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Record W4411004414 · doi:10.1017/s0026749x24000428

The Manchurian saviour? Re-examining the ‘Otpor Incident’ in imperial and contemporary Japan

2025· article· en· W4411004414 on OpenAlexaff
Rotem Kowner, Joshua A. Fogel, Dylan H. O’Brien

Bibliographic record

VenueModern Asian Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicJapanese History and Culture
Canadian institutionsYork University
Fundersnot available
KeywordsPraiseNarrativePopularityHistoryNationalismThe HolocaustHEROVictoryPolitical scienceLawMedia studiesLiteratureSociologyArt

Abstract

fetched live from OpenAlex

Abstract In recent years, the Japanese public has hailed a new national hero, the late Lieutenant General Higuchi Kiichirō. Unlike other notable military figures of his era, Higuchi’s heroism is unconventional, if not unique. Despite playing a leading role in the defence of Hokkaido against the Soviet Red Army in 1945, it is humanitarian efforts that have cemented Higuchi’s lasting legacy in public memory. Presently, a plethora of publications, TV documentaries, a museum, and monuments praise his actions during the ‘Otpor Incident’, in which he is said to have saved up to 20,000 Jewish refugees stranded in the winter of 1938 along the Soviet-Manchukuo border. This article questions the authenticity of Higuchi’s acclaimed rescue efforts, highlighting discrepancies that cast doubt on the entire narrative. It suggests the possibility of the ‘Otpor Incident’ being a complete fabrication or, at best, an extremely exaggerated account of a minor event, aimed at enhancing post-war personal and national reputations. Critically, this piece contends that Higuchi’s current recognition is part of a strategic move by nationalist groups in Japan to use Holocaust narratives to divert attention from Japan’s history of wartime aggression and colonialism. To substantiate this view, this article assesses the evidence of Higuchi’s involvement in the supposed rescue, examines the narrative’s post-war evolution, and analyses the motives for its initial dissemination and recent surge in popularity.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.051
GPT teacher head0.324
Teacher spread0.273 · 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.

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

Citations1
Published2025
Admission routes1
Has abstractyes

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