Financial Literacy in Contexts of Vulnerability: Determinants Among Women Horticulturists in Guinea-Bissau
Bibliographic record
Abstract
Financial literacy plays a crucial role in promoting social and economic resilience, particularly in vulnerable contexts where access to education and financial services is limited. This study provides the first empirical analysis of the determinants of financial literacy among women horticulturists in Guinea Bissau in West Africa, a group that sustains household income and local markets through informal work. A survey with face-to-face data collection was employed, using a structured questionnaire to assess financial literacy across three dimensions: financial attitude, financial behavior, and financial knowledge. All 978 women horticulturists at the Pessubé Farm were invited to participate in the survey, and 200 valid questionnaires were returned and used as the final sample. Data were analyzed using descriptive statistics and multiple linear regression. Results revealed prudent and consistent financial behaviors, mid to low financial attitudes marked by concern about expenses and short-term planning, and limited conceptual financial knowledge, with frequent uncertainty on basic topics such as inflation, interest, and diversification. Regression analysis showed that financial satisfaction and food sufficiency are positively associated with higher levels of financial literacy, while overdue debts exert a negative effect. These findings highlight that strengthening financial literacy in low income and informal settings requires context sensitive strategies integrating financial education, debt management, and food security initiatives, emphasizing the multidimensional nature of financial literacy and its role in inclusive and sustainable development.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".