Valuations of diversity: the role of marquee quotas in creative industries
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 This article examines how creative industry workers engage with diversity, absent a formal organizational mandate to do so. Through in-depth interviews with independent music industry personnel (N = 50), the article identifies how marquee quotas—racially diverse representation on rosters and festival bills—are used to pursue and implement diversity. Such quotas are justified via four distinct valuations of diversity: aesthetic, economic, reputational and moral. Both people of colour and white participants justify the importance of diversity on moralistic grounds. By contrast, white participants more often justify the value of diversity by making claims about the aesthetic, economic and reputational benefits of marquee quotas. The deployment of these more self-serving valuations has consequences for the extent to which people of colour can feel authentically included. The analysis contributes to critiques of the socio-economic role and consequences of diversity valuations, within the context of a creative industry.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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