Coming into fashion: Expanding the entrepreneurial ecosystem concept to the creative industries through a Toronto case study
Bibliographic record
Abstract
This paper considers the entrepreneurial ecosystem concept, which in recent years has gained interest from a variety of perspectives including entrepreneurship, management, and economic geography. Specifically, the paper identifies a gap in the literature regarding the concept's sectoral or industrial focus. Prior applications to real‐world case studies have focused on a fairly narrow range of industries and places. In this paper, we apply the concept to a case study of one creative and cultural industry, the fashion industry, to help us understand not only the performance and function of entrepreneurs and small businesses in this industries, but also potential policy supports. We map the institutions and spaces in Toronto's entrepreneurial ecosystem, drawing on extensive qualitative research to consider the dynamics and interactions therein. In parallel, we advance the concept theoretically, questioning its tenability and applicability in a wider range of economic systems by adding the perspective of cultural and creative industries.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.005 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".