TOWARDS A SOCIOLOGY OF HARM REDUCTION: A COMPARATIVE STUDY OF DRUG POLICY CHANGE IN CANADA AND THE UNITED KINGDOM BETWEEN THE YEARS 1900 AND 2017
Bibliographic record
Abstract
The primary goal of this dissertation is to advance a sociological understanding of harm reduction policy development and change. Drawing on social constructionism, as well as comparative and historical methodologies, this dissertation accomplishes the abovementioned goal by comparing and contrasting the development of harm reduction policies for intravenous drug use (IDU) in Canada and the United Kingdom (UK).This dissertation addresses a gap in the drug policy scholarship: namely a lack of sociological research using comparative methods to explain similarities and differences in the development of harm reduction policy across geographical locations and over time. While there exists a large, multi-disciplinary literature that explores the development of specific harm reduction programs such as needle exchanges and drug consumption rooms, to my understanding this is the first large-scale study to approach the topic from a sociological perspective. To accomplish the goals set out in this paper, I analyse content drawn from 60 federal Hansard documents, 47 municipal council documents (Vancouver City Council minutes), 32 committee reports and 2,609 newspaper and online news articles from Canada (N=1,866) and England and Wales (N=7443) that were published between 1997 and 2017.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.011 | 0.025 |
| Science and technology studies | 0.026 | 0.020 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".