Global COVID-19 childhood disability data coordination: A collaborative initiative of the International Alliance of Academies of Childhood Disability
Bibliographic record
Abstract
PURPOSE: The International Alliance of Academies of Childhood Disability created a COVID-19 Task Force with the goal of understanding the global impact of COVID-19 on children with disabilities and their families. The aim of this paper is to synthesize existing evidence describing the impact of COVID-19 on people with disabilities, derived from surveys conducted across the globe. METHODS: A descriptive environmental scan of surveys was conducted. From June to November 2020, a global call for surveys addressing the impact of COVID-19 on disability was launched. To identify gaps and overlaps, the content of the surveys was compared to the Convention on the Rights of the Child and the International Classification of Functioning, Disability and Health. RESULTS: Forty-nine surveys, involving information from more than 17,230 participants around the world were collected. Overall, surveys identified that COVID-19 has negatively impacted several areas of functioning - including mental health, and human rights of people with disabilities and their families worldwide. CONCLUSION: Globally, the surveys highlight that impact of COVID-19 on mental health of people with disabilities, caregivers, and professionals continues to be a major issue. Rapid dissemination of collected information is essential for ameliorating the impact of COVID-19 across the globe.
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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 | 0.006 | 0.110 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".