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Record W3187789141 · doi:10.1080/10826084.2021.1954022

Structural Conditions as Cause: Explaining the Rapid Rise in Youth E-Cigarette Use by Re-thinking Models of Addiction

2021· article· en· W3187789141 on OpenAlexafffund
Jason Hirsch, Robert Schwartz

Bibliographic record

VenueSubstance Use & Misuse · 2021
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsCentre for Addiction and Mental HealthPublic Health OntarioOntario Tobacco Research UnitUniversity of Toronto
FundersOntario Ministry of Health and Long-Term Care
KeywordsAddictionPhenomenonSurprisePsychologySocial phenomenonSocial psychologyField (mathematics)MultitudeCriminologyPsychiatrySociologyEpistemologySocial science

Abstract

fetched live from OpenAlex

Background: E-cigarette use has spread rapidly and widely among youth, to an extent that has surprised some researchers.Objectives: We suggest that this surprise is owing to a particular limitation in the dominant models of addiction – namely, a strong focus upon addictive substances as cause. We argue that the phenomenon at hand is easier to comprehend when less attention is placed upon preventing the use of specific substances and more upon what we identify as structural susceptibility to addiction instead.Results: Drawing upon neurobiology, history, public health theory, and social theory, we re-conceive addictive substances as mechanisms of escape from social structures that predispose whole societies to addiction.Conclusions/Importance: We argue that the surge in youth e-cigarette use in particular, as well as the phenomenon of addiction in general, are easier to comprehend if models of addiction are expanded to conceptualize the problem in its wider dimensions. We invite addictions researchers to join us in expanding the field’s analytical view.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.109
Threshold uncertainty score0.633

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 communication0.0000.001
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 head0.072
GPT teacher head0.307
Teacher spread0.235 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

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