Accessibility of higher education: socio-economic aspect
Notice bibliographique
Résumé
The paper is devoted to investigation of the problems of inequality in higher education in three main aspects:• Analysis of the results of the global rankings of national educational systems on access to higher education;• The role of mass distance education in promoting equality in higher education;• International university rankings in the context of the development of elite and mass higher education.1. Analysis of the results of two global rankings of national educational systems (by the Canadian researchers Alex Usher, Amy Cervenan, Jon Medow), confirmed the expediency of the two rankings that divide the social and economic aspects of inequality in higher education. To assess Russia's place among 14 countries surveyed, there were determined the approximate values of the indicators of both rankings characterizing the Russian system of higher education: the values of eight indicators for determining affordability, and four indicators for the social aspects of accessibility. When determining the strengths and weaknesses of the Russian higher education system the results of the rankings for each indicator were taken into account.The main results of the assessment of inequality in Russian higher education:• At an estimated assessment Russia refers to one of the least successful countries with the low ranking of the accessibility of higher education (social aspect) and with a relatively good indicator in the ranking of affordability of higher education (financial aspect);• In the final ranking of accessibility (social aspect) Russia occupies one of the last places due to the low rate of social equality in education, which has the maximum weight of the four indicators. The values of Russian indices of three other indicators are relatively high: 3-4th place on the participation of young people in higher education; 4-5th place on the achieved level in higher education of young people; 8th place in gender parity index.2. The case of Russia shows the efficiency of mass distance-teaching University (mega-University) raising equity in access to higher education, including people living in geographically remote areas and socially vulnerable groups of the population (persons with disabilities, prisoners, military personnel etc.). 3. Consideration of methodological bases and the results of five international university rankings (2007-2013) showed:• The role of Webometrics Ranking of World Universities in the assessment of national systems of higher education, taking into account the scale factor and the development of regional universities in the country.• The growth of the network activity of Russian universities, especially regional (in the latest rankings of Webometrics among 3000 world's best universities are universities of all federal districts of Russia).
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».