Downstream Human Rights Due Diligence: Informing Debate Through Insights from Business Practice
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 The United Nations Guiding Principles on Business and Human Rights conceive of human rights due diligence (HRDD) as covering potential impacts across value chains, including downstream. The proposed EU Corporate Sustainability Due Diligence Directive and the revision process of the OECD Guidelines for Multinational Enterprises have sparked renewed discussion on how and whether companies should conduct HRDD downstream to identify and prevent or mitigate adverse human rights impacts. Whilst some debate has occurred previously on downstream HRDD, this has predominantly centred on specific sectors, products and services where the links to egregious human rights harms may be more readily identifiable. This piece seeks to inform the current debate by broadening the examples of sectors, products and services and current business practice which demonstrate the critical need for, and ability of, companies to consider human rights risks downstream.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.000 |
| Scholarly communication | 0.003 | 0.008 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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