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Innovations du travail et syndicats de la fonction publique: un partenariat À construire

2006· article· fr· W1996375488 on OpenAlexaffabout
Denis Harrisson, Guy Bellemare

Bibliographic record

VenueAnnals of Public and Cooperative Economics · 2006
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsUniversité du Québec en OutaouaisUniversité du Québec à Montréal
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Résumé ** : Au cours des dix dernières années, les acteurs de l’administration publique du Québec ont expérimenté une configuration organisationnelle créative et originale constituée des Comités ministériels sur l’organisation du travail (CMOT). Peu d’études et de recherches se sont intéressées à cette forme de partenariat entre l’État, les syndicats et les associations professionnelles. Nous proposons une étude de cas de trois CMOT que nous considérons comme étant des innovations sociales dans l’administration publique. Les acteurs ont du mal à s’entendre sur les frontières délimitant la zone d’influence des CMOT au sein des ministères. Des nouvelles tensions naissent entre les gestionnaires et les représentants syndicaux. Néanmoins, une nouvelle zone de coopération se forme conduisant à un nouvel équilibre dans les relations entre les acteurs de l’administration publique. Nous proposons une analyse de la mise en place des CMOT, de sa lente évolution marquée de ruptures et de reprises. Malgré les obstacles, les acteurs s’entendent pour affirmer que le partenariat est nécessaire à la bonne marche du processus de transformation de l’administration publique.

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)0.015
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.225
Threshold uncertainty score0.448

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.005
Science and technology studies0.0130.028
Scholarly communication0.0210.009
Open science0.0020.007
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0110.001

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 head0.045
GPT teacher head0.310
Teacher spread0.265 · 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

Citations7
Published2006
Admission routes2
Has abstractyes

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