Feeling like a group or feeling united: Effects on intention to return in youth soccer
Bibliographic record
Abstract
It has been established recently that groupness and cohesion have independent and additive effects on athlete's intention to return to a hypothetical sport team (Spink et al., in press). Given that the study was conducted using vignettes and global measures of cohesion, the current study examined the effects of both task and social cohesion and groupness on intention to return of players from intact soccer teams. Young athletes (N=127) from 10 soccer teams completed measures of groupness (Spink et al., 2010), cohesion (Eys et al., 2009), and intention to return to the team in the following season (Spink, 1995) near the end of the season. Perceptions of groupness, and both task cohesion and social cohesion, were coded as higher or lower using a median-split. Four groupings were created: high cohesion/high groupness [HH], high cohesion/low groupness [HL], high groupness/low cohesion [LH], and low cohesion/low groupness [LL] perceptions for task and social cohesion, separately. ANOVA results differed for each cohesion measure. A significant condition main effect, p LL, LH > LL, ps LL, p < .01, Cohen's d = .75). Similarities and differences with Spink and colleagues (in press) are considered.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".