Can conditional cash transfer programs generate equality of opportunity in highly unequal societies? Evidence from Brazil
Bibliographic record
Abstract
This article examines whether the state, through conditional cash transfer programs (CCT), can reduce the poverty and extremely poverty in societies marred by high levels of income concentration. We focus on one of the most unequal countries in the globe, Brazil, and analyze the extent to which this country's CCT program - Bolsa Família (BF, Family Grant) program - is able to improve the life chances of extremely poor beneficiaries, through the three major goals of PBF: First, to immediately end hunger; second, to create basic social rights related to healthcare and education; finally, considering also complementary policies, to integrate adults into the job market. The analysis relies on a quantitative survey with 4,000 beneficiaries and a qualitative survey comprised of in-depth interviews with 38 program's participants from all the regions of the country in 2008, it means that this study is about the five first years of the PBF. In order to answer the research questions, we ran four probit analyses related: a) the determinants of the realization of prenatal care; b) the determinants of food security among BF beneficiaries, c) the determinants that adult BF recipients will return to school, d) the determinants that a BF beneficiary will obtain a job. Important results from the study are: First, those who before their participation on PBF were at the margins have now been able to access healthcare services on a more regular basis. Thus, the women at the margins who were systematically excluded - black women, poorly educated and from the North - now, after their participation in the CCT program, have more access to prenatal care and can now count with more availability of public healthcare network. Second, before entering the Bolsa Família program, 50.3% of the participants faced severe food insecurity. This number went down to 36.8% in very five years. Men are more likely than women; non-blacks more likely than blacks; and South and Centre-West residents more likely than Brazilians from other regions; to become food secure while participating in BF. Third, instead, that moment in 2008, a small proportion of the adult participants indeed were able to return to school and to increase their educational qualifications. The lack of technical skills and the huge predominance of informal employment are central social problems in Brazil and that the PBF has failed to address such issues. This study confirms what other previous studies have reported on: BF has had a positive impact in reducing poverty in the country. Hence the main contribution of the present study is in identifying the main determinants of unequal results among individuals participating in the BF program: why some, but not others, are more easily able to access the healthcare or to overcome food insecurity while in the program?
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".