A Case Study of Junior Elite Tennis Players' and their Parent’s Self-Talk
Bibliographic record
Abstract
Automatic self-talk of elite athletes provides valuable insight into their emotional experience and self-regulation strategies in competition. To date, there is a shortage of research examining elite junior athletes’ automatic self-talk in competition through a qualitative lens. Despite parents’ key role in the well-being and performance of their child, there is no study about junior elite athletes’ and their parents’ self-talk during a competition. Hence, the aim of this study is to examine the content of elite junior tennis players’ automatic self-talk as well as the content of their parents’ self-talk regarding their emotions during important matches. In each of the two cases under investigation, individual in-depth interviews were conducted with a tennis player and his or her most dedicated parent. The results were analyzed using Yin’s (2014) multiple-case study strategy and Polkinghorne’s (1995) narration inquiry strategy. An analysis of automatic self-talk content was conducted individually for each case, followed by an intra-case and cross-case analysis. The results reveal that each player’s and parent’s automatic self-talk is related to their own subjective emotional experience during the matches. The findings highlight similarities in athletes’ and parents’ self-talk patterns, reflecting the potential influence of parents in athletes’ performance pressure and their goal-directed self-talk strategies. The differences observed between the self-talk of players and their parents demonstrate the relevance of examining their profiles to better understand the origin of individual differences in self-talk.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".