MétaCan
Menu
Back to cohort
Record W4399393256 · doi:10.3390/bs14060484

Navigating the Grey Zone: The Impact of Legislative Frameworks in North America and Europe on Adolescent Cannabis Use—A Systematic Review

2024· article· en· W4399393256 on OpenAlexaff
Barbara Jablonska, Lilian Negura

Bibliographic record

VenueBehavioral Sciences · 2024
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCannabisLegislatureLegalizationSocioeconomic statusContext (archaeology)LegislationGrey literatureDemographicsAffect (linguistics)Political scienceGeographyPsychologyEnvironmental healthMedicinePopulationDemographySociologyPsychiatryMEDLINELaw

Abstract

fetched live from OpenAlex

OBJECTIVES: This paper aims to systematically review the impact of legislative framework changes in North America and Europe on adolescent cannabis use. It not only seeks to examine the prevalence of adolescent marijuana use following legislative changes but also to identify the driving forces behind fluctuations in use and to address the gaps left by previous studies. METHODS: = 453 studies), 24 met the inclusion criteria. Articles were considered if they analyzed the impact of legislative changes on adolescent cannabis use in countries across North America and Europe. SYNTHESIS: The overall findings suggest an inconsistency regarding the prevalence of cannabis use among youth and adolescents following policy changes. The effects of modifications in cannabis policies on marijuana consumption are complex and influenced by various factors. These include the details of legislation, societal perspectives, enforcement methods, socioeconomic status, and cultural background. CONCLUSIONS: The results of this analysis reveal a nuanced reality. Although research suggests a rise in cannabis use after legalization, there are variations in the outcomes observed. This highlights the significance of considering context and demographics. Moreover, studies shed light on how specific policy changes, such as depenalization, can affect cannabis use.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.224
Threshold uncertainty score0.853

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.051
GPT teacher head0.408
Teacher spread0.357 · 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 designObservational
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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueBehavioral SciencesSame topicCannabis and Cannabinoid ResearchFrench-language works237,207