Hustling in the creative industries: Narratives and work practices of female filmmakers and fashion designers
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 paper examines practices and narratives of hustling in the creative industries. We draw on two illustrative cases: independent female filmmakers in Nairobi, Kenya, and independent female fashion designers in Toronto, Canada, with a combined 69 interviews. Taking a comparative, intersectional approach, we explore both the practices and narratives that entrepreneurial creative workers construct. In doing so, we contribute to ongoing conceptual debates regarding the contemporary nature of work in creative industries. We define hustling in the creative industries as entrepreneurially navigating precarity to build and sustain creative businesses. We argue that hustling is not merely a “stage” of work and life to be moved past or overcome, but instead an ongoing, entrepreneurial creative practice. This fact has implications for how we think about success and creative work: hustling is not a deviation from the good life, but a way of making a good life in precarious circumstances.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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