Financiamento público da educação superior: um estudo comparativo entre Brasil, Canadá e China
Bibliographic record
Abstract
This doctoral dissertation aims to demonstrate the importance of public funding for the development of actions and initiatives in higher education, using as reference indicators and public policies for the financing of higher education in Brazil, Canada and China between 2003 and 2012. For this purpose, we present concepts of planning, finance and public budget, showing the functions of government, the evolution of the public budget and government intervention and its economic responsibilities. Once we know the role played by government in all dimensions, was limited then to the dimension of higher education, starting with the main challenges of the global higher education, focusing on the effects of globalization. Later, as a junction of the two aforementioned topics, this study presents the public funding of higher education, detailing the various actions and initiatives of the Brazilian, Canadian and Chinese government. As regards to the methodology, this dissertation is outlined on the principles of Functionalist paradigm, defined as an exploratory study, qualitative and quantitative approach, applied, empirical and multi case study. Data were collected through documental research, bibliographic research, semi-structured interviews with government officials and unstructured questionnaires with experts in higher education and student leaders of the respective countries. The quantitative data analysis was divided into three stages. In the first stage, a comparative analysis was made between general indicators of Brazil, Canada and China, using log-linear regression models via Quasi-likelihood method, in order to understand the performance of the three countries. In the second stage, a correlation analysis was performed between the same indicators using a Spearman correlation matrix and a perceptual map generated via Principal Component Analysis, in order to understand which indicators have significant influence each other. In the third and final stage, a performance analysis for public policies of the countries studied was performed, showing the performance of all public policies analyzed. For the qualitative analysis, the data collected through the questionnaires unstructured and semi-structured interviews were treated using as reference the categorical content analysis, in order to confirm or refute the findings in quantitative stage. From the analysis of quantitative and qualitative data, propositions were written in order to contribute to the debate on the progress of higher education in Brazil. The propositions were outlined in three major dimensions: propensity propositions, funding propositions and structural propositions. The propensity propositions analyzed the impact of variables that directly relate to the expansion of higher education, generating at the end a structural model. The funding propositions demonstrated investment options for the Brazilian higher education, either by creating new policies or adequacy of existing policies. The structural propositions suggested organizational changes for the Brazilian higher education system. Finally, it was demonstrated the need to promote progress in higher education in Brazil, and as evidenced, nations that had good results can be an excellent reference to finally transform the country through education.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".