Athletes’ Perceptions of Role Acceptance in Interdependent Sport Teams
Bibliographic record
Abstract
Roles are structural components of groups and represent the patterns of behavior expected of an individual within a specific social context (Biddle, 1979). Literature in sport as well as organizational domains has emphasized the importance of roles in groups characterized by a high degree of task interdependence (Carron & Eys, 2012; Kahn, Wolfe, Quinn, Snoek, & Rosenthal, 1964). In other words, in interdependent groups where performance is the main goal, the differentiation and specialization of role responsibilities is crucial to team effectiveness (Wageman, Fisher, & Hackman, 2009). Kahn et al. (1964) developed a theoretical framework to examine the nature of how role expectations are transmitted in a group setting. Underscoring the importance of roles in sport, researchers have embraced this framework to examine a number of aspects related to the generation, communication, and execution of role responsibilities in interdependent teams. For example, how well an athlete understands his/her role responsibilities (i.e., role clarity) is positively linked with perceptions of group cohesion, leadership behaviors, and individual role performance outcomes (e.g., Beauchamp, Bray, Eys, & Carron, 2002; Beauchamp, Bray, Eys, & Carron, 2005; Bosselut, McLaren, Eys, & Heuze, 2012). However, though ensuring athletes understand their role responsibilities is important, athletes who choose not to subsequently accept the responsibilities/expectations defined for them will likely eradicate any positive outcomes of clear role communication processes (Benson, Surya, & Eys). As such, scholars have posited that accepting one’s role is a fundamental process related to the performance of role responsibilities and, ultimately, the group (Carron & Eys, 2012)—a sentiment that is echoed in the popular media as the following quote illustrates:
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 | 0.003 | 0.007 |
| 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 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".