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Record W3081368856 · doi:10.1097/cxa.0000000000000088

Reflections on the Impending Lawsuits by Governments Against Pharmaceutical Opioid Producers in Canada

2020· article· en· W3081368856 on OpenAlexaffvenueabout
Benedikt Fischer, Rebecca Haines‐Saah

Bibliographic record

VenueThe Canadian Journal of Addiction · 2020
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsUniversity of TorontoUniversity of CalgarySimon Fraser University
Fundersnot available
KeywordsPolitical scienceOpioidPublicsHumanitiesLiabilityWelfare economicsMedicineEconomicsPhilosophyLaw

Abstract

fetched live from OpenAlex

ABSTRACT Canada has experienced an unprecedented opioid-related public health crisis. Several Canadian (provincial) governments are preparing lawsuits against pharmaceutical opioid manufacturers towards liability and reparations for the extensive costs of opioid-related harms. We briefly examine these efforts on ethical, practical and commonsensical grounds. Specifically, the opioid drugs fuelling the crisis were actively approved by public regulators, and governments for long neglected explicit warnings about and failed to implement crucial interventions towards the emerging opioid crisis when needed. The opioid crisis arose out of interactive dynamics (of actions and non-actions) by multiple protagonists neither accounted for nor corrected by one-sided responsibility assignments. Le Canada a connu une crise sans précédent au niveau de la santé publique liée aux opioïdes. Plusieurs gouvernements canadiens (provinciaux) préparent des poursuites contre les fabricants d’opioïdes pharmaceutiques pour responsabilité civile et réparation en raison des coÛts élevés des méfaits liés aux opioïdes. Nous avons examiné ces efforts aux niveaux éthique, pratique et logique. Plus précisément, les médicaments opioïdes qui alimentent la crise ont été activement approuvés par les régulateurs publics, et les gouvernements ont longtemps négligés les avertissements explicites. De plus, ils n’ont pas réussi à mettre en œuvre des interventions cruciales contre la crise des opioïdes émergente en cas de besoin. La crise des opioïdes est née de la dynamique interactive (des actions et des non-actions) de multiples protagonistes. Elle n’a été ni expliquée ni corrigée par des attributions de blâmes unilatérales.

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)0.000
metaresearch head score (Gemma)0.000
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.342
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.039
GPT teacher head0.300
Teacher spread0.261 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2020
Admission routes3
Has abstractyes

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