Exploring Physical Activity Intention as a Response to the Vancouver Olympics: an Application and Extension of the Theory of Planned Behavior
Bibliographic record
Abstract
The theory of planned behavior (TPB) was used to understand motivational factors behind individuals' intention to become more active in response to the Vancouver 2010 Olympics. Gender, geographic proximity to the event, past behavior, and descriptive norm were explored as extensions of the TPB model. Just over 400 (n=405) students attending undergraduate classes in two universities at opposite ends of Canada completed a questionnaire prior to the start of the Games. Results from the hierarchical multiple linear regression analysis revealed that 50.7% of the variance in respondents' intention scores was explained by the variables in the proposed extended TPB model. Specifically, attitude toward the behavior, past behavior, and descriptive norms (i.e., people's perceptions about the degree to which other people were going to become more active as a result of the Olympic Winter Games) emerged as significant predictors of intention to become more active in response to the event. Implications for the design of interventions aimed at enhancing participation legacies of Olympic Games are discussed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".