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Record W573571961

Readiness for school - Educators' perceptions and the Australian early development index

2008· article· en· W573571961 on OpenAlexaboutno aff
Reesa Sorin

Bibliographic record

VenueResearchOnline at James Cook University (James Cook University) · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsnot available
Fundersnot available
KeywordsEarly childhoodCompetence (human resources)Child developmentPsychologyMaturity (psychological)Government (linguistics)Context (archaeology)Index (typography)PerceptionSocial competenceDevelopmental psychologyPedagogyMedical educationSocial changePolitical scienceSocial psychologyGeographyMedicine
DOInot available

Abstract

fetched live from OpenAlex

The Canadian-based Early Development Index (EDI) defines school readiness within five developmental domains: physical health and wellbeing: social competence; emotional maturity; language and cognitive skills and communication skills and general knowledge. Based on other early development indices and trials within Canada, the EDI uses over one hundred indicators to determine 'whether a child is "performing well", average or "developmentally vulnerable." From its introduction to Australia in 2003 and subsequent modifications for an Australian audience, the Australian Early Development Index (AEDI) has been used in over 50 communities throughout Australia to collect data on school readiness for school, community and government use. However, the definition of school readiness is still a debate in schools, early childhood centres and homes nationwide. It is a question I asked of early childhood educators in a region where the AEDI results were recently announced. Their responses went beyond the child skills articulated in the AEDI to include the child's social context and relationships as components of school readiness.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.663
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.003
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.030
GPT teacher head0.283
Teacher spread0.254 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations1
Published2008
Admission routes1
Has abstractyes

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