COVID-19 Vaccination for People with Disabilities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Internationally, people with disabilities have been disproportionately impacted by COVID-19, accounting for nearly 60% of COVID-19 deaths in the UK and overall higher mortality rates based on social, clinical, and demographic factors. Ontario has prioritized people with disabilities across the three phases of its COVID-19 vaccination program, but there is a difference between availability and accessibility of vaccination. Ontario’s 34 public health units are responsible for leading the local distribution and administration of COVID-19 vaccines, and their public facing websites serve as entry points for information on the accessibility of vaccination. On average, these websites contain information about 5 of 18 key accessibility features, across three domains: accessible communication, physical accessibility, and accessible social and sensory environments. Ontario needs a multi-pronged strategy to reach all people with disabilities that includes improving information about communication accessibility, physical accessibility, and social and sensory environment accessibility throughout the COVID-19 vaccination journey. Ontario’s progress on vaccinating people with disabilities needs to also be measured through enhanced data monitoring efforts.
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.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 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 it