The Real Dope: Social, Legal, and Historical Perspectives on the Regulation of Drugs in Canada, edited by Edgar-Andre? Montigny (Toronto:University of Toronto Press, 2011)
Bibliographic record
Abstract
In The Real Dope: Social, Legal, and Historical Perspectives on the Regulation of Drugs in Canada, Edgar-Andre? Montigny brings together a broad range of recent writing on a wide variety of drugs. The collection is well worth reading for the insights it provides into Canada’s socio-legal historical experience of the regulation of different psychoactive substances and for its documentation of the wealth of expertise coalescing in this area of research. This subject matter has inspired much critical analysis and scholarly debate about the role of academics in informing policy discussions about drug use and support for liberal drug policy reform. The present contribution is unique in its broad coverage of different “types” of drugs in different eras, and in its accessible, coherent presentation of historical material. Each chapter stands both alone and as an asset to its larger contemporary relevance, as interpreted by authors drawn from a variety of disciplinary backgrounds.
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 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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.015 |
| Science and technology studies | 0.017 | 0.027 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".