Examining Venture-Related Myths Concerning Women Entrepreneurs
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
Despite the increasing number of women who are starting businesses, distinct hurdles exist for them. For instance, there is a lower occurrence of females as business owners and a paucity of academic research on the topic of female entrepreneurs. Another major hurdle is the presence of derogatory like those specified in the U.S. Diana Project. A random sample of nascent entrepreneurs in Canada is utilized to examine these myths about women entrepreneurs. Although many of the myths were unsubstantiated, the findings show that perhaps women do not have the right educational background to start large businesses and they may be starting businesses unattractive to venture capitalists. These findings are a clear wake-up call for the implementation of new programs and policies to increase the number of females studying computer and engineering sciences and to encourage and nurture a higher incidence of females as lead entrepreneurs. (Publication abstract)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it