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Record W4404426682 · doi:10.1111/ilrs.12336

Diseño regulatorio e interacciones de gobernanza en la responsabilidad social impulsada por los trabajadores. Acuerdo de Dindigul

2024· article· es· W4404426682 on OpenAlexaff
Judy Fudge, Genevieve LeBaron

Bibliographic record

VenueRevista Internacional del Trabajo · 2024
Typearticle
Languagees
FieldBusiness, Management and Accounting
TopicGlobal trade, sustainability, and social impact
Canadian institutionsSimon Fraser UniversityMcMaster University
Fundersnot available
KeywordsBusinessPolitical scienceWelfare economicsEconomics

Abstract

fetched live from OpenAlex

Resumen En este artículo se investiga el auge de las iniciativas de responsabilidad social impulsada por los trabajadores (RST) para combatir los abusos laborales y la vulneración de los derechos humanos en las cadenas mundiales de suministro. Se analiza el Acuerdo de Dindigul, un caso pionero de RST impulsado por un sindicato independiente de mayoría dalit dirigido por mujeres en Dindigul (India) para abordar la violencia por razón de género en las cadenas de suministro de la confección. Mediante entrevistas con informadores clave y análisis documental codificado en NVivo 12, se estudia la génesis del Acuerdo de Dindigul, su singularidad y sus interacciones con otros instrumentos de gobernanza.

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)0.006
metaresearch head score (Gemma)0.010
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.008
Scholarly communication0.0050.002
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.012
GPT teacher head0.296
Teacher spread0.284 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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