Team Building and Group Cohesion in the Context of Sport and Performance Psychology
Bibliographic record
Abstract
Abstract Over the past 30 years, researchers studying group dynamics in sport have provided insight regarding the importance of considering a team’s environment, structure, and processes for its effective functioning. An emergent property resulting from activities within the group is cohesion. Cohesion is a dynamic property reflecting members’ perceptions of the unity and personal attractions to task and social objectives of the group. Generally speaking, cohesion remains a highly valued group property, and a strong body of evidence exists to support positive links to important individual and group outcomes such as adherence and team performance. Given the importance attached to cohesion and other group variables for sport teams, coaches and athletes often attempt to engage in activities that facilitate group functioning. Team building is a specific approach designed to facilitate team effectiveness and individual members’ perceptions of their group. Cohesion has been the primary target of team-building interventions in sport, although recent work on team-building outcomes suggested that the effects of these interventions on cohesion may be limited. The most effective team-building approaches include a goal setting protocol, last at least two weeks in duration, and target a variety of outcomes in addition to cohesion, including individual cognitions and team performance. There is a clear need to identify a team’s requirements prior to intervening (i.e., a targeted approach), consider a variety of approaches to team building, and investigate the effects of team building via more stringent research methods.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".