State Fragility and Implications for Aid Allocation: An Empirical Analysis
Why this work is in the frame
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Bibliographic record
Abstract
In recent years, state fragility has gained importance as a result of the perceived links between poverty, conflict, and global terrorism. In this paper, we examine the relationship between state fragility and aid by evaluating the literature and research programs currently extant. We bring conceptual clarity to the issue by developing and testing an alternative theoretical framework using CIFP's fragility index (articulated around the concepts of authority, legitimacy, and capacity [ALC]) and by using data collected for the period 1999—2005 to identify the empirical determinants of fragility. We then examine the effects of state fragility on aid allocation, using the ALC framework as defined. Our results indicate that aid allocation is directed toward states on the basis of their capacity and authority scores and not on the basis of their legitimacy scores. Finally, we assess the theoretical and policy implications of these findings and specify directions for future research.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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