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Record W2067398477 · doi:10.7202/1022057ar

Constructing an Urban Drug Ecology in 1970s Canada

2014· article· en· W2067398477 on OpenAlexvenueaboutno aff
Greg Marquis

Bibliographic record

VenueUrban History Review · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsCommissionEthnographyParticipant observationCannabisSociologyCriminologySubstance abuseAddictionMedical anthropologySocial sciencePolitical scienceMedicinePsychiatryAnthropologyLaw

Abstract

fetched live from OpenAlex

In 1970, youthful researchers carried out participant-observer studies of the drug scene in Vancouver, Winnipeg, Toronto, Montreal, and Halifax. This ethnographic research, prepared for the federal Commission of Inquiry into the Non-Medical Use of Drugs (the LeDain Commission), was part of the commission’s extensive series of unpublished studies. The commission, which released an initial report in 1970, one on cannabis in 1972 and a final report in 1973, adopted a broad approach to the issue of drugs and society. This article examines the unpublished studies as examples of social science “intelligence gathering” on urban social problems. The reports discussed the local market in illegal drugs, its geographic patterns and organizational features, the demographic characteristics of drug sellers and consumers, the culture of the drug scene, and the attitudes of users. Unlike earlier sociological and anthropological studies that focused on prisoners and lower-class “junkies” or more recent studies that examine marginalized inner-city populations, the city studies reflected the era’s fixation on middle-class youth culture and the addiction-treatment sphere’s growing concern with amphetamine abuse.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.693
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.263
Teacher spread0.246 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2014
Admission routes2
Has abstractyes

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