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Record W2293335243 · doi:10.55016/ojs/sppp.v9i1.42566

Is ‘Charter-City Status’ a Solution for Financing City Services in Canada — or Is That a Myth?

2016· article· en· W2293335243 on OpenAlexaffabout
Harry Kitchen

Bibliographic record

VenueThe School of Public Policy Publications · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicTransport and Economic Policies
Canadian institutionsTrent University
Fundersnot available
KeywordsMythologyCharterFinanceBusinessPublic administrationPolitical scienceHistoryLaw

Abstract

fetched live from OpenAlex

In 2007, the province of Ontario effectively granted Toronto “charter-city status,” handing the municipal government a new arsenal of tools it could use to raise additional revenue. Charter-city status has often been held up as a reasonable way to help satisfy municipal-financing demands without cities relying on property taxes and provincial transfers — something municipal politicians have been known to say they very much need. Since Toronto got its charter, however, the city has barely touched these tools. Free to impose municipal levies on bars, cars, land sales, parking lots, billboards and road tolls, the city has so far only implemented a tax on billboards and land transfers. It tried taxing vehicle registrations, but that tax was soon cancelled. Toronto is not unique in that it has been given special legislation to levy municipal taxes beyond traditional property taxes: There are nearly a dozen cities across Canada that now benefit from similar legislation. They have proven even less inclined to use additional revenue tools. Calgary and Edmonton signed a memorandum of understanding with the Alberta government to gain charter-city status; the process has gone no further than that. Most often, the reason Canada’s so-called charter cities do not seize the apparent opportunity provided by this special legislation is that it typically does not provide them that many additional tools. Toronto is, in fact, exceptional in the range of taxes it can use. One possible reason that Canadian charters have been kept within rather confining bounds is that provinces tend to be reluctant to share their tax bases more than they already do through property tax sharing. But if Toronto is any guide, even having a wider scope of taxing powers does not mean a city will take advantage of them. It may be that local politicians relish the idea of new taxes in theory, but recoil at the political reaction the new taxes are sure to provoke. After all, former Toronto mayor Rob Ford’s 2010 election was partly based on voters’ annoyance over the city’s personal-vehicle-registration and land-transfer taxes, and his vow to change them. That the city then eliminated the vehicle tax, but not the land-transfer tax, may have to do with the latter being borne considerably by future residents of the city, who are not yet voters. Given cities’ growing funding responsibilities, it behooves them to find revenue-raising tools they are willing to use. Notwithstanding Toronto’s experience, vehicles are inefficiently priced, occupying roads and parking with little incentive for drivers to ration their usage. Fuel taxes and taxes on vehicle registration can be easily tacked onto provincial taxes and transferred back to cities, and so can be efficient, fair, accountable and transparent. The technology for toll roads, meanwhile, is readily available, even if the political will is not, and an advantage of tolls is that they collect revenue from commuters who use the city’s services, but live outside its boundaries. Similarly a municipal income tax, ideally charged on local businesses’ payrolls, would raise revenue from everyone working in the city, even if they lived elsewhere. Of course, as Toronto’s experience demonstrates, new taxes can be difficult to sell politically. The best remedy for this is to earmark taxes for specific spending priorities. This has the added benefit of facilitating long-term planning and preventing the abuse of funds. And raising funds locally, rather than relying on transfers, increases municipal accountability and efficiency, encouraging better fiscal discipline. The charter-city experiment has so far been discouraging, but it would certainly stand a better chance were provinces willing to grant more access to their tax base, and were municipal politicians more willing to defend their need to use it.

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 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)0.001
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 score0.252
Threshold uncertainty score0.880

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.003
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.059
GPT teacher head0.258
Teacher spread0.199 · 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 teacher head, 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

Citations1
Published2016
Admission routes2
Has abstractyes

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