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Record W3043073077 · doi:10.1111/maq.12577

Veteran Therapeutics: The Promise of Military Medicine and the Possibilities of Disability in the Post‐9/11 United States

2020· article· en· W3043073077 on OpenAlex

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

VenueMedical Anthropology Quarterly · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Security, and Conflict
Canadian institutionsUniversity of Toronto
FundersNational Science Foundation
KeywordsCollateral damageAnticipation (artificial intelligence)EthnographyCollateralDisability studiesPosttraumatic stressPsychologyPsychotherapistMedicinePsychiatryPsychoanalysisCriminologySociologyPolitical scienceLawGender studies

Abstract

fetched live from OpenAlex

This article draws on a decade of ethnographic work with injured U.S. soldiers and veterans to show the collateral effects of military medicine's salvific promise. In tracing these effects through recent changes in amputation protocols and less spectacular conditions such as posttraumatic stress disorder, I show that the prevalent model of "veteran therapeutics," which posits cure as the aim of post-war, has perverse and cruel effects. Drawing on disability theory, I explore alternative ways to read the frictions that soldiers and veterans experience, stretched between the medical model of veteran therapeutics and an emergent sense that cure may be an impossible goal. Alternatively, the article turns to moments when veterans learn to live with disability, rather than living in anticipation of its end. Though small, such moments contain possibilities for a less cruel mode of inhabiting disability, offering incipient signs of what we might call a crip art of failure.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.371
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.035
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.042
GPT teacher head0.343
Teacher spread0.301 · 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