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Record W2077416457 · doi:10.1509/jimk.14.4.110

Interactive Effects of Appeals, Arguments, and Competition across North American and Chinese Cultures

2006· article· en· W2077416457 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of International Marketing · 2006
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicConsumer Behavior in Brand Consumption and Identification
Canadian institutionsConcordia UniversityUniversity of Guelph
FundersSocial Sciences and Humanities Research Council of CanadaConcordia University
KeywordsArgument (complex analysis)AppealChinaCompetition (biology)AdvertisingContrast (vision)Cultural diversityPsychologyMarketingBusinessPolitical scienceLaw

Abstract

fetched live from OpenAlex

Using data from actual consumers in North America and China, this research analyzes the interactive effects of appeals and arguments in a competitive environment. The theoretical basis for this study is that contrast effects are most likely to occur when consumers experience advertisements with distinct culture-laden advertising appeals and comparable arguments. The findings indicate that a culturally congruent appeal and a strong argument embedded in an advertisement may create more favorable responses when competing advertisements contain culturally incongruent appeals and neutral arguments than when competing advertisements contain culturally congruent appeals and neutral arguments.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.284

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 communication0.0000.001
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 head0.004
GPT teacher head0.255
Teacher spread0.251 · 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