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Record W3205107323 · doi:10.1177/10534512211051068

Sexuality Education for Children and Youth With Autism Spectrum Disorder in Canada

2021· article· en· W3205107323 on OpenAlexaffabout
Adam Davies, Alice-Simone Balter, Tricia van Rhijn, Jennifer Spracklin, Kimberly Maich, Rsha Soud

Bibliographic record

VenueIntervention in School and Clinic · 2021
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsMemorial University of NewfoundlandSt. John’s Health Sciences CentreUniversity of Guelph
Fundersnot available
KeywordsHuman sexualityAutism spectrum disorderPsychologySexuality educationCurriculumAutismContext (archaeology)NeurotypicalDevelopmental psychologyDiversity (politics)Special educationPedagogySex educationGender studiesSociology

Abstract

fetched live from OpenAlex

With no standardized approach to sexuality education among Canada’s 13 provinces and territories and the various curricula focusing on neurotypical and non-disabled children, educators have insufficient instruction and lack appropriate training on how to address sexuality education for children and youth with disabilities, particularly children and youth with autism spectrum disorder (ASD). This article provides the current context of sexuality education for children and youth with ASD in Canadian schools and guidance for more inclusive approaches with attention to three important areas: puberty, relationships, and gender and sexual diversity. Recommendations are offered to support more inclusive approaches to sexuality education, acknowledging that a one-size-fits-all approach is insufficient for children and youth with ASD. The recommendations focus on three goals: (a) moving beyond simple knowledge-based approaches to include skill-building; (b) including parents, autistic voices, and advocates in planning and ongoing conversations; and (c) providing supports for educators.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.556

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0090.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.027
GPT teacher head0.337
Teacher spread0.310 · 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

Citations30
Published2021
Admission routes2
Has abstractyes

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Same venueIntervention in School and ClinicSame topicAutism Spectrum Disorder ResearchFrench-language works237,207