Political orientation and public attributions for the causes and solutions of physical inactivity in Canada: Implications for policy support
Bibliographic record
Abstract
Objectives: To examine how public attributions for the causes and solutions of physical inactivity and individuals' self-identified political orientation are associated with support for different policy actions in addressing physical inactivity. Methods: A secondary data analysis was conducted with a sample of 2,044 Canadian adults. Two sets of 2 X 3 analyses of variance were conducted to assess (1) the mean differences by the causal attributions for physical inactivity and political orientation, and (2) responsibility for solutions and political orientation on support for least, moderate, and most intrusive policy actions. Results: No interaction effects existed between causal attribution and political orientation on policy support, but the main effect of causal attributions and political orientation was significant. Those who held internal causal attributions showed less support for policies compared to those who held external or both internal and external causal attributions. Conservative individuals reported the least support for all policy actions in comparison to liberals or centrists. There were interaction effects between responsibility for solutions and political orientation on policy support. Conservatives who perceived the responsibility for solving physical inactivity as a private matter had less support for all three policies. Conclusions: Public acceptance of policy actions addressing physical inactivity varies by the attributions the public have regarding causes and responsibility for solving the problem, and by political orientation. Advocacy and messaging for policy implementation in the physical activity arena need to be communicated in ways that encourage reflective and informed deliberation that is representative of the Canadian population.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".