Interorganizational Relationships in the Heart and Stroke Foundation’s Spark Together for Healthy Kids™
Bibliographic record
Abstract
The Heart and Stroke Foundation's Spark Together for Healthy Kids™ (Spark) is a multiyear initiative in Ontario, Canada, that takes a population approach to obesity prevention. It focuses on creating healthy environments by improving access to healthy foods and physical activity, with an emphasis on strengthening the advocacy capacity of organizations and citizens. Consistent with the complexity of the intervention, the evaluation of Spark applied systems concepts and methods to test the utility of network analysis as a method for evaluation, and to inform collaborations of organizations involved in programs and advocacy. Relationships among organizations from different sectors and jurisdictional levels with a focus on school community environments were of particular interest. Interorganizational network analysis was used to understand these relationships, including the role of the Heart and Stroke Foundation. Findings revealed a niche brokering role for the Heart and Stroke Foundation and other provincial and national organizations, and the importance of these brokers for engaging local and regional organizations. Findings also reinforced the importance of a mixed methods approach to network analysis, and the potential value of the analysis for scientific and practical purposes.
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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 | 0.014 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.009 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".