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Record W4391394230 · doi:10.1177/00207152241227810

The impact of marketization on school segregation and educational equity and effectiveness: Evidence from Australia and Canada

2024· article· en· W4391394230 on OpenAlex
Laura B. Perry, Ee‐Seul Yoon, Michael G. Sciffer, Christopher Lubienski

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

VenueInternational Journal of Comparative Sociology · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSchool Choice and Performance
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMarketizationEquity (law)Political scienceSociologyEconomic growthPublic economicsEconomicsChina

Abstract

fetched live from OpenAlex

While marketization has been promoted as a mechanism for improving educational equity and effectiveness, substantial evidence suggests that it may have the opposite effect. We contribute to this debate by examining educational equity and effectiveness in two similar countries that have embraced educational marketization to different degrees. Drawing on data from the Program for International Student Assessment and a causal-comparative design, we show that Australian schooling has more choice and competition, is more socially segregated, has larger school stratification of human and material resources, and has greater inequalities of educational outcomes and overall lower effectiveness than Canadian schooling. Our findings suggest that educational marketization reduces educational equity and effectiveness by increasing school social segregation and stratification of resources.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.940

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.082
GPT teacher head0.477
Teacher spread0.394 · 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