A model who looks like me: Communicating and consuming representations of disability
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Diversity in the fashion industry, it seems, is on the rise, with recent efforts poised to address the exclusion of people with disabilities. Based on a content analysis of editorials, advertising campaigns, and 213 online consumer comments between 2014 and 2019, we examine how diversity is showcased: specifically, whether images of disability serve to challenge or reinforce negative stereotypes. We find that market logics constrain the use of models with disabilities and shape their posturing in advertisements and fashion images. While consumers respond favorably to these images, demanding disability be more regularly and prominently featured, they are often responding to images that are sanitized and naïvely conceived. Nonetheless, we show how consumer feedback interacts with the production process, which in turn can challenge market logics, providing opportunities for increased representation. We shed light on how cultural representations reflect, shape, and challenge broader sociocultural norms and values.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it