Key Word Signing Usage in Residential and Day Care Programs for Adults With Intellectual Disability
Bibliographic record
Abstract
Abstract Key word signing (KWS) is a means of augmentative and alternative communication frequently used with adults with intellectual disabilities (ID). Their acquisition ofKWShas been described in the literature; however, little is known about the everydayKWSuse among adults withIDand their support staff. This study aimed to give an account of the prevalence ofKWSand the sign knowledge of adults withIDand their support staff inFlemish residential programs (RPs) and day care programs (DCPs). Communication specialists in allRPs andDCPs for adults withIDinFlanders, theDutch‐speaking part ofBelgium, were contacted by phone and were asked whether they usedKWS, and if so, whether they were willing to fill out a questionnaire about theKWSuse of support staff and clients. Findings show that of 347RPs andDCPs inFlanders, 85% met the inclusion criteria. Half (51.2%) of these programs usedKWS. Of these 152 programs, 93 (61.2%) completed our questionnaire. A quarter (26.6%) of their adult clients withIDusedKWS. Most of them knew 10–50 signs, whereas most support staff knew fewer than 10 signs. The presence of a speech and language therapist as well as sign knowledge and attitude of support staff were significantly related to the sign knowledge of their clients. Motivational problems for staff to useKWSwere quite common.KWSsupport should be more widespread and more easily accessible.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".