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Record W2591973101 · doi:10.3280/ess2-2016oa3934

Organizations' choices when implementing an Early Intensive Behavioral Intervention program (EIBI)

2016· article· en· W2591973101 on OpenAlexaffabout
Carmen Dionne, Jacques Joly, Annie Paquet, M. Rousseau, Mélina Rivard

Bibliographic record

VenueEDUCATION SCIENCES AND SOCIETY · 2016
Typearticle
Languageen
FieldPsychology
TopicBehavioral and Psychological Studies
Canadian institutionsUniversité du Québec à MontréalUniversité de SherbrookeCentre intégré universitaire de santé et de services sociaux de la Mauricie-et-du-Centre-du-QuébecUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsDiversity (politics)Intervention (counseling)Context (archaeology)AutismPopulationAutism spectrum disorderQuality (philosophy)Plan (archaeology)PsychologyRehabilitationApplied psychologyMedicineDevelopmental psychologyEnvironmental healthPsychiatryGeographySociology

Abstract

fetched live from OpenAlex

The organizations' characteristics and choices are essential components of an action plan that favors quality program implementation, a prelude to effectiveness, especially in natural environment. The objectives of this study are to describe the choices made by rehabilitation centers (CRDITED) in the context of a universal community based on Early Intensive Behavioral Intervention program (EIBI) for 2 to 5 year-old children with autism spectrum disorder (ASD) in Québec (Canada). Based on a theoretical evaluation model, a questionnaire was filled out by 15 CRDITEDs, covering the large majority of the Quebec territory but also the Quebec population. Results show a great diversity between the different CRDITEDs. Factors that impact implementation quality are identified. Absence of evidence-based implementation practices and the diversity of the approaches to EIBI are discussed.

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)0.005
metaresearch head score (Gemma)0.014
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 score0.092
Threshold uncertainty score0.182

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.203
GPT teacher head0.466
Teacher spread0.263 · 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

Citations7
Published2016
Admission routes2
Has abstractyes

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Same venueEDUCATION SCIENCES AND SOCIETYSame topicBehavioral and Psychological StudiesFrench-language works237,207