A meta-method analysis of qualitative research examining positive youth development through sport
Bibliographic record
Abstract
For this study we examined the methods used in qualitative studies of positive youth development (PYD) through sport. A meta-study comprised of four components: meta-method analysis, meta-theory analysis, and meta-data analysis was conducted, resulting in a meta-synthesis (Paterson, Thorne, Canam, & Jillings, 2001). Results of the meta-method analysis are presented. We used a custom-designed keyword search with a qualitative filter to search databases. Initial searches returned 1,089 citations. Following removal of duplicates, gray literature, reviews, and other irrelevant papers, 455 abstracts were retained. Abstract screening yielded 129 articles that were subjected to full text review. Fifty-nine qualitative articles were retained. Studies had a combined total sample of 1,999 participants, comprised of 342 children (aged 8-12 years), 1,216 adolescents (aged 13-18 years), 137 parents, 240 coaches, and 64 other adults. Studies were conducted in eleven different countries and focused on school, after-school, competitive sport, and summer camp settings. Interviews were used in 52 of the studies, and 34 studies used multiple data collection techniques, including journals, surveys, and participant observation. Methodologies most frequently used were case study (7), general qualitative (6), grounded theory (5), and phenomenological (4). Named methodologies were not reported in thirty-one studies. Forty-six studies reported validity techniques (e.g. rapport building, triangulation, and reflexivity). Strengths across studies included the use of purposeful sampling techniques and checks establishing analytical validity. More use of named methodologies may improve the sophistication of qualitative research in this area.Acknowledgments: Kacey C. Neely, Hayley DeBeaudrap, and Nicholas L. Holt
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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 | 0.248 | 0.335 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.012 | 0.033 |
| Bibliometrics | 0.038 | 0.026 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".