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Record W6992376224

Le retour au travail dans un contexte de\n barrières linguistiques : Une étude comparative des politiques et des pratiques\n d’indemnisation des victimes de lésion professionnelle au Québec et en Ontario

2021· article· fr· W6992376224 on OpenAlexaffabout

Bibliographic record

VenueÉrudit (Université de Montréal) · 2021
Typearticle
Languagefr
FieldArts and Humanities
TopicLinguistics, Language Diversity, and Identity
Canadian institutionsInstitut de recherche Robert-Sauvé en santé et en sécurité du travailUniversity of OttawaInstitute for Work & HealthUniversity of WaterlooMcMaster University
Fundersnot available
KeywordsDiversification (marketing strategy)Context (archaeology)Perspective (graphical)Politics
DOInot available

Abstract

fetched live from OpenAlex

La façon dont les régimes d’indemnisation des victimes de lésion professionnelle doivent tenir compte des barrières linguistiques est d’une importance capitale à la lumière de la diversification linguistique croissante du Canada. S’appuyant sur des entrevues menées auprès de travailleurs accidentés et d’informateurs clés, cette étude est la première à examiner, de manière empirique, les politiques et les pratiques du retour au travail sous l’angle des barrières linguistiques. En comparant les juridictions du Québec et de l’Ontario, l’étude met en lumière des similitudes et des différences touchant les accommodements linguistiques ainsi que les politiques et les pratiques du retour au travail qui déterminent les expériences des travailleurs accidentés ayant des besoins linguistiques. Elle fait valoir que les lacunes à cet égard, qui sont plus marquées au Québec, contribuent à un faible retour au travail pour ces travailleurs dans les deux provinces.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.140
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0050.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.237
Teacher spread0.215 · 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 teacher head, not a consensus.

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 routes2
Has abstractyes

Explore more

Same venueÉrudit (Université de Montréal)Same topicLinguistics, Language Diversity, and IdentityFrench-language works237,207