Our Life Depends on This Drug: Competence, Inequity, and Voluntary Consent in Clinical Trials on Supervised Injectable Opioid Assisted Treatment
Bibliographic record
Abstract
Supervised injectable opioid assisted treament (siOAT) prescribes injectable opioids to individuals for whom other forms of addiction treatment have been ineffective. In this article, we examine arguments that opioid-dependent people should be assumed incompetent to voluntarily consent to clinical research on siOAT unless proven otherwise. We agree that concerns about competence and voluntary consent deserve careful attention in this context. But we oppose framing the issue solely as a matter of the competence of opioid-dependent people and emphasize that it should be considered in the context of inequities in access to siOAT as a medical treatment. Consequently, we suggest that bioethics literature on nonexploitation, which focuses on clinical research in low-income countries, is helpful due to locating ethical issues within systemic social conditions. Finally, we consider the implications of our argument for the ethics of clinical research on siOAT.
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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 | 0.556 | 0.673 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.056 |
| Scholarly communication | 0.012 | 0.019 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.013 | 0.016 |
| 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".