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Record W2123697427 · doi:10.2105/ajph.2012.300992

From Promotion to Cessation: Masculinity, Race, and Style in the Consumption of Cigarettes, 1962–1972

2013· article· en· W2123697427 on OpenAlexafffund
Cameron White, John L. Oliffe, Joan L. Bottorff

Bibliographic record

VenueAmerican Journal of Public Health · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsBC Centre for Disease Control
FundersCanadian Institutes of Health ResearchHealth CanadaInstitute of Gender and HealthMichael Smith Health Research BC
KeywordsMasculinityConsumption (sociology)Race (biology)Style (visual arts)Promotion (chess)Psychological interventionPsychologyHealth promotionSurvey data collectionSocial psychologyAdvertisingMedicineSociologyPublic healthGender studiesPolitical scienceGeographySocial sciencePolitics

Abstract

fetched live from OpenAlex

In the United States, analysis of survey data provided by projects such as the National Health Interview Survey and the Youth Tobacco Survey has revealed the extent to which cigarette consumption patterns are influenced by gender and race. Taking our lead from a broader field of research that analyzed the sociological characteristics of cigarette consumption, we analyzed these intersections between race and gender through a study of masculinity and style in Marlboro and Kool cigarette advertisements during the 1960s and 1970s. We focused on this period because it was then that the racial bifurcation of cigarette consumption practices first became apparent. We suggest that style provides both a theoretical framework and methodology for understanding how and why White American and African American male consumers learned to consume in different ways. We also argue that the analysis of tobacco consumption in terms of masculinity and style provides a useful method for approaching the design of antismoking interventions.

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)0.002
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.489
GPT teacher head0.585
Teacher spread0.096 · 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

Citations11
Published2013
Admission routes2
Has abstractyes

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