Status of early hearing detection and intervention programs in Canada: Results from a country-wide survey
Bibliographic record
Abstract
In Canada, early hearing detection and intervention programs go beyond population screening of newborn hearing and offer services to confirm the presence or absence of hearing loss and provide services should permanent hearing loss be detected. Early hearing loss identification and intervention is critical to promote language, literacy, and social skills in developing children. However, a report card issued in 2014 from the Canadian Infant Hearing Task Force indicated that comprehensive early hearing detection and intervention programs were not uniformly available across Canada. The current work aimed to update the status of early hearing detection and intervention programs in Canada through a 24-item survey completed by 19 representatives in all 13 provinces and territories. Since 2014, there have been some improvements in early hearing detection and intervention programs in some areas of Canada. In others, comprehensive infant hearing services are not available province-or territory-wide or have not been provided with the necessary resources to sustain a suitable early hearing detection and intervention program. Results revealed that Canada is insufficient in offering comprehensive, accessible, and sustainable early hearing detection and intervention programs. Babies born in Canada deserve access to all components of an early hearing detection and intervention program, regardless of where they live. Continued action from Canada’s provincial and territorial governments in addition to federal policy leadership is needed to achieve sufficient and sustainable early hearing detection and intervention programs across the country.
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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".