The Quest to End Modern Slavery: Metaphors in corporate modern slavery statements
Bibliographic record
Abstract
This paper focuses on the modern slavery statements of three major UK high street retailers who are known for their relatively pro-active approach to the debate on corporate responsibility for ethical trading. Drawing on our earlier research in relation to metaphors in British newspaper reporting of modern slavery and human trafficking since 2000, we explore the metaphors that recur across the statements these companies have published in 2016, 2017 and 2018. These statements were published in accordance with the UK Modern Slavery Act 2015, which requires all commercial organisations operating in the UK, with a turnover greater than GBP 36 million, to publish an annual statement outlining the work done to assess and address (the risk of) modern slavery in their supply chains. We find that the metaphors used in these statements generally fail to acknowledge the agency of those workers affected by modern slavery and labour exploitation in a broader sense, the potential complicity of the retailers in sustaining an exploitative industry, and the underlying socio-economic factors that leave workers vulnerable to exploitation. We conclude that more needs to be done to account for the causes of modern slavery so that retailers can prevent rather than react to it.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.004 | 0.027 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".