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Record W2689502776 · doi:10.1177/186810261704600107

Anti-Japanese Sentiment among Chinese University Students: The Influence of Contemporary Nationalist Propaganda

2017· article· en· W2689502776 on OpenAlex
Min Zhou, Hanning Wang

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.

Bibliographic record

VenueJournal of Current Chinese Affairs · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicHong Kong and Taiwan Politics
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsNationalismEliteChinaBeijingCommunismPolitical scienceMedia studiesSentiment analysisSociologyLawPolitics

Abstract

fetched live from OpenAlex

This study looks at the sources of anti-Japanese sentiment in today's China. Using original survey data collected in June 2014 from 1,458 students at three elite universities in Beijing, we quantitatively investigate which factors are associated with stronger anti-Japanese sentiment among elite university students. In particular, we examine the link between the Chinese Communist Party (CCP)'s nationalist propaganda (especially patriotic education) and university students’ anti-Japanese sentiment. We find that nationalist propaganda does indeed have a significant effect on negative sentiment towards Japan. Reliance on state-sanctioned textbooks for information about Japan, visiting museums and memorials or watching television programmes and movies relating to the War of Resistance against Japan are all associated with higher levels of anti-Japanese sentiment. The findings suggest the effectiveness of nationalist propaganda in promoting anti-Japanese sentiment. We also find that alternative sources of information, especially personal contact with Japan, can mitigate anti-Japanese sentiment. Thus, visiting Japan and knowing Japanese people in person can potentially offset some of the influences of nationalist propaganda.

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)0.001
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 score0.008
Threshold uncertainty score0.723

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
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 head0.021
GPT teacher head0.339
Teacher spread0.318 · 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