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
This article examines the role of industry in implementing and interpreting the international legal norm of human rights due diligence. Our study focuses on a multi-industry association called the Responsible Minerals Initiative (RMI), which has assumed a leading role in implementing conflict minerals legislation and interpreting the norm of human rights due diligence in mineral supply chains. Drawing on interviews with RMI staff, corporate representatives, and independent members of the RMI’s governance committees, we analyze the RMI’s risk assessment tools that facilitate corporate compliance with global mineral supply chain regulations. We demonstrate that these technocratic tools mask the underlying corporate interests that control how human rights due diligence is being interpreted and implemented on the ground. We then argue that global supply chains are being “governed at a distance” through these technical practices whereby companies divest themselves of responsibility to their suppliers. Supply chain governance at a distance is therefore transforming the norm of human rights due diligence from an instrument of corporate accountability to a tool of corporate legitimacy.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it