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Record W4400745771 · doi:10.1080/15575330.2024.2379846

The fate of closed schools: Documenting the relationships between school property reuses and their beneficiaries in Ontario, Canada

2024· article· en· W4400745771 on OpenAlexafffundabout
Rachel Barber, Patricia Collins, Jeffrey R. Masuda

Bibliographic record

VenueCommunity Development · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicUrbanization and City Planning
Canadian institutionsUniversity of VictoriaQueen's University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsProperty (philosophy)Economic growthPublic administrationBusinessSociologyEnvironmental planningPolitical scienceGeographyEconomics

Abstract

fetched live from OpenAlex

Public schools play a pivotal role in successful community development. Yet, with school closures on the rise across North America, there is limited knowledge on the outcomes of closed school properties. This study documents the afterlife of closed school properties in Ontario, Canada, identifying their potential beneficiaries, and assessing the prevalence of property vacancies. Using a dataset of over 400 schools closed between 2011 and 2021, we determined that the prevalence of certain school property reuses varied by degree of urbanicity. Fewer than one-fifth of reused properties were designed to benefit highly deprived populations, despite over half of the school closures occurring in neighborhoods with higher levels of deprivation. Furthermore, one-third of school properties remained vacant at the time of study, 36% of which closed over a decade ago. The findings reflect the need for additional consideration of the future uses of school properties prior to their closures.

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)0.005
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.253

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.007
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.001
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 head0.074
GPT teacher head0.269
Teacher spread0.195 · 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

Citations0
Published2024
Admission routes3
Has abstractyes

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