Female Varsity Athletes’ Perceptions of The Development of Optimism
Bibliographic record
Abstract
This study examined female athletes’ perceptions of how they became optimistic. In order to identify optimistic athletes, 83 members of female varsity sport teams at the University of Alberta completed a sport-specific version of the Life Orientation Test (LOT; Dunn, Causgrove Dunn, & Lizmore, 2015). Nine participants (M age = 19 years) who scored high in optimism (M score = 36.89, SD = 1.9) then completed individual semi-structured interviews. Seven of these participants also completed a member-checking interview. Data analysis followed Interpretative Phenomenological Analysis (Smith, Flowers, & Larkin, 2009). Results were organized across a developmental framework documenting shared aspects of participants’ perspectives of experiences that contributed to development of optimism during childhood, adolescence, and adulthood. During childhood participants perceived that their parents were supportive, provided feedback, and allowed them to have choice over the sports in which they participated. During adolescence coaches began to play a more important role in developing optimism and participants were able to learn about being optimistic through experiences, particularly negative experiences. Finally, during early adulthood participants developed personal narratives about the ways in which they approached sport with optimism. Practical implications arising from these findings include increasing parents’, coaches’, and athletes’ understanding of how to increase the development of optimism.
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 | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".