Youth Female Ice Hockey Players’ Enjoyment and Commitment to Sport
Bibliographic record
Abstract
The purpose of this study was to identify sport-specific predictors of youth female athletes’ sport commitment and sport enjoyment. Based on the expectancy-value model, athletic identity and gender stereotypes were hypothesized to predict sport commitment and sport enjoyment in ice hockey, which has a masculine gender association. Participants consisted of 130 (89.2% Caucasian) youth female ice hockey players (Mage = 11.7, SD = 2.6). They completed measures of athletic identity; personal gender beliefs; perceived gender beliefs of parents, teammates, siblings, and the general population; and two outcome measures: sport commitment and sport enjoyment. The prediction model for sport commitment was significant, F(7, 122) = 9.56, p < .001, and accounted for 35.4% of the variance. The prediction model for sport enjoyment was also significant, F(7, 122) = 2.25, p < .01, and accounted for 11.5% of the variance. Overall, youth female ice hockey players held pro-feminine beliefs about competence and values of girls in hockey. Participants’ personal gender beliefs correlated moderately with perceived gender beliefs of their (socializers) parents, teammates, and the general population (r = .54–.56), suggesting youth female ice hockey players’ pro-feminine beliefs might be informed by these social influences. However, two multiple mediation analyses found no support for the hypotheses that personally held stereotypes mediated the link between all four socially based gender stereotypes and enjoyment and commitment.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".