The Role of Dynamic Social Norms in Promoting the Internalization of Sportspersonship Behaviors and Values and Psychological Well-Being in Ice Hockey
Bibliographic record
Abstract
Conducted among parents of young ice hockey players, this field experiment tested if making salient increasingly popular (i.e., dynamic) social norms that promote sportspersonship, learning, and having fun in sports, increases parents’ own self-determined endorsement of these behaviors and values, improves their psychological well-being, and impacts on their children’s on-ice behaviors. Hockey parents (N= 98) were randomly assigned to the experimental condition (i.e., presenting dynamic norms that increasingly favor sportspersonship, learning, and fun) vs. control condition (i.e., presenting neutral information). Parents’ motivations for encouraging their child to learn and to have fun in hockey were then assessed. Score sheets for the games that followed the study provided access to their children’s on-ice behaviors (i.e., penalties), as indicators of sportspersonship. Parents in the experimental condition reported higher self-determination for encouraging their child to learn and have fun in hockey compared to parents in the control condition. Furthermore, children of parents in the experimental condition had more assists. A mediation model revealed that the dynamic norms manipulation increased parents’ self-determined motivation for encouraging their child to learn and to have fun in hockey, which in turn, predicted higher psychological well-being (i.e., lower anxiety, more vitality). Together, these results provide support for the contention that highlighting increasingly popular social norms that promote sportspersonship, learning, and fun in sports, represents a promising strategy for creating positive social change in this life context.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".