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Record W3035328964 · doi:10.13162/hro-ors.v8i2.4186

Fighting Fatality: Insight into British Columbia’s Sanctioning of Overdose Prevention Sites

2020· article· en· W3035328964 on OpenAlexaffvenueabout
Nicole Davidson

Bibliographic record

VenueHealth Reform Observer - Observatoire des Réformes de Santé · 2020
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsCriminologyCase fatality ratePolitical scienceEnvironmental healthMedicineSociology

Abstract

fetched live from OpenAlex

Due to the alarming rate of illicit drug toxicity deaths in British Columbia, a public health emergency was declared by Provincial Health Officer Dr. Perry Kendall on 14 April 2016. In response to the unsanctioned supervised consumption sites opened by concerned community members, and following the advice of Dr. Perry Kendall, Health Minister Terry Lake enacted a Ministerial Order in December 2016 to rapidly sanction overdose prevention sites. The Ministerial Order allowed regional health authorities the opportunity to provide overdose prevention services as necessary on an emergency basis for the duration of the public health emergency. The emergency sanctioning of overdose prevention sites enabled the BC government to take swift action to address the crisis while completing the lengthy and onerous application process for more permanent supervised consumption sites. The Ministerial Order allowed overdose prevention sites to operate without a strategic plan and prior community consultation. In May 2017, Parliament adopted Bill C-37, accepting a more streamlined application process for supervised consumption sites. Overdose prevention sites are an integral part of a multi-faceted solution to the opioid crisis, however, evaluation of the cost benefits and data reflecting the impact on first responders is wanting.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.049
GPT teacher head0.316
Teacher spread0.267 · 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 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

Citations1
Published2020
Admission routes3
Has abstractyes

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