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Record W3192687339 · doi:10.1075/jerpp.20012.bau

Scholarly publication of Brazilian researchers across disciplinary communities

2021· article· en· W3192687339 on OpenAlexaff
Laura Knijnik Baumvol, Simone Sarmento, Ana Beatriz Arêas da Luz Fontes

Bibliographic record

VenueJournal of English for Research Publication Purposes · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPortugueseDisciplineContext (archaeology)PublishingPreferenceInclusion (mineral)Knowledge productionCurriculumEnglish languagePolitical sciencePublic relationsWork (physics)SociologyLibrary scienceSocial sciencePedagogyKnowledge managementPsychologyGeographyEngineeringMathematics educationLinguisticsComputer science

Abstract

fetched live from OpenAlex

Abstract This paper examines the context of scholarly knowledge production and dissemination in Brazil by comparing the publishing practices in both Portuguese and in English of Brazilian scholars who hold a research grant, across eight fields of knowledge. Data consists of 1,874 Curricula Vitae and the analysis focused on the language, number, and genres of publications over a three-year period (2014 to 2016). The study revealed a clear contrast regarding the more frequent use of English by researchers in the ‘harder’ sciences and the preference for Portuguese by those in the ‘softer’ sciences. The results also suggested an interconnection in which scholars who published the most tended to adopt English. Multiple factors involved in the genre and language choices made by academics were analysed, such as characteristics of the work produced by each disciplinary community, the audience of the research, the type of language used, and the need to obtain research funding. This investigation can potentially inform policies and investments in Brazilian higher education and research to provide continued support specific to the needs of different disciplinary communities, as well as foster the inclusion of multilingual scholars who do not have English as their first language in the global arena of knowledge production and dissemination.

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)0.031
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication, 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 score0.516
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.031
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.005
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.245
GPT teacher head0.464
Teacher spread0.220 · 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

Citations5
Published2021
Admission routes1
Has abstractyes

Explore more

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