Female varsity athletes' perception of how coaches influence their self-confidence
Bibliographic record
Abstract
Communities and athletes see coaches generally as leaders, mentors, and role models in sport. Recent research in the field of coaching revealed that coaches must have the ability to encourage, challenge, and understand the athlete (Bloom, 2002b). Further research indicates that females are known to be psychologically and physically different than males (Fasting & Pfister, 2000); therefore, most females need to be coached differently than men during practice and competition. The notion of self-confidence is an essential element in Vealey's (1986) Sport Confidence Model, in which it is defined as: "the belief or degree of certainty individuals possess about their abilities to be successful in sport" (p. 222). The purpose of this qualitative study was to understand female varsity athlete's perception of how coaches influence their self-confidence. The study used twelve participants (N = 12) among Canadian Interuniversity Sport teams: basketball (3), soccer (3), hockey (2), rugby (2), and volleyball (2). Semi-structured interviews were conducted regarding athletes perception of (a) athlete's perception of self-confidence, (b) different coaching qualities that may positively or negatively influence athletes self-confidence, and (c) athletes perception of an 'ideal' coach that positively influences their self-confidence. The results displayed a combined definition of all 12 athlete's perception of self-confidence, which is "one who believes in herself, has inner strength (while not worrying about others beliefs), and stays positive throughout their sport and life." Secondly the results found four main qualities that athletes perceive essential for a coach to positively influence their self-confidence. Finally, the results revealed 12 predominant coaching characteristics that athletes perceive essential for positively influence their self-confidence. An 'ideal coach' would display these characteristics.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".