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Record W2097637919 · doi:10.2105/ajph.2005.083873

Association Between the Decline in Workers’ Compensation Claims and Workforce Composition and Job Characteristics in Ontario, Canada

2007· article· en· W2097637919 on OpenAlexafffundabout
F. Curtis Breslin, Emile Tompa, Cameron Mustard, Ryan Zhao, Peter Smith, Sheilah Hogg‐Johnson

Bibliographic record

VenueAmerican Journal of Public Health · 2007
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsInstitute for Work & Health
FundersCanadian Institutes of Health ResearchUniversity of Toronto
KeywordsWorkforceIncentiveInvestment (military)DemographicsDemographic economicsLabour economicsBusinessCompensation (psychology)DemographyEnvironmental healthMedicineEconomicsEconomic growthPsychologyPolitical science

Abstract

fetched live from OpenAlex

We examined associations between workforce demographics and job characteristics, grouped by industrial sector, and declines in workers' compensation claim rates in Ontario, Canada, between 1990 and 2003. Gender, age, occupation, and job tenure were predictors for claim rates in 12 industrial sectors. The decline in claims was significantly associated with a decline in the proportion of employment in occupations with high physical demands. These findings should generate interest in economic incentives and regulatory policies designed to encourage investment in safer production processes.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.177

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.062
GPT teacher head0.372
Teacher spread0.310 · 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

Citations12
Published2007
Admission routes3
Has abstractyes

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