An evaluation of running involvement: a cross-cultural perspective on Japanese and Euro-Canadian runners
Bibliographic record
Abstract
This study investigated the effect of culture on running involvement by reference to both Euro-Canadian and Japanese runners. The objective of the study was to identify similarities and differences in the running involvement-related and sociodemographic characteristics of runners participating in organized Euro-Canadian and Japanese running events. In terms of running involvement, this study considered three factors: attraction, centrality, and self-expression. The total sample included 122 valid responses from Canada and 340 valid responses from Japan. The findings revealed a significant effect of running involvement among both Japanese and Euro-Canadian runners in terms of three dimensions. The results also revealed a significant effect of country on three factors pertaining to running involvement. In summary, the results indicated that Euro-Canadian runners were likely to attain higher scores than were Japanese runners. The results of this study support the role of experience in running in these countries. The findings of this study revealed that some factors related to running involvement were lower among Japanese runners than among Euro-Canadian runners. Accordingly, this study improves our understanding of the effect of culture on running involvement. Additionally, the results of this study can be used to promote lifelong sports involvement.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 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".