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Record W2891634088 · doi:10.26686/pq.v5i1.4287

The 20 hours (free) programme: important choices ahead for New Zealand’s new government

2009· article· en· W2891634088 on OpenAlexaboutno aff
Brenda K. Bushouse

Bibliographic record

VenuePolicy Quarterly · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)Christian ministryPolitical scienceQuarter (Canadian coin)FellEarly childhood educationIndex (typography)Economic growthEconomicsPublic administrationGeography

Abstract

fetched live from OpenAlex

The 20 Hours Free programme was implemented in July 2007 after having been one of three new education policies announced in the Labour Party’s 2005 election manifesto. The new programme was the brainchild of Education Minister Trevor Mallard and provided 20 hours of government-funded early childhood education (ECE) for all three and four year olds, regardless of family income. When the Free ECE programme began, participation was large enough to affect the Consumer Price Index: ‘Education prices fell 5.2 percent [for the September quarter], due to lower prices for early childhood education as a result of changes to government funding’ (Statistics New Zealand, 2007). The most recent data indicate that 86%of eligible services participate and 93% of eligible children participate (Ministry of Education, 2008). With its tremendous success, the 20 Hours Free ECE programme has become the biggest, most expensive early education programme in the country.

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)0.013
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.427
Threshold uncertainty score0.849

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0060.005
Scholarly communication0.0090.011
Open science0.0020.005
Research integrity0.0110.010
Insufficient payload (model declined to judge)0.0380.004

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 head0.020
GPT teacher head0.324
Teacher spread0.304 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations5
Published2009
Admission routes1
Has abstractyes

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