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Record W4392312901 · doi:10.1386/csmf_00077_1

Uniform-undone: A study in the repurposing of military attire through history and in experimental practice

2023· article· en· W4392312901 on OpenAlexaff
Tricia Crivellaro, Anthony Lungu

Bibliographic record

VenueCritical Studies in Men’s Fashion · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicArtistic and Creative Research
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsRepurposingMedicineHistoryEngineering

Abstract

fetched live from OpenAlex

This article reports on a practice-led research project focusing on military attire as both a subject and an agent of change. An historical account situates the origins of modern military attire within the emergent modern state during the nineteenth century, and then examines its subsequent role as part of the project to create a ‘new man’ in Fascist Italy and Nazi Germany. This is followed by a critical discussion of the decoupling of military attire from its associations with the institutions of state and warfare during the Vietnam War – where fatigues entered the popular atmosphere as casual attire that was variously subversive, countercultural and aesthetic in nature. Employing the MA-1 bomber jacket and camouflage as illustrative examples, the article then highlights the continued repurposing of military attire and its concomitant commoditization. The practice-led research employs object-based research, speculative artistic methodologies and various garment-making techniques in the production of a novel ‘military’ garment that explores the symbolism of military uniforms and critiques their traditional concept as utilitarian combat wear. The material outcomes interrogate linkages between military attire and notions of masculinity, class and gender identity. The research project further attempts to speculate on how military attire may be repurposed within the atmosphere of the twenty-first century – one that contemplates new forms of identity and other challenges that are responsive to contemporary circumstances.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.321
Threshold uncertainty score0.414

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.000
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 head0.197
GPT teacher head0.432
Teacher spread0.235 · 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 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
Published2023
Admission routes1
Has abstractyes

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