Better with others: Groupness, cohesion and satisfaction in exercise and sport settings
Bibliographic record
Abstract
In a recent pilot study, a positive relationship was reported between group satisfaction in an exercise setting and both perceiving oneself as belonging to a group (i.e., groupness) and a measure of task cohesion (Priebe et al., 2011). The purpose of this study was two-fold: 1) To replicate the results of the previous pilot study using a larger and more diverse sample. 2) To extend the results to a sport setting. The latter was deemed important given the suggestion that the construct of groupness deserves attention in other group settings such as sport (Spink et al., 2010). Structural equation modeling was used to examine groupness and cohesion as predictors of satisfaction in exercise and sport settings. Adult exercisers (N=142) and athletes (N=144) completed a questionnaire assessing groupness (Spink et al., 2010), cohesion (Carron et al., 1985) and group satisfaction (Bruner & Spink, in press). Results revealed that the models for both the exercise and the sport settings had an acceptable fit (exercise: CFI = .95; RMSEA = .077; sport: CFI = .94; RMSEA = .086). In both settings, task cohesion and groupness predicted satisfaction (p
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".