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Record W2099659194

Is Positive Information Less Well Received in Korea versus Canada? Cross-Cultural Comparisons

2014· article· en· W2099659194 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueKorean Journal of Marketing · 2014
Typearticle
Languageen
FieldComputer Science
TopicTechnology and Data Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsInferenceContradictionDual (grammatical number)Political scienceComputer scienceArtificial intelligenceEpistemologyPhilosophyLinguistics
DOInot available

Abstract

fetched live from OpenAlex

긍정적 정보는 항상 호의적 반응을 유발시켜왔다. 하지만, 긍정적 정보일지라도 긍정적 반응이 아닌 다른 반응이 나타날 수 있다. 특히 문화 차이(cultural differences)는 다양한 반응을 유발 시킬 것이다. 본 연구 결과에 따르면, 긍정적 정보에 대해 한국인은 캐다나인보다 높은 수준의 심리적 불편함을 경험하였다. 그 이유는 한국인들이 정보처리과정에서 상황중심의 추론 (situation-based inference)과 모순(laws of contradiction) 을 바탕으로 한 양면추론(dual inference)통해 긍정적 정보의 가치를 낮게 평가하여 수용하기 때문이다. 결과적으로 한국인은 긍정적 정보에 노출된 후, 제품에 대한 낮은 긍정적 태도를 보였으나, 캐나다인은 긍정적 태도가 강화되거나 변화하지(낮아지지) 않았다. 따라서 본 연구는 광고주에 대한 긍정적 정보를 강조하여 제공하는 비교광고가 동양에서 효과가 없었는지를 설명할 수 있다. 또한 긍정적 정보가 반드시 긍정적 결과를 유발시키지도 않을 수 있음을 제시한다.

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)0.001
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 score0.356
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
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 head0.014
GPT teacher head0.260
Teacher spread0.245 · 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