Transgender fashion: Fit challenges and dressing strategies
Bibliographic record
Abstract
Clothing is part of our material culture and allows individuals to portray their self-image and articulate their personas to others. Clothing is performative and helps position individuals as their desired gender, which is why clothing is so important to transgender people. While the transgender medical experience has been examined, few have investigated wardrobe building for transgender people undergoing hormone replacement therapy (HRT). This research explored clothing worn by two trans women, and a trans man who experienced pregnancy, to answer the research question ‘What are the clothing issues and dressing strategies of transgender individuals?’. A convenience sample ( n =3) was recruited using snowball methods. Data collection followed three phases to foster a empathy and learning utilizing a qualitative, human-centred approach. To better understand the market, research began with a competitive analysis of retailers and bloggers catering to this niche market. At-home wardrobe interviews utilized participant’s clothing as probes to discuss and demonstrate anatomy in relation to clothing choices and how participants felt when wearing the right clothing. Themes in the data included transition strategies, shopping and fit challenges as well as clothing solutions. Key outfits were photographed, providing insights regarding clothing assortment, fit criteria, as well as desirable/problematic design details and styling tips used to achieve the desired aesthetic/identity. The findings of this study offer empowering strategies to support wardrobe choices for transgender people and are important to designers, product developers and retailers.
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How this classification was reachedexpand
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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".