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Features of the waterpipe tobacco industry: A qualitative study of the third International Hookah Fair

2018· preprint· en· W2788591835 on OpenAlexaff
Neil Singh, Mohammed Jawad, Andrea Darzi, Tamara Lotfi, Rima Nakkash, Benjamin Hawkins, Elie A. Akl

Bibliographic record

VenueF1000Research · 2018
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsMcMaster University
FundersNational Institutes of HealthNational Cancer InstituteNational Institute for Health and Care Research
KeywordsLegislatureTobacco industryPsychological interventionBusinessGlobalizationPublic policyMarketingPolitical scienceMedicineLaw

Abstract

fetched live from OpenAlex

Background: Little research has been done to uncover the features of the waterpipe tobacco industry, which makes designing effective interventions and policies to counter this growing trend challenging. The objective of this study is to describe the features of the waterpipe industry. Methods: In 2015, we randomly sampled and conducted semi-structured interviews with 20 representatives of waterpipe companies participating in a trade exhibition in Germany. We used an inductive approach to identify emerging themes. Results: We interviewed representatives and four themes emerged: industry globalisation, cross-industry overlap, customer-product relationship, and attitude towards policy. The industry was described as transnational, generally decentralized, non-cartelized, with ad hoc relationships between suppliers, distributors and retailers. Ties with the cigarette industry were apparent. The waterpipe industry appeared to be in an early growth phase, encroaching on new markets, and comprising of mainly small family-run businesses. Customer loyalty appears stronger towards the waterpipe apparatus than tobacco. There was a notable absence of trade unionism and evidence of deliberate breaches of tobacco control laws. Conclusion: The waterpipe industry appears fragmented but is slowly growing into a mature, globalized, and customer-focused industry with ties to the cigarette industry. Now is an ideal window of opportunity to strengthen public health policy towards the waterpipe industry, which should include a specific legislative waterpipe framework.

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)0.009
metaresearch head score (Gemma)0.011
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 score0.075
Threshold uncertainty score0.149

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0160.013
Scholarly communication0.0050.005
Open science0.0020.007
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0070.001

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 head0.105
GPT teacher head0.434
Teacher spread0.329 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

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