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Record W3214710037 · doi:10.1017/s1355770x21000346

Investigating the role of spatial spillovers as determinants of land conversion in urbanizing Canada

2021· article· en· W3214710037 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEnvironment and Development Economics · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsEndowmentSpillover effectEconomic geographyLand useNatural resourceMetropolitan areaGeographySpatial econometricsPopulationNatural resource economicsEconomicsEcologyEconometrics

Abstract

fetched live from OpenAlex

Abstract Although the impacts of income, population growth, and other important determinants of land-use change have been widely studied, there is less understanding of how spatial spillovers matter. Utilizing a spatial econometric approach, we investigate the main determinants of natural landscape conversion, focusing on quantifying local and global spatial spillovers. The empirical investigation applies to the Edmonton Metropolitan Region and the Calgary Regional Partnership in Canada. Key results include: (1) determinants of land conversion have significant spillover effects; (2) income, population density, road density, natural land endowment and land suitability for agriculture are all found to have influences on natural land conversion both in the own and neighboring areas; and (3) local (i.e., within the immediate neighboring areas) and global (in the entire study region) spillovers are different in strength and direction. Our work provides useful information for understanding the spillover issues in land conservation, resource governance, and optimal conservation design.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.992

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)0.0000.000

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 head0.027
GPT teacher head0.160
Teacher spread0.133 · 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