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Record W3184667874 · doi:10.3390/covid1010014

Disorder in ADHD and ASD Post-COVID-19

2021· article· en· W3184667874 on OpenAlexaff
Carol Nash

Bibliographic record

VenueCOVID · 2021
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSocial distancePsychologyAutism spectrum disorderMeaning (existential)SocializationPandemicDistancingCoronavirus disease 2019 (COVID-19)Affect (linguistics)Attention deficit hyperactivity disorderDevelopmental psychologyPsychiatryPsychotherapistMedicineAutismCommunicationDisease

Abstract

fetched live from OpenAlex

A diagnosis of either attention deficit/hyperactivity disorder (ADHD) or of autistic spectrum disorder (ASD) identifies an individual as unable to attend expectedly and appropriately, particularly in school settings. Until the COVID-19 pandemic, what defined the expected and the appropriate was considerate, close physical contact among people. In understanding that aerosol droplets from vocalization cause the transmission of the COVID-19 virus, what is acceptable contact has now shifted to distancing oneself from people and communicating in a way that eliminates vocal spray. The norms for socialization diametrically changed as a consequence of the pandemic. Yet, there has been no concurrent reassessment of the meaning of “disorder” related to ADHD and ASD within the school setting. A diagnosis of ADHD and/or ASD often brings with it an expectation for special education. Therefore, it is important that changes in social norms be recognized as they define the meaning of “disorder”. Investigated here is in what way each diagnosis demonstrates disorder in response to the imposed COVID-19 restrictions and how this can be anticipated to affect the schooling of those with ADHD and ASD during the pandemic.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.056
GPT teacher head0.357
Teacher spread0.301 · 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 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

Citations3
Published2021
Admission routes1
Has abstractyes

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