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Record W2923975077 · doi:10.23965/ajec.43.3.06

Helping Communities Improve Child Development Outcomes: The Importance of Governance in the Kids in Communities Study (KiCS)

2018· article· en· W2923975077 on OpenAlexafffund
Rachel Robinson, Geoffrey Woolcock, Tammy Findlay

Bibliographic record

VenueAustralasian Journal of Early Childhood · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsMount Saint Vincent University
FundersAustralian GovernmentMount Saint Vincent University
KeywordsDisadvantageCorporate governanceLeverage (statistics)Neighbourhood (mathematics)Early childhoodProject commissioningCommunity developmentSociologyEconomic growthPolitical sciencePublishingBusinessPsychologyEconomicsDevelopmental psychology

Abstract

fetched live from OpenAlex

THIS CASE STUDY CONSIDERS the multi-level governance environment of child development policy in two suburbs in Victoria, Australia. The mixed methodology draws on material from the governance domain of the Kids in Communities Study (KiCS). KiCS investigates the relationship between neighbourhood factors and Early Childhood Development (ECD) in communities of advantage and disadvantage across Australia. KiCS has enabled researchers to consider the ECD governance environment in multiple sites, reflect on the potential to develop community-level indicators for child outcomes, and leverage policy opportunities to improve child development.

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)0.000
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 score0.117
Threshold uncertainty score0.897

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.053
GPT teacher head0.342
Teacher spread0.289 · 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

Citations2
Published2018
Admission routes2
Has abstractyes

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