Understanding the process of learning life skills in mixed martial arts
Bibliographic record
Abstract
Life skill development has been identified as an outcome of youths' participation in organized sports (e.g., Holt et al., in press). Mixed Martial Arts (MMA) is a sport that combines techniques from a variety of martial art forms (e.g. karate, Brazilian jujitsu, wrestling, boxing). In recent years, MMA has grown in popularity, with programs often claiming to successfully develop youths' life skills; however, there is little consensus within the literature on MMA's potential to enhance youths' development (Theeboom, 2012). This study explored the experiences of youth MMA participants in relation to life skill development, using a phenomenological approach (Creswell, 2013). Participants included 13 youth (n=11 boys) ages 9-18 enrolled in youth MMA programs in Toronto. Semi-structured interviews focused on youths' background, knowledge of life skills, MMA experiences, self-reflection, and transfer. Interviews were analyzed using thematic analysis (Braun & Clark, 2006). Consistent with findings in other sports (e.g., Camire et al., 2013), the coach was found to be the most influential facilitator of life skill development, by having a strong connection with athletes, partnering youth with appropriate peer teachers, explicitly teaching life skills, and focusing on transfer to non-sport contexts. Perhaps unique to the MMA context, was that other adults who were present in the gym (i.e., in other adult classes/programs) had a substantive impact on some youth by modelling competence, confidence, and MMA skills. Findings are discussed using the conceptual frameworks of Ecological Systems Theory (Bronfenbrenner, 2005) and Experiential Learning Theory (Kolb, 1984).Acknowledgments: Social Sciences and Humanities Research Council, Sport Participation Research Initiative
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".