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Record W2138926224 · doi:10.1093/ajae/aap022

The Effect of Strict Agricultural Zoning on Agricultural Land Values: The Case of Ontario's Greenbelt

2010· article· en· W2138926224 on OpenAlexaffabout
Brady J. Deaton, Richard J. Vyn

Bibliographic record

VenueAmerican Journal of Agricultural Economics · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsZoningLegislationMetropolitan areaAgricultureAgricultural economicsBoundary (topology)GeographyLand useLand ValuesAgricultural landEnvironmental protectionEconomicsArchaeologyLawPolitical scienceEcology

Abstract

fetched live from OpenAlex

In 2004, the provincial government of Ontario passed legislation that imposed a moratorium on urban development of agricultural land within a “Greenbelt” boundary. This legislation, which became known as the Greenbelt legislation, has a direct effect on over 1.8 million acres of land located near one of the larger metropolitan areas in North America: the Greater Toronto Area. We use a hedonic model to examine 7760 farmland sales and we find evidence that the Greenbelt legislation influenced farmland property prices; the effect depends on the proximity of the farmland to the Greater Toronto Area.

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)0.007
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 score0.033
Threshold uncertainty score0.240

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0040.003
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.006
GPT teacher head0.185
Teacher spread0.179 · 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

Citations44
Published2010
Admission routes2
Has abstractyes

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