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Record W2063756280 · doi:10.3406/oss.2006.1125

L’accès à l’indemnisation pour les incapacités attribuables aux lésions psychiques et aux lésions musculo-squelettiques liées au travail au Québec

2006· article· en· W2063756280 on OpenAlexaboutno aff
Katherine Lippel

Bibliographic record

VenueSanté Société et Solidarité · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsLegislationCompensation (psychology)Context (archaeology)Mental healthPolitical scienceWorkers' compensationMental illnessWelfare economicsPsychologyMedicinePsychiatrySocial psychologyLawEconomicsGeography

Abstract

fetched live from OpenAlex

This article examines the application of the Quebec workers’ compensation scheme to two health problems whose causes are often multi-factorial: mental health problems and musculo-skeletal disorders. After presenting policy governing acceptance of these claims by the workers’ compensation board (CSST), and certain specific obstacles to compensation, the author examines the application of Quebec social policy and suggests why these work-related health problems are often not declared. Quebec compensation legislation covers all injury and illness that can be shown to be either an occupational illness or caused by a work-related accident. Other Canadian provinces have excluded mental health problems attributable to chronic stress from the purview of their legislation. While these cases are covered by workers’ compensation in Quebec, the number of such claims is relatively low, although this is not true for musculoskeletal disorders. The author concludes that policy choices regarding access to compensation, in the context of universal health insurance, may favour under-reporting of these injuries to the CSST, a phenomenon that may have serious repercussions on prevention strategies.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.415
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0050.002
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.055
GPT teacher head0.397
Teacher spread0.342 · 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 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

Citations2
Published2006
Admission routes1
Has abstractyes

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