Municipal Revenue Generation and Sprawl: Implications for the Calgary and Edmonton Metropolitan Regions Derived from an Extension of “Causes of Sprawl” (Technical Paper)
Bibliographic record
Abstract
There are good reasons to expect that attributes of local public finance may impact urban land use and, specifically, sprawl. A detailed and novel investigation of U.S. metropolitan areas published in 20061 provides substantial insights into the causes of sprawl, but it overlooks the main characteristics of local public finance (taxes and user charges). Using a subset of the data matched to city public finance data, a parallel analysis gives insight into the impacts of local public finance on sprawl. There is evidence that greater reliance on local property taxes reduces sprawl. The evidence that user charges (primarily for water, sewerage and solid waste services) could have a similar effect is weak but suggestive. The combined effects of a high reliance on property taxes and user charges (compared to typical levels) might reduce sprawl by as much as one-third. For Calgary and Edmonton, this means that the current heavy reliance on property taxes in both cities reduces sprawl and that the adoption of alternative local taxes—that reduce reliance on property taxes—is expected to increase sprawl. Further analysis of the impacts of local public finance on urban sprawl is warranted.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".