Changing the Paradigm in Public Health and Disability through a Knowledge Translation Center
Bibliographic record
Abstract
People with disabilities are a health disparity population that face many barriers to health promotion opportunities in their communities. Inclusion in public health initiatives is a critical approach to address the health disparities that people with disabilities experience. The National Center on Health, Physical Activity and Disability (NCHPAD) is tackling health disparities in the areas of physical activity, healthy nutrition, and healthy weight management. Using the NCHPAD Knowledge Adaptation, Translation, and Scale-up Framework, NCHPAD is systematically facilitating, monitoring, and evaluating inclusive programmatic, policy, systems, and environmental (PPSE) changes in communities and organizations at a local and national level. Through examples we will highlight the importance of adapting knowledge, facilitating uptake, developing strategic partnerships and building community capacity that ultimately creates sustainable, inclusive change.
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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 | 0.120 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.013 | 0.064 |
| Scholarly communication | 0.027 | 0.037 |
| Open science | 0.005 | 0.033 |
| Research integrity | 0.017 | 0.025 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".