Research in the wild(s): Opportunities, affordances and constraints doing assistive technology field research in underserved areas
Bibliographic record
Abstract
The particular needs of disabled children in the 'Majority World' is under researched. There is an assumption that children's needs are the same as those supported by well-developed healthcare infrastructures. Field research is necessary to understand the design challenges, opportunities and affordances for these children. For research and design to meet their unique needs, processes must start with children in their own communities. AAC (Alternative and Augmentative Communication) technology design rarely benefits from early stage in situ fieldwork. We report on the conceptualization, development and lessons learned from field research surrounding our AAC device, we call the RE/Lab Comunicación Aumentada Móvil (Mobile Augmented Communication) device, developed specifically for disability design fieldwork with indigenous communities in Cochabamba, Bolivia. Our device is part of Diseñando para el Futuro (Designing for the Future), which is supporting the indigenous community in the creation of custom adaptations for disabled children in Cochabamba. In order to ascertain design requirements of AAC devices and applications for such communities, we took our prototype AAC device into the field as both a tool 'in development' and as a communication artifact to enable us to understand the needs of these children. The project PI (an Autistic self-advocate) situates research practice within the 'nothing about us without us' paradigm, accordingly, project goals are to work with children to create communication tools to help them express their goals, interests and needs and enable the co-creation of new tools with them.
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 | 0.027 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.017 | 0.026 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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; 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".