MAPEO REPARADOR: DESHACIENDO LA CIUDAD BLANCA, PATRIARCAL Y CLASISTA CON MUJERES EN LA DIÁSPORA RESIDENTES EN CHILE
Bibliographic record
Abstract
Este estudio explora un método de mapeo participativo que documenta las experiencias urbanas distintivas de las comunidades en la diáspora, reivindicando la agencia de estas experiencias para dar forma a futuros urbanos equitativos. El estudio se centra en mujeres inmigrantes económicamente vulnerables y racializadas, generando conocimiento en conjunto con un grupo poblacional que ha sido históricamente omitido de los estudios urbanos a pesar de su creciente presencia en las ciudades chilenas. Invitamos a las participantes a apropiarse de un mapa urbano abstracto y dejar su huella en él, enfatizando su capacidad para liderar procesos de cambio. Denominamos este proceso “mapeo reparador” debido a que los mapas ofrecen una guía para abordar las injusticias históricamente imbricadas en el hacer-ciudad. Al comparar nuestros resultados con los datos abstractos existentes, demostramos que los estudios sobre la equidad urbana deben basarse en la experiencia directa de las comunidades
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".