Whose Knowledge Counts? Examining Paradigmatic Trends in Adapted Physical Activity Research
Bibliographic record
Abstract
Who is the expert? Whose knowledge counts and what knowledge for whom and by whom is produced? Consequentially, whose knowledge is marginalized? These are critical questions to ask in relation to the field of Adapted Physical Activity (APA). Guided by epistemic and ethical responsibility, the purpose of this study was to respond to these questions through an extensive review of the paradigmatic trends in APA and to report on the roles of people experiencing disability in APA research other than as participant. Attending to the level of epistemology, we go beyond reporting the state of the field to reveal in what ways APA research may or may not be guided by the concerns and needs of the people it is intended to serve and support. Building on the findings, we discuss participatory research and its relevance to APA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.285 | 0.247 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.014 | 0.014 |
| Science and technology studies | 0.014 | 0.082 |
| Scholarly communication | 0.033 | 0.049 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.001 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".