Bibliographic record
Abstract
Although individual sport athletes (e.g., running, golf, and gymnastics) compete independently, an interdependent group environment often plays an important role in their sport performance and overall experiences. The current research sought to develop an understanding of teammate interpersonal influence in individual sport group settings, using a grounded theory methodological approach. Six male and eight female elite individual sport athletes participated in semi-structured qualitative interviews designed to gain an understanding of their experiences with teammates in their sport. The elite level athletes (i.e., National to Olympic competitive levels) competed in middle to long distance running (n = 6), cross country skiing (n = 6), mountain biking (n = 1), and wrestling (n = 1). Athletes described a range of interpersonal influences from teammates, and suggested that individual sport teams were a main source of motivation, social facilitation, and social comparisons along with other general forms of social influence (e.g., encouragement). Furthermore, athletes described how concepts such as groupness, cohesion, and competitiveness were determinants of the type of influence groups had on their experiences. These results indicated that group experiences are central for many individual sport athletes, and that the management of group processes should be an important concern for individual sport coaches and practitioners.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".