How ideology shapes the evidence and the policy: what do we know about cannabis use and what should we do?
Bibliographic record
Abstract
In the United Kingdom, as in many places, cannabis use is considered substantially within a criminal justice rather than a public health paradigm with prevention policy embodied in the Misuse of Drugs Act. In 2002 the maximum custodial sentence tariff for cannabis possession under the Act was reduced from 5 to 2 years. Vigorous and vociferous public debate followed this decision, centred principally on the question of whether cannabis use caused schizophrenia. It was suggested that new and compelling evidence supporting this hypothesis had emerged since the re-classification decision was made, meaning that the decision should be reconsidered. The re-classification decision was reversed in 2008. We consider whether the strength of evidence on the psychological harms of cannabis has changed substantially and discuss the factors that may have influenced recent public discourse and policy decisions. We also consider evidence for other harms of cannabis use and public health implications of preventing cannabis use. We conclude that the strongest evidence of a possible causal relation between cannabis use and schizophrenia emerged more than 20 years ago and that the strength of more recent evidence may have been overstated--for a number of possible reasons. We also conclude that cannabis use is almost certainly harmful, mainly because of its intimate relation to tobacco use. The most rational policy on cannabis from a public health perspective would seem to be one able to achieve the benefit of reduced use in the population while minimizing social and other costs of the policy itself. Prohibition, whatever the sentence tariff associated with it, seems unlikely to fulfil these criteria.
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 | 0.195 | 0.364 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.009 | 0.073 |
| Scholarly communication | 0.038 | 0.057 |
| Open science | 0.007 | 0.013 |
| Research integrity | 0.031 | 0.035 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".