MétaCan
Menu
Back to cohort
Record W2769331242 · doi:10.1080/15265161.2017.1388449

Our Life Depends on This Drug: Competence, Inequity, and Voluntary Consent in Clinical Trials on Supervised Injectable Opioid Assisted Treatment

2017· article· en· W2769331242 on OpenAlexaff
Daniel Steel, Kirsten Marchand, Eugenia Oviedo‐Joekes

Bibliographic record

VenueThe American Journal of Bioethics · 2017
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBioethicsFraming (construction)Competence (human resources)Informed consentOpioidAddictionClinical trialMedicinePsychologyResearch ethicsPsychiatryPsychotherapistSocial psychologyAlternative medicinePolitical scienceLaw

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.043
metaresearch head score (Gemma)0.103
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.240
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0430.103
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.006
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.753
GPT teacher head0.639
Teacher spread0.114 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations19
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueThe American Journal of BioethicsSame topicEthics in Clinical ResearchFrench-language works237,207