Passion and engagement in sport: A look at athletes and coaches using a quadripartite approach
Bibliographic record
Abstract
Athletes and coaches often feel a great deal of passion for sport. But are these highly passionate individuals also highly engaged in sport? Based on the theoretical underpinnings and empirical findings from the dualistic model of passion (Vallerand, 2015), it is unclear if the highest levels of sport engagement are associated with high levels of passion, or with specific combinations of high/low levels of harmonious and obsessive passion. We examined this issue in samples of athletes (N = 403) and coaches (N = 208). Participants completed online questionnaires assessing dimensions of sport passion (i.e., harmonious and obsessive passion) and engagement (i.e., confidence, vigor, dedication, enthusiasm). In both samples, we found that the highest levels of engagement were associated with high harmonious passion. This means that those who are passionate toward sport are not necessarily engaged in sport; engagement is found when passion involves high harmonious passion.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".