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Record W3097335089 · doi:10.1177/1035304620962724

Enforcing workers’ compensation rights for Chinese seafarers in human resource supply chains

2020· article· en· W3097335089 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

VenueThe Economic and Labour Relations Review · 2020
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsBusinessEnforcementSupply chainLiabilityIntermediaryMultinational corporationCompensation of employeesHuman rightsCompensation (psychology)Human resourcesResource (disambiguation)FinanceMarketingLawEconomicsManagement

Abstract

fetched live from OpenAlex

Non-compliance with labour standards impedes enforcement of workers’ rights in human resource supply chains. Despite governments’ efforts to improve labour standards and encourage employer-centred voluntary compliance programmes, infringements of workers’ rights are widely reported. Using a qualitative socio-legal study of Chinese seafarers’ workers’ compensation rights, we investigate whether shipping companies and their crewing agencies comply with their legal obligations following workplace injuries and fatalities. Through 74 semi-structured interviews and analysis of crew management policies from 7 shipping companies, we identify a failure of most shipowners’ internal policies to comply with legal obligations. Furthermore, multinational shipping companies use crewing agencies to evade their liabilities to injured seafarers. We propose the establishment of a joint liability mechanism between employers and labour intermediaries to fill this compliance gap that exists in global human resource supply chains. JEL Codes: J81, J83, L91, M54, N75

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.399
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.066
GPT teacher head0.418
Teacher spread0.352 · 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