Investigating the participation motives of women rugby union players in Canada and Wales
Bibliographic record
Abstract
Previous interview research has indicated that women's rugby union participation is multifaceted, with most players providing several different motives for getting involved in the sport.The aim of this study was to further examine participation motivation in women's rugby by replicating and extending the findings of the earlier research (Kerr, 2021) using a different approach to data collection and a larger sample size.Snowball sampling was used to recruit rugby playing female participants.A qualitative study focusing on participant responses to open-ended questions on participation motivation from an online survey was then undertaken.Thematic analysis was utilized to identify sub-themes and major themes from the data.These were found to be common to both Canadian and Welsh female rugby players.Four major themes were identified from the survey data.These were: Intrinsic motivation; Unique culture; Barriers to participation; and Acknowledgment of future generations.These major themes subsumed a number of sub-themes with overlapping characteristics.Empowerment and sense of challenge were included under the major theme Intrinsic motivation, and counterculture and stereotypes included under the major theme Barriers to participation.The current study replicated a number of findings from the original study, but there were two new findings.The first was that some players experienced a strong sense of empowerment through playing rugby.The second was the desire to give something back and help to continue to grow the sport.Reversal theory was used to interpret the findings and explain the psychological background to the players' participation motives.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".