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Record W4249198451 · doi:10.3138/cpp.38.4.591

Does Full Day Kindergarten Help Kids?

2012· article· en· W4249198451 on OpenAlexaffvenue
William Warburton, Rebecca Warburton, Clyde Hertzman

Bibliographic record

VenueCanadian Public Policy · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsUniversity of British ColumbiaLearning PartnershipUniversity of Victoria
Fundersnot available
KeywordsInstrumental variablePopulationEducational attainmentMathematics educationPsychologyGeographyDemographyEconomic growthSociologyEconomicsEconometrics

Abstract

fetched live from OpenAlex

Full day kindergarten (FDK) is expanding across North America, but program impacts remain poorly understood. Using administrative data, this paper reports impacts from a targeted program in British Columbia for Aboriginal and English as a Second Language (ESL) students. Staged implementation of FDK created natural controls, allowing unbiased two-stage least squares (instrumental variables) estimates of program impacts. We find that the targeted FDK program increased grade 4 educational attainment, producing statistically and socially significant impacts. Further research, longer follow-up, and rigorous methods are needed to guide FDK policy for the general student population.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.883
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.022
GPT teacher head0.292
Teacher spread0.270 · 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

Citations10
Published2012
Admission routes2
Has abstractyes

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