Bibliographic record
Abstract
Youth sport has the potential to provide numerous psychological, physical, and social benefits, however with high dropout rates (participation decreases by about 20% between 10-15 years old according to Active Healthy Kids Canada, 2014) not all children have the opportunity to receive these benefits. The overall climate of youth sport can contribute to dropout (Hedstrom & Gould, 2004) and adult involvement in youth sport is part of shaping that climate. One adult group that influences children's sport experience and the overall climate of youth sport is parents, who provide various types of support but can also negatively influence the climate through their behavior on the sidelines. Using Bronfrenbrenner's Ecological Systems Theory (1977), the purpose of this poster is to outline what is known about sport parent sideline behavior and build a model that identifies gaps in current research and frames future studies about sport parent sideline behavior. A database search yielded 21 studies that were used to build the model. From this model, it is clear that the perspective of the parent is not often considered and therefore future research about parental preferences for sideline behavior, including whether these preferences are influenced by personal or situational factors, is proposed. Specifically, gender and previous sport experience are personal factors that need to be examined and the situational factors of type of sport, the stakes, and type of occurrence on the playing field are factors that need to be considered simultaneously in a large scale study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".