Financiamento da Educação Superior: A Realidade das Universidades Públicas Canadenses
Bibliographic record
Abstract
O objetivo deste trabalho é analisar o financiamento da educação superior em universidades públicas canadenses realizando uma comparação das fontes de recursos financeiros e as despesas por categoria econômica. Os dados foram levantados por intermédio dos demonstrativos financeiros existentes na Internet de cada instituição. Fazem parte do estudo as universidades provinciais do Canadá: University of British Columbia (UBC), University of Toronto (Toronto) e University of Alberta (Alberta). Os resultados a pesquisa apontam que a principal fonte de recursos financeiros das universidades Canadenses são recursos provenientes do governo. Dentre as três universidades, a UBC apresenta uma maior participação na média dos últimos três anos com 65,48%, seguida pela Alberta com 63,81% e Toronto com 54,35%. Em relação às despesas, percebe-se que nas universidades pesquisadas a maior despesa é referente aos salários e benefícios passando de 60 para 70%, na média dos últimos três anos.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.061 | 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; both teacher heads agree on what is shown here.
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".