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Record W2792891421 · doi:10.1093/phe/phy001

Overdose Education and Naloxone Distribution Programmes and the Ethics of Task Shifting

2018· article· en· W2792891421 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePublic Health Ethics · 2018
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsLunenfeld-Tanenbaum Research InstituteSchwartz/Reisman Emergency Medicine InstituteUniversity of TorontoUniversity Health Network
FundersDepartment of Family and Community Medicine, University of TorontoSchwartz/Reisman Emergency Medicine Institute
KeywordsHarm reductionRedressHealth care(+)-NaloxoneContext (archaeology)HarmMainstreamMedicinePublic relationsPublic healthNursingPsychologyPolitical scienceOpioidSocial psychologyLaw

Abstract

fetched live from OpenAlex

Abstract North America is in the grips of an epidemic of opioid-related poisonings. Overdose education and naloxone distribution (OEND) programmes emerged as an option for structurally vulnerable populations who could not or would not access mainstream emergency medical services in the event of an overdose. These task shifting programmes utilize lay persons to deliver opioid resuscitation in the context of longstanding stigmatization and marginalization from mainstream healthcare services. OEND programmes exist at the intersection of harm reduction and emergency services. One goal of OEND programmes is to help redress the health-related inequities common among people who use drugs, which include minimizing the gap between people who use drugs and the formal healthcare system. However, if this goal is not achieved these inequities may be entrenched. In this article, we consider the ethical promises and perils associated with OEND as task shifting. We argue that public health practitioners must consider the ethical aspects of task shifting programmes that may inadvertently harm already structurally vulnerable populations. We believe that even if OEND programmes reduce opioid-related deaths, we nevertheless question if, by virtue of its existence, OEND programmes might also unintentionally disenfranchise structurally vulnerable populations from comprehensive healthcare services, including mainstream emergency care.

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)0.005
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.805
Threshold uncertainty score0.645

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.078
GPT teacher head0.411
Teacher spread0.333 · 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