A Study of Differentiation within the Ontario College Sector and the Impact of Geography
Notice bibliographique
Résumé
In 1965 Ontario Education Minister, William G. Davis, introduced a new sector of Ontario post-secondary institutions, Colleges of Applied Arts and Technology. A primary purpose of this sector was to create access to education, particularly for those who were not accessing university. Additional primary characteristics of colleges were that they were to be comprehensive institutions offering a variety of primarily occupationally focused programs, and that they were to respond to local education and training needs. Over five decades later, although colleges have evolved in numerous ways, this study demonstrates that these key characteristics are still present. In 2012 the Ministry of Training, Colleges and Universities (MTCU) indicated it would be pursuing a policy direction of differentiation to, in part, create a more efficient post-secondary system in Ontario. This study explores potential impacts of differentiation policy on the traditional mandate of colleges as institutions designed to promote local student access and to respond to local community needs, and the potential impact on Ontario students and communities. Using theoretical frameworks of institutional diversity and differentiation, social policy theory and the capability approach, this study examines the levels and dimensions of existing diversity and differentiation in the Ontario post-secondary system. It draws on three data sources to undertake this study: document analysis of strategic mandate agreements; geographic attendance data for college and university students in Ontario; and interviews with institutional leaders and senior policy actors. The study’s findings confirm that college students in rural and remote communities tend to attend colleges that are located close to them. Students in the Toronto area demonstrate higher mobility between colleges located in Toronto but overall also display a tendency to attend regionally close institutions. University students also demonstrate in-region attendance patterns within the Toronto area but rural and remote university students overall are more mobile across the province. Through qualitative interviews and document analysis, this study also finds that rural and remote colleges still, five decades after their inception, demonstrate very high community connectedness and characteristics of strong regional responsiveness.
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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) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».