Can the Use of English as a Medium of Instruction Promote a More Inclusive and Equitable Higher Education in Brazil?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this paper, we present the status quo and challenges regarding the use of additional languages as a medium of instruction in Brazilian higher education. We begin by contextualizing the importance of the process of internationalization at home (IaH) and additional languages in higher education. Next, the teaching of additional languages in Brazil, which has been until very recently relegated to the private sector and accessible only to an elite, is introduced. We then provide an overview of the present state of affairs of English as a Medium of Instruction (EMI) in the country, which is still in its infancy. We move on to describe different ways in which language and content can be integrated in higher education, as well as how EMI can be introduced in disciplinary courses. We finish concluding that EMI can maximize the learning of academic English by Brazilian students and content instructors, as well as encourage a more international higher education and balanced academic mobility by allowing foreign students to study in Brazil while preserving and even increasing the international interest in the Portuguese language. In a country located in the periphery of knowledge production and dissemination, we understand that the adoption of EMI can potentially foster the inclusion of more Brazilians in the global academic and research scenario. It gives them access to the knowledge produced internationally and, at the same time, enables the research produced in the country to be disseminated globally.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it