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Record W1705523050

Cuando las escuelas se convierten en zonas muertas de la imaginación: Manifiesto de la Pedagogía Crítica

2015· article· es· W1705523050 on OpenAlexaff
Henry A. Giroux

Bibliographic record

VenueAmericanae (AECID Library) · 2015
Typearticle
Languagees
FieldSocial Sciences
TopicDiverse Education Studies and Reforms
Canadian institutionsMcMaster University
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Este artículo examina el llamado movimiento de reforma de la nueva escuela dirigido por una serie de ideólogos de derecha, multimillonarios, y fundaciones. Argumenta que en vez de ser reformadores, estos agente son parte de una contra-revolución en la educación estadounidense para desmantelar las escuelas públicas no porque están fracasando, sino porque son públicas; y así hacer un reclamo -aunque deficiente- al servicio del bien público. No sólo estos no-reformistas han presionado para promover prácticas áulicas que son totalmente instrumentales y reduccionistas, sino que también han convertido las escuelas públicas estadounidenses en máquinas de la desimaginación, divorciadas de cualquier noción viable de gobernabilidad democrática y valores. Matan a la imaginación de los profesores y estudiantes al confundir la educación con el entrenamiento, y la enseñanza con prácticas instrumentales que aturden la mente. En oposición a estas no-reformas, el artículo argumenta a favor de las escuelas como esferas públicas democráticas y construye una arquitectura teórica para el desarrollo de los elementos de una pedagogía crítica que ofrecen un desafío directo a la noción de las escuelas como zonas muertas dedicadas en su mayoría al entrenamiento y evaluación de los estudiantes.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0120.045
Scholarly communication0.0170.013
Open science0.0020.008
Research integrity0.0050.011
Insufficient payload (model declined to judge)0.0070.002

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 head0.349
Teacher spread0.331 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2015
Admission routes1
Has abstractyes

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