Dapper dudes: an exploration of young men's fashion consumption and conceptions of masculinity
Bibliographic record
Abstract
If sensationalized media reports are any indication, the men’s fashion industry has entered into an exciting phase of expansion and evolution. As the market diversifies to become increasingly vibrant and varied, prominent ready-to-wear labels continue to showcase evermore divergent and gender-blurring designs in what is celebrated as an anything-goes period in menswear. To examine whether these clothing trends and industry transitions have lasting real world implications, this research seeks to give voice to fashion-conscious male consumers - the subject of scarce qualitative scholarship. Insights gleaned from 20 in-depth interviews with young Canadian men point to contemporary shifts not only in shopping habits and tastes, but also in hegemonic masculinity. Responding to romantic assertions that there are “no rules” in twenty-first century fashion, findings examine the extent to which long withstanding Western menswear conventions prevail. Through illuminating the lived experiences of sartorially savvy males aged 19 to 29, this study uncovers how Generation Y men navigate gender norms and expectations while crafting an idiosyncratic sense of style. Ultimately, this research enriches existing industry and theoretical understandings of how young men approach fashion.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".