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Record W7161711846 · doi:10.3138/cjfms-2024-0040

Dressing the Wounds: Medical Internationalism and Embodied Realism in <i>Dr. Bethune</i>

2025· article· en· W7161711846 on OpenAlexaboutno aff
Ling Zhang

Bibliographic record

VenueCanadian Journal of Film and Media Studies · 2025
Typearticle
Languageen
FieldPsychology
TopicHistorical Psychiatry and Medical Practices
Canadian institutionsnot available
Fundersnot available
KeywordsInternationalism (politics)IdeologyPoliticsChinaRealismGeopoliticsBattlefield

Abstract

fetched live from OpenAlex

This article explores the cinematic and political significance of Dr. Bethune, a Chinese biographical film that transforms internationalist ideals into lived, corporeal experience through what I term “embodied realism.” Against the backdrop of twentieth-century medical internationalism and revolutionary humanism, the film foregrounds “blood ties” forged across racial and national boundaries through anti-fascist and anti-imperialist struggle. Situating Dr. Bethune within transnational currents of socialized medicine and global solidarity, it intersects multiple historical temporalities, transnational connections, political tensions, and media formats, raising critical questions: How does a 1960s Chinese film about a 1930s Canadian internationalist speak to the contemporary geopolitical context? By tracing Bethune’s medical and ideological legacy—from battlefield surgeries to contemporary struggles for medical justice—this article examines how “embodied realism” as a socialist aesthetics and revolutionary cinematic approach continues to illuminate the urgent need for transnational solidarity. Dr. Bethune stands as both a cinematic act of internationalism and a call to reimagine medical justice beyond the confines of the nation-state.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.774
Threshold uncertainty score0.955

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.043
GPT teacher head0.376
Teacher spread0.333 · 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 designNot applicable
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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