Bibliographic record
Abstract
Gender inequality is common in cultural industries, including in the fashion industry, where women far outnumber men. How does the social organization of cultural work shape this inequality? This question is examined using 62 in-depth interviews with women and men creative workers in the fashion industry. I examine how gendered organizational logics are embedded in entrepreneurial labor practices and passionate work norms, both of which are common in cultural work. I find that women experience: (1) discrimination within the industry, (2) criticism from outside the industry, (3) intensified time pressure and work-family conflict, and (4) constrained choice about whether to have children. Although the demanding and insecure nature of cultural work creates time pressure and stress for men as well, men experience less anxiety, conflict, and negative judgment. These findings contribute to knowledge about gender inequality in cultural industries, as well as to the theory of gendered organizations. The gendered organizations approach traditionally entails case studies focused on the inner workings of specific organizations. I show how gendered logics can operate outside organizational boundaries, in the practices and norms of cultural work more generally.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.013 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| 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".