Sharing and Supporting the Hopes and Dreams of Students and Faculty in a Canadian BScN Program
Bibliographic record
Abstract
Healthcare educators are in a unique position to support students’ personal and professional development. The UOIT-DC Nursing Program curriculum is founded on caring values that assert a commitment to the primacy of relationships. According to humanistic nursing, caring involves the interrelated concepts of ‘being’ and ‘doing’ in which both require an active presence and willingness to come to know another person (Paterson and Zderad, 1976). A deeply held tenet of nursing practice is the notion that when a nurse knows or understands a person, he or she will be better able to care for that person. We believe that this notion also pertains to student and faculty relationships in nursing education, ultimately leading to more effective and meaningful learning opportunities and experiences.This poster will report on a qualitative study exploring undergraduate nursing students’ hopes and dreams when they begin their education and the ways these hopes and dreams may shift and evolve as they progress through the program. The intersections of students’ hopes and dreams for their education and faculty members’ hopes and dreams in teaching students will be presented. The impetus for the project arose from conversations among faculty members about the complex relational nature of nursing education and our hope to enhance relational awareness and practices through a deeper understanding of the aspirations and goals that students hold. Exploration of how the findings may contribute to deeper understandings of and responsiveness to students and the significance of nursing practice and education to them will be presented.ReferencesPaterson, J. G., and Zderad, L. T. (1976). Humanistic nursing. New York: John Wiley and Sons.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.038 | 0.010 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".