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Record W1992642957 · doi:10.1080/08990220802388263

A Back Door Approach to Autism and AAC

2008· review· en· W1992642957 on OpenAlexaff
Pat Mirenda

Bibliographic record

VenueAugmentative and Alternative Communication · 2008
Typereview
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsUniversity of British ColumbiaUniversity of British Columbia Hospital
Fundersnot available
KeywordsAugmentative and alternative communicationAutismPsychologyIntervention (counseling)Psychological interventionLiteracyIntellectual disabilityCognitive psychologyGross motor skillAutism spectrum disorderDevelopmental psychologyMotor skillPedagogyPsychiatry

Abstract

fetched live from OpenAlex

The conventional view is that most individuals with autism or pervasive developmental disorder-not otherwise specified (PDD-NOS) have no significant motor impairments but do have severe intellectual disabilities. These assumptions impact the nature and types of augmentative and alternative communication (AAC) interventions that are typically provided, which tend to be narrowly focused on basic, functional communication skills such as requesting. However, recent research has provided evidence that challenges these assumptions and suggests the potential of intervention approaches targeting motor, language, and literacy development. The author encourages practitioners and researchers to examine current assumptions about autism and to invent and investigate new ways to support people with autism to communicate.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.003
Science and technology studies0.0010.004
Scholarly communication0.0030.006
Open science0.0010.003
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0070.005

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 head0.178
GPT teacher head0.420
Teacher spread0.242 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations74
Published2008
Admission routes1
Has abstractyes

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