MétaCan
Menu
Back to cohort
Record W2085779472 · doi:10.12735/jbm.v2i4p22

The Effects of Education and Incongruent Images on Product Warnings

2013· article· en· W2085779472 on OpenAlexvenueno aff
Haeran Jae

Bibliographic record

VenueJournal of Business & Management · 2013
Typearticle
Languageen
FieldPsychology
TopicSafety Warnings and Signage
Canadian institutionsnot available
Fundersnot available
KeywordsProduct (mathematics)PsychologyCognitive psychologyComputer scienceMathematics

Abstract

fetched live from OpenAlex

The research reported in this article investigates how the education level of consumers affects liking and safety feeling toward a product when incongruent images are present with product warnings. The current study used a 2 by 2 experimental methodology to investigate underlying psychological processes of adult consumers who have varying levels of education. The current study finds that relative to high-education consumers, low-education consumers (those who did not complete high school) were more significantly affected by the presence of incongruent images in the product warnings. They displayed higher liking and more safety feeling toward a product when warnings accompanied incongruent images versus warnings with no images. This effect is not found among high-education consumers. That result has alarming implications. Low-education consumers may be unable to critically evaluate product warnings and can be persuaded to misjudge product warnings and product safety when product warnings include incongruent images. The current research extends the previous research on low-education consumers by studying the impact of incongruent images in the product warnings. Specifically, we focus on investigation of subjective attitude formation of warnings (liking and safety feeling) in the presence of incongruent images which was not investigated in the past.

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 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)0.000
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 score0.963
Threshold uncertainty score0.254

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.005
GPT teacher head0.252
Teacher spread0.248 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Business & ManagementSame topicSafety Warnings and SignageFrench-language works237,207