Accessibility and participatory design: time, power, and facilitation
Bibliographic record
Abstract
This paper documents the goals, techniques, and outcomes of nine interventions designed to improve the accessibility of a design charette (DC). These interventions focused on Time, Power, and Facilitation and were developed based on critiques found in design literature, critical disability scholarship, and the lived expertise of disabled people. Data was collected through recording activities and outputs, recorded observations, and elicited feedback. We found that adjusting time, which is essential for access, was difficult and required trade-offs. We also suggest that the presence of a ‘vibes watch’ facilitation role to monitor participation frequency, emotional tone, and power dynamics can be useful to address uneven power relations, caucusing can also be valuable but should be used at specific moments. Non-neutral facilitation, anti-oppression training, and regular reflection can help facilitation/design teams identify and address exclusionary practices. Technology can aid but also constrain access. Finally, despite all interventions, access remains a site of friction and political choices. Stakeholders continue to participate in different and not always equally valued ways, so secondary analysis is useful for understanding charette products or outputs.
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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 | 0.118 | 0.115 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.028 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".