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Record W2077726819 · doi:10.5993/ajhb.29.2.1

Smoking Decisions from a Teen Perspective: A Narrative Study

2005· article· en· W2077726819 on OpenAlexaff
Lynne Baillie, Chris Y. Lovato, Joy L. Johnson, Cecilia Kalaw

Bibliographic record

VenueAmerican Journal of Health Behavior · 2005
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsBC Cancer Agency
FundersNational Cancer Institute
KeywordsPerspective (graphical)NarrativePsychologyAddictionNarrative inquirySocial psychologyDevelopmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: To explore the transitional phase between experimental and regular smoking from the perspective of teens. METHOD: Narrative analysis of semistructured, individual interviews. RESULTS: The need to belong and immediate social gain are major themes influencing teen smoking decisions. CONCLUSIONS: Our findings have significance for public health workers planning and implementing tobacco-use prevention programs aimed at teens whose smoking behaviors are not yet determined by nicotine addiction. How such programs have been traditionally framed and the ways in which peer influence and risk behaviors have been addressed may be largely irrelevant to the rationale of the adolescents themselves.

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)0.003
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 score0.003
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0030.003
Open science0.0000.002
Research integrity0.0010.002
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 head0.051
GPT teacher head0.418
Teacher spread0.367 · 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

Citations39
Published2005
Admission routes1
Has abstractyes

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