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Record W4238971348 · doi:10.32920/ryerson.14648838.v1

Fashion autobiographies: a case study with fourteen subjects

2021· preprint· en· W4238971348 on OpenAlexaboutno aff
Filomena Natale Gasparro

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicFashion and Cultural Textiles
Canadian institutionsnot available
Fundersnot available
KeywordsBiographyLife writingNarrativeClothingObject (grammar)AestheticsArtIdentity (music)Visual artsLiteratureSociologyHistoryPhilosophyLinguistics

Abstract

fetched live from OpenAlex

“Fashion Autobiographies: A Case Study with Fourteen Subjects” creates a narrative at the intersection of fashion, affect, and autobiography. Underlying this study is the theoretical assumption that, more than a protective skin for hiding or showcasing the body, clothing is a repository for emotion and memory. It is also a powerful medium for communicating and writing a life. To illustrate fashion’s potential as a medium for life writing, specifically as fashion autobiography, this Major Research Paper (MRP) pursues two distinct goals. First, it theorizes the novel concept of the fashion autobiography using theories of fashion, life writing and gender. Second, it includes an arts-based project, “Fashion Autobiographies: A Case Study with Fourteen Subjects,” involving fourteen women and the creation of fourteen fashion autobiographies written on canvas dresses and exhibited at the Design Exchange in Toronto in February 2015. The author designed three template dresses using three iconic silhouettes from the 1950s, 60s, and 70s, which the women were encouraged to manipulate and deconstruct as they wished. Thus, each woman used one of these template dresses to articulate a pivotal experience, illustrating a moment that defined her life. Together, this MRP argues, these fourteen dresses stand as a collection of moments told through fashion life writing, exhibiting deeply personal memories and emotions. They represent the objects of study for this MRP, presented through detailed description and object analysis. This MRP conjoins theory and art to advance our understanding of the form, function, and significance of the fashion autobiography.

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), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.049
GPT teacher head0.251
Teacher spread0.201 · 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.

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
Published2021
Admission routes1
Has abstractyes

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