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Record W209476255 · doi:10.18584/iipj.2015.6.1.7

Canadian Drug Policy and the Reproduction of Indigenous Inequities

2015· article· en· W209476255 on OpenAlexaffvenueabout
Shelley Marshall

Bibliographic record

VenueInternational Indigenous Policy Journal · 2015
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsIndigenousLegislationHarm reductionGovernment (linguistics)Context (archaeology)CriminalizationPublic policyCriminologyCriminal justicePolitical scienceHarmPublic administrationSociologyLawPublic healthGeography

Abstract

fetched live from OpenAlex

Canada’s federal drug policy under the Harper government (2006 to present) is “tough on crime” and dismissive of public health and harm reduction approaches to problematic drug use. Drawing on insights from discourse and critical race theories, and Bacchi’s (2009) poststructural policy analysis framework, problematic representations in Canada’s federal drug policy discourse are examined through proposed and passed legislation, government documents, and parliamentary speaker notes. These problem representations are situated within their social, historical, and colonial context to demonstrate how this policy is poised to intersect with persistent racial inequalities that position Indigenous peoples for involvement with illicit substances and markets, and racialized discourses and practices within law and law enforcement that perpetuate Indigenous over-representation in the criminal justice system.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.594
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.047
GPT teacher head0.364
Teacher spread0.317 · 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 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

Citations50
Published2015
Admission routes3
Has abstractyes

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