Incubators and Accelerators as Illusionary Leaders for Equality in Entrepreneurial Ecosystems
Bibliographic record
Abstract
A small but growing body of research investigates issues pertaining equity, diversity and inclusion (EDI) in entrepreneurial ecosystems (EEs). While studies in the broader entrepreneurship literature suggest that barriers for women and underrepresented groups exist profoundly at the early stages of new venture creation, there is limited understanding as to how ecosystem actors and interactions contribute to these. We present findings from a critical discourse analysis of the websites of 176 Canadian business incubators and accelerators (BIAs) that show the effects of a power struggle of these organizations to cater to multiple stakeholders on EDI in the EE. Specifically, we find that BIAs create discursive practices that position them as what we label illusionary ecosystem leaders. While using language to show leadership in addressing entrepreneurs and external stakeholders, they largely follow institutional pressures present in the EE, making their leadership illusionary. We develop a theoretical model of the impact on systemic inequalities of the discursive practices, contribute to the literature on EDI and leadership in EEs, and discuss implications for management.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".