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Record W4362654865 · doi:10.38055/sof010103

Methodologies for the Creolization of Fashion Studies

2023· article· en· W4362654865 on OpenAlexvenueno aff

Bibliographic record

VenueFashion Studies · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicFashion and Cultural Textiles
Canadian institutionsnot available
Fundersnot available
KeywordsCreolizationArtLiterature

Abstract

fetched live from OpenAlex

Since its inception fashion studies has occupied niche fields of enquiry that have focussed largely on Eurocentric paradigms of discussion around the engagement with fashion objects and the development and display of status and identity. Pockets of enquiry have focussed on areas outside of the Eurocentric western cannon but largely remain apart from what is considered established fashion studies. With this in mind it is clear that the structures and parameters of what can be determined as legitimate fashion study are based firmly within the considerations of Eurocentric epistemologies. This then shapes all other studies of clothing and determines whether they are allowed a place within the exclusive world of fashion studies.
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\nThis poses a challenge which the Costume Institute of the African Diaspora (CIAD) has sought, in some way, to rectify. CIAD has been developed and established to collate research and broaden academic discourse around the development of fashion studies from the perspective of people within the African Diaspora. With that aim in mind, CIAD held its first dress conference on the 4th of May, 2018 in order to bring together researchers in the field with this focus. The conference was entitled Si Wi Yah: Sartorial Representations of the African Diaspora. “Si Wi Yah” a Jamaican patois phrase which translates to “we are here” was a call for the wider fashion studies community to recognise and acknowledge the engagement with the sociology and psychology of dress taking place which doesn’t centre white western hegemonic ideology.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.624
Threshold uncertainty score0.619

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 studies0.0010.001
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 head0.521
GPT teacher head0.440
Teacher spread0.081 · 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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