A Mercantilização da Universidade na América Latina: políticas neoliberais na educação superior
Bibliographic record
Abstract
The article addresses the advance of neoliberalism in higher education policies in Latin America and Brazil. To achieve this goal, the research follows a qualitative approach through critical analysis developed based on authors such as Laval (2019), Robertson; Dale (2017), Peroni; Caetano; Arelaro (2019). The methodology used includes a narrative review in the Scielo database. After reading the articles related to neoliberalism in higher education, the categories of analysis that indicated a crucial role in the expansion of knowledge about the advancement of neoliberal policies in higher education were established. From the introduction of neoliberalism in Latin America to the continuous privatization of this level of education in Brazil, university policies and management have been shaped to a market-aligned model. The studies demonstrate the need to rescue the main purpose of the university in the process of a human formation committed to emancipation.
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How this classification was reachedexpand
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 teacher head, 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".