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Backshoring, Local Sweatshop Regimes and CSR in India

2014· article· en· W2160329418 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCompetition & Change · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal trade, sustainability, and social impact
Canadian institutionsnot available
FundersEconomic and Social Research CouncilUniversity of British ColumbiaMinistry of Textiles, Government of IndiaBritish Academy
KeywordsSweatshopCorporate social responsibilityCommodity chainCommodityProduction (economics)BusinessProduct (mathematics)EconomicsMarket economyEconomic systemPolitical scienceMicroeconomicsLaw

Abstract

fetched live from OpenAlex

Deploying an approach to chain analysis concerned with regional differentiation and backshoring, this article investigates the regional complexities of the garment commodity chain in India and its multiple local sweatshop regimes to illustrate the limitations of corporate social responsibility (CSR) norms. First, the article shows that India's distinctively regional organization of production and product specialization, arising from different local historical legacies of production, reproduces labour outcomes that prevent the effectiveness of CSR. Second, it shows that the backshoring practices used by a powerful group of Pan-Indian buyer-exporters, who increasingly behave like global buyers, further reproduce the logic of the local sweatshop, hence reinforcing the limitations of corporate approaches to labour 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.616
Threshold uncertainty score0.534

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.030
GPT teacher head0.256
Teacher spread0.226 · 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