposantes.

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)0.003
metaresearch head score (Gemma)0.008
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.300

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0130.010
Scholarly communication0.0070.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0130.001

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 head0.064
GPT teacher head0.399
Teacher spread0.335 · 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
Published2021
Admission routes3
Has abstractyes

Explore more

Same venueNouvelles perspectives en sciences socialesSame topicWorkplace Health and Well-beingFrench-language works237,207