Satisfaction in unstructured exercise settings: Role of cohesion and group identity
Bibliographic record
Abstract
Satisfaction has been associated with various measures of adherence in activity settings (Funk et al., 2011; Remers et al., 1995). What is less clear, however, are the factors that might impact these feelings of satisfaction. From a group perspective, the perceived cohesiveness of a structured activity group has been positively linked to feelings of satisfaction (Priebe et al., 2011). Further, social identity also has been found to be positively related to satisfaction in activity settings (Burns et al., 2012). Given the conceptual link between cohesion and identity (Hogg et al., 2004), this study sought to examine the relationship of task cohesion and group identity to group task satisfaction in unstructured exercise groups. Participants (N=148) were asked to recall their experience in an unstructured exercise group and report their perceptions of group identity (Rimal & Real, 2005), task cohesion (modified GEQ; Carron & Spink, 1992) and group task satisfaction (Bruner & Spink, 2011). SEM was performed with direct paths from identity and task cohesion to group task satisfaction. Model fit was acceptable (RMSEA=.075, CFI=.93). Task cohesion measures (ATG-T, b=.38, 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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".