Engaging Axiology: Enabling Meaningful Transdisciplinary Collaboration in Adapted Physical Activity
Bibliographic record
Abstract
In this article, I explore the concept of axiology in the context of adapted physical activity research and analyze its connection to the more commonly discussed paradigmatic assumptions of epistemology and ontology. Following methodological scholars, I argue for an acknowledgment of the pivotal role that axiology already plays in adapted physical activity research and for the potential interdisciplinary and transdisciplinary opportunities that could be enabled by engaging with axiology in more explicit ways. I discuss a number of potential axiological gaps between the field of adapted physical activity and disability communities, arguing that such differences may undermine attempts at doing meaningful transdisciplinary research with such communities. I offer strategies for bridging these axiological gaps, encouraging us to work together in axiologically reflexive ways in order to increase meaningful opportunities for more people with disabilities to be engaged in the movement-based activities and communities of their choice.
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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 | 0.057 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.014 | 0.054 |
| Scholarly communication | 0.020 | 0.024 |
| Open science | 0.003 | 0.047 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 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".