Scholarly publication of Brazilian researchers across disciplinary communities
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.074 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".