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Arabian nights in Hong Kong: Chinese young adults’ experience of waterpipe smoking

2020· article· en· W3072825661 on OpenAlexaff
Jung Jae Lee, Karly Cheuk Yin Yeung, Man Ping Wang, Sally Thorne

Bibliographic record

VenueTobacco Control · 2020
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPleasureYoung adultPerceptionPsychologyMedicineEnvironmental healthDemographyGerontologySociology

Abstract

fetched live from OpenAlex

BACKGROUND: Waterpipe smoking (WPS) has increased among young adults who may be oblivious to its harmful effects. We explored Chinese young adults' experiences of using waterpipes. METHODS: Semi-structured interviews with 49 Chinese young adults aged between 18 to 30 years who had smoked waterpipes in the past 30 days were undertaken between May and October 2019. We analysed transcripts using interpretive description that includes an inductive analytical approach and constant comparison strategy. RESULTS: Six themes on the WPS experience emerged: fostering social connections on weekend nights; bars as a natural setting for waterpipe smoking; providing pleasure; securing social status among young females; growing acceptance and a lack of education; lack of regulation on waterpipe smoking. CONCLUSIONS: We provide the first evidence regarding Chinese young adults' WPS use. Policy measures to de-normalise false perceptions of WPS are urgently needed to deter use among young adults.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.236
Threshold uncertainty score0.470

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.015
GPT teacher head0.267
Teacher spread0.252 · 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

Citations7
Published2020
Admission routes1
Has abstractyes

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