MétaCan
Menu
Back to cohort
Record W4395003108 · doi:10.1111/1471-3802.12672

The digital citizenship of children with autism: Challenges, considerations and educational needs of paediatric practitioners

2024· article· en· W4395003108 on OpenAlex
Yael Mayer, Tessa Goldberger, Nicole Di Spirito, Mor Cohen‐Eilig, Tal Jarus

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Research in Special Educational Needs · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsSunny Hill Health Centre for ChildrenUniversity of British Columbia
Fundersnot available
KeywordsAutismCitizenshipPsychologySpecial educational needsSpecial needsMedical educationPedagogyMedicineSpecial educationDevelopmental psychologyPsychiatryPolitical science

Abstract

fetched live from OpenAlex

Abstract This exploratory study examined paediatric practitioners' challenges and considerations when they support caregivers and children with autism regarding children's screen use. Current research often focuses on the problematic use of screen time among children with autism. No clear strategies or recommendations for clinicians to support the beneficial use of screens exist yet in the field. Participants in the study were 15 experienced paediatric practitioners invited to participate in semistructured interviews that were analysed using summative content analysis. Practitioners expressed the urgent need for accessible and valuable educational resources to guide digital citizenship and screen time use for their clients with autism. This exploratory study provides an initial roadmap for the educational needs of paediatric practitioners supporting positive screen use and digital citizenship of autistic children.

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 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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.360
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.061
GPT teacher head0.375
Teacher spread0.314 · 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