Brazil’s <i>Bolsa Família</i> Programme
Bibliographic record
Abstract
Abstract The first experiences with conditional cash transfers (CCTs) took place in the mid-1990s in Brazil, at the local level. They were later adopted at the national level in Mexico (in 1997, with the Prospera programme), in Brazil (by 2001, with several CCTs), as well as in other Latin American countries. In 2003, the Bolsa Família programme unified previous national CCTs and massively expanded their number of beneficiaries. It managed to reach almost a quarter of the Brazilian population and became the most progressive cash transfer made by the state. Over time, numerous evaluations measured the programme’s impacts on the reduction of poverty and inequality and the improvement of education and health indicators. Domestically, these impacts, together with strong support by researchers and multilateral organizations, eventually translated this ‘good policy’ (quality design and implementation) into ‘good politics’ (political support from beneficiaries and non-beneficiaries alike, and public commitment to the programme’s maintenance by all relevant political forces). The Bolsa Família ‘model’ is now adopted in sixty-seven different countries according to the World Bank in 2017.
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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 | 0.001 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".