The Woman-Entrepreneur: The State of Research on Entrepreneurship Education, Business Incubation, and Women in the Philippines
Bibliographic record
Abstract
In the Philippines, entrepreneurship education is seen as essential in boosting economic growth, generating new ideas, and starting new businesses. Despite of offering BS Entrepreneurship, mandated by CHED Memorandum Order No. 18, Series of 2017, for more than two decades, wherein the program stresses the importance of entrepreneurial skills and venture development, but gaps and challenges remains, especially when it comes to fostering creativity, maintaining institutional support, and bringing together industry collaboration. This review aims to look into the current status of entrepreneurship education in the Philippines and how it closes the economic gaps and addresses gender equality in doing business. The study observes that action-based learning, grounded on Dewey's experiential theory, Saravatsy's causation and effectuation, and Frese's action regulation theory, is a major advancement in the field of entrepreneurship education. This was built by looking at recent literature, policies, frameworks, programs, and case studies of university-based Technology Business Incubators (TBIs) and innovation centers. On the other hand, the results also showed that women are still underrepresented in the entrepreneurial landscape, specifically in scalable and innovation-driven businesses, due to systemic problems and mental blocks. The review mentions that innovation centers and TBIs have been instrumental in assisting individuals who aspire to become entrepreneurs, but transforming their programs and strategies to ensure that they are gender-responsive. It suggests that entrepreneurship education should include mentorship, soft innovation, and inclusive teaching methods to help and empower women entrepreneurs.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".