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Record W4378378622 · doi:10.3390/children10060942

Children with Disabilities in Canada during the COVID-19 Pandemic: An Analysis of COVID-19 Policies through a Disability Rights Lens

2023· article· en· W4378378622 on OpenAlexafffundabout
Keiko Shikako‐Thomas, Raphael Lencucha, Matthew Hunt, Sébastien Jodoin, Ananya Chandra, Anna Katalifos, Miriam González, Sakiko Yamaguchi, Roberta Cardoso, Mayada Elsabbagh, Anne Hudon, Rachel Martens, Derrick L. Cogburn, Ash Seth, Genevieve Currie, Christiane Roth, Brittany Finlay, Jennifer Zwicker

Bibliographic record

VenueChildren · 2023
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsMontreal Neurological Institute and HospitalUniversity of CalgaryUniversité de MontréalMcGill University Health CentreMcGill University
FundersCanadian Institutes of Health ResearchMcGill University Health CentreCentre for Interdisciplinary Research in RehabilitationMcGill University
KeywordsPandemicThematic analysisMental healthConvention on the Rights of Persons with DisabilitiesPublic healthPolitical sciencePublic policyHealth policyPsychological interventionHuman rightsCoronavirus disease 2019 (COVID-19)Economic growthPublic relationsPsychologyMedicineNursingQualitative researchSociologyPsychiatryDisease

Abstract

fetched live from OpenAlex

Children with disabilities were especially vulnerable during the COVID-19 pandemic, and policies designed to mitigate its effects were limited in addressing their needs. We analyzed Canadian policies related to children with disabilities and their families during the COVID-19 pandemic to identify the extent to which these policies aligned with the United Nations Convention on the Rights of Persons with Disabilities (UN CRPD) and responded to their mental health needs by conducting a systematic collection of Canadian provincial/territorial policies produced during the pandemic, building a categorization dictionary based on the UN CRPD, using text mining, and thematic analysis to identify policies' alignment with the UN CRPD and mental health supports. Mental health was addressed as a factor of importance in many policy documents, but specific interventions to promote or treat mental health were scarce. Most public health policies and recommendations are related to educational settings, demonstrating how public health for children with disabilities relies on education and community that may be out of the healthcare system and unavailable during extended periods of the pandemic. Policies often acknowledged the challenges faced by children with disabilities and their families but offered few mitigation strategies with limited considerations for human rights protection.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.672

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.040
GPT teacher head0.324
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2023
Admission routes3
Has abstractyes

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