Who Made That?: Influencing Foreign Labour Practices through Reflexive Domestic Disclosure Regulation
Bibliographic record
Abstract
An important tool of "decentred" regulation, including reflexive law, is corporate information disclosure. Disclosure regulation can have an important normative influence on corporate behaviour because it introduces a risk element that must be managed by corporate leaders. The challenge for regulators is to identify the scope of disclosure that will cause corporate responses of the sort desired by the state. This article considers the potential role of disclosure regulation as a tool for influencing labour practices beyond the borders of the regulating state and, in particular, within the vast global supply chains of multinational corporations. In the context of improving labour practices in developing states, the goal of regulation must be foremost the empowerment of the workers and their organizations in those states, and of the indigenous and emerging global social movements that assist them. The article examines three recent proposals for mandatory disclosure of information about global labour practices, and concludes that the least ambitious of them (disclosure of factory addresses) may contribute to this goal more effectively than broader proposals that seek to inject raw information about actual labour practices into the consumer and investor markets of advanced economic states.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".