Team building using a challenge rope course experience in youth sport: A case study
Bibliographic record
Abstract
Team building (TB) has been associated with many benefits in a sport setting including increased group cohesion (Martin, Carron & Burke, 2009). One promising strategy for conducting a TB intervention is through challenge rope courses, as they have been found to increase cohesion in education and adventure therapy settings (Glass & Benshoff, 2002; Long, 2001). Yet, to our knowledge, challenge rope courses have not been examined empirically to determine their effectiveness as a TB intervention in sport. The purpose of this study was to examine whether a TB protocol delivered through a challenge rope course could increase group cohesion in a youth sport team. Participants (n = 10, Mage = 12.3) from a competitive female U14 ringette team participated in a TB challenge rope course intervention. Prior to and after the intervention, participants completed a questionnaire to assess group cohesion. Following the intervention, focus group interviews were conducted with the players and a personal interview was conducted with the head coach to further explore the efficacy of the intervention on the group’s dynamics. Results revealed that task cohesion significantly increased pre-post intervention. Many themes, such as increased trust, teamwork, communication and cohesion, were also identified post- intervention by both players and the coach during interviews. Collectively, the findings offer preliminary support for the efficacy of a challenge rope course TB intervention to enhance group cohesion in a youth sport setting.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| 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".