Community Belonging and Sedentary Behaviour Among Métis Canadians: A Gendered Analysis
Bibliographic record
Abstract
Study Purpose: Framed by intersectionality theory, this study examined how gender and sense of community belonging interact to influence sedentary behaviour during leisure among Métis adults in Canada. Methods: Data were obtained from 1,169 Métis adults who completed the Canadian Community Health Survey in 2012. Weighted linear regression models examined associations between sedentary behaviour and community belonging stratified by gender, adjusting for confounders. Results: Male gender, younger age, physical activity, and increased socioeconomic status were associated with less sedentary behaviour among Métis adults. Métis men with a very strong sense of community belonging spent 3.6 fewer hours per week engaged in sedentary pursuits during leisure than Métis men who reported a very weak sense of community belonging. Conversely, Métis women with a very strong sense of community belonging spent 1 additional hour per week engaged in sedentary pursuits during leisure than Métis women who reported a very weak sense of community belonging. These associations remained significant after adjustment for sociodemographic covariates and perceived mental health and overall health, suggesting other factors were influencing these differences. Conclusions: A strong sense of community belonging among Métis men may reduce sedentary behaviour during leisure by as much as 30 minutes per day, which may be clinically significant. Increased community belonging among Métis women was associated with increased sedentary behaviour. These findings suggest that interactions between community belonging and gender should be considered when developing interventions to reduce leisure sedentary behaviour among Métis adults in Canada.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".