Use of Q-Methodology to Identify Nursing Faculty Viewpoints of a Collaborative BScN Program Experience
Bibliographic record
Abstract
The McMaster Mohawk Conestoga Collaborative Bachelor of Science in Nursing Program, established in 2000, brought together three nursing programs from one university and two colleges. The existing university curriculum, which used a problem-based, small-group and student-centred approach, was implemented at all three sites. Considerable adjustments were required by faculty as they adapted to a collaborative approach in implementing this nursing curriculum. Q-methodology was used to identify nursing faculty viewpoints about the collaborative program experience. Sixty-one participants from the three sites completed a 50-item Q-sort representing their statements about collaboration. Data were analyzed using PQMethod version 2.11. Six salient viewpoints were identified: Champions of Collaboration, Proponents of Scholarship and Clinical, Critics of Collaboration, Defenders of McMaster Curriculum, Acceptors of Collaboration and Detractors of the Partnership. On the whole, the collaboration has been a success and a spirit of cooperation prevails. However, a number of faculty issues were identified that should be addressed. The results will be of value to other collaborative nursing programs as they work together to foster faculty commitment and collegiality.
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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 | 0.052 | 0.073 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".