Person‐Oriented Research Ethics to Address the Needs of Participants on the Autism Spectrum
Bibliographic record
Abstract
Research ethics scholarship often attends to vulnerability. People with autism may be vulnerable in research, but are also vulnerable to unjust exclusion from participation. Addressing the needs of participants with autism can facilitate inclusion and honor the bioethics principle of respect for persons while accounting for risk and vulnerability. Drawing from a review of the literature and informed by a moral deliberation process involving a task force of stakeholders (including autistic people and parents of autistic people), we use the model of person-oriented research ethics to identify several practical strategies researchers can use to address these needs and foster inclusion. Strategies include using multiple means of communication, addressing the sensory environment, preparing participants in advance, and accounting for social context. These practical strategies are not just methodological or design choices; they are inherently related to ethical issues. Method and design choices fulfill ethical aspirations by facilitating inclusion, reducing discomfort, and focusing on individuals.
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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 | 0.246 | 0.158 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.034 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".