School Infrastructure and Socioeconomic Status in Brazil

Abstract

The paper analyzes the infrastructure of public schools in Brazil by examining the hypothesis that the institutions with poor material conditions have students with a lower socioeconomic level. The characterization of the institutions is based on data from the 2013 School Census, submitted to latent class modeling, which revealed the existence of four different school profiles. In order to carry out a socioeconomic differentiation of the institutions, the Poverty In School Indicator (IPE in Portuguese) was created, which uses data from Bolsa Família, an income transfer program. The results confirm the available body of literature on the subject by showing that the location, the administrative dependency, the size of the school and the region of the country in which it is inserted are related to the inequalities of school infrastructure. In addition, the study finds that the public schools with better infrastructure conditions generally have lower proportions of poor students. On the other hand, most institutions with the worst infrastructure profile have mostly poor or extremely poor students, confirming the hypothesis of this research.

Indicadores multidimensionais para avaliação da infraestrutura escolar: o ensino fundamental

“…The results per state are in the Appendix (Table A4). We found that the patterns of regional inequalities are similar to those in the literature (GOMES;DUARTE, 2017;CERQUEIRA;SAYWER, 2007;SOARES NETO et al, 2013a;2013b). Schools in the South and Southeast systematically have higher averages than schools in the North and Northeast.…”

“…Although schools are better, our results do not show that most students are enrolled in public schools with high quality conditions, according to Gomes and Duarte (2017). There is still a lot be done, mainly for municipal rural schools in the North and Northeast.…”

“…This result may be explained by the fact that the schools with more advanced grades have facilities and resources that were assessed in this study; for example, science laboratories. Soares Neto et al (2013a) and Gomes & Duarte (2017) observed a different pattern of this item in the assessment of the infrastructure of elementary schools with primary and lower secondary education. Our results reinforce these findings.…”

“…The Brazilian literature includes many studies that use Brazilian School Census data to characterize infrastructure (ALMEIDA et al, 2011;CERQUEIRA;SAWER, 2007;GOMES;DUARTE, 2017;MATOS;RODRIGUES, 2016;PASSADOR;CALHADO, 2012;PIERI;SANTOS, 2014;PONTILI;KASSOUF, 2007;RIANI;RIOS-NETO, 2008; SOARES; ALVES; XAVIER, 2016; SÁTYRO; SOARES, 2007; SOARES NETO et al, 2 (cont.) children from 0 to 3 years of age (nursery schools) and from 4 to 5 (pre-school); (ii) elementary schools, divided into ISCED 1 or primary education, for children aged from 6 to 10 years of age, and ISCED 2 or lower secondary education, for children aged approximately 11 to 14 years; and (iii) ISCED 3 or upper secondary education, with a minimum of three years' attendance, from 15 to 17 years of age (BRASIL, 2016a).…”

Framing the discussion of microorganisms as a facet of social equity in human health

“…Water damage and building deterioration contribute to indoor air pollution and accrual of microorganisms, often making the space unsuitable for occupants [71], something that disproportionately affects low-income populations [72,73]. Many schools or other public infrastructure buildings contain high microbial biomass in the air and on surfaces [71,74], which can also disproportionately affect people of lower SES [75,76]. Similarly, very little infrastructure or policy considers microorganisms in prisons, as evidenced by a lack of hand-washing stations or showers, inadequate food service infrastructure, or difficulty in cleaning or quarantining areas [77].…”