Perspectives in Fiscal Decentralization: Challenges and the Unfinished Agenda
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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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 | 0.027 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.008 | 0.032 |
| Scholarly communication | 0.012 | 0.023 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.010 | 0.019 |
| Insufficient payload (model declined to judge) | 0.008 | 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".