MétaCan
Menu
Back to cohort
Record W4206730751 · doi:10.1177/14707853211063845

A Cross-Cultural Study on the Effects of Envy-Evoking Ads

2022· article· en· W4206730751 on OpenAlexaff
Sowon Ahn, Myung‐Soo Jo, Emine Sarigöllü, Chang Soo Kim

Bibliographic record

VenueInternational Journal of Market Research · 2022
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsMcGill University
Fundersnot available
KeywordsIndependence (probability theory)ConstrualsSocial psychologyPsychologySelf construalAdvertisingConstrual level theorySociologyBusinessInterdependence

Abstract

fetched live from OpenAlex

Ads often feature celebrities or others similar to the target viewer and thereby evoke envy. Envy occurs when people make an upward social comparison, and evoked envy can be either benign or malicious. The authors propose that people with different self-construals feel different degrees of benign and malicious envy depending on who is being envied: a celebrity or a similar other. Three studies were conducted comparing Americans to Koreans (Study 1), Americans to the Chinese (Study 2), and Koreans with different self-construals (Study 3). The results showed that people with high independence showed less benign envy toward the celebrity ad than toward the similar others ad, while people with low independence showed the opposite pattern. People with high interdependence showed less malicious envy toward the celebrity ad than toward the similar others ad, while people with low interdependence showed the opposite pattern.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.193
GPT teacher head0.538
Teacher spread0.345 · 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 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

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Market ResearchSame topicCultural Differences and ValuesFrench-language works237,207