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Record W1921490643 · doi:10.1002/cb.389

Mixing emotions: The use of humor in fear advertising

2012· article· en· W1921490643 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

VenueJournal of Consumer Behaviour · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicMedia Influence and Health
Canadian institutionsMcGill University
Fundersnot available
KeywordsPersuasionPsychologyArousalFear appealVulnerability (computing)Social psychologyAdvertisingComputer securityComputer science

Abstract

fetched live from OpenAlex

ABSTRACT Fear is used to advertise many products, services, and causes such as antismoking, sunscreen usage, and safe driving. Past research indicates that high levels of fear tension arousal can prompt defensive responses in the audience, which, in turn, can reduce the persuasive effect of the ad. We show in two studies that humor can reduce these defensive responses and hence increase the persuasiveness of fear advertising. Specifically, we show that increasing the level of fear tension arousal decreases persuasion when humor is absent but increases persuasion when humor is present. Further, this interaction of humor and fear tension arousal is mediated by defensive responses related to message elaboration and vulnerability to threat. Our results suggest that the effectiveness of fear advertising can be increased by adding an element of humor to the ad. Copyright © 2012 John Wiley & Sons, Ltd.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score0.600

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.151
GPT teacher head0.319
Teacher spread0.168 · 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