Drug Use in Cultural Contexts 'Beyond the West': Tradition, Change and Post-colonialism
Bibliographic record
Abstract
Considerable research, policy and media attention has focused recently on drug use in Britain, wider Europe, the US and other advanced "western" societies such as Australia and Canada. However, the place of drugs in other cultural contexts has received far less attention. Little is known about the use of drugs in non-western societies and this lack of comparative knowledge hinders a broader understanding of drug use, the way problems are attached to it and the nature of inappropriately applied social and regulatory policies. This book examines drug use (including alcohol) in different cultural contexts, showing how the claim of tradition can persist even while the impetus toward change is pervasive. In some cases, change is strongly resisted; in others its effects are profound and potentially highly destructive. In a world of globalization, western investment and leisure tourism can combine with the profiteering of international drug trafficking to transform traditional patterns of intoxicant use; in a world of post-colonialism, the legacies of past impositions are still causing tragedies; and in a world of western-led drug control policies, unproblematic cultural incorporation of drug use into everyday life and sacred ritual is threatened by remote and ill-informed politicians and bureaucracies. This book will be of interest to academics, students and receptive policy audiences interested in understanding drugs and the issues raised by their use in unfamiliar contexts.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.025 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".