The Connected Life: Using Access Technology at Home, at School and in the Community
Bibliographic record
Abstract
Hearing technologies such as hearing aids, cochlear implants and bone-anchored devices provide students with hearing loss with far greater access to auditory information (and most importantly, to spoken language) than even a decade ago. However, in a student’s daily life, many situations arise where effective communication and participation can be comprised by factors such as distance, noise, reverberation, difficulty hearing peer input, missing or obscured visual information (e.g., due to masks during the COVID-19 pandemic), speakers with accents or poor auditory/visual quality (e.g., on the phone or during online learning). Access technologies such as remote microphone systems, wireless connectivity platforms and captioning can be used to supplement and/or clarify auditory and visual information, so that students can fully participate in all aspects of their lives. This article discusses how access technologies can provide support for students in preschool, elementary, secondary and postsecondary education. The importance of universal design for access to public spaces, such as schools and community spaces, to ensure that individuals with hearing loss live in an equitable and inclusive world are also discussed.
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 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".