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Record W3123517908

From A to F: Grading the Fiscal Transparency of Canada’s Cities, 2019

2019· article· en· W3123517908 on OpenAlexaboutno aff
Farah Omran, William B. P. Robson

Bibliographic record

VenueC.D. Howe Institute Commentary · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsAccrualTransparency (behavior)Fiscal yearFinanceBusinessAccountabilityCapital expenditureAccountingRevenueLedgerEconomicsEarningsPolitical science
DOInot available

Abstract

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Financial presentations are key tools for Canadians who want to understand what their governments are doing with their money, and hold them to account. Unfortunately, Canada’s cities do not typically present information that lets Canadians do this. The problem is not so much their end-of-year financial statements as their budgets: nearly every major Canadian city presents budgets that separate current spending and capital spending on big-ticket items, and use accounting and aggregation methods that are inconsistent with their financial statements. Worse, many make the key numbers hard to find and recognize, and councillors often vote these non-transparent budgets after the fiscal year has already started and money has gone out the door. Bad budgeting practices impede councillors, taxpayers and voters seeking accountability from city staff and elected representatives. Simple information, such as how much the municipality plans to spend this year, or how its spending plan this year compares with the previous year’s plan, is hard or impossible for a non-expert to find. Moreover, the differences between how the numbers appear in budgets and in year-end financial statements have real-world consequences. Budgets that exclude key services such as water and the user fees that fund them, for example, understate their claim on community resources. Budgeting the cost of capital items on an up-front, cash basis, rather than recording the relevant expenses over the useful life of the asset through accrual accounting, exaggerates the cost of infrastructure investments, hides the cost of pension obligations, and undermines intergenerational fairness by mismatching costs and benefits over time. This report card grades the financial presentations of 31 major Canadian municipalities, based on their most recent budgets and financial statements. Of those we assessed, Durham Region, Windsor, London, Quebec City, Laval and Longueuil fail, providing little information in reader-friendly form. More happily, Vancouver garners an A+ for the clarity and completeness of its financial presentations, followed by Surrey and Richmond, each with an A-. Our overarching recommendation is that municipal governments should present budgets using the same public sector accounting standards (PSAS) and format that they use in their year-end financial statements. Most do not, and those that present supplementary PSAS-consistent information in their budgets typically do not do it in userfriendly ways. One key implication of this change would be that municipal budgets would use accrual accounting with respect to capital, recording revenues and expenses as assets deliver their services. Provincial governments that impede the preparation of PSAS-consistent municipal budgets – by mandating that cities present separate operating and capital budgets, for example – should stop doing so. Better would be to require cities to present PSAS-consistent budgets. Municipalities in provinces that continue to impede PSAS-consistent budgets can, and should, release the relevant information on their own. A second implication of this change is that municipal budgets, like municipal financial statements, would show city-wide consolidated, gross revenue and spending figures that represent the city’s full claim on its citizens’ resources and the full scope of its activities. Our second key recommandation is that cities should present and concillors should vote, budgets before the beginning of the fiscal year. These changes would help raise the fiscal accountability of Canada’s municipalities to a level more commensurate with their importance in Canadians’ lives.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.071
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.886
Threshold uncertainty score0.830

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.071
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0100.010
Science and technology studies0.0160.003
Scholarly communication0.0120.004
Open science0.0020.006
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0180.003

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 head0.017
GPT teacher head0.255
Teacher spread0.237 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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
Published2019
Admission routes1
Has abstractyes

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