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Record W1914774401 · doi:10.22230/cjc.2010v35n2a2207

Methamphetamine Discourse: Media, Law, and Policy

2010· article· en· W1914774401 on OpenAlexaffvenueabout
Susan Boyd

Bibliographic record

VenueCanadian Journal of Communication · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicCrime, Deviance, and Social Control
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsNewspaperOrder (exchange)SociologyThe InternetPrint mediaMedia studiesNews mediaPolitical scienceAdvertisingLawBusiness

Abstract

fetched live from OpenAlex

This article examines the emergence of methamphetamine use and production as a social problem in Canada, particularly through media discourse. Rather than confine our discussion to print media, we also examine news photographs and headlines as cultural products. In addition, we briefly discuss several drug scares and media campaigns in Canada in the nineteenth century to contextualize the “crystal meth scare.” We discuss the tendency of contemporary newspaper articles, photographs and Internet sites about methamphetamine to reiterate conventional ideas about drugs and the people who use and produce them. Our analysis of print media and photos about methamphetamine centres on a special 2005 supplement to Vancouver newspaper The Province. Drawing from critical researchers whose analyses of media argue that news is a cultural product and that “law and order” is an important news category, we conclude with an examination of Canadian federal, provincial, and local responses to the crystal meth threat, which most often support law-and-order initiatives.

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)0.004
metaresearch head score (Gemma)0.012
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.937
Threshold uncertainty score0.718

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.008
Science and technology studies0.0360.034
Scholarly communication0.0230.007
Open science0.0020.005
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0080.000

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 head0.020
GPT teacher head0.343
Teacher spread0.323 · 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

Citations35
Published2010
Admission routes3
Has abstractyes

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