Radical Transformation of Nursing Education in Ontario: Multiple Case Study of Four Ontario Colleges
Bibliographic record
Abstract
In this study I sought to explore the forces that led to Ontario’s Ministry of Colleges and Universities (MCU) policy reform of 2020 which permits colleges and universities to offer standalone nursing degree programs. While the policy impacts both colleges and universities, this study focused on the forces of change specifically for the Ontario Colleges of Applied Arts & Technology (CAATs). Using a multiple case study research design, I explored the factors that led each of the four participating case study Ontario CAATs to move forward in implementing a standalone baccalaureate nursing degree program at their institution. I examined their experiences and the processes undertaken in the development and implementation of these programs. Study findings were generated from document analysis, semi-structured interviews with ten participants responsible for the program conceptualization, development and implementations and from cross case study analysis. To understand the political nature of state authority, the role of market demands, and the broader impact on nursing education policy, Burton Clark’s (1983) "triangle of coordination" was applied as a theoretical framework. This framework facilitated the analysis of how state, market, and academic oligarchy intersected in shaping the policy and its outcomes. Key findings revealed that political advocacy led by the CAATs and Colleges Ontario, combined with key stakeholder support from policy actors exerting high influence on government. Furthermore, intermediary bodies, specifically the College of Nurses of Ontario and the Post Secondary Quality Assurance Board (PEQAB) played a key role in facilitating this policy change. Moreover, the findings illustrate that political will fostered by a critical nursing shortage and compounded by the COVID-19 pandemic were critical enablers. This study highlights the intersecting and dynamic roles of government, market and academic oligarchy in transforming the nursing education landscape in Ontario. Implications of these findings consider the policy and practice consequences and contributions to this higher education policy reform, particular as the complexity of healthcare increases, the demand for a greater skilled nursing workforce continues and access to higher education remain paramount for entry to practice in nursing.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.023 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".