Bibliographic record
Abstract
Feeling connected to one’s community has been associated with increased self-rated health and well-being. Connectivity has also been linked to health behaviours such as smoking and obesity, which have been related to overall health status. Physical activity is related to overall health status as it protects against many chronic diseases. Unfortunately, less than 50% of Canadian adults are meeting the physical activity requirements set out by Canada’s Physical Activity Guide to Healthy Living. Thus, this study determines whether sense of connectedness is associated with current participation in leisure-time physical activity and intention to start or increase engagement in physical activity. \nCross-sectional data from the Canadian Community Health Survey (CCHS) cycle 3.1 was used to analyze the association between sense of community belonging and physical activity among Canadians aged 25 to 64. A series of logistic regression models were used to analyze the data. \nPeople reporting a stronger sense of connectedness had greater odds of being physically active with income, education and sex often moderating the relationship. It appeared that the relative odds of being physically active were greatest among people who felt very strongly connected to their communities and in the highest socioeconomic groups. Further, feeling more that very weakly connected to the community increased the odds of intending to start or increase physical activity among inactive females and decreased the odds of intending to increase physical activity among moderately active males. \nThis study provides preliminary results regarding how important social factors may alter population level physical activity. The results from this study inform our understanding of barriers and facilitators associated with physical activity and how policies and conditions which affect community connectedness may be used to enhance 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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".