Back to <scp>L</scp>ittle <scp>H</scp>avana: Controlling Gentrification in the Heart of <scp>C</scp>uban <scp>M</scp>iami
Bibliographic record
Abstract
Abstract In this article we examine the nature and implementation of governing strategies to control the gentrification of Little Havana, the symbolic heart of Cuban Miami. We ask how Cuban American power relations at the neighborhood level operate to ‘produce’ the citizen best suited to fulfill and help reproduce policies and practices of ‘securing’ in order to gentrify Little Havana. Based on long‐term ethnographic research in Little Havana and Miami, our analysis reveals how governance operates through neighborhood‐level intermediaries and interpersonal relations. We apply Foucault's ‘pastoral power’ to Miami's Cuban exile community in order to explain how the ‘Cuban‐ness’ and ‘Latin‐ness’ of governing relations and the personification of political power are crucial to socio‐spatial control in Little Havana. Elites shape the conduct of individuals in order to achieve strategic goals in the name of community interest. Residents are key partners in the relational ensemble that governs and disciplines the neighborhood comprised mostly of low‐income, Central‐American immigrants.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".