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Record W4200462936 · doi:10.1186/s13033-021-00512-9

Shifting North American drug markets and challenges for the system of care

2021· article· en· W4200462936 on OpenAlexafffund
Michael Krausz, Jean N. Westenberg, Nickie Mathew, G. Thomas Budd, James S.H. Wong, Vivian W. L. Tsang, Marc Vogel, Conor King, Vijay Seethapathy, Kerry L. Jang, Fiona Choi

Bibliographic record

VenueInternational Journal of Mental Health Systems · 2021
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsVancouver General HospitalProvincial Health Services AuthorityUniversity of British Columbia HospitalBC Mental Health & Substance Use ServicesUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsRevenueHealth careCorporate governancePublic healthHealth administrationBusinessCompetition (biology)LegislationDrugHealth economicsPublic economicsMedicineEconomicsEconomic growthPsychiatryPolitical scienceFinanceNursing

Abstract

fetched live from OpenAlex

Drug markets are dynamic systems which change based on demand, competition, legislation and revenue. Shifts that are not met with immediate and appropriate responses from the healthcare system can lead to public health crises with tragic levels of morbidity and mortality, as experienced Europe in the early 1990s and as is the case in North America currently. The major feature of the current drug market shift in North America is towards highly potent synthetic opioids such as fentanyl and fentanyl analogues. An additional spike in stimulant use further complicates this issue. Without understanding the ever-changing dynamics of drug markets and consequent patterns of drug use, the healthcare system will continue to be ineffective in its response, and morbidity and mortality will continue to increase. Economic perspectives are largely neglected in research and clinical contexts, but better treatment alternatives need to consider the large-scale macroeconomic conditions of drug markets as well as the behavioural economics of individual substance use. It is important for policy makers, health authorities, first responders and medical providers to be aware of the clinical implications of drug market changes in order to best serve people who use drugs. Only with significant clinical research, a comprehensive reorganization of the system of care across all sectors, and an evidence-driven governance, will we be successful in addressing the challenges brought on by the recent shifts in drug markets.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.386
Threshold uncertainty score0.240

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 head0.022
GPT teacher head0.329
Teacher spread0.306 · 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 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

Citations37
Published2021
Admission routes2
Has abstractyes

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