Perspectives in Fiscal Decentralization: Challenges and the Unfinished Agenda
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
Fiscal decentralization has received a great deal of academic research attention in the past three decades. Much of this work has been directed toward advising countries on how they should structure their intergovernmental fiscal systems to move government decision making closer to local constituencies. Yet even with all this good work, there are many areas where major questions remain. This paper is about where the next round of research might be focused. It begins with an explanation of why attempts to measure fiscal decentralization are unsatisfactory, and ends with a discussion of what might be done about the equally unsatisfactory state of availability of comparative data. The more detailed discussions in this paper cover tax and expenditure assignments, intergovernmental transfers, debt, and the controversy about whether fiscal decentralization has worked.
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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