Social Robots: Views of Staff of a Disability Service Organization
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
Social robotics is an emerging field, with many applications envisioned for people with disabilities. This project examined the so far invisible views of disability service organization workers towards social robotics. Because community service workers’ views shape community-based rehabilitation (an area of health interventions that focuses on social determinants), it is important to examine their views towards social robotics applications which are largely developed under a clinical/medical view of disability. We administered a survey to employees of a Saskatchewan disability service organization. Out of 44 respondents, 80 % were female, most aged 21–65 years. Robotics applications perceived to be important included domestic robots, and rehabilitation robots. Least important applications included eldercare robots, companion robots, and pet robots. Most participants felt that robots cannot replace human touch, human interaction, or emotional companionship, and that they cannot/should not replace human workers in the disability setting. Many expressed concerns about safety, normality for disabled people, and artificial interactions. Respondents also had views on whether a social robot can be a bully or could be bullied. We submit that the perspectives our respondents exhibited might be useful to consider in the development of social robots for applications around disability in order to ensure acceptable and relevant products.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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