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Record W2331145010 · doi:10.1386/csfb.4.1-2.71_1

Fashion cultures in a small town: An analysis of fashion- and place-making

2013· article· en· W2331145010 on OpenAlexaff
Denise Nicole Green, Van Dyk Lewis, Charlotte Jirousek

Bibliographic record

VenueCritical Studies in Fashion and Beauty · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicFashion and Cultural Textiles
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSociologyContext (archaeology)Citizen journalismClothingCraftSpace (punctuation)EthnographyPerspective (graphical)AestheticsVisual artsMedia studiesArtComputer scienceGeographyWorld Wide WebAnthropology

Abstract

fetched live from OpenAlex

Abstract In her introduction to this issue, Kaiser advances a perspective that highlights dimensions of place and time in a dynamic and non-stereotypical way. Rather than treating these dimensions as background factors in the architecture of interaction context, she critically unpacks the ways in which time and place impact individual and collective fashion meanings. In our article we draw on Kaiser’s focus by using ethnographic methods to investigate how fashion is ‘produced’ to convey identification with place, group and/or a temporary alliance in a rural community where landscape is constitutive of social configurations and the student population is always transient. To that end we replace the notion of fixed visual identities with phatic communities, which are ad hoc groupings sharing a cause or a circumstance (Tseëlon 2010). Next, we address the problem of how to preserve the meanings and looks of ad hoc fashions, which exist in a constant state of change. We apply the logic of phatic communities to the building of a museum collection, which has to meet the challenge of capturing a fleeting and evolving phenomenon without freezing it into fixed categories. Contrary to the logic of traditional museums, a museum documenting ongoing clothing changes invites a different mode of engagement: one that is participatory and interactive. Finally, our conception of the sartorial museum, which documents changing time in a particular place, replaces the notion of the museum as a ‘space of death’ with the notion of a ‘space of regeneration’. The regeneration is the recycling, which repositions clothes in a ‘second life’.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.666
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.094
GPT teacher head0.347
Teacher spread0.253 · 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

Citations6
Published2013
Admission routes1
Has abstractyes

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