Financiamento público da educação superior: um estudo comparativo entre Brasil, Canadá e China
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,008 |
| Études des sciences et des technologies | 0,004 | 0,002 |
| Communication savante | 0,004 | 0,001 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».