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Record W4407273029 · doi:10.54097/t8epy436

Official and Grassroot Responses to the Japanese Textbook Controversy: A Comparative Study on China and Korea

2025· article· en· W4407273029 on OpenAlexaff
Tiantian Cheng

Bibliographic record

VenueHighlights in Business Economics and Management · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Educational Reforms and Inequalities
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsChinaPolitical scienceLibrary scienceMedicineLawComputer science

Abstract

fetched live from OpenAlex

Japan’s ongoing revision of its wartime history, particularly through its school textbooks, continues to be a major source of diplomatic friction in East Asia, intertwining issues of national identity and collective memory. The intensification of these disputes in 2002 and 2005 marked significant turning points in Sino-Japanese and Korea-Japanese relations. This paper delves into the official and grassroots responses from both China and South Korea, shedding light on the different characteristics exhibited by each country’s approach to manage disputes, as well as the relationship between government-led diplomatic maneuvers and popular nationalist movements. Through a constructivist lens, the analysis reveals how these countries not only react to historical controversies but also play an active role in shaping regional narratives and international perceptions. This study aims to provide a deeper understanding of the nuanced dynamics between official state responses and grassroots movements in China and South Korea as strategic efforts to shape national identity, public sentiment, and international legitimacy.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.159

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0050.004
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.026
GPT teacher head0.315
Teacher spread0.289 · 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 designQualitative
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

Citations0
Published2025
Admission routes1
Has abstractyes

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