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THE BIG BANG? AN EVENTFUL YEAR IN WORKERS' COMPENSATION

2006· review· en· W2102367211 on OpenAlexaboutno aff
Tee L. Guidotti

Bibliographic record

VenueAnnual Review of Public Health · 2006
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsnot available
Fundersnot available
KeywordsPresumptionLegislatureApportionmentCompensation (psychology)Workers' compensationCausationPolitical scienceHealth carePublic relationsBusinessPublic administrationPsychologyLaw

Abstract

fetched live from OpenAlex

Workers' compensation in the past two years has been dominated by events in California, which have been so fundamental as to merit the term big bang. Passage of Senate Bill 899 has led to a comprehensive program of reform in access to medical care, access to rehabilitation services, temporary and permanent disability, evidence-based management, dispute resolution, and system innovation. Two noteworthy developments thus arose: a new requirement for apportionment by cause in causation analysis, and the adoption of evidence-based criteria for impairment assessment, treatment guidelines, and, soon, utilization review. Elsewhere in the United States, changes were modest, but extensive legislative activity in Texas suggests that Texas will be next to make major changes. In Canada, the Workers' Compensation Board of British Columbia has adopted an ambitious strategic initiative, and there is a Canadawide movement to establish presumption for certain diseases in firefighters. Suggestions for future directions include an increased emphasis on prevention, integration of programs, worker participation, enhancing the expertise of health care professionals, evidence-based management, process evaluation, and opportunities for innovation.

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)0.012
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: Review · Consensus signal: Review
Teacher disagreement score0.967
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.183
GPT teacher head0.394
Teacher spread0.211 · 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
GenreReview

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

Citations3
Published2006
Admission routes1
Has abstractyes

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