Perceptions of Intimidation in the Psychiatric Educational Environment in Edmonton, Alberta
Bibliographic record
Abstract
OBJECTIVE: To examine the perceptions of intimidation in the psychiatric educational environment in Edmonton, Alberta. METHODS: We distributed a 7-point modified Likert scale questionnaire that included questions with respect to intimidation perceptions and experience in psychiatry during a 1-week period to all student interns on psychiatry rotations, residents, and teaching faculty in the 5 teaching hospitals in Edmonton. RESULTS: A total of 92 individuals responded, with response rates of 81% for faculty, 82% for residents, and 84% for students. Response rates did not differ among sites. While there were differences between site and group with respect to comparing the perceived intimidation in psychiatry with other specialties, respondents did not view psychiatry as worse than other specialties. Although, overall, women perceived intimidation as more prevalent at their sites than did men, the overall means reflect sites that are relatively free from intimidation. Faculty and student interns within sites, except for the university hospital, tended to disagree on management's approach to perceived intimidation. All groups, however, reported little personal experience and felt their sites had little tolerance for intimidators. CONCLUSIONS: Reported perceptions and personal experiences of intimidation within the psychiatric learning environment in Edmonton are low.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".