Enhancing partnerships and collaboration in times of change
Bibliographic record
Abstract
Abstract Issue In 2019, the government of the Canadian province of Ontario announced major changes to the structure, governance and funding of public health services. Throughout these changes, publicly funded local and regional public health organizations are still expected to provide effective, evidence-informed programming to their communities. The National Collaborating Centre for Methods and Tools (NCCMT) has facilitated collaborations to support Ontario public health through this transition. Description of the problem In order to support evidence-informed public health in Ontario during this transition, the NCCMT reached out to current and potential partners, within and beyond the public health sector for a multidisciplinary approach. We conducted a needs assessment for an evidence review repository, which would allow public health practitioners to share and build upon each other's work. Finally, demonstrating the value of public health to policymakers can be inherently challenging as the return on investment in public health is often very long term. We partnered with health units in varying capacities to find and synthesize evidence to advocate for continued investment in public health. Results This initiative has provided important lessons in developing and maintaining strong partnerships. Looking beyond the public health sector can establish mutually beneficial partners and allies in other disciplines. A key finding was the need to establish infrastructure to support collaboration and resource sharing. Finally, we learned that big picture questions like demonstrating the value of public health require many different perspectives, inputs and areas of expertise. Lessons Through this initiative, we have developed a multidisciplinary, collaborative approach to supporting evidence-informed public health through times of major restructuring. This approach can be applied to future changes to public health on smaller or larger scales, or within other geographic regions. Key messages Multidisciplinary approaches can support collaboration, unity and advocacy in times of change. Establishing infrastructure to support collaboration and sharing of resources is valuable.
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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 | 0.079 | 0.114 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.027 | 0.024 |
| Scholarly communication | 0.029 | 0.029 |
| Open science | 0.005 | 0.049 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".