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Record W2242891309 · doi:10.1177/0022022115606803

The Role of Regulatory Focus in How Much We Care About Enemies

2015· article· en· W2242891309 on OpenAlexaffabout
Liman Man Wai Li, Takahiko Masuda

Bibliographic record

VenueJournal of Cross-Cultural Psychology · 2015
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsRegulatory focus theoryPromotion (chess)Focus groupInterpersonal communicationFocus (optics)PsychologySocial psychologyPolitical scienceBusinessMarketing

Abstract

fetched live from OpenAlex

Past cross-cultural research studies in regulatory focus have showed that East Asians in general tend to be prevention-focused, whereas Westerners tend to be promotion-focused. Three studies extend these findings by investigating the role of regulatory focus on people’s experiences in enemyship—how people deal with their personal enemies. Study 1 demonstrated that Hong Kong Chinese, as one of representative prevention-focused East Asian groups, showed greater concern about their enemies in terms of perceived threats from their enemies, subjective awareness of enemies, and negative emotional experiences in enemyship, compared with European Canadians as one of representative promotion-focused Western groups. In addition, Study 2 demonstrated that Hong Kong Chinese memorized more pieces of information about a hypothetical enemy than did their Canadian counterparts, which demonstrated a greater concern about enemies among Hong Kong Chinese. Finally, while replicating Study 1, Study 3 demonstrated that participants’ regulatory focus explained the cultural differences in enemyship experiences. Implications for regulatory focus, cross-cultural research, and interpersonal relationship research are discussed.

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)0.001
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 score0.324
Threshold uncertainty score0.494

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.089
GPT teacher head0.447
Teacher spread0.358 · 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

Citations19
Published2015
Admission routes2
Has abstractyes

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