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Enregistrement W2253827978 · doi:10.55016/ojs/sppp.v7i1.42466

The Free Ride is Over: Why Cities, and Citizens, Must Start Paying For Much-Needed Infrastructure

2014· article· en· W2253827978 sur OpenAlexaffabout
Philip Bazel, Jack Mintz

Notice bibliographique

RevueThe School of Public Policy Publications · 2014
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueTransportation Planning and Optimization
Établissements canadiensUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésBusinessFinanceTransport engineeringEngineering

Résumé

récupéré en direct d'OpenAlex

Canada’s roads, bridges, wastewater treatment centres and sewer systems are already past their prime. On average, and across the country, these key elements of municipal infrastructure are now past the halfway point of their useful lifespans. In the next 10 to 15 years, Canadian cities will face some very expensive bills for replacing critical infrastructure. But there are better means of funding needed infrastructure than raising local taxes or pleading with the provincial and federal governments for more transfers. A better solution, for many reasons, is user fees. Municipal governments have already managed to extract a great deal of infrastructure funding out of higher levels of governments. In the last 50 years, the portion of municipal revenues provided by federal and provincial transfers has increased from under 30 per cent to roughly 45 per cent, while the portion of revenues representing local property taxes has fallen from over 50 per cent to roughly 35 per cent. Yet, federal-provincial government funding is a seriously flawed means of funding local infrastructure. Money gathered at the federal and provincial level is placed in municipal coffers, breaking the chain of political accountability for the outcomes. This alters the spending priorities of municipal governments as they are inclined to favour those projects with federal or provincial subsidies attached. Such subsidies lower the political costs for local governments allowing municipalities to maintain artificially low taxes for their constituents by spending federal or provincial tax revenue. This is essentially having their cake and eating it too, and on a policy level, we are left to wonder how decision making surrounding municipal priorities is affected. These projects come at a discount to local governments, but not their constituents who will ultimately pay through federal or provincial income taxes. Most importantly, this kind of funding results in unpriced infrastructure access and contributes to the over-usage of infrastructure. It is only rational for residents to live further from work by taking full advantage of underpriced highways, bridges, transit and other infrastructure that someone else pays for, exacerbating congestion and commuting times in Canada’s major cities. If Canadian cities are serious about replacing aging infrastructure and, just as importantly, alleviating the evergrowing problem of traffic congestion and urban sprawl, then cities must begin making proper use of user fees, and charging citizens for the use of the infrastructure they value. As it stands, while urban centres around the world increasingly embrace user fees, Canadians remain stuck in their old ways. Aside from international crossings, in 2012, Canada had only eight tolled bridges, and less than 0.25 per cent of Canada’s paved public roads were tolled. In Alberta, across the five largest cities, user fees (combined with sales) only make up an average of less than 25 per cent of municipal program operational revenues. User fees would bring a predictable and dedicated revenue stream that would allow municipalities to responsibly take on the debt required to invest in much-needed infrastructure projects. Canadian city governments already have the tools they need to keep up with their pressing infrastructure needs; they need only find the creativity and political will to make use of them.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,006
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,842
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,006
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0020,001
Communication savante0,0010,001
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,026
Tête enseignante GPT0,299
Écart entre enseignants0,273 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations5
Publié2014
Routes d'admission2
Résumé présentoui

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