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Record W2915898433 · doi:10.1136/medethics-2018-105099

‘I just need an opiate refill to get me through the weekend’

2019· article· en· W2915898433 on OpenAlexaboutno aff
Eric G. Yan, Dennis John Kuo

Bibliographic record

VenueJournal of Medical Ethics · 2019
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsBeneficenceAutonomyMedical prescriptionDutyFiduciaryMedicineMedical ethicsOpioidOpioid epidemicPsychiatryPolitical scienceNursingLaw

Abstract

fetched live from OpenAlex

In this article, we discuss the ethical dimensions for the prescribing behaviours of opioids for a chronic pain patient, a scenario commonly witnessed by many physicians. The opioid epidemic in the USA and Canada is well known, existing since the late 1990s, and individuals are suffering and dying as a result of the easy availability of prescription opioids. More recently, this problem has been seen outside of North America affecting individuals at similar rates in Australia and Europe. We argue that physicians are also confronted with an ethical crisis where a capitalist-consumerist society is contributing to this opioid crisis in which societal, legal and business interests push physicians to overprescribe opioids. Individual physicians often find themselves unequipped and unsupported in attempts to curb the prescribing of opioid medications and balance competing goals of alleviating pain against the judicious use of pain medications. Physicians, individually and as a community, must reclaim the ethical mantle of our profession, through a more nuanced understanding of autonomy and beneficence. Furthermore, physicians and the medical community at large have a fiduciary duty to patients and society to play a more active role in curbing the widespread distribution of opioids in our communities.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.651
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0010.000

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 head0.064
GPT teacher head0.401
Teacher spread0.337 · 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; a candidate call from one teacher head, not a consensus.

Study designNot applicable
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

Citations7
Published2019
Admission routes1
Has abstractyes

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