Confounding Anti-racism: Mixture, Racial Democracy, and Post-racial Politics in Brazil
Bibliographic record
Abstract
In this article, I analyze the particularity of post-racial ideology in Brazil. I examine recent deployments of mixture and racial democracy as re-articulations of historically hegemonic versions of these ideologies that minimize the problem of racism, deny its systemic nature, and deem ethno-racial policies as threats to achieving nonracial belonging and citizenship. Drawing on scholarship on race and racism from the United States, Brazil, and elsewhere in Latin America, I delineate a relational framework for analyzing the post-racial and apply this framework to three examples of post-racial ideology. Through these examples, I illustrate the problematic logics shaping aggressive investments in the post-racial as future promise to the detriment of addressing the unequal effects racial difference presents for inclusion/exclusion today. The article asserts the necessity of mounting transnational and interdisciplinary theoretical, epistemological, and practical strategies to challenge the ways post-racial ideologies rearticulate racial hierarchies, maintain racial subordination, and delimit social change.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".