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Record W6987883408

Vehículos de significación y transformación de la cultura universitaria en Latinoamérica

2016· article· en· W6987883408 on OpenAlexaboutno aff

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicPhilosophy and Education Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsMeaning (existential)Order (exchange)Face (sociological concept)Point (geometry)Matrix (chemical analysis)Embodied cognitionLatin Americans
DOInot available

Abstract

fetched live from OpenAlex

RESUMEN "La significación se encarna y encuentra su soporte en la intersubjetividad humana, en el arte, en los símbolos, en el lenguaje, en las vidas y en los hechos de las personas…" (Lonergan, 1994, p. 57).Este ensayo parte del supuesto de que para responder a la necesidad de reformar la educación superior en Latinoamérica y enfrentar los desafíos del cambio de época, resulta indispensable cambiar, además de las prácticas y las estructuras organizacionales de la educación, la cultura universitaria.Para apuntar hacia una reforma universitaria profunda que incluya la transformación de esta cultura resulta pertinente el análisis y renovación de los vehículos de la significación planteados por Lonergan: el clima intersubjetivo de la universidad, el arte que rodea la vida universitaria, el lenguaje predominante entre los profesores, los símbolos de la tradición universitaria y las personas que participan en la formación.A partir de la propuesta de los siete saberes necesarios para la educación del futuro escrito por Morin (2001), este trabajo aporta una matriz que describe de manera preliminar algunos elementos de transformación de los vehículos de la significación para cambiar la cultura universitaria en Latinoamérica y puede servir como instrumento para la investigación sobre los elementos de dicha transformación.

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.069
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.016
Scholarly communication0.0090.004
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.026
GPT teacher head0.288
Teacher spread0.262 · 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 designQualitative
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
Published2016
Admission routes1
Has abstractyes

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