Breaking the Silence: A Phenomenological Study of Student-Initiated Confrontation as Experienced by Social Work Educators
Bibliographic record
Abstract
Mounting evidence suggests that, over the past three decades, post-secondary educators increasingly face concerning behaviours initiated by students, both in and outside of the classroom. The behaviours range from incidental rude and disruptive behaviours to more ongoing, intentional, hostile, aggressive, and even violent behaviours. These student-initiated confrontations (SICs) present personal and professional challenges for educators and are often exacerbated by insufficient institutional support and training with respect to SIC and classroom management. This qualitative phenomenological study aimed to understand the experience of SIC among post-secondary social work educators across Canada and to identify potential strategies to mitigate these challenges. Additionally, the study examined institutional responses to SICs, with a focus on social work education. Particular interest was paid to the implications of SIC for social work education. Fifteen post-secondary social work educators were interviewed using semi-structured interviews, and the data were analyzed using Colaizzi’s descriptive phenomenological approach. Findings suggest that SIC is a present and serious problem within schools of social work that has implications for social work educators, social work education, and the profession itself. Findings specific to social work education suggest that increased mandatory training for educators on classroom management and SIC, as well as increased institutional leadership support for educators, are important in preventing and mitigating this phenomenon.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.018 | 0.021 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| 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".