MétaCan
Menu
Back to cohort
Record W1781683478 · doi:10.47678/cjhe.v32i2.183412

The Use of Market Mechanisms in Higher Education Finance and State Control: Ontario Considered

2002· article· en· W1781683478 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Higher Education · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Governance and Development
Canadian institutionsInstitute for Christian StudiesUniversity of Toronto
Fundersnot available
KeywordsMarketizationCompromiseControl (management)Government (linguistics)State (computer science)Higher educationEconomicsAutonomyPublic administrationPublic economicsSociologyEconomic growthPolitical scienceSocial scienceManagementLaw

Abstract

fetched live from OpenAlex

Marketization has been so liberally applied to understanding higher education finance policy change that it has become a less potent conceptual tool. Through its evolution as a conceptual tool, the relationship between state control and market control has become an either/or proposition. In Ontario, state control over higher education has been strengthened with the use of market mechanisms, particularly as they have been utilized in resource allocation. This article outlines seven major higher education policy changes that make use of market mechanisms while enhancing state control. It is argued that marketization is a compromise between privatization, academic autonomy, and blatant state control in the face of the backlash against government intrusion in western socio- economic life.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.393
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.038
GPT teacher head0.263
Teacher spread0.225 · 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