Bibliographic record
Abstract
Abstract The fashion industry has long neglected people with disabilities, opting instead for a cast of uniformly slender and (overwhelmingly) White models. But recent efforts toward diversity and inclusion suggest that change may be underway. This chapter examines these changes with a focus on fashion media published online. Specifically, this chapter looks to a collection of 50 editorial articles published by Teen Vogue between 2018 and 2020 to determine how disability is framed for consumers. It does this within a broader discussion on the cultural logics and industry conventions that shape the production of fashion content. The findings reported here suggest that online fashion media may hold unique opportunities for diversity and inclusion, with stories and images that cast disability in new and less narrow terms than have been previously reported. These include terms related to the importance of representation across cultural industries and stories that center disability rights in focus. Moving forward, more work is needed to ensure that this representation carriers forward in cultural productions within and outside of the fashion industry.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".