Creating a Just Culture: The Ottawa Hospital’s experience
Bibliographic record
Abstract
We describe The Ottawa Hospital's (TOH) journey to create a Just Culture. We will describe the concept of a Just Culture, why TOH initiated this transformation, how TOH went about creating the Just Culture, and some of its early impacts. Following two events that called into question our hospital's safety culture, the hospital leadership adopted a deliberate and methodical organization-wide approach to change. These efforts included generating leadership commitment, incorporating the efforts within its corporate strategy, obtaining stakeholder engagement, developing and delivering an education program, and last but not least, efforts to improve safety systems. TOH has attempted to develop an increased focus on safety-for staff, visitors, and patients. The Ottawa Hospital has had demonstrable success throughout this journey as a result of a disciplined effort to create a Just Culture. This work will require ongoing efforts to ensure the culture shift is sustained.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.043 | 0.024 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".