Empowerment in decision-making for autistic people in research
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Empowerment in research is important in many autism and autistic communities and an important part of ‘nothing about us without us’. It is also an important component of person-oriented research ethics. This article reviews the literature on ethics in autism research for information related to decision-making empowerment for autistic people. A review of 81 articles reveals several themes and specific strategies. Empowerment is important for, but also goes beyond, establishing informed consent. Empowerment is a form of participant and community engagement, and necessarily shaped by specific context. The view of research ethics put forth in this article envisions ethics as a potential avenue for empowerment, where research participants are able to decide how to be involved and to shape research processes and contexts. This view of research ethics is aligned with the aspirations of many in advocacy communities, though it may not correspond to conventional understandings of research ethics.Points of interestThis article talks about ethics in autism research.It focuses on the importance of people with autism having the power to make choices about research.It describes what published articles have said about this issue.Making choices about research includes not only the choice to take part in a study or not, but also many other choices before, during, and after the study.The way that this article talks about research ethics helps achieve goals of many autistic people and disabled people to be included.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it