Framing Modern Slavery: Do Stakeholders Talk Past Each Other?
Bibliographic record
Abstract
ABSTRACT Modern slavery literature has thus far mostly adopted a downstream perspective, in the sense that researchers investigated corporate actors' responses after the enactment of transparency legislation. The common finding is that corporate disclosure is poor and ineffective, contributing to a failure to eradicate modern slavery. Our contribution is to adopt an upstream perspective in which we examine debates before regulation is crafted. We conceive of modern slavery as a public policy issue where multiple actors—NGOs, institutional investors, corporations and policymakers—hold various views about modern slavery and how to act upon it. Drawing on framing theory as used in public policy research, our aim is to uncover how stakeholders comparatively frame the issue of modern slavery, enabling a better understanding of why transparency legislation fails. Focussing on the Canadian context, where regulatory requirements on modern slavery were recently enacted, we examine an extensive set of communications, including testimony before parliamentary committees by four stakeholder groups. We explore stakeholders' rhetorical frames, uncovering how they conceive of modern slavery and their action frames, highlighting how they believe it should be acted upon. We show that stakeholders' rhetorical and action frames are embedded within overarching opposing metacultural frames, namely a community frame held by NGOs and a market frame held by institutional investors, corporations and policymakers. NGOs' community metacultural frame paves the way for approaches focused on eradication because harm to a community implies removing the harm. In opposition, other stakeholders' market metacultural frames pave the way for approaches focused on risk assessment, management and reporting, since the appearance of information on modern slavery and associated risks implies being able to manage it. Although stakeholders talk past each other about the issue of modern slavery, we identify possibilities for reframing, where holders of a market frame could move closer to a community frame.
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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 | 0.027 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.020 | 0.030 |
| Scholarly communication | 0.012 | 0.014 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".