Macroeconomic Agenda for Fiscal Policy and Aid Effectiveness in Post-Conflict Countries
Bibliographic record
Abstract
Acknowledgments: This paper has been presented at the “Peace and Development” Workshop at McGill University on November 7, 2008. Comments by participants, and in particular by Sonia Laszlo, who was the discussant, and by Ibrahim Elbadawi, Philip Oxhorn, and Stergios Skaperdas, are gratefully acknowledged, without implicating. Abstract: This paper first presents a simple game-theoretic framework for thinking about the roles of deterrence and redistribution in peace-keeping. It shows that institutional deficiencies and military weakness may combine to undermine the political will of the incumbent government in favor of peace, and thus result in the outbreak of violence. Both types of policies for buying peace require budgetary resources that are in short supply in post-conflict countries. This remark suggests where the international community should focus the application of foreign aid for preventing a civil war from resuming. Then, the paper reviews the standard institutional response that have been tried to reduce the risk of violent conflict erupting. These include federalism, majority rule and power-sharing. The required conditions for each type of institutional response to be effective are then brought out. 1 1.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.019 | 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".