229 Evaluation of the Global Matrix of Para Report Cards on Physical Activity of Children and Adolescents with Disabilities
Bibliographic record
Abstract
Abstract Purpose Physical activity provides a wide range of health benefits for children and adolescents with disabilities (CAWD). However, despite CAWD being at higher risk of physical inactivity, there is a lack of surveillance systems that capture physical activity data of CAWD. To address this gap, the Global Matrix of Para Report Cards on physical activity of CAWD was set up with 14 participating countries/jurisdictions (Ng et al., 2023) based on the methodology of the Active Healthy Kids Global Alliance’s Global Matrix 4.0 (Aubert et al., 2023). This study aims to evaluate the process, outcome, and impact of the Global Matrix of Para Report Cards. Methods The evaluation was informed by the Global Matrix 3.0 evaluation process (Aubert et al., 2020). Process, outcome, and impact indicators were informed by online surveys, reports/publications, and website analytics of the special issue published in Adapted Physical Activity Quarterly. Results Two online surveys have been completed by 64-71% of targeted respondents. Moderate-to-high satisfaction rates were reported for the development of and participation in the Global Matrix initiative and open-ended comments reported issues (e.g., data availability, inconsistency in definitions) and positive feedback (e.g., networking/collaboration, visibility). The participating Report Card teams assigned and contributed a total of 139 physical activity grades—overall physical activity, organised sport, active play, active transport, physical fitness, sedentary behaviour, family and peers, schools, community and environment, government—to the Global Matrix of which 45% were incomplete. Twelve Report Card teams published a short Para Report Card article for their country. As of February 2024, >47,000 views have been recorded for the special issue comprising the Global Matrix and country Para Report Card articles. Conclusions This evaluation highlights the need for more discussion on the definitions of disability and benchmarks of physical activity indicators to improve the grading process and more support in accessing and synthesising data related to CAWD. These are important steps to support inclusion and representation of CAWD in (inter)national surveillance of physical activity and health.
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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 | 0.107 | 0.127 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".