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Record W4315574153 · doi:10.21638/spbu14.2022.312

Legalization of marijuana use in comparative criminal legislation

2022· article· en· W4315574153 on OpenAlexaboutno aff
Vukan Slavković

Bibliographic record

VenueVestnik of Saint Petersburg University Law · 2022
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsnot available
Fundersnot available
KeywordsLegislationLegalizationCannabisCriminal codeLawConventionPolitical scienceNarcotic drugsNarcoticCriminal lawCriminologyMedicinePsychologyPsychiatry

Abstract

fetched live from OpenAlex

In light of the rapidly shifting legislation regarding the legalization of marijuana use, the popular notion seems to be that marijuana is a harmless pleasure, access to which should not be regulated or considered illegal. World Health Organization recommended to delete cannabis and cannabis resin from Schedule IV of the UN Single Convention on Narcotic Drugs (1961), but to maintain it in Schedule I of the 1961 Convention. The UN Commission on Narcotic Drugs decided by 27 votes to 25 and with one abstention to follow this recommendation. Тhere is the issue of how much this decision will affect the legalization of marijuana in the world. In the paper are analyzed two legislation of the Anglo-Saxon legal system, which supported this initiative (Canada and USA) and legislation of Euro-Continental legal area (Russia) that did not accept the reclassifying of cannabis from the 1961 Convention. Author has compared the Canadian code with Uruguayan, and the U. S. bill with the Mexican legislation, because Mexican bill does not provide the full legalization of marijuana use. In the Russian Federation, all deeds related to narcotic drugs, which were committed on a significant, large, and an especially large scale, and also all acts coherent to traffic of narcotic drugs, regardless of its scale, are regulated by Criminal Code of the Russian Federation. Otherwise, there will be applied an administrative law.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.729
Threshold uncertainty score0.799

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 head0.083
GPT teacher head0.302
Teacher spread0.220 · 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 designTheoretical or conceptual
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

Citations0
Published2022
Admission routes1
Has abstractyes

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