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Record W2733727893

Ontario Education Governance 1995 to the Present: More Accountability, More Regulation, and More Centralization?

2015· article· en· W2733727893 on OpenAlexaboutno aff
Xiaobin Li

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate governanceAccountabilityGovernment (linguistics)Context (archaeology)Public administrationPolitical scienceSection (typography)Higher educationSociologyLawEconomicsManagementBusinessGeography
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this study was to examine the general trend of education governance in the Canadian province of Ontario since 1995 when the Progressive Conservatives led by Michael Harris formed a new majority government. The article is divided into three sections. The first section provides the context and a historical background of Ontario education from its beginning to 1995 when the Conservatives started significantly transforming the governance of education. The second section describes the changes the Conservative government and the following Liberal government made between 1995 and the present, paying attention to the important shifts and tensions in the relationship between school boards and the government and how these shifts and tensions affected the overall education governance. The third section presents the tension between the government and two teachers’ unions in the last round of collective bargaining when school boards did not play a significant role. The paper concludes with an attempt to draw lessons from the shifts in education governance since 1995 in terms of how it is likely to evolve in the future.

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)0.004
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.211
Threshold uncertainty score0.916

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0070.008
Scholarly communication0.0080.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.149
GPT teacher head0.472
Teacher spread0.323 · 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 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

Citations1
Published2015
Admission routes1
Has abstractyes

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