Subversive formalization: efforts to (re)form land, labor, and behavior in a carioca favela
Bibliographic record
Abstract
State entities in Brazil have rolled out numerous programs to “integrate” precarious settlements into the so-called formal city of Rio de Janeiro. Two of the most visceral integration projects in Rio’s favelas have been infrastructural upgrading and public security via military police occupation. Drawing on participant observation, interviews, and policy analysis, in this paper I trace how these projects attempt to formalize land, labor, and behavior in a complex of favelas called Complexo do Alemão. Inspired by postcolonial urban approaches to formalization, I argue that formality/informality as it operates through these projects is, in part, a performative distinction deployed by the state, echoing elite and popular socio-spatial imaginaries. I add, however, that non-state actors are also involved in their own practices of formalization. Residents themselves are re-making diverse forms of property, employment, and behavior through processes of subversive formalization, informed by their geographically-embedded and historical relationships with one another.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.018 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 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".