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Record W2012367085 · doi:10.3389/fpsyt.2013.00160

Identity Formation, Marijuana and “The Self”: A Study of Cannabis Normalization among University Students

2013· article· en· W2012367085 on OpenAlexafffundabout
Amir Mostaghim, Andrew Hathaway

Bibliographic record

VenueFrontiers in Psychiatry · 2013
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of Guelph
FundersUniversity of Guelph
KeywordsCannabisNormalization (sociology)PsychologyIdentity (music)Clinical psychologyPsychiatrySociologyArtAnthropology

Abstract

fetched live from OpenAlex

Over the past half-century, as use of marijuana has become more widespread in Canadian society, there are indications of a normalizing process in societal reactions and experiences of use. Among other research avenues, these trends suggest a need for further exploration of young people's understandings of how they make the choice to use or not and how decisions relate to presentation of the self. This study draws on interviews with 30 undergraduates recruited from a larger online survey of respondents at the University of Guelph, ON, Canada. In probing their perceptions of the use of marijuana, we often found that trying/using "pot" was the default option, whereas choosing not to use required more conscious effort. With specific reference to Goffman's contribution to a situated understanding of the self, our findings are interpreted with emphasis on further theoretical development of the normalization thesis and on the role of marijuana in identity formation among persons in the process of transition to adulthood.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0170.011
Scholarly communication0.0060.004
Open science0.0020.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.312
Teacher spread0.304 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations37
Published2013
Admission routes3
Has abstractyes

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