Development and Validation of a Survey Instrument to Build Capacity for Examining Constraints to Sport Participation
Bibliographic record
Abstract
It is well documented that sport participation is relatively low among adolescent girls due to various constraints.Though much knowledge exists on these constraints, there is a need to examine if and whether constraints interact to influence sport participation.The purpose of this study was to develop a survey instrument to facilitate the examination of interactions of constraints to sport participation among adolescent girls, and to verify the survey's validity.Two theoretical frameworks were combined to guide the survey development.Newell's model of constraints was used to categorize constraints, into environmental, individual and task constraints.The 40 Developmental Assets Profile was used to index the constraints into broader categories within each constraint type.In total, 51 constraints were sorted into the combined frameworks which developed an 81-question survey.An expert panel was consulted to review for construct and content validity.This study has contributed a new survey instrument to the literature on constraints to sport participation.When used in different locations globally, the survey has the potential to reveal the most salient constraints, as well as build capacity for research to better inform future interventions and promote further discussions regarding sport.
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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 | 0.087 | 0.082 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".