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Record W4384652768 · doi:10.5281/zenodo.8161512

I Lost all the Services Offered to my Child Overnight: Families' Experience of the Interruption of Early Intervention Services for Autism During the Covid-19 Pandemic in Quebec

2023· article· en· W4384652768 on OpenAlexaffabout
Mélina Rivard, Céline Chatenoud, Charlotte Magnan, Manuelle Beuchat, Catherine Mello, Heather M. Aldersey, Chun‐Yu Chiu

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2023
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsQueen's UniversityUniversité du Québec à Montréal
Fundersnot available
KeywordsPandemicCoronavirus disease 2019 (COVID-19)AutismIntervention (counseling)Psychology2019-20 coronavirus outbreakMedicineDevelopmental psychologyPsychiatryVirologyOutbreak

Abstract

fetched live from OpenAlex

Families of young children diagnosed with autism around the spring of 2020 were especially vulnerable as Covid-19 pandemic-related restrictions interrupted the delivery of their specialized early intervention services. This paper examined 34 families' perceptions of the impact of this situation in Quebec on their child and their family using a mixed-methods design. Parents reported largely detrimental effects on their access to, and relationships with, service providers and their child's transition to school. They noted negative changes in several domains of child development. The need to combine childcare responsibilities with telework was also a source of stress. This situation resulted in family adjustment challenges and in the exacerbation of pre-existing vulnerabilities. However, parents also remarked on their family's ability to adapt and mobilize resources.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.146
Threshold uncertainty score0.294

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0140.004
Scholarly communication0.0030.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.072
GPT teacher head0.347
Teacher spread0.275 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)→Same topicFamily and Disability Support Research→French-language works237,207→