Aquilombar the city: women of the favelas and city-making in Rio de Janeiro
Bibliographic record
Abstract
This paper explores the concept of aquilombar as a paradigm for understanding the city-making practices of women living in the favelas of Rio de Janeiro. Drawing on Afro-Brazilian historian Beatriz Nascimento’s conceptualization of the quilombo, I argue that aquilombar—the act of creating quilombos—engages with Afro-diasporic cosmologies and shapes the everyday practices of city-making among favela women. Situated within a broader decolonial and feminist framework in urban studies, these practices are understood as a pluriversal-izing form of urbanization—that is, as part of the multiple social imaginaries and worldviews shaping urban transformations. Through an extensive examination of the historical origins of the terms kilombo, quilombismo, and quilombo, with a primary focus on Nascimento's scholarship, I first propose a working definition of the verb aquilombar. Drawing on key examples collected during my most recent 2025 fieldwork, alongside my longer engagement with the favelas, I then connect Nascimento's understanding of the quilombo with favela women's own interpretations. In doing so, this paper highlights the specific gestures, actions, and ways of knowing through which women in the favelas actively shape their city, despite living within an often-hostile urban environment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.013 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".