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Record W2035018259 · doi:10.1177/003804070708000104

The Impact of Sector on School Organizations: Institutional and Market Logics

2007· article· en· W2035018259 on OpenAlexaffabout
Scott Davies, Linda Quirke

Bibliographic record

VenueSociology of Education · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicSchool Choice and Performance
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsIsomorphism (crystallography)ElitePrivate sectorPublic sectorEconomicsSociologyPublic relationsPolitical scienceEconomic growthEconomy

Abstract

fetched live from OpenAlex

Drawing on new institutional and market theories, this article derives three hypotheses for the effects of markets on educational organizations: They (1) weaken formal structures, (2) reverse tendencies toward isomorphism, and (3) force schools to recouple and compete via performance indicators. These ideas are investigated with data on private and public schools in Toronto, which, the authors argue, is a strategic research site. The findings vary by market sector. Newer, nonelite private schools seek niches, avoid performance indicators, and dilute formal structures, while older elite schools do the opposite. Thus, market effects on school organizations vary by sector. In conclusion, the authors argue that the impact of markets on schools is mitigated by local institutional conditions. Specifically, the presumed impact of markets on educational quality may be contingent upon certain institutional conditions that, when absent, channel market forces in more consumerist directions.

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)0.002
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.006
Scholarly communication0.0030.003
Open science0.0000.002
Research integrity0.0000.000
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 head0.023
GPT teacher head0.374
Teacher spread0.351 · 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

Citations72
Published2007
Admission routes2
Has abstractyes

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