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Presupuestos participativos: ¿neoliberalizadores?, ¿educativos?

2021· article· es· W4200329568 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEncounters in Theory and History of Education · 2021
Typearticle
Languagees
FieldSocial Sciences
TopicPublic Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.853
Threshold uncertainty score0.752

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.017
GPT teacher head0.333
Teacher spread0.316 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it