Contracting for Tax Room: The Law and Political Economy of Tax-Point Transfers
Bibliographic record
Abstract
Tax-point transfers are potentially a foundational tool for changing the allocation of tax room between governments, but they have fallen into disuse in Canadian fiscal federalism. This article argues that the infrequent use of tax-point transfers can be explained, in part, by impediments to the enforcement of intergovernmental contracts. The problem is twofold: (1) tax-point transfers typically consist of long-term non-sequential transactions, in which governments perform their obligations at substantially different points in time; and (2) the common mechanisms for assuring performance in long-term non-sequential transactions are either unavailable or of only modest force in tax-point transfer agreements. The primary implication is that these contractual impediments may discourage governments from using tax-point transfers to achieve an optimal allocation of tax room.
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.023 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".