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Record W2612164186 · doi:10.7202/1034990ar

Ressources universitaires et travailleurs syndiqués : l’expérience d’un programme conjoint université-syndicats

2016· article· fr· W2612164186 on OpenAlexaffvenueabout
Michel Lizée

Bibliographic record

VenueInternational Review of Community Development · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsPolitical scienceHumanitiesSociologyArt

Abstract

fetched live from OpenAlex

L’article décrit un programme de formation et de recherche mené conjointement par l’Université du Québec à Montréal (UQAM), la Confédération des syndicats nationaux (CSN) et la Fédération des travailleurs du Québec (FTQ). Après avoir expliqué les origines du projet, l’auteur décrit les principales caractéristiques de ce programme, lequel repose sur une adaptation des ressources universitaires aux besoins de recherche ou de formation du mouvement syndical, dans le cadre de démarches initiées et contrôlées par lui. Par la suite, l’auteur analyse certains acquis et difficultés de ce programme : des activités de formation qui respectent la démarche syndicale mais un problème pédagogique d’adaptation des ressources universitaires, des activités de recherche orientée originales et utiles mais dont la diffusion dans certains cas demeure insuffisante, la reconnaissance graduelle mais lente de la nécessité, de la légitimité et de la spécificité de l’intervention universitaire en promotion collective.

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)0.011
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 score0.376
Threshold uncertainty score0.747

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0150.008
Scholarly communication0.0070.003
Open science0.0020.011
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0120.001

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 head0.044
GPT teacher head0.314
Teacher spread0.270 · 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
Published2016
Admission routes3
Has abstractyes

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Same venueInternational Review of Community DevelopmentSame topicSocial Sciences and GovernanceFrench-language works237,207