“They can crush you”: Nursing students’ experiences of bullying and the role of faculty
Bibliographic record
Abstract
This paper will explore the faculty role when nursing students experience bullying, and what teaching practices best support student confidence and learning. Failure to address the issue of bullying in nursing education contributes to bullying in the profession, and creates an atmosphere of distrust between students and faculty. Nursing students have reported that faculty sometimes behave in bullying ways or are ill-prepared to address bullying as it occurs. Faculty may contribute to bullying unknowingly, as students may perceive teaching behaviours, such as giving feedback, as bullying. Giving feedback is a skill in itself, and faculty members should consider factors influencing a student’s perception of student/teacher interactions. Having a firm grasp on conflict resolution processes and reviewing related curriculum are responsibilities of post-secondary nurse educators. Faculty also have the responsibility to recognize and address conflict in a timely manner, and turn difficult situations into learning experiences or teachable moments. In order to prevent faculty bullying of students, faculty members should acknowledge the inherent vulnerability of learners, and also reflect on their own communication practices and their potential impact on learners.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.007 |
| 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".