Access to Augmentative and Alternative Communication (AAC) Technology in Canada: Evaluation of Current System
Bibliographic record
Abstract
Alternative and augmentative communication (AAC) systems enable persons to communicate, yet access to these devices is limited. In 2019, the Government of Canada introduced “The Accessible Canada Act”, an act to ensure a barrier-free Canada. However, its primary source for data collection on persons with disabilities (Canadian Survey on Disability) does not include communication disabilities in its list of disabilities, neglecting people with complex communication needs. This research sought to determine the barriers to accessing AAC technology in Canada. A scoping review was conducted to understand the identified barriers in literature that occur in Canada. Barriers are present in accessing services, funding, technology, and even about baseline knowledge required to access and use the system itself. Identification of associations to enable access included 43 government programs and charitable organizations. While the websites for charitable organizations were objectively easier to navigate than the government websites, both provided insufficient information to confirm AAC eligibility and often had outdated or unreliable links. Many websites do not conform to the World Content Accessibility Guidelines, applications are too difficult to read, and crucial program information is dispersed across multiple web pages, documents, and websites. There are numerous opportunities for information and documents to be misinterpreted, unnoticed, or forgotten. To gain access to AAC in Canada, there are different procedures based on the location in which one lives (rural, urban, province, territory), access to clinicians, and the ability to navigate websites and application procedures. As AAC device selection is limited through government programs and charitable organizations, the process of application to these programs must be clear and barrier-free. Optimization of services would greatly improve AAC access and improve the possibility of reaching a barrier-free Canada by 2040, the goal of the Accessible Canada Act.
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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 | 0.034 | 0.104 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.013 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".