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Record W2471424818

Reforms to Funding Education in Four Canadian Provinces.

2014· article· en· W2471424818 on OpenAlexvenueaboutno aff
Joseph Garcea, Dustin Munroe

Bibliographic record

VenueCanadian Journal of Educational Administration and Policy · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsChristian ministryProperty taxPrincipal (computer security)Political sciencePublic administrationEconomic growthEconomicsLawTax reform
DOInot available

Abstract

fetched live from OpenAlex

This article provides an analysis of the features, determinants, and effects of a series of reforms to funding the primary and secondary education systems in Alberta, Ontario, Saskatchewan, and Manitoba during the past two decades. The principal focus is on the reforms that have shifted the authority for setting property tax mill rates for education and responsibility for funding the education system between school boards and provincial governments. The article reveals that, whereas Alberta, Ontario, and Saskatchewan have followed the lead of six other provinces in centralizing such authority and responsibility in the provincial ministry of education, Manitoba has moved slightly in the opposite direction by reducing its role in setting property taxes for some classes of property and reducing its level of responsibility for funding the education system. The article concludes with some questions regarding potential future trends in relation to alignment of authority for funding education between provincial governments and school boards.

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)0.003
metaresearch head score (Gemma)0.011
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.750
Threshold uncertainty score0.870

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.008
Science and technology studies0.0090.003
Scholarly communication0.0040.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.022
GPT teacher head0.339
Teacher spread0.317 · 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
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

Citations12
Published2014
Admission routes2
Has abstractyes

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