Fiscal transfer in Canada: Drawing comparisons and lessons
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Canadian system of fiscal transfers, which has been developed over a long period of time, has two central features: equalisation grants, which are constitutionally guaranteed, and the Canadian Health and Social Service Transfers (CHST). This paper examines the relevance and applicability of the Canadian system of intergovernmental transfers in the Indian case. Equalisation grants are meant to ensure that provinces have sufficient revenues to provide reasonably comparable levels of services at reasonably comparable levels of taxation. An elaborate `Representative Tax System' approach using individual revenue bases is used in Canada for determining the equalisation grants, although there has recently been a debate to use a more macro approach. The source by source approach is less practical in the Indian case for want of comparable and reliable information required for applying the method. A more practical alternative is the macro approach, which is adopted in India, but better indicators of fiscal capacity than those based on GSDP need to be used. In addition, the concept of ensuring that resources are available for maintaining the per capita expenditure of select basic services at certain levels among states, as attempted in Canada through the CHST transfers, is worth exploring.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it