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Record W4242738766 · doi:10.3138/uhr.42.01.02

Constructing an Urban Drug Ecology in 1970s Canada

2013· article· en· W4242738766 on OpenAlexvenueaboutno aff
Greg Marquis

Bibliographic record

VenueUrban History Review · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsCommissionEthnographyParticipant observationCannabisCriminologySociologySubstance abuseAddictionMedical anthropologySocial sciencePolitical sciencePsychologyAnthropologyPsychiatryLaw

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of Inquiry into the Non-Medical Use of Drugs (the LeDain Commission), was part of the commission’s extensive series of unpublished studies.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 This article examines the unpublished studies as examples of social science “intelligence gathering” on urban social problems.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 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)0.001
metaresearch head score (Gemma)0.001
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 score0.092
Threshold uncertainty score0.666

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.007
Science and technology studies0.0090.009
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.019
GPT teacher head0.260
Teacher spread0.241 · 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

Citations4
Published2013
Admission routes2
Has abstractyes

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