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Record W1846614335 · doi:10.1177/001979390706100107

The Impact of Provider Choice on Workers' Compensation Costs and Outcomes

2005· article· en· W1846614335 on OpenAlexaff
David Neumark, Peter S. Barth, Richard B. Victor

Bibliographic record

VenueIndustrial and Labor Relations Review · 2005
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsWorkers Compensation Board of British Columbia
Fundersnot available
KeywordsWorkers' compensationLimitingCompensation (psychology)BusinessWork (physics)Actuarial scienceLabour economicsDemographic economicsEconomicsPsychologySocial psychology

Abstract

fetched live from OpenAlex

Using survey data collected in 2002 and 2003 in California, Massachusetts, Pennsylvania, and Texas on workers injured 3 to 3.5 years earlier, coupled with information on the associated workers' compensation claims from the Workers Compensation Research Institute, the authors examine how provider choice in workers' compensation is related to costs and to workers' outcomes. They find that employee choice of the provider, by comparison with employer choice, was associated with higher costs and worse return-to-work outcomes. Although the same rate of physical recovery was found for both groups, workers who chose their providers reported higher satisfaction with medical care. The higher costs and worse return-to-work outcomes associated with employee choice arose largely when employees selected a new provider, rather than a provider with whom they had a pre-existing relationship. The findings lend some support to recent policy changes limiting workers' ability to choose a provider with whom they do not have a prior relationship.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.691
Threshold uncertainty score0.295

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.098
GPT teacher head0.345
Teacher spread0.247 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2005
Admission routes1
Has abstractyes

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