Bibliographic record
Abstract
Harassment is commonly experienced within the hierarchical world of medicine by both learners and faculty. There are different types of harassment; however, all types of harassment have a negative impact on individuals professionally and personally. Harassment also negatively impacts groups, by impacting team dynamics, perceptions of leaders, and upon workplace psychological safety and wellness. To address harassment, the Faculty of Medicine and Dentistry (FoMD) at the University of Alberta (UAlberta) has developed a structured institutional response to harassment through: (1) providing institutional members and leaders with explicit expectations of behaviour, outlining types of harassment, and starting to integrate psychological safety priorities at all levels of the institution; (2) through aiding, training, selecting, and evaluating workplace leaders in psychological safety, workplace wellness, and harassment interventions, guiding leaders through options of: coaching types of interventions, investigations, and when there is a duty to report to formal bodies; (3) educating and providing tools for workplace members to deal with harassment situations either; directly or by reporting; and (4) being aware of, and addressing, unique aspects of: racial, sexual, and online harassment. Through such iterative institutional process improvement and reflection, we are moving towards effectively addressing harassment within all learning and working environments. Our ultimate institutional goal is to eradicate harassment occurrence within our institution, thus creating a psychologically safe, transparent, and accountable culture for individuals, workplaces, and groups.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 teacher head, 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".