Vulnerability and risk management: the importance of financial inclusion for beneficiaries of conditional transfers in Colombia
Bibliographic record
Abstract
This paper studies effects of savings, credit and insurance on the vulnerability of households to idiosyncratic income shocks. This approach is made through matching methods using data from around 650 households that have been beneficiaries of the Colombian conditional cash-transfer programme Familias en Acción. Results indicate that access to savings and credits, both formal and informal, have significant and differentiated effects on the vulnerability of families. These results focus attention on promoting financial inclusion for a population group that has generally been excluded from the formal financial system. Résumé Cette étude examine les effets des épargnes, de crédit et de l'assurance sur la vulnérabilité des foyers aux chocs idiosyncrasiques de revenus. Cette approche est faite en jumelant des méthodes utilisant les données d'à peu près 650 foyers qui ont bénéficié du programme de transfert conditionnel de fonds Familias en Acción. Les résultats indiquent que l'accès aux épargnes et crédits, à la fois formels et informels, a des effets importants et différenciés sur la vulnérabilité des familles. Ces résultats mettent l'accent sur la promotion de l'inclusion financière pour une section de la population qui a généralement été exclue jusqu'à présent d'un système formel financier.
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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 | 0.001 | 0.008 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".