Expanding the male ideal: The need for diversity in men’s fashion advertisements
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
Abstract While an emerging stream of scholarship has focused on women’s perceptions of body diversity in fashion advertising, few studies have investigated men’s responses to diverse male models. Interviews with 30 men were conducted to examine how they interpret male models of various sizes, ages and races in fashion advertisements as well as how these models influence their body image and perceptions of the advertisement. Analysis revealed that men identified with models whom they shared physical traits, expressed aversion towards idealized bodies, rejected muscularity as a symbol of masculinity, and wanted to see more diverse models in fashion advertising. Participants expressed body anxiety and negative perceptions of advertisements when they viewed idealized models, whereas they communicated body satisfaction and favourable perceptions of advertising when the models reflected their bodies. Results from this study elucidate how men evaluate and respond to male models in fashion advertising and particularly highlight the influence of viewer – model similarity on men’s responses to models. Menswear brands are advised to cast models that reflect the diversity of their target market in order to foster body confidence and advertising effectiveness.
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 | 0.001 | 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 | 0.002 | 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