Adolescent Girls’ Leisure: A Conceptual Framework Highlighting Factors That Can Affect Girls’ Recreational Choices
Bibliographic record
Abstract
In Australia adolescent girls are less fit than boys, and this is a matter of some concern. This has also been found in American and Canadian studies. Although many adolescent girls engage in physically active recreation activities in public places, others choose more passive recreation in private spaces, which has implications for their health. This article shows how a conceptual framework can be useful to provide a pictorial representation of the relationships between factors that can affect girls’ leisure choices and their potential outcomes. For example, prior to choosing to participate in a recreational activity, girls often weigh up the potential for ridicule of their physical appearance or athletic competence against the potential enjoyment of the activity. This paper contains a vignette to illustrate how the framework can work, followed by potential strategies to consolidate or challenge the framework, and how it could be used to develop strategies for change. This snapshot of girls’ decision-making processes should be of use to recreation programmers, facility providers and education authorities. It can help to focus efforts to improve factors that increase girls’ levels of participation in healthy physical activity and decrease those factors that inhibit participation.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".