Managing Tax Expenditures and Government Program Spending: Proposals for Reform
Bibliographic record
Abstract
The federal government implemented a new expenditure management system in 2007. Under the new system, departments are required to review programs on a four-year cycle to determine if they are aligned with federal responsibilities and priorities, if they are efficiently delivered and if they are providing value for money, or effective. Based on the results from these strategic reviews, which are expected to be supported by formal evaluations that provide the evidence base for decisions, departments are expected to identify five per cent of their direct program spending that could be reallocated to other priorities, including deficit reduction. This system has much to recommend it, but to realize the full potential of the new system two fundamental changes should be made. First, spending programs delivered through the tax system should be integrated into the expenditure management system. Integration implies that departments would be given responsibility for both tax and spending initiatives that are relevant to their mandates, and that tax-based expenditures would be subject to the government’s evaluation policy and be included in strategic reviews. Second, while departments should continue to have responsibility for evaluating program efficiency, evaluations of both tax- and spending-program effectiveness should be undertaken by an independent entity such as the Parliamentary Budget Officer. Effectiveness evaluations should be carried out using a variant of the benefit-cost framework that is now applied to government regulatory initiatives. In order for the reformed system to work, more resources will need to be allocated to developing the performance data needed to undertake effectiveness evaluations and to perform the evaluations. These changes go well beyond a recent recommendation by a House of Commons committee to include tax expenditures in departmental reports to Parliament, along with planned program spending. The government rejected the recommendation, arguing that the change would undermine the finance minister’s authority over the tax system. Reform cannot proceed unless the finance minister relinquishes his power, exercised jointly with the prime minister, to introduce, modify, or eliminate tax measures related to the mandate of a program minister without the consent of the minister.
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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 | 0.045 | 0.095 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.016 | 0.020 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.022 | 0.012 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".