Addressing Trauma in Adaptive Physical Activity: A Call to Reflection and Action
Bibliographic record
Abstract
Trauma is pervasive, embodied, and can be perpetrated or perpetuated by researchers, educators, and practitioners, including those within adaptive physical activity (APA). In this article, we highlight the need to address trauma within APA as a matter of access and justice. We share various conceptualizations of trauma from psychiatric, embodied, anti-pathologizing, and sociopolitical perspectives. Trauma-informed practice is introduced as a framework for creating safer, more inclusive programs and services, so we can recognize the impacts of trauma and affirm those who experience it. As the first step to a multistep trauma-informed process, our aim is to raise awareness of trauma and introduce resources for enacting trauma-informed practice. We also pose difficult questions about how we, as "helping" practitioners, researchers, and educators may be perpetuating or perpetrating harm and trauma, in particular sanism, within our profession. Ultimately, we invite readers to join us in reflection and action toward anti-pathologizing trauma-informed APA.
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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 | 0.094 | 0.119 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.016 | 0.092 |
| Scholarly communication | 0.028 | 0.046 |
| Open science | 0.008 | 0.031 |
| Research integrity | 0.033 | 0.100 |
| Insufficient payload (model declined to judge) | 0.005 | 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".