Almost 4 out of every 10 candidates for councilor who said they were black, brown or mixed race were not confirmed as belonging to the declared race, according to research by Gemaa (Affirmative Action Multidisciplinary Study Group), linked to Uerj (State University of Rio de Janeiro ).
According to the (Superior Electoral Court), municipal councils had 432,002 requests for candidate registrations for councilor, 176,617 of which were self-declared browns, 50,772 were black and 2,461 were indigenous.
The group set up a racial heteroclassification panel —when the classification is done by third parties— made up of five researchers, three of them black and two white. 4,200 applications were evaluated, drawn from the total number of council candidates registered with the TSE, reaching a representative sample of candidates.
To carry out the analysis, the researchers considered the photo of the candidates’ ballot boxes. They were instructed to make the racial classification according to the division adopted by: yellow, white, indigenous, brown and black.
The larger sample, with more than 4,000 people, mitigated, according to Luiz Augusto Campos, coordinator of Gemaa and professor of sociology at Uerj, the limiting factor of the classification being carried out using photos, which do not always represent the candidate well or have good quality. . The limitation was identified in around 5% of cases.
The analysis was carried out as academic research and does not affect the election results of the candidates evaluated.
Playing against the central hypothesis that the presence of black people is reduced in positions of power and taking into account that race is a “complex and historically determined social construction”, experts were advised to, when in doubt, classify people in the most dark.
Even so, 38% of self-declared PPI candidates (black, mixed race or indigenous) were classified as white or yellow by at least 3 of the 5 researchers.
“This means that almost 4 in every 10 PPI candidates did not have their self-declaration validated by the analysis team, impacting 20% of the total number of applications”, points out an excerpt from the study.
According to Campos, the panel also identified a difference in classification in the opposite direction: people identified by them as PPIs who said they were white. The percentage, however, was much lower in this case, just 5%.
The research also pointed out which parties had the highest rates of discrepancy between self-declared race and that assessed by the panel. PRD, PDT, PL and União Brasil showed the biggest divergences. Avante and Solidarity, the smallest. PT, PSD, Podemos and PSDB were within the average.
According to Campos, some reasons may explain the difference between the parties. The main one, he points out, is probably the disregard that some acronyms have for the racial classification of their members.
“Although the variable is self-declaration, those who record this data are the party directories”, he states. “Some of them register anyway.”
The racial classification of candidates interferes with the distribution of resources within parties. The objective is to reduce the still present inequality. In 2020, the (Federal Supreme Court) determined that campaign acronyms and funds should be proportional to the number of black candidates.
The following year, Congress determined that votes given to black people in the 2022 to 2030 elections would count double for the purpose of distributing resources from party and electoral funds.
In 2024, however, the Amnesty PEC was approved by the Chamber of Deputies, which limited the electoral budget for black people to 30%, after widespread non-compliance by parties with the STF’s determination.
Gemaa also identified a significant difference between Brazilian regions. The South is the one with the most discrepant cases — 48% of candidates said to be black, mixed race or indigenous were classified as white by the panel. The Southeast region was the one with the smallest difference. Even in this case, the rate of 34% was considered high.
The racial fluidity between regions and the size of the brown category — considered the most ambiguous of all — are elements that can justify regional differences, according to Campos.
According to the researcher, the result of the research reignites the discussion about the need for institutions to intensify control over self-declaration.
He suggests measures such as identifying, in campaign materials, that the candidate has benefited from affirmative action policies. “This way the voter himself could judge whether that benefit is legitimate”, he says.
In 2024, the to curb fraud. According to , “in the event that a black or brown color is declared in the candidacy registration in disagreement with information on the electoral register or with a previous registration request, the candidate and the party, federation or coalition will be summoned to confirm the change of the racial declaration”.
Understanding the real number of candidate PPIs is important because inflated data can camouflage the intensity of the still present, points out Campos. , 39% of councilors elected in the 2024 elections said they were mixed race, 7% black and 0.4% indigenous.
