Bibliographic record
Abstract
There has been limited research on the role of visible minority status on health in Canada. In particular, the physical activity of visible minorities has not been extensively examined. Participation in physical activity is influenced by various biological, environmental, and social factors, and these factors act as either facilitators or barriers to physical activity participation. Previous research has shown that the main barriers to participation in physical activity identified by visible minorities have been the different ethnic and cultural norms and practices of participants. A cross-sectional, online survey was conducted to examine the barriers to physical activity in visible minorities living in St. John’s, Newfoundland. Participants included 75 visible minorities who participated in the web-based survey; 52 participants had complete data. A stepwise forward regression model was tested with total physical activity participation as the outcome variable. Sociodemographic, sociocultural, self-efficacy, and health-related variables were not significantly related to total physical activity levels. Only two barrier items were found to be significant and positively and highly correlated to physical activity: physical activity taking too much time away from taking care of family members (ß = 0.42, t = 2.538, p = .017) and not being talented in physical activity (ß = 0.339, t = 2.131, p = .042). This model was a significant fit (F₍₂,₅₆₎ = 5.870, p = . 007) and accounted for 24% of the variance. All other barrier items were found to have insignificant partial correlations and thus did not improve the model. Limitations of the study are discussed with emphasis recruitment of visible minorities and future research recommendations are provided.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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".