The art and science of a strategic grantmaker: the experience of the Public Health Agency of Canada’s Innovation Strategy
Bibliographic record
Abstract
SETTING: The Public Health Agency of Canada's Innovation Strategy (PHAC-IS) was established amid calls for diverse structural funding mechanisms that could support research agendas to inform policy making across multiple levels and jurisdictions. Influenced by a shifting emphasis towards a population health approach and growing interest in social innovation and systems change, the PHAC-IS was created as a national grantmaking program that funded the testing and delivery of promising population health interventions between 2009 and 2020. INTERVENTION: During its decade-long tenure, the PHAC-IS supported the development of innovative, locally driven programs that emphasized health equity, encouraged iterative learning to respond reflexively to complex public health problems (the art), while at the same time promoting and integrating population health intervention research (the science) for improved health at the individual, community, and systems levels through four program components. OUTCOMES: PHAC-IS projects reached priority audiences in over 1700 communities. Over 1400 partnerships were established by community-led organizations across multiple sectors with more than $30 million of leveraged funds. By the final phase of funding, 90% of the projects and partnership networks had a sustained impact on policy and public health practice. By the end of the program, 82% of the projects were able to continue their intervention beyond PHAC-IS funding. Through a phased approach, projects were able to adapt, reflect, and build partnership networks to impact policy and practice while increasing reach and scale towards sustainability. IMPLICATIONS: Analysis and reflection throughout the course of this initiative showed that strong partnerships that contribute sufficient time to collaboration are critical to achieving meaningful outcomes. Building on evaluation cycles that strengthen project design can ensure both scale and sustainability of project achievements. Furthermore, a flexible, phased approach allows for iterative learning and adjustments across various phases to realize sustained population and systems change. The model and reflexive approach underlying the PHAC-IS has the potential to apply to a broad range of public programs.
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How this classification was reachedexpand
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 | 0.024 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".