The making of a feminist urban space and commons: the case of Montevideo’s Plaza las Pioneras
Bibliographic record
Abstract
Inaugurated in March 2020 in Montevideo (Uruguay), the Plaza las Pioneras is a new minimalist public space in tribute of Uruguay’s feminists or “pioneers”. It is both a city managed public square and an adjacent building given by the city to an assembly of six feminist collectives to administrate and use for the common good. It a rare example of an urban feminist space and commons. This article argues that conditions specific to the political, social and temporal context in Montevideo led to the creation of the Plaza. The goal of this article is to analyse process around the creation and development of the Plaza as well as the actors involved, their role, dynamics and intentions. It also aims at using this case study to enhance the concept of feminist urban commons. This article is based on documentary research, 13 interviews and participatory observation that took place in November 2022 in Montevideo. It finds that the context specific conditions in which it emerged as well as the process led to its feminist nature and goals. This also shaped how it is used by feminist collectives to advance their own goals. This case study is important to understanding the production process of feminist urban spaces and commons, their contribution to the feminist movement and to a feminist city. It implies that leadership at the municipal level is key, as are horizontal partnerships between government and the feminist movement.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.017 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".