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Record W2590363732 · doi:10.1177/0020715217694078

Values of deference to authority in Japan and China

2017· article· en· W2590363732 on OpenAlexvenueno aff
Yida Zhai

Bibliographic record

VenueInternational Journal of Comparative Sociology · 2017
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsnot available
Fundersnot available
KeywordsDeferencePoliticsCollectivismChinaAsian valuesHarmony (color)ConformityPolitical cultureSociologyPolitical sciencePolitical economyLawIndividualism

Abstract

fetched live from OpenAlex

Values of deference to authority have long been prevalent in Japan and China. These two societies feature hierarchical social structures, harmonious orientations, and collectivism, which are regarded as cultural characteristics of East Asia. Through distinguishing traditional values in the political sphere from those in the non-political sphere, this article examines the relationship between traditional values and political deference levels in Japan and China. The empirical results show that conformity in family and school, preference for political harmony, and prioritization of national interests positively correlated with political deference in the two countries. However, prioritizing family and collective interests significantly correlated with political deference in China, while no significant effect was observed in Japan. Neither did preference for harmony in community and in the workplace have a positive effect on political deference in Japan.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.081
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.184
GPT teacher head0.489
Teacher spread0.305 · 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

Citations65
Published2017
Admission routes1
Has abstractyes

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