Are Tertiary Institutions Losing Sight of Their Duty to <i>Cura Personalis</i> ?
Bibliographic record
Abstract
Purpose: Physical education requirements (PERs) have been suggested as a potential solution for increasing physical activity (PA) among undergraduate students, specifically for the inactive who face the greatest barriers to PA. In 2010, among a nationally-representative, random sample of tertiary institutions in the U.S. only 39% had PERs as part of their general education curriculum. But, being a decade old, this data may be outdated. The aim of this study was to examine the current status of PERs in U.S. tertiary institutions and to explore what institutional characteristics are associated with having a PER. Methods: Academic catalogs of a nationally representative, random sample of 331 institutions were searched for PER information. Results: The majority of U.S. tertiary institutions did not mandate physical education (PE) courses (56.2%), whereas 31.7% fully and 12% partially required their undergraduate students to complete a PE course to graduate. The characteristics most associated with an institution having a PER included being private, having a small enrollment size, having an academic degree program related to the field, having both activity and conceptual components, being <3 credit hours, offering an elective program in physical activity education, and being located in the south. Conclusion: Future work is needed to identify important elements of PER courses, reasons why PERs are sustained by some institutions versus others, and to establish practical guidelines regarding best practices for quality PER courses. More direct action within the discipline of kinesiology is needed to underscore the importance and need of PERs at the tertiary level.
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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 | 0.005 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.038 | 0.007 |
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".