Degree-completion opportunities for ontario college students: a framework for understanding and facilitating college university collaboration: a college perspective
Bibliographic record
Abstract
This descriptive, qualitative study examines the contextual, institutional, and leadership factors that influence collaboration between colleges and universities and explores what might be done to facilitate the development of collaborative programs between the colleges and universities in Ontario. Using a collaborative model identified by Couture, Delong and Wideman (1999), this study focused on degree-completion programs as the only type of college university collaborative program that builds on a previously earned community college diploma, does not have university entrance requirements and is common to both the Colleges' of Applied Arts and Technology collaborations with universities inside and outside of the province. Individuals within the Ontario community college system who had been involved in developing degree-completion programs with Canadian universities were interviewed. It is their personal “stories” about their collaborative experiences with universities and a review of the literature on leadership that provided the basis for this research. The study found leadership to be an important factor in college university collaboration and reinforced the need for “missionaries” on both sides. Successful collaboration seemed to have more to do with the leadership skills and abilities of the individuals involved in the process and their desire to create a more seamless system of education that provides students with ongoing opportunities including pursuing degree credentials, than it had to do with formalized management responsibilities or policies within the institutions. A better understanding of college university collaboration in Ontario puts government officials and postsecondary leaders alike, including administrators and educators, in a stronger position to positively impact future college university collaborative efforts in this province.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.036 | 0.027 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".