Community Revitalization Levy as a Municipal Financing Mechanism in Alberta
Bibliographic record
Abstract
What do Edmonton’s glittering new Arena District and Calgary’s complete overhaul of its Rivers District have in common? Both cities pulled their projects off using a novel method of financing: the community revitalization levy (CRL). Because CRLs can cause economic harm when they are used incorrectly, there are general principles that cities should follow when using them. Unfortunately, these principles are not fully in place in Alberta. The result could be that, for all their charm, Calgary’s Rivers District and Edmonton’s Capital City Downtown Plan may not have lived up to be quite the deal citizens might have expected. A CRL should only be used if it is in fact the best financial tool available for the project. It must past certain tests. In the case of Calgary’s River District, it appears that those tests were not properly met, and so it is unclear whether the CRL really was the best financial tool available for the city to use in its effort to improve the area. While the property tax base in the Rivers District has grown more quickly than in the rest of the city, it is impossible to know how much more quickly it would have grown without the use of the CRL as a tool. There also seems to be a lack of clarity of whether new projects funded by the CRL will be in the public’s best interest or if the money would be better used if returned to the tax base. Edmonton, meanwhile, did not pre-define the scope and the cost of all the projects it expects for its Capital City Downtown Plan. While that provides flexibility to develop new project ideas as more revenue materializes, it also allows for scope creep, and the risk that revenues will continue to be spent, even beyond their need, rather than being returned to the tax base. It is also unclear whether the Edmonton plan has actually succeeded in inducing economic growth. It may be that it has only shifted where people spend their money away from other parts of the city and into the downtown district, potentially harming some residents and businesses. 1 CRLs are powerful tools, but they come with risks. They can lead to poor outcomes for taxpayers or businesses and residents in other areas, and they can divert tax revenues away from necessary infrastructure into subsidizing private infrastructure, as may be the case with the Edmonton arena. It is unclear whether the CRL plans in Calgary and Edmonton have turned out to be the best approach for revitalizing parts of the two cities’ downtowns. The province, and the two cities, should look at implementing new measures to better protect taxpayers, and ensure CRLs are being used correctly.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".