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Smoking in Movies, Implicit Associations of Smoking With the Self, and Intentions to Smoke

2007· article· en· W1991820896 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePsychological Science · 2007
Typearticle
Languageen
FieldArts and Humanities
TopicMedia Influence and Health
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPsychologySmokeNarrativeImplicit attitudeDevelopmental psychologyQuit smokingTask (project management)Social psychologyClinical psychologySmoking cessationMedicine

Abstract

fetched live from OpenAlex

We examined whether identifying with a film character who smokes increases implicit associations of the self with smoking. Undergraduate men were randomly assigned to view film clips in which the male protagonist either smoked or did not smoke. We measured subsequent levels of self-smoking associations using a reaction time task, as well as self-reported beliefs about smoking and smokers. Greater identification with the smoking protagonist predicted stronger implicit associations between the self and smoking (for both smokers and nonsmokers) and increased intention to smoke (among the smokers). Stronger implicit self-smoking associations uniquely predicted increases in smokers' intentions to smoke, over and above the effects of explicit beliefs about smoking. The results provide evidence that exposure to smoking in movies is causally related to changes in smoking-related thoughts, that identification with protagonists is an important feature of narrative influence, and that implicit measures may be useful in predicting deliberative behavior.

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.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.647
Threshold uncertainty score0.334

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.109
GPT teacher head0.383
Teacher spread0.273 · 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