Redefining women's entrepreneurial financing mechanism in Kenya and Nigeria: the emergence of Chama and Esusu
Bibliographic record
Abstract
In many nations across the world there has been significant growth in the level of female entrepreneurs, this spans from developed economies (McAdam, 2013) such as the US, Australia, Canada, to the developing economies of Sub-saharan Africa (Aliyu, 2013). Also, as Sub-saharan African countries yearn for economic prosperity through growth and development of entrepreneurship, policymakers and governments are turning to female entrepreneurs as a way of achieving this (Adetiloye et al., 2020). However, female business owners face diverse challenges of which access to finance is most critical (Onoshakpor, Cunningham & Gammie, 2022). While research suggests that their inability to access finance comes from a lack of enough accumulated personal funds (Bastian, Sidani & El-Amine, 2018; Sindani, 2022), which results in lower levels of overall capitalisation, reduced ratios of debt finance and venture capital financing (Onoshakpor, Cunningham & Gammie, 2023). While these reasons convey much of the findings of western literature, there is still a dearth of knowledge from non-western contexts and sub-Saharan African contexts in particular. In addition to highlighting the challenges around access to finance for female entrepreneurs from mainstream finance institutions, the ways in which these disadvantaged groups finance their businesses are also a relevant contribution to the body of literature. This research, therefore, investigates women's financing mechanisms in the context of two sub-Saharan African countries with strong arguable patriarchal structures and offers solutions on how these financing mechanisms can be supported in order to support more female entrepreneurs.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".