Groupness, cohesion, and intention to return to sport: A study of intact youth teams
Bibliographic record
Abstract
The positive benefits for youth participating in sport have been well documented. Yet, keeping athletes returning to sport has been a concern. While various factors have been examined to explain this attrition, facets of the sport group experience have started to emerge. From a group perspective, it has been established that athlete intentions to return to a sport team the following season are positively associated with perceived team cohesion. While cohesion is a key group construct, other group factors are worthy of examination. The purpose of the current study was to build upon the research base by examining whether the relationship between cohesion and intention to return would be moderated by another group factor—the level of groupness ascribed to the team. At the end of a competitive season, youth soccer athletes ( N = 156) completed measures of task cohesion, groupness, and intention to return to their team in the future. Results revealed that the task cohesion-intention to return relationship was significantly moderated by groupness, p = .03. Simple slopes analysis revealed that the strongest relationship between task cohesion and intention to return occurred under conditions of lower groupness. These initial results indicated that intention to return was highest when the team was perceived as higher in task cohesion, regardless of groupness perceptions. However, when the team was perceived to be lower in task cohesion, those who perceived their team as being more like a group indicated a greater willingness to return to the team in the future.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".