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Record W2153822755 · doi:10.32920/24150423

Mapping the Early Intervention System in Ontario, Canada

2023· article· en· W2153822755 on OpenAlexaboutno aff
Kathryn Underwood

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsnot available
Fundersnot available
KeywordsIntervention (counseling)Scope (computer science)Special educationLegislationEarly childhoodService (business)Formative assessmentPsychologyGeographyPolitical scienceBusinessPedagogyDevelopmental psychologyComputer science

Abstract

fetched live from OpenAlex

This study documents the wide range of early intervention services across the province of Ontario. The services are mapped across the province showing geographic information as well as the scope of services (clinical, family-based, resource support, etc.), the range of early intervention professionals, sources of funding and the populations served by the services. Results of the study provide a picture of the range and scope of early intervention service in the province and identify variability of services across the province. The study highlights systemic variables that are of interest across Canada in early intervention practices, at a time when significant focus is on the importance of the early years, particularly for children with disabilities. The study aims to identify the scope of early intervention services across the province of Ontario. In the international literature on early intervention, there are frequent references to early intervention systems (for example in the Part C programs in the US, described by Bruder & Dunst, 2008). In Ontario, and other Canadian provinces, it is difficult to define one system of early intervention services. This is because early intervention has no federal guidelines or funding, and at the provincial level, there are is no defining legislation that ensures early intervention services or defines a system of services. Early intervention is a growing area of interest in research on special education and disability in educational settings (Guralnick, 2011). Interest in the early years stems from the understanding that the years preceding elementary school-age are formative and learning in these years can set an educational trajectory for life (Willms, 2002). This is a deterministic view of child development, and ongoing research in early intervention is warranted. However, in some jurisdictions there is not a clear "system" of early intervention services, which makes it challenging to investigate the efficacy of these approaches. This study aims to identify both consistent and variable characteristics of a system of early intervention services in Ontario, Canada, which provide a starting point for analysis of systemic issues in early intervention practice. This mapping of services is designed to identify the scope of organizational characteristics that make up the early intervention system in Ontario. (Contains 1 table and 3 figures.)

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)0.006
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 score0.807
Threshold uncertainty score0.936

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.019
Science and technology studies0.0100.002
Scholarly communication0.0040.001
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.083
GPT teacher head0.322
Teacher spread0.239 · 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

Citations25
Published2023
Admission routes1
Has abstractyes

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