Understanding (and extending) the conceptual boundaries of policy research in physical education: A scoping review
Bibliographic record
Abstract
Given limited investigation into the state and status of physical education policy research internationally, we suggest there is a need for a more comprehensive empirical review of physical education policy research internationally to inform a future research agenda. The purpose of this scoping review is to map the international peer-reviewed empirical literature detailing policy research in school-based physical education between 2010 and 2020 to understand and make recommendations for extension, where appropriate, of the conceptual boundaries of how to ‘do’ policy research in this field. We followed a three-phase approach to the scoping review: (i) identifying relevant sources; (ii) charting of sources; and (iii) reporting the findings from the charting of sources. Results were interpreted through two theoretical lenses: (a) Rizvi and Lingard's (2010) framework of policy issues and questions and (b) Diem et al.’s (2014) traditional and critical approaches to educational policy research. Findings are discussed in relation to the charting categories which included: journal; year; affiliations; country of work; funding acknowledgements; research question; policy definition; policy issues; and traditional and/or critical research. We hope this research can be useful to those looking to enter the physical education policy research space, as it introduces them to the research landscape, and to those already engaged in this space looking to fill gaps in the literature.
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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 | 0.258 | 0.435 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.046 | 0.048 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.025 | 0.031 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".