Progress in physical activity research, policy, and surveillance in Canada: The global observatory for physical activity – GoPA!
Bibliographic record
Abstract
BACKGROUND: The purpose of this paper is to examine the evolution of physical activity research and the comprehensiveness of national physical activity policies and surveillance systems in Canada. METHODS: A systematic review was conducted by the Global Observatory for Physical Activity (GoPA! ) on physical activity and health publications between 1950 and 2019. Findings from Canada were extracted and included in the present analysis. The number of articles published, female researcher involvement in authorship, author institution affiliations, and publication themes were examined. Policies were evaluated by determining if there was a standalone physical activity plan and if national guidelines existed. Surveillance systems were assessed for periodicity, instruments used, and age inclusivity. RESULTS: Out of 23,000 + publications analyzed worldwide; 1,962 included data collected in Canada. Physical activity research in Canada increased considerably from the 2000s to 2010s (543 articles vs. 1,288 articles), but an apparent stabilization has been observed more recently. Most physical activity publications in Canada focused on surveillance (37%), with fewer articles on policy (8%) and interventions (7%). The proportion of female first authors increased from 38% in the 1980s to 60% in the last decade. However, females remain the minority for senior authors. With respect to policy, "A Common Vision" is Canada's national plan, which has a singular policy focus on physical activity. National surveillance data is collected regularly with both the Canadian Health Measures Survey (CHMS) and the Canadian Community Health Survey. In addition to self-report, the CHMS also collects accelerometer data from participants. CONCLUSION: Through collaborative and coordinated action, Canada remains well equipped to tackle physical inactivity. Continued efforts are needed to enhance sustained awareness of existing physical activity promotion resources to increase physical activity.
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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 | 0.087 | 0.143 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.026 | 0.059 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.017 | 0.006 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".