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Record W4205759255 · doi:10.1344/ridas2021.12.9

Un compromiso para la transformación social: el plan UC para consolidar a A+S en América Latina

2022· article· es· W4205759255 on OpenAlexaff
F. Del Valle, R. Fontana, Javiera Ocampo Sepúlveda

Bibliographic record

VenueRIDAS Revista Iberoamericana de Aprendizaje y Servicio · 2022
Typearticle
Languagees
FieldSocial Sciences
TopicHigher Education and Sustainability
Canadian institutionsAdidas (Canada)
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

En marzo de 2021, la Pontificia Universidad Católica de Chile (UC) inició su plan de acompañamiento regional en el marco del proyecto Uniservitate en América Latina. Este proyecto global pretende institucionalizar y potenciar la implementación de la metodología de aprendizaje servicio (A+S) en universidades católicas del continente, en coherencia con su misión institucional promoviendo así una educación integral que permita formar ciudadanos socialmente responsables. El objetivo del artículo es mostrar las etapas del plan de acompañamiento de la UC para las universidades Católica de Argentina, Católica de Pernambuco, Pontificia Javeriana de Bogotá y Católica de Ecuador. El plan de acompañamiento para institucionalizar el aprendizaje-servicio en el continente posee un diseño definido con elementos fuertes en la formación, el acompañamiento y la evaluación siendo estos los ejes para una primera etapa de implementación en las universidades acompañadas. El aprendizaje-servicio es una metodología que busca desarrollar una educación integral a través de la formación de la responsabilidad social en el estudiantado y su institucionalización representa una oportunidad para que las universidades profundicen su contribución a una sociedad más justa y equitativa.

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 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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.879
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.003
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.339
Teacher spread0.319 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations0
Published2022
Admission routes1
Has abstractyes

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