The National Physical Activity Measurement Study of Children and Youth with Disabilites in Canada Final Study Report 2023
Bibliographic record
Abstract
The National Physical Activity Measurement (NPAM) study was designed to capture the typical movement behaviours (i.e., physical activity, sedentary behaviour, and sleep) of Canadian aged children and youth (ages 4-17 years) with any type of disability. Data for the NPAM were collected using three different methods: 1) Parent Survey Parents completed an online survey. The online survey consisted of standardized measures of their child's daily physical and sedentary activities and well-being, and how they support their child's involvement in physical activity. 2) Fitbit® and Accelerometers Children and youth wore a Fitbit® for 30 days and kept a daily log of their wear time. The Fitbit® provided daily minute-by-minute heart rate and step count data. Given the novelty of wearable activity monitors, such as the Fitbit®, among children and youth with disabilities, accelerometers were worn by a subsample of participants to conduct validation work. 3) Youth Survey Youth over the age of 10 years were also given the opportunity to complete the survey. This survey consisted of similar items to the parent survey. In 2022-2023, the completion of surveys by both parents and youth were emphasized to obtain a sample of parent-child dyads. This report provides an overview of the study timeline, sample demographics, main findings and research outputs.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".