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Record W4392501852 · doi:10.32920/25355842.v1

A Fashion Studies Manifesto: Toward an (Inter)disciplinary Field

2024· preprint· en· W4392501852 on OpenAlexaboutno aff
Ben Barry, Alison Matthews David

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicFashion and Cultural Textiles
Canadian institutionsnot available
Fundersnot available
KeywordsManifestoDisciplineField (mathematics)Political scienceSociologySocial scienceLawMathematics

Abstract

fetched live from OpenAlex

<p>We are two scholars who locate ourselves within Fashion Studies and outside of it. In this paper, we draw from our professional experiences and research programs to argue that <em>Fashion Studies</em> should be both a stand-alone and a cross-disciplinary field. Fashion provides a lens to understand the social, visual, and material worlds, while <em>Fashion Studies</em> fosters community among scholars who are deeply “invested” in the study of dress, adornment, and the body. First, framing our discussion through autoethnographic and embodied lenses allows us to how examine how we came into <em>Fashion Studies</em>. Our academic backgrounds are outside of <em>Fashion Studies</em>, but these routes led us to become faculty within a fashion department and inspired our work in building a diverse <em>Fashion Studies </em>community. Second, we explore our research programs as examples of how scholars in our field have to strategically position themselves. The federal grant system in Canada, where we live and work, does not recognize <em>Fashion Studies</em>. As such, we have made the case that fashion is a lens to advance new knowledge in History and Sociology, established disciplines recognized by granting agencies. We discuss how we made this case in our applications, discussing how Fashion Studies’ frameworks, methodologies, and tools of mobilization have allowed us to contribute to a range of disciplines. Finally, we discuss the need for <em>Fashion Studies </em>to welcome scholars who recognize diverse ways of knowing in order to decolonize, queer, and crip the field. The global pandemic, the Black Lives Matter movement, and the climate change crisis have alerted us to the urgency of the need for care, communication, and community. We discuss how we have supported graduate students from diverse intersections as Fashion Studies scholars and those from established fields. We ask how we can continue to create spaces for questioning and reflection to ensure that the powerful voices of the next generation of scholars and creatives in the field we love will be heard loud and clear.</p>

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.396
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.181
GPT teacher head0.358
Teacher spread0.177 · 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; both teacher heads agree on what is shown here.

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
Published2024
Admission routes1
Has abstractyes

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