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Record W2124521087 · doi:10.1111/irj.12000

The effectiveness of socially sustainable sourcing mechanisms: Assessing the prospects of a new form of joint regulation

2013· article· en· W2124521087 on OpenAlexaboutno aff
Chris F. Wright, William Brown

Bibliographic record

VenueIndustrial Relations Journal · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsnot available
FundersEconomic and Social Research Council
KeywordsCompetition (biology)BusinessProduct (mathematics)Joint (building)Service (business)Quarter (Canadian coin)Industrial organizationEconomicsSustainable developmentProduct marketMarket economyLabour economicsMarketingIncentiveLawPolitical science

Abstract

fetched live from OpenAlex

Abstract The traditional mechanisms for improving and protecting labour standards in advanced economies are failing. In Britain, the effectiveness of collective bargaining has diminished substantially over the past quarter century. Legally enforceable minimum labour standards have been an inadequate substitute. A new form of ‘joint regulation’ is emerging that may be better attuned to the contemporary structure of product market competition. It involves employers and unions coordinating action on labour standards across the supply chains of firms that contribute to the production of a particular good or service. This article explores the circumstances in which these ‘socially sustainable sourcing’ mechanisms develop and examines their impact on labour standards, by means of two case studies.

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)0.100
metaresearch head score (Gemma)0.091
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.100
Threshold uncertainty score0.530

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1000.091
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0040.019
Scholarly communication0.0110.011
Open science0.0020.009
Research integrity0.0060.003
Insufficient payload (model declined to judge)0.0070.000

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 head0.035
GPT teacher head0.305
Teacher spread0.269 · 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 designQualitative
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

Citations68
Published2013
Admission routes1
Has abstractyes

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