Investigating the role of spatial spillovers as determinants of land conversion in urbanizing Canada
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".