Presupuestos participativos: ¿neoliberalizadores?, ¿educativos?
Bibliographic record
Abstract
El artículo estudia los presupuestos participativos (PPs) como una política que, diseñada e implementada originalmente como instrumento de democracia participativa y educación social, puede ser, transformada y en determinados contextos, funcional al proyecto neoliberal. Su análisis sirve para ponderar una nueva teoría de la Geografía humana que designaríamos metonímicamente como “políticas aceleradas”. Esta estudia el “neoliberalismo realmente existente” considerando los espacios y las formas en los que se manifiesta por todo el globo, con redes y nodos electrónicos que permiten procesos acelerados, horizontales y dependientes de los contextos, sin núcleos ni periferias. El artículo discute las características que deberían mantener los PPs para no convertirse en neoliberalizadores y las inconcreciones de la teoría en torno a sus agentes, uso de los medios digitales y la rapidez de las nuevas políticas, aspectos que incidirían en una nueva conformación del neoliberalismo y en la reformulación de los estudios del transfer.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.030 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".