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Record W3159419377 · doi:10.55016/ojs/sppp.v11i1.43330

Has the City-Rural Tax Base and Land-Use Balance Changed in Alberta? Explorations into the Distribution of Equalized Property Assessments Among Municipality Classes

2018· article· en· W3159419377 on OpenAlexaffabout
Melville McMillan

Bibliographic record

VenueThe School of Public Policy Publications · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicLocal Government Finance and Decentralization
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsProperty taxProperty (philosophy)Distribution (mathematics)GeographyBalance (ability)Base (topology)Agricultural economicsSocioeconomicsBusinessEconomicsPublic economicsMathematicsTax reformPsychology

Abstract

fetched live from OpenAlex

Alberta ended its regional planning commissions in 1996. They were replaced by voluntary inter-municipal negotiation, but this has raised concerns about adverse effects on land use. Pressure to terminate the commissions came largely from the rural municipalities. Some of them felt the commissions retarded their economic development. They believed that in a less restrictive planning environment, they would be able to attract a greater share of development, especially business. This study assesses the consequences of that change. Alberta’s rapid growth over much of the post-1995 period affords an exceptional opportunity to search for noticeable changes in the urban-rural tax base and land-use patterns and balance. Municipal tax base is measured, and land use reflected, by property values. Those values are taken to be the provincially determined equalized assessments used for property tax purposes. Fortunately, these provide a reliable and consistent measure of property values across municipalities and over time for properties of different kinds. For the types of properties of prime interest for this analysis, residential and unregulated business property, equalized assessments approximate 100 per cent of market value. Residential property represents over 60 per cent of total provincial equalized assessments and business property about 20 per cent. In cities, the percentages are 70 per cent and 24 per cent; residential and business properties represent almost all the taxable property. The focus of the analysis is whether, during the past two decades, the shares of residential and/or business property have shifted from cities to rural municipalities. The possibility of shifting city-rural tax base/land-use patterns is explored from four perspectives. This report examines trends in the distribution of residential and business equalized assessments among the types of municipalities in the province. To obtain a better perspective in specific cases, the city-rural split of assessments is reported for the Edmonton and Calgary metropolitan areas and nine cities between 1997 and 2014. Examining the movements in the ratios of business to residential assessments of 31 city and rural municipalities provides further insight. The final approach is to simply review changes in the location of population and dwellings between cities and rural areas. There has been no notable or general shift of land development away from cities and to rural areas. Despite the rapid growth and the devolved planning environment, the cityversus-rural distribution of tax base and land use has, overall, been remarkably constant although development was definitely not uniform across Alberta cities. If anything, the cities’ shares of residential development may have increased while their shares of business development have been more uneven. For both types of property, however, the development patterns have varied across both city and rural municipalities. Concern that the changed planning environment might have shifted property development towards the rural municipalities does not appear to have been justified. Whether this development met other planning criteria is not explored here. This analysis encourages more detailed investigations using alternative indicators.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.470
Threshold uncertainty score0.863

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.002
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.113
GPT teacher head0.370
Teacher spread0.257 · 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

Citations0
Published2018
Admission routes2
Has abstractyes

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