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Record W2811066899 · doi:10.3138/cras.2018.005

Agent Orange Bodies: Việt, Đức, and Transnational Narratives of Repair

2018· article· en· W2811066899 on OpenAlexvenueno aff
Natalia Duong

Bibliographic record

VenueCanadian Review of American Studies · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicVietnamese History and Culture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAgent OrangeNarrativeAmbivalenceVietnameseNormativeNoticePoliticsSociologyPolitical scienceAestheticsHistoryLawPsychoanalysisLiteratureArtPsychologyPhilosophyLinguistics

Abstract

fetched live from OpenAlex

Bodies affected by Agent Orange trouble judicial and psychic notions of “reparation” as they become the sight/site of repair on behalf of national body politics. The simultaneous public display and quarantined seclusion of bodies affected by the herbicide point toward the ambivalent role of disabled bodies in Vietnam. In my discussion, I analyze how the surgical separation of conjoined twins Việt and Đức Nguyễn came to represent an act of reparation that meant to rhetorically unite Japan and Vietnam against the United States. Through analyses of a book titled Cheer Up Viet and Duc and a music video collaboration between Vietnamese and Japanese pop musicians, I discuss how attempts to “heal” disability conflate non-normative bodies with wartime trauma, thereby reproducing a eugenic narrative that seeks to eradicate disability as a demonstration of neo-liberal modern progress. Against these dominant narratives of repair, I suggest that the transnational circulation of Agent Orange creates networks that are dependent upon recognizing a shared, and differentially distributed, vulnerability to contamination.

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)0.003
metaresearch head score (Gemma)0.004
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 score0.085
Threshold uncertainty score0.169

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0120.028
Scholarly communication0.0070.007
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.037
GPT teacher head0.345
Teacher spread0.308 · 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

Citations10
Published2018
Admission routes1
Has abstractyes

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Same venueCanadian Review of American StudiesSame topicVietnamese History and Culture StudiesFrench-language works237,207