Women’s Entrepreneurship Policy and Access to Financial Capital in Different Countries: An Institutional Perspective
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 explores women’s entrepreneurship policy and practice in three different countries: Canada, Ireland and the U.S. We focus specifically on policies relating to access to financial capital, and ask: How are ‘access to financial capital’ policies and practices operationalized at national and regional level? We draw on institutional theory to identify gaps in policy and practice, and to highlight similarities and differences between countries. We contribute a novel perspective on women’s entrepreneurship policy by drawing attention to the underlying institutional pillars and the importance of institutional fit in informing a coherent and future-looking policy framework. Our findings enhance understanding of how ‘access to financial capital’ policies and practices geared toward women entrepreneurs reflect different institutional contexts.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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