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Record W2053904946 · doi:10.1002/ajim.22023

Building a human rights framework for workers' compensation in the United States: Opening the debate on first principles

2012· article· en· W2053904946 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Journal of Industrial Medicine · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Labor and Employment Law
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsCompensation (psychology)Human rightsWorkers' compensationFoundation (evidence)ConformityLawLaw and economicsInternational human rights lawMedicinePolitical scienceSociologySocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: This article introduces the idea of human rights to the topic of workers' compensation in the United States. It discusses what constitutes a human rights approach and explains how this approach conflicts with those policy ideas that have provided the foundation historically for workers' compensation in the United States. METHODS: Using legal and historical research, key international labor and human rights standards on employment injury benefits and influential writings in the development of the U.S. workers' compensation system are cited. RESULTS: Workers' injury and illness compensation in the United States does not conform to basic international human rights norms. CONCLUSIONS: A comprehensive review of the U.S. workers' compensation system under international human rights standards is needed. Examples of policy changes are highlighted that would begin the process of moving workers' compensation into conformity with human rights standards.

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.

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)0.004
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.908
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.125
GPT teacher head0.396
Teacher spread0.271 · 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