The CRAB Workshop: Using Forum Theatre and Cognitive Rehearsal to Address Bullying in Nursing Education
Bibliographic record
Abstract
Bullying is a pervasive issue in nursing and other health care professional programs. As a student/faculty team at one university in Western Canada, we have created a number of initiatives within an overall project entitled Cognitive Rehearsal to Address Bullying (CRAB) that was designed to support students in managing bullying if they witnessed or experienced it during their program of study. One such initiative is the CRAB Workshop (herein referred to as “the CRAB Workshop” or “the Workshop”). In this paper, we describe the Workshop, which emerged in response to concerns shared by students and faculty regarding the normalized and long-standing prevalence of bullying experienced by nursing students. The Workshop brought faculty members and pre-licensure students from our School of Nursing together to creatively and collaboratively address these concerns. Together with the university’s Department of Theatre and Film, we designed an interactive educational workshop to prepare nursing students to independently identify and act on bullying witnessed or experienced in the clinical setting. In the Workshop, we engaged in forum theatre and cognitive rehearsal to foster cognitive, affective, and embodied learning. In this paper, we explain and discuss what comprised the creation and implementation of the CRAB Workshop. We address implications for future nursing education, and we offer recommendations for educators who are considering forum theatre and cognitive rehearsal as pedagogies for addressing challenging situations, such as bullying in nursing education.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".