Say What You Mean: Rethinking Disability Language in Adapted Physical Activity Quarterly
Bibliographic record
Abstract
Adapted Physical Activity Quarterly (APAQ) currently mandates that authors use person-first language in their publications. In this viewpoint article, we argue that although this policy is well intentioned, it betrays a very particular cultural and disciplinary approach to disability: one that is inappropriate given the international and multidisciplinary mandate of the journal. Further, we contend that APAQ's current language policy may serve to delimit the range of high-quality articles submitted and to encourage both theoretical inconsistency and the erasure of the ways in which research participants self-identify. The article begins with narrative accounts of each of our negotiations with disability terminology in adapted physical activity research and practice. We then provide historical and theoretical contexts for person-first language, as well as various other widely circulated alternative English-language disability terminology. We close with four suggested revisions to APAQ's language policy.
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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 | 0.096 | 0.155 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.012 | 0.051 |
| Scholarly communication | 0.024 | 0.032 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.007 | 0.020 |
| 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".