Athletes' perspectives of competition within elite sport teams: Understanding intra-team competition
Bibliographic record
Abstract
Competition is a pervasive human phenomenon. It commonly occurs in many contexts, but most frequently in sport (Stanne, Johnson, & Johnson, 1999). However, the nature of sport competition, in particular, depends on the situational context. Competition between teams and/or individuals (e.g., league games, tournaments) differs from intra-team competition (e.g., during practice). Much of the literature in sport psychology has focused on competition between teams/individual; there has been little attention paid to intra-team competition. The purpose of this study was to explore athletes’ experiences with intra-team competition. Semi-structured interviews were conducted with 19 university (CIS) team sport athletes (soccer, volleyball, basketball, track and field, hockey; female n=12; age m=20.4, sd=2.2; years experience m=2.9, sd=1.8). Data were transcribed verbatim and analyzed inductively resulting in 581 codes. These were grouped into 32 themes. The results indicated that intra-team competition is an omni-present phenomenon in elite sport teams. Two general types of intra-team competition are common. Discrete or situational competition is used during individual practices to enhance motivation/effort or promote team bonding. Latent, or ongoing positional competition, is used to determine starting roles or the amount of playing time a player will receive. Both types of competition are seen to impact other team processes including performance at the individual and group level, and team cohesion. The present study suggests intra-team competition is a complex phenomenon. Further research needs to better define and conceptualize the processes of intra-team competition as a psychological team process. Implications and research directions will be discussed.
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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 | 0.005 | 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 | 0.008 | 0.010 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".