Building and Sustaining a Culture of Innovation in an Academic Health Centre
Bibliographic record
Abstract
Although innovative organizations have the advantage of superior performance, the idea of adopting innovative practices and embracing risk taking at work can be intimidating, especially for those working in healthcare. When responsible for the health and safety of others, healthcare workers tend to gravitate away from ideas that could result in failure. The challenge of promoting innovation in a healthcare context can be addressed by creating an organizational culture of innovation - where innovative thinking is normalized, rewarded and even expected of employees. In this article, we share our journey and outline lessons learned in creating a culture of innovation at Holland Bloorview, Canada's largest pediatric rehabilitation hospital. It is our hope that those seeking to create a culture of innovation within their organization can learn from and apply these lessons in their own contexts.
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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 | 0.041 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.019 | 0.024 |
| Scholarly communication | 0.030 | 0.006 |
| Open science | 0.003 | 0.022 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".