Understanding the process of life skills application beyond sport
Bibliographic record
Abstract
The life skills process (i.e., sport to life) involves three interrelated stages: (a) life skills learning in sport, (b) life skills transfer, and (c) life skills application in at least one life domain beyond sport (Pierce, Gould, & Camire, 2017). The purpose of the study was to examine how athletes apply in life the skills learned or refined in sport in order to develop new theoretical explanations for the third stage of the life skills process (i.e., application). The study employed a Straussian grounded theory methodology (Corbin & Strauss, 2015). Data collection occurred over ten months and involved: (a) interviewing, (b) chronological charting, (c) timelining, and (d) solicited journaling with university intramural athletes (n = 13) between the ages of 18 and 24 years (M = 21.77; SD = 2.2). Social agents (n = 29) aged 19 to 58 years (M = 31; SD = 13.4) playing key roles in the athletes' lives (e.g., parents, partners, work colleagues) in life skills application contexts were theoretically sampled and interviewed. Analysis involved an iterative process of open coding, axial coding, and theoretical integration. The substantive grounded theory is constructed on the core category of mutually beneficial person-context regulations. Within the theory, life skills application is framed as an ongoing process of (a) decision-making, (b) application, (c) appraisal, and (d) adaptation. The study's contribution lies in the grounded theory putting forth new theoretical explanations for how athletes apply in their everyday lives the skills they deem to have learned or refined in sport.Acknowledgments: Social Sciences and Humanities Research Council
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".