By the Numbers: The Fiscal Accountability of Canada's Senior Governments, 2015
Bibliographic record
Abstract
Control over public money is fundamental to democratic government, and presents huge challenges to legislators and taxpayers. Getting the information needed to answer simple questions such as how planned spending in the upcoming year compares to actual results in the prior year can be hard, and ensuring that governments treat their budget targets seriously is an never-ending task. This latest edition of the C.D. Howe Institute’s annual report on the fiscal accountability of Canada’s federal, provincial and territorial governments assesses the quality of financial information these governments present, and looks at their success or failure in achieving their budgetary goals over the past decade. Its survey of the financial reports reveals some good news: more governments now prepare their budgets on the same basis as their end-of-year public accounts, making comparisons over time easier for their citizens. While these improvements mean that more governments earn high marks for their reporting, some jurisdictions still present numbers in which such key figures as total spending and total revenue are obscure. Inconsistent presentation of numbers to legislators, late reporting, and qualified audits are too common. A major aim of this report is to celebrate the relatively transparent reporting found in New Brunswick and Saskatchewan, and in Ontario and Ottawa, and encourage other jurisdictions to raise their game. When it comes to the degree to which results match intentions, the survey also finds some good news. In the second half of the past decade, the spending and revenues reported by Canada’s senior governments at the end of each fiscal year have tended to match the projections in the budget at the beginning of the year more closely than in the first half of the decade. That said, federal, provincial and territorial governments tend to overshoot their budget targets by large amounts. Over the decade, Canada’s senior governments overshot their spending targets by some $48 billion in total. They also brought in far more revenue than anticipated in budgets, and while caution in forecasting can explain some of this overshoot, the survey finds a disturbing tendency for revenue and spending surprises, up or down, to occur together – more suggestive of opportunism than good fiscal management. Improving control over public funds in Canada will require two things. Legislators and the public must demand more transparent, timely and accurate reporting of governments’ fiscal plans and results. And legislators must use their powers over appropriation more effectively. Votes on budgets are votes of confidence that determine whether governments stand or fall. Only when legislators ensure that budget plans are meaningful do they hold governments accountable for their use of public funds.
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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 | 0.011 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.025 | 0.007 |
| Scholarly communication | 0.021 | 0.005 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.021 | 0.005 |
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".