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MAKING SPACE FOR CANNABIS POLICY EXPERIMENTS

2011· article· en· W1934743125 on OpenAlexaffabout
Wayne Hall, Benedikt Fischer, Simon Lenton, Peter Reuter, Robin Room

Bibliographic record

VenueAddiction · 2011
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsStalemateCannabisPolitical scienceEnforcementIllicit drugDrug controlLegislatureCriminologyLawPsychologyPsychiatryPoliticsDrug

Abstract

fetched live from OpenAlex

We thank Mark Kleiman for his considered and critical analysis of our book [1]. In the space of a brief reply we can address only some of the many interesting issues that he raised. We acknowledge that our book has not broken the cannabis policy stalemate. Our subtitle was, after all, moving beyond stalemate. Our aims were more realistic. We wanted to describe the important ways in which cannabis differs from other illicit drugs, namely: the greater extent of its global use, the modest adverse impacts it has on mortality and morbidity compared to the opioids and cocaine; and the selective and commonly discriminatory enforcement of criminal penalties against its use, even in countries such as the United States that are nominally tough on cannabis. We also wanted to summarize the international evidence on the mixed impacts of the limited policy reform options that are available to nation states under existing international drug control treaties. Secondly, we wanted to make the case for modifying the way that international control treaties govern cannabis to permit nation states to conduct and evaluate cannabis policy experiments that extend beyond minor variations in the severity of penalties for cannabis use. As Kleiman notes, such policy experiments could possibly include the regulation of a commercial cannabis market along the lines of current regulatory regimes for alcohol. We include this as one among a series of options without privileging it over the others. In choosing between these regimes, states will need to take into consideration many of the issues that Kleiman raised, namely, the potential irreversibility of such a policy; the likelihood that legal markets, lower price, implicit social approval and commercial promotion of the product could increase heavy cannabis use and cannabis-related harm; and uncertainty about the impact that increased cannabis use would have on alcohol-related harm. However, these states should not only look at the consequences of changing policy: they also need to examine the extensive adverse effects of current cannabis control regimes. We agree that there are policy options other than a legal cannabis market that deserve consideration as policy experiments. These include: the Spanish growers’ clubs; the Californian quasi-medical marijuana prescription regime; and state monopolies modelled on those adopted for alcohol in Scandinavia, Canada and many US states in the first part of the last century. All these are potentially interesting policy frameworks for cannabis, but there is necessarily very limited evidence on their impact because all are proscribed under current international treaties. Adequate evaluations will require serious trials and rigorous evaluations of these policy regimes. Our aim was to encourage the type of policy experiments and evaluations needed to better inform the development of cannabis policy. To that end we suggested how the international treaties could be liberalized to allow such experiments while allowing states to operate under the current treaty, if that is what they prefer. In our view, cannabis control systems that operate under the constraints of the current international regime fail to deliver good public policy and have an unfavourable balance of policy benefits and harms. There is a danger that the high standards that Mark Kleiman demands for evidence of the effectiveness of alternative cannabis policies will prevent the policy experimentation we advocate and so, by default, perpetuate the policy stalemate that we hoped to show a way beyond. None.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.287
Threshold uncertainty score0.505

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.075
GPT teacher head0.374
Teacher spread0.300 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2011
Admission routes2
Has abstractyes

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