Female Entrepreneurship in Dakar: A Multidimensional Approach Where the Entrepreneurial Culture Reflects the Sociological Diversity of Female Entrepreneurs in Dakar
Bibliographic record
Abstract
We investigated female entrepreneurship in Dakar with the following objectives: the study of individual characteristics of female entrepreneurs, their motivations, the existence of an entrepreneurial culture and their insertion in the networks. We were also interested in the entrepreneurial choice and when they take on the choice of the “administrative” sector (informal/formal). We have thus shown the importance of entrepreneurial culture and social capital in the Senegalese female entrepreneurship, as well as the motivations that distinguish entrepreneurial engagement in the informal sector compared to the formal sector. Necessity entrepreneurship is found more in the “small informal” sector, it participates, thanks to the support from relatives, to the participation of women’s networks, in the smooth running of a developing economy since it is a source of employment that is adapted to the social and human capital of the majority of Senegalese women.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".