Benchmarking global supply chains: the power of the ‘ethical audit’ regime
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.
Bibliographic record
Abstract
Abstract This article critically investigates the growing power and effectiveness of the ‘ethical’ compliance audit regime. Over the last decade, audits have evolved from a tool for companies to track internal organisational performance into a transnational governing mechanism to measure and strengthen corporate accountability globally and shape corporate responsibility norms. Drawing on original interviews, we assess the effectiveness of supply chain benchmarks and audits in promoting environmental and social improvements in global retail supply chains. Two principal arguments emerge from our analysis. First, that audits can be best understood as a productive form of power, which codifies and legitimates retail corporations’ poor social and environmental records, and shapes state approaches to supply chain governance. Second, that growing public and government trust in audit metrics ends up concealing real problems in global supply chains. Retailers are, in fact, auditing only small portions of supply chains, omitting the portions of supply chains where labour and environmental abuse are most likely to take place. Furthermore, the audit regime tends to address labour and environmental issues very unevenly, since ‘people’ are more difficult to classify and verify through numbers than capital and product quality.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it