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Record W3146662246 · doi:10.7202/1075974ar

Des travailleurs et des travailleuses pauvres à « mettre en mouvement » : l’activation et la notion d’aptitude au travail au sein des services publics d’emploi

2021· article· fr· W3146662246 on OpenAlexvenueaboutno aff
Catherine Charron

Bibliographic record

VenueCahiers de recherche sociologique · 2021
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsPublicsHumanitiesPolitical scienceSociologyArt

Abstract

fetched live from OpenAlex

Cet article s’intéresse aux rapports sociaux tels qu’ils se construisent sur le terrain de l’administration publique, dans la prestation de services publics d’emploi destinés aux personnes assistées sociales. À partir d’un certain nombre de pratiques visant l’intégration en emploi et qui composent leur intervention auprès des prestataires jugés « aptes au travail », nous dégagerons la façon dont les « street-level bureaucrats » perçoivent et catégorisent les prestataires, définissent leur propre rôle et celui de l’État. Ce faisant, nous mettrons en relief la manière dont se conjuguent les éthos du travail social, du service public et de l’activation chez les intervenantes et intervenants qui travaillent quotidiennement auprès de cette population sans emploi dite « apte au travail ». Les résultats exposés dans cet article sont issus d’une enquête qualitative menée auprès agent.e.s d’aide du ministère, dans le contexte de l’implantation d’un programme obligatoire d’insertion au Québec en 2018 (Objectif emploi).

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)0.006
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.014
Scholarly communication0.0070.005
Open science0.0010.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0100.002

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 head0.204
GPT teacher head0.412
Teacher spread0.209 · 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

Citations1
Published2021
Admission routes2
Has abstractyes

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