Inclusive Entrepreneurial Ecosystems: Current Landscape & Future Research
Bibliographic record
Abstract
An alarming disconnect exists between the promise of entrepreneurship and the current cultural and material infrastructure of entrepreneurship ecosystems. On the one hand, theoretical frameworks highlight entrepreneurship's potential as a transformative force in society (Lounsbury & Glynn, 2019; Stephan, Patterson, Kelly, & Mair, 2016; Vedula et al., 2022). An increased focus on entrepreneurship as a pathway out of poverty is bolstered by growing studies of entrepreneurship’s emancipatory potential, particularly for individuals who experience discrimination and marginalization (Bacq, et al., 2023, Rindova, Barry, & Ketchen, 2009; Rindova, Srinivas, & Martins, 2022; Ruebottom & Toubiana, 2021). On the other hand, the very entrepreneurial ecosystems that have arisen - with hefty government support - as integral components in contemporary economic development strategies are now facing mounting criticism regarding their limited scope and exclusionary nature. This panel symposium marks the coalescence of an emergent and important research stream on inclusive entrepreneurial ecosystems.
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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 | 0.016 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.019 | 0.029 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.023 | 0.004 |
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".