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Record W2171496276 · doi:10.1080/09575140701594384

The Early Development Index and children from culturally and linguistically diverse backgrounds

2007· article· en· W2171496276 on OpenAlexafffund
Jianghong Li, Amedeo D’Angiulli, Garth Kendall

Bibliographic record

VenueEarly Years Journal of International Research and Development · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsCarleton University
FundersUniversity of British Columbia
KeywordsPopularityChecklistPsychologyIndex (typography)PopulationCulturally sensitiveCulturally appropriateChild developmentCultural diversityMedical educationApplied psychologyDevelopmental psychologyMedicineComputer scienceSocial psychologySociologyGerontologyWorld Wide Web

Abstract

fetched live from OpenAlex

The Early Development Index (EDI) is a teacher‐completed checklist, intended to be a population‐level tool to measure children's readiness for school and to alert communities to potential developmental problems in children. In response to the increasing popularity of the EDI, this paper provides a critical and timely evaluation and identifies the areas for improvement and modifications. The paper aims: (1) to identify the limitations of the EDI as a universal screening tool, particularly with regard to children from culturally and linguistically diverse backgrounds (CALD); (2) to alert readers to the potential negative implications of the current EDI for communities and society, and (3) to recommend ways for improvement so that the EDI will become a valid and culturally appropriate screening tool for monitoring early development in CALD children. The ultimate aim is to help build an education system and a society that can respect cultural and individual differences.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.186
Threshold uncertainty score0.709

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.042
GPT teacher head0.369
Teacher spread0.327 · 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 teacher head, 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

Citations26
Published2007
Admission routes2
Has abstractyes

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