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Record W7014404415

The Political Economy of the Overdose Crisis in Western Canada: An Exploratory Case Study

2022· dissertation· en· W7014404415 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2022
Typedissertation
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Exploratory researchPoliticsQualitative propertyQualitative researchCapitalismWork (physics)
DOInot available

Abstract

fetched live from OpenAlex

Background: Canada is in the throes of a drug/substance overdose crisis causing unprecedented numbers of overdose and death. Responses to the crisis have been largely reactive and/or medical in nature, highlighting the need for better understanding of its underlying structural determinants. The crisis has emerged in an era of neoliberal capitalism which has deepened health and social inequities and brought changes to the organization of work leading to increased precarity. Such broader economic influences have been identified as among important determinants of substance use and related harms in other contexts. Scant research evidence exists investigating structural determinants in the Western Canadian context and no studies have explored potential links among these confluent dynamics.\nMethodology: The study used a qualitative case study methodology to explore the contextual influences on the overdose crisis in Western Canada. A contextual synthesis and analysis combined different sources of data to better understand economic influences of the crisis in four sites of study (Saskatoon, SK; Fort McMurray, AB; Kelowna, BC; and Nanaimo, BC). The study drew on three sources of data: publicly available crisis-related data and reports from federal, provincial, and First Nations bodies, 45 interviews with 51 key informants from the sites, and publicly available economic data from Statistics Canada. Within-site and across-site analyses were completed to understand both local and broader economic influences of the crisis. Crystallization, a multidimensional enhancement of triangulation, and member checking were used to build trustworthiness of this research.\nFindings: Patterns of deaths in the overdose crisis in Western Canada reveal an inequitable distribution of harms where working-aged men, First Nations people, and those working in blue- collar and service industries are overrepresented in overdose deaths. Thematic analysis of key informant interviews in each site reveals socioeconomic pressures, the illicit drug trade and prescription opioids and pain management as economic influences on overdose deaths within and across sites. Increased precarity due to employment changes inherent to neoliberalization is explored as a potential link to increased substance use for particular populations, reflected in the patterns of death amid the overdose crisis. Observations on data sources and limitations for exploring contextual dynamics of the crisis are noted throughout.\nConclusion: The overdose crisis in Western Canada is evolving within neoliberal capitalist structures that may be creating risk of substance use and related harms for particular populations. Pathways between those structures and risk appear to be numerous, economically driven, and unevenly distributed among different groups. Data limitations and the nature of exploratory study restrict conclusions about the structural drivers of the crisis, yet certain trends are evident. This study provides emerging insight on the economic influences of crisis-related harms in a Western Canadian context, offering a theoretical framework and suggested hypotheses for ongoing inquiry and suggestive of upstream intervention.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.696

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.006
Science and technology studies0.0320.008
Scholarly communication0.0050.001
Open science0.0030.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.017
GPT teacher head0.238
Teacher spread0.221 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2022
Admission routes1
Has abstractyes

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