Taking role responsibility within individual sport environments
Bibliographic record
Abstract
Though the majority of sport group dynamics research focuses on interdependent sport teams (e.g., soccer, basketball), various lines of investigation have examined group dynamics in the context of more individual types of sports (e.g., track and field, swimming, wrestling). Individual sports often involve task interdependence (e.g., athletes training together in shared spaces, travelling to and attending competitions together with a group identity), and the group’s structure and teammate interactions can significantly influence athletes’ experiences in these sports. Extending this body of research, the present study examined the dynamics of roles—a group’s structural element that encompasses a set of behavioral expectations for group members—in individual sport teams. Semi-structured interviews were conducted with 19 former or current athletes (Mage = 20.5 years) who had, on average, 7.5 years of experience in competitive individual sports. Interview data were analyzed using reflexive thematic analysis. Participants discussed that leadership-oriented roles (e.g., captainship, informal leadership, mentorship) were important for group functioning, and emphasized the need to create more natural, informal leadership/mentorship opportunities rather than delegating formalized responsibilities. Various informal roles were also discussed, including team comedians, cheer captains/supporters, social conveners, spark plugs, and team mediators, all of which served diverse functions. Additionally, participants described the detrimental influence that team cancers had within their groups. These findings highlight the relevance of roles within individual sport teams and provide a foundation for continued research that can identify strategies for promoting effective dynamics of individual sport teams.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".