The One Health Leadership Experience at the University of Saskatchewan, Canada
Bibliographic record
Abstract
in 2011. Since then, several educational interventions have been aimed at increasing awareness and capacity for inter-professional collaboration. At the University of Saskatchewan, Canada, a 3-day event, the One Health Leadership Experience (OHLE), was initiated in 2012 and continues to the present. The event targets students entering their first year of a health professional program and consists of presentations by invited OH guest speakers, networking sessions, small-group case discussions of OH scenarios, and leadership development through panel discussions and interactive small-group dialogues. Post-conference surveys, a 5-year follow-up survey, and two focus groups were conducted to evaluate the impact of participation in the OHLE. After the event, the proportion of students who said they clearly understood OH and its goals was substantially higher than before: 86% versus 14% in 2012, 91% versus 23% in 2013, and 69% versus 24% in 2014. In the 5-year follow-up survey, most respondents (90%) indicated that attending the OHLE increased their interaction with other students from health sciences colleges or schools on campus. Also, most (81%) believed that OH should be formally taught in their program and 80% anticipated implementing, or had already implemented, OH practices after graduation. The OHLE increased participants' awareness of the importance of interdisciplinary approaches and is a successful educational model that can be adapted to health professional curricula at other institutions.
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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 | 0.010 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 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".