Community-Based Participatory Design for Research That Impacts the Lives of Transgender and/or Gender-Diverse Autistic and/or Neurodiverse People
Bibliographic record
Abstract
Objective: Research addressing the co-occurrence of autism (and/or neurodiversity) and gender-diversity (A/ND-GD) has been conducted largely without the perspectives and voices of the A/ND-GD community. Including A/ND-GD community advocates as research partners may be a critical next step for advancing research initiatives on the co-occurrence given the apparent complexity and alterity of the A/ND-GD experience. Method: Consistent with the community-based participatory research (CBPR) model we propose herein, our authorship team includes a partnership between clinician researchers and diverse A/ND-GD community collaborators. Multiple facets of the A/ND-GD lived experience are examined, including through narratives provided by our A/ND-GD community partners. Results: Based on our experience conducting A/ND-GD-related research and our lived experience as A/ND-GD self-advocates, we highlight challenges in this line of research, including risks of conducting studies without the involvement of the A/ND-GD community. And given that many A/ND-GD youth present with gender-related urgency during the teen years, we provide a developmental framework for how CBPR-informed methods may enrich our understanding of the care needs of these young people and provide context for the apparent heterogeneity in their gender needs and trajectories over time. Conclusions: Integrating CBPR methodologies in A/ND-GD research initiatives has the potential to optimize the relevance of the research questions asked and the interpretation and contextualization of study findings. Implications for Impact Statement The perspectives and priorities of the autistic and/or neurodiverse transgender and/or gender-diverse community need to be considered when conducting research that impacts autistic/neurodiverse transgender/gender-diverse individuals. Employing community-based participatory designs for studies of this co-occurrence will help to align research agendas with community needs and appropriately contextualize research findings.
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 | 0.148 | 0.106 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.012 | 0.014 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.005 | 0.015 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.017 | 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".