Where the Bucks Stop: A Shadow Federal Budget for 2016
Bibliographic record
Abstract
The 2016 edition of the C.D. Howe Institute’s annual Shadow Federal Budget puts a sustainable financial position and fiscal path at the centre of its plans. Confidence that the country will successfully navigate an environment of slower global growth and population aging is an essential backdrop for government measures to support economic growth in the medium and long term and to promote better opportunities for all Canadians. This Shadow Budget reflects our view that the new government in Ottawa must temper the sense created by the election campaign and early post-election announcements that there are no limits to what the federal government can spend and borrow. The commitment during the election campaign to borrow for infrastructure spending can justify only modest deficits: most federal infrastructure projects last a long time, and writing their cost off over long periods adds modest amounts to annual expenditure. Deficits beyond what capital projects justify add to the federal government’s net debt, and hurt growth by absorbing saving that would otherwise fund Canadian investment. Canada needs fiscal measures that will boost productive capacity. This Shadow Budget emphasizes growth-friendly tax policy, openness to trade and competition, and supportive reform of institutions and regulations. It prioritizes spending on federal infrastructure projects while holding the line on the funding already committed for projects under provincial or municipal control. The Shadow Budget will support financial sustainability by reforming federal employee compensation arrangements, providing a more accurate picture of Ottawa’s balance sheet, ensuring federal transfers to the provinces stay on a sustainable course, and limiting exposure to contingent mortgage insurance liabilities. Looking to the future, a key theme of this Shadow Budget is improving opportunities for Canadians. It proposes new spending in several areas, including federal support for provincial drug programs and onreserve education, and proposes measures to level the playing field for Canadians saving for retirement. Reflecting our approach of holding the line in some areas and increasing spending in others, this 2016 Shadow Budget projects modest deficits of $15.3 billion and $12.2 billion over the next two fiscal years, setting the stage for a return to surplus in 2019/20.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.040 | 0.021 |
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".