"Knowledge Comes Through Participation": Understanding Disability through the Lens of DIY Assistive Technology in Western Kenya
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
People with disabilities in Low- and Middle-Income Countries (LMICs) have limited access to digital assistive technologies (ATs). Most ATs in LMICs are manufactured elsewhere and are expensive and difficult to maintain. Do-It-Yourself Assistive Technologies (DIY-ATs) designed, customized, and repaired by non-technical users offer exciting directions in these contexts. We have been exploring the possibilities and challenges of DIY-ATs in Western Kenya, using community-engaged workshops in rural and urban special education schools for the past three years. We present findings from a concluding-stage research activity: a multiple stakeholder focus group where teachers, disability advocates, and representatives from the local government and technology innovation hubs, discussed the possibilities and challenges of addressing disability issues through DIY-ATs in this context. Participants identified opportunities for DIY-ATs for social inclusion, disability assessment, and inclusive education, and shared concerns about their sustainability, safety, and contextual relevance.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| 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