| Title |
Racial Inequality in Education in Brazil: A Twins Fixed-Effects Approach
|
|---|---|
| Published in |
Demography, July 2016
|
| DOI | 10.1007/s13524-016-0484-8 |
| Pubmed ID | |
| Authors |
Letícia J. Marteleto, Molly Dondero |
| Abstract |
Racial disparities in education in Brazil (and elsewhere) are well documented. Because this research typically examines educational variation between individuals in different families, however, it cannot disentangle whether racial differences in education are due to racial discrimination or to structural differences in unobserved neighborhood and family characteristics. To address this common data limitation, we use an innovative within-family twin approach that takes advantage of the large sample of Brazilian adolescent twins classified as different races in the 1982 and 1987-2009 Pesquisa Nacional por Amostra de Domicílios. We first examine the contexts within which adolescent twins in the same family are labeled as different races to determine the characteristics of families crossing racial boundaries. Then, as a way to hold constant shared unobserved and observed neighborhood and family characteristics, we use twins fixed-effects models to assess whether racial disparities in education exist between twins and whether such disparities vary by gender. We find that even under this stringent test of racial inequality, the nonwhite educational disadvantage persists and is especially pronounced for nonwhite adolescent boys. |
X Demographics
The data shown below were collected from the profiles of 11 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 27% |
| Brazil | 3 | 27% |
| Bolivia, Plurinational State of | 1 | 9% |
| United Kingdom | 1 | 9% |
| Denmark | 1 | 9% |
| Unknown | 2 | 18% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 55% |
| Scientists | 4 | 36% |
| Science communicators (journalists, bloggers, editors) | 1 | 9% |
Mendeley readers
The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 58 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 19% |
| Professor | 7 | 12% |
| Researcher | 5 | 9% |
| Student > Bachelor | 5 | 9% |
| Professor > Associate Professor | 5 | 9% |
| Other | 10 | 17% |
| Unknown | 15 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Social Sciences | 21 | 36% |
| Economics, Econometrics and Finance | 7 | 12% |
| Medicine and Dentistry | 3 | 5% |
| Psychology | 3 | 5% |
| Nursing and Health Professions | 2 | 3% |
| Other | 6 | 10% |
| Unknown | 16 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 29. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 November 2023.
All research outputs
#1,367,096
of 25,576,275 outputs
Outputs from Demography
#363
of 2,011 outputs
Outputs of similar age
#25,564
of 379,423 outputs
Outputs of similar age from Demography
#9
of 19 outputs
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