MétaCan
Menu
Back to cohort
Record W1953511025 · doi:10.47678/cjhe.v45i2.184344

Anatomy of a Tuition Freeze: The Case of Ontario

2015· article· en· W1953511025 on OpenAlexaffvenueabout
Deanna Rexe

Bibliographic record

VenueCanadian Journal of Higher Education · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicPolicy Transfer and Learning
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPoliticsStakeholderPreferencePublic administrationPublic policySociologyFunction (biology)Policy analysisPublic opinionPublic relationsPolitical scienceEconomicsLaw

Abstract

fetched live from OpenAlex

Using two conceptual frameworks from political science—Kingdon’s (2003) multiple streams model and the advocacy coalition framework (Sabatier & Jenkins-Smith, 1993)—this case study examines the detailed history of a major tuition policy change in Ontario in 2004: a tuition freeze. The paper explores the social, political, and economic factors that influenced policymakers on this particular change to shed light on the broader questions of the dynamics of postsecondary policymaking. The study found that the Liberal Party’s decision to freeze postsecondary tuition fees was a function of stakeholder relations, public opinion, and brokerage politics, designed for electoral success. The policy implementation strategy was intended to facilitate the cooperation and interests of the major institutions. Within the broader policy community, student-organized interest groups and other policy advocates were aligned in a policy preference, a critical component for successful change.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.137
Threshold uncertainty score0.994

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0320.009
Scholarly communication0.0050.002
Open science0.0020.004
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0070.000

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 head0.042
GPT teacher head0.359
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 designQualitative
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
Published2015
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Higher EducationSame topicPolicy Transfer and LearningFrench-language works237,207