Fashion autobiographies: a case study with fourteen subjects
Bibliographic record
Abstract
“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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.017 | 0.008 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".