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Record W2606154966 · doi:10.5539/elt.v10n5p127

The Relevance of English in Colombian Scientific Research Awareness

2017· article· en· W2606154966 on OpenAlexvenueno aff
Ivan Dario Arellano

Bibliographic record

VenueEnglish Language Teaching · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsnot available
FundersUniversidad Tecnológica de Pereira
KeywordsLatin AmericansRelevance (law)VisibilityPsychologyPublishingObstacleEnglish languageMathematics educationSociologyPedagogyPolitical scienceGeographyLaw

Abstract

fetched live from OpenAlex

Even though the majority of Colombian professors are also involved in research, they have limitations in their English language skills that separate them from the rest of the scientific society. Evidently, these limitations have become an obstacle in the awareness of professors’ modest, but no less important, research work. In order to carry out this study, we selected three remarkable higher education institutions of Pereira, Risaralda in Colombia. We used collected data from 2012 to 2015. A quantitative analysis of the number of articles in English in comparison to Spanish was done. Even though there has been an increasing number of articles in English, they are still limited. This research suggests an approach to evaluate the hypothesis raised by the authors that states that the low English-language proficiency of the scientists is affecting the visibility of Colombian and, overall, Latin American science. We propose to increase the visibility of Colombian science by publishing research papers in both languages, Spanish and in English. Finally, Latin American English writing skills require attention from their own governments to increase the awareness and contribution of these countries in a globalized world.

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)0.008
metaresearch head score (Gemma)0.029
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.329
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0060.001
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.049
GPT teacher head0.335
Teacher spread0.286 · 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 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

Citations3
Published2017
Admission routes1
Has abstractyes

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