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Record W7027875004

Descolonialidad y producción del conocimiento en internacionalización de la educación superior

2023· article· en· W7027875004 on OpenAlexaboutno aff

Bibliographic record

VenueRevista de Lengua y Literatura (National University of Comahue) · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicLatin American Cultural Politics
Canadian institutionsnot available
Fundersnot available
KeywordsInternationalizationTheme (computing)VisionLatin AmericansEvent (particle physics)Presentation (obstetrics)
DOInot available

Abstract

fetched live from OpenAlex

The REDALINT Network organized on June 10, 2022 the webinar: "Decoloniality and production of knowledge in the internationalization of higher education" with the participation of three leading specialists in the subject: Dr. Fernanda Leal, from the Universidade Federal de Santa Catarina,, from Brazil; Dr. Sharon Stein, from the University of British Columbia, from Canada; and Dr. Eduardo Rinesi, from the Universidad Nacional de General Sarmiento, Argentina The presentation and moderation of the event was carried out by the members of the REDALINT Network: María Julieta Abba, from UNISINOS, Brazil; Paulina Latorre, from UFRO, Chile; and Lionel Korsunsky, from UNCo, Argentina; who contextualized the theme of the event and started the debate based on two essential questions about the characteristics of internationalization processes at the regional level and the different critical theoretical constructions. Thus, they also inquired about the possibilities of generating an autonomous perspective of university internationalization and the strategies to carry it out from practices and concrete actions. Based on two initial questions, the specialists discussed their visions of regional university internationalization from their different perspectives and experiences, generating an interesting debate that highlights the main aspects of the process of building an alternative model of internationalization for higher education institutions. from the Latin American region.

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)0.001
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 score0.944
Threshold uncertainty score0.669

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.308
Teacher spread0.296 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2023
Admission routes1
Has abstractyes

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