Jack of All Trades, Master of One: Examining Tensions Around Preparing Work-Ready Kinesiology Graduates in Canada
Bibliographic record
Abstract
This paper draws on findings from a study aimed at examining how Canadian Kinesiology programs define themselves within the post-secondary education landscape, and their students’ understandings and experiences of their studies. Using critical discourse analysis, our findings demonstrate Kinesiology’s ability to preserve its appeal among undergraduate students through its successful positioning of itself as a disciplinary field of choice and flexibility, and students’ own enthusiasm for and optimism about Kinesiology as a meaningful area for study. However, our findings also highlight Kinesiology’s entrenched alignment with narrow conceptualizations of health/healthcare, and inherent vulnerabilities in the current post-secondary education landscape given that such programs do not necessarily produce workplace-ready graduates as much as they produce ready-for-more-education graduates. We conclude by discussing the implications of such tensions.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.040 | 0.015 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".