Sex-based labour market segregation and women's perceptions of entrepeneurship
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
Sex-based labour market segregation and women's perceptions of entrepeneurship Here Professors Tonoyan, Strohmeyer, and Jennings investigate sex-based labour market segregation and women's perceptions of entrepreneurship. As noted in a prior Open Access Government article, women tend to participate in entrepreneurial activity at lower rates than men within most countries included in the Global Entrepreneurship Monitor. Numerous plausible reasons for this gender gap exist. A large-scale study by Professors Vartuhi Tonoyan (California State University, Fresno), Robert Strohmeyer (University of Mannheim), and Jennifer E. Jennings (University of Alberta) put forth and examined the argument that women are likely to possess less favourable perceptions than men, on average, of how easy it would be to start a business. These scholars further argued that this disparity can be attributed to sex-segregated positions within traditional wage-and-salary employment, which present structural disadvantages for women’s entrepreneurship.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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