Conceptualizing Dissemination Research and Activity: The Case of the Canadian Heart Health Initiative
Bibliographic record
Abstract
Cardiovascular diseases are now the world's leading cause of death. To reduce high rates of such preventable premature deaths, evidence-based approaches to heart health promotion must be disseminated across public health systems. To succeed, we must build capacity to disseminate strategies that are practical and effective. However, we know little about such dissemination, and we lack both conceptual frameworks to guide our thinking and appropriate scientific methodologies. This article presents conceptual and analytic frameworks that integrate several approaches to understanding and studying dissemination processes within public health systems. This work is based on the Canadian Heart Health Dissemination Project, a research program examining a national heart health dissemination initiative. The primary focus is the development of a systematic protocol for measuring levels of capacity and dissemination, and determining successful conditions for, and barriers to, capacity and dissemination, as well as the nature of the relationship between these key concepts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.080 | 0.070 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.020 | 0.030 |
| Science and technology studies | 0.017 | 0.066 |
| Scholarly communication | 0.024 | 0.016 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.012 | 0.008 |
| 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".