Financial Inclusion and Intersectionality: A Case of Business Funding in the South African Informal Sector
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
Financial inclusion is a critical tool in the fight against poverty. This is especially important in economies where informal markets are prevalent due to the pervasion of market failures. Marginal identities such as gender, income and race are generally noted in the literature as factors influencing access to finance. However, these marginalities are often investigated linearly, with little attention paid to the fact that they interact to compound financial exclusion. Using a survey of informal traders, the paper investigates how having multiple marginalities influences the choice of start-up capital. A sample is drawn from three different provinces in South Africa. A multinomial logit model is estimated. Using a simulation of representative groups, the paper shows that multiple marginalities matter in accessing finance. Education emerges as the most important factor that can temper the effect of other marginalities in the financial sector. Both females and blacks with higher levels of education have better access to more stable sources of start-up capital.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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