Trends in Government-Initiated Public Engagement in Canadian Health Policy From 2000 to 2021
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction: Canada has a rich history of public engagement in health policy; however, shifts in engagement practices over time have not been critically examined. Methodology: We searched for cases of government-initiated public engagement in Canadian health policy from 2000 to 2021 at the federal, provincial (Ontario, British Columbia, Nova Scotia) and pan-Canadian levels. Government databases, portals and platforms for engagement were searched, followed by academic and grey literature using relevant search terms. A coding scheme was iteratively developed to categorize cases by target population, recruitment method and type of engagement. Results: We identified 132 cases of government-initiated public engagement. We found a predominance of feedback and consultation engagement types and self-selection recruitment, especially at the federal level from 2016 onward. Engagements that targeted multiple populations (patients, public and other stakeholders) were favoured overall and over time. Just over 10% of cases in our survey mentioned efforts to engage with equity-deserving groups. Conclusion: Overall, our results identify a heavy reliance over time on more passive, indirect engagement approaches, which limit opportunities for collaborative problem solving and fail to include equity-deserving populations. Those overseeing the design and implementation of government-initiated public engagement will draw valuable lessons from this review to inform the design of engagement initatives.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it