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Record W3150483991

Investigating the Spatial Effects of Agricultural Land Abandonment and Expansion

2016· preprint· en· W3150483991 on OpenAlexaboutno aff
Haoluan Wang, Feng Qiu

Bibliographic record

VenueRePEc: Research Papers in Economics · 2016
Typepreprint
Languageen
FieldEnvironmental Science
TopicLand Use and Ecosystem Services
Canadian institutionsnot available
Fundersnot available
KeywordsAbandonment (legal)AgricultureAgricultural landLand useLand use, land-use change and forestryLand information systemGeographyLand developmentNatural (archaeology)Land managementEcologyPolitical science
DOInot available

Abstract

fetched live from OpenAlex

This study investigates the agricultural land abandonment and agricultural land expansion in the case of the Edmonton-Calgary Corridor, Canada. Using remote sensing data from 2000 to 2012, we include environmental and socio-economic factors to explore the drivers of land use conversions between agriculture and natural land. This research also adopts spatial techniques to allow for spatial effects from neighboring areas’ land-use activities. Key results from this study include: (1) higher land suitability for agriculture is negatively associated with agricultural land abandonment; (2) road density contributes to land use conversions between agriculture and natural land; and (3) land-use activities and decisions have strong spatial effects on neighboring regions, and the incorporation of spatial interactions can result in less biased results. In addition, an investigation of bidirectional land transitions helps in better understanding the associated gains and losses of agriculture and natural land.

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 score0.667
Threshold uncertainty score0.669

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.012
GPT teacher head0.242
Teacher spread0.230 · 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
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueRePEc: Research Papers in Economics→Same topicLand Use and Ecosystem Services→French-language works237,207→