La calidad de los procesos participativos locales: indicadores y factores explicativos contextuales. El caso de Andalucía
Bibliographic record
Abstract
En este trabajo se revisan los distintos indicadores que la literatura ha propuesto para medir la calidad de las experiencias participativas ciudadanas a nivel local. A continuación, se seleccionan una serie de variables para medir este fenómeno y se observa su relación con las características de los municipios en que se desarrollaron. Finamente se propone un modelo multivariante para estimar los indicadores básicos de la calidad de los procesos participativos locales a partir de estas variables contextuales. Para los análisis se ha utilizado una encuesta realizada durante el otoño de 2009 a técnicos de unos 120 municipios andaluces. La misma recoge información sobre la existencia y características de este tipo de procesos participativos desde el año 2003. El estudio concluye que los factores contextuales resultan hasta cierto punto influyentes, y decididamente importantes para algunas dimensiones de la calidad, como la deliberación.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".