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Record W2160605927 · doi:10.1177/10883576030180040301

Social Story Interventions for Young Children With Autism Spectrum Disorders

2003· article· en· W2160605927 on OpenAlexaff
Hoa Kuoch, Pat Mirenda

Bibliographic record

VenueFocus on Autism and Other Developmental Disabilities · 2003
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPsychological interventionAutismPsychologyIntervention (counseling)Developmental psychologyClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

This study examined the effectiveness of social story interventions for 3 young children diagnosed With autism spectrum disorders. For 2 participants, an ABA design Was used, With a social story presented in the B phase. For the 3rd participant, an ACABA design Was used, With the C phase serving as a book + reminder condition that Was used to examine the impact of adult attention and the B phase consisting of a social story. Results confirmed previous research With regard to the effectiveness of this intervention for reducing the frequency of target behaviors. For the 3rd participant, the B phase Was more effective than the C phase (book + reminder). In addition, target behaviors for all 3 participants remained at a loW level, even after the social story interventions Were discontinued. This suggests that irreversible learning of appropriate behaviors may have occurred during the course of the interventions.

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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.034
GPT teacher head0.293
Teacher spread0.259 · 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

Citations190
Published2003
Admission routes1
Has abstractyes

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