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Record W2010452120 · doi:10.1177/1747016112461731

Good intentions and dangerous assumptions: Research ethics committees and illicit drug use research

2012· article· en· W2010452120 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueResearch Ethics · 2012
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsResearch ethicsIncentivePublic relationsInformed consentIllicit drugPopulationPsychologyPolitical scienceEngineering ethicsCriminologyDrugMedicineAlternative medicinePsychiatryEnvironmental healthEngineering

Abstract

fetched live from OpenAlex

Illicit drug users are frequently identified as a ‘vulnerable population’ requiring ‘special protection’ and ‘additional safeguards’ in research. However, without specific guidance on how to enact these special protections and safeguards, research ethics committee (REC) members sometimes fall back on untested assumptions about the ethics of illicit drug use research. In light of growing calls for ‘evidence-based research ethics’, this commentary examines three common assumptions amongst REC members about what constitutes ethical research with drug users, and whether such assumptions are borne out by a growing body of empirical data. The assumptions that form the focus of this commentary are as follows: (i) drug users do not have the capacity to provide informed consent to research; (ii) it is ethically problematic to provide financial incentives to drug users to participate in research; and (iii) asking drug users about their experiences ‘re-traumatizes’ and ‘re-victimizes’ them.

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 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)0.388
metaresearch head score (Gemma)0.601
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesMetaresearch, Science and technology studies, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.652
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.3880.601
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0050.016
Scholarly communication0.0010.001
Open science0.0010.005
Research integrity0.0040.126
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.944
GPT teacher head0.736
Teacher spread0.208 · 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