Brain-Computer Interfaces, Inclusive Innovation, and the Promise of Restoration: A Mixed-Methods Study with Rehabilitation Professionals
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
Over the last two decades, researchers have promised “neuroprosthetics” for use in physical rehabilitation and to treat patients with paralysis. Fulfilling this promise is not merely a technical challenge but is accompanied by consequential practical, ethical, and social implications that warrant sociological investigation and careful deliberation. In response, this paper explores how rehabilitation professionals evaluate the development and application of BCIs. It thereby also asks how the BCIs come to be seen as desirable or not, and implicitly, what types of persons, rights, and responsibilities are assumed in this discourse. To this end, we conducted a web-based survey (N=135) and follow-up interviews (N=15) with Canadian professionals in physical therapy, occupational therapy, and speech-language pathology. We find that rehabilitation professionals, like other publics, express hope and enthusiasm regarding the use of BCIs for assistive purposes. They envision BCI devices as powerful means to reintegrate patients and disabled people into social life but also express practical and ethical reservations about the technology, positioning themselves as uniquely qualified to inform responsible BCI design and implementation. These results further illustrate the nascent “co-production” of neural technologies and social order. More immediately, they also pose a serious challenge for implementing frameworks of responsible innovation; merely prescribing more inclusive technology development may not counteract technocratic processes and widely held ableist views about the need to augment certain bodies using technology.
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Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Science and technology studies Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Qualitative | high |
| gpt | Science and technology studies Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Other design | high |
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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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