Intimidation and harassment in residency: a review of the literature and results of the 2012 Canadian Association of Interns and Residents National Survey
Bibliographic record
Abstract
BACKGROUND: Intimidation and harassment (I&H) have been longstanding problems in residency training. These behaviours continue to be prevalent, as evidenced by the 2012 Canadian Association of Interns and Residents (CAIR) National Resident Survey. More than seven in ten (72.9%) residents reported behaviour from others that made them feel diminished during their residency. We conducted a literature review to identify other surveys to determine the prevalence, key themes, and solutions to I&H across residency programs. METHOD: PubMed and MEDLINE searches were performed using the key words "intimidation," "harassment," "inappropriate behaviour," "abuse," "mistreatment," "discrimination," and "residency." The search was limited to English language articles published between 1996 and 2013, and to papers where ten or more residents were surveyed or interviewed. RESULTS: A total of ten articles were reviewed. Our findings showed that I&H continue to be highly prevalent with 45-93% of residents reporting this behaviour on at least one occasion. Verbal abuse was the most predominant form; staff physicians and nurses tended to be the dominant source. Residents reported that I&H caused significant emotional impact; however, very few incidents of inappropriate behaviour were reported. Very few solutions to I&H were proposed. CONCLUSIONS: I&H in residency education continue to be common problems that are under-reported and under-discussed. The opportunity exists to improve efforts in this area. Definitions of what incorporates I&H should be revisited and various educational and structural initiatives should be implemented.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.024 | 0.038 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".