Pilot on evaluating social participation following the use of an assistive technology designed to facilitate face-to-face communication between deaf and hearing persons
Bibliographic record
Abstract
We know very little about social participation following the use of an assistive technology, and nothing reagarding device designed to facilitate face-to-face communication between hearing persons and deaf people who use sign language, and cannot speak and write. A pilot on evaluating social participation following the use of a new assistive technology is proposed. Fifteen deaf adults completed a three-month field study, with pre and post intervention measures. Three standardized instruments (LIFE-H, FACS, QUEST) were adapted for sign language interpretation and pretested. One month into the study, all participants had used the AT in 40% of ADL and 33% of social roles. AT use in life habits subsequently declined. The results for social participation showed only one significant improvement (p=0.026) after one month of AT use: the item concerning conversation with a hearing person. For functional communication, we found a significant improvement after 8 (p=0.016) and 12 weeks (p=0.012) for “social communication” only. The users were “neither dissatisfied nor satisfied” with the AT. Effectiveness, ease of use and follow-up services are considered critical. Methodological and technical improvements are suggested for researchers, developers, promoters and clinicians.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".