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Record W2775413673 · doi:10.7202/1034720ar

Les pratiques de formation en entreprise au Québec

2016· article· fr· W2775413673 on OpenAlexaffvenueabout
Pierre Pâquet

Bibliographic record

VenueInternational Review of Community Development · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesPolitical sciencePhysicsPhilosophy

Abstract

fetched live from OpenAlex

Au point de départ, l’auteur cherche à fournir des éléments de réponse à des questions touchant l’accès à la formation, les caractéristiques des activités de formation et le degré de contrôle exercé par les partenaires en présence sur ces activités. Ces questions sont interreliées et permettent, selon l’auteur, de saisir les enjeux de la formation en entreprise. Postulant l’existence d’un marché du travail segmenté, stratifié, l’auteur émet deux hypothèses; la première : les travailleurs bénéficieront d’un accès différencié à la formation en fonction de leurs propres caractéristiques et en fonction de celles des milieux de travail où ils s’insèrent; la seconde : au Québec, les pratiques de formation en entreprise sont le fait d’une proportion relativement restreinte d’entreprises et les travailleurs susceptibles d’en bénéficier représentent une faible proportion de la main-d’oeuvre. Enquête chiffrée à l’appui, l’auteur aboutit entre autres à la conclusion que les activités en formation sont axées sur les besoins immédiats de l’entreprise et négligent, compte tenu de la conjoncture, d’autres besoins de qualification des travailleurs.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.275

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.004
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.003
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 head0.060
GPT teacher head0.376
Teacher spread0.315 · 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 designObservational
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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