The Corruption-Terrorism Nexus: A Panel Data Approach
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
<p>Corruption has been increasingly recognized as the major threat to economic development, political stability and peace. It is also acknowledged by international community as the breeding ground for terrorism. This paper examines the relationship between corruption and terrorism in the long run. Previous studies examining the link between these two phenomena used only time series cointegration tests. In this paper, we make use of a dataset for a panel of 123 developed and developing countries over the period 2003-2014. We use Pedroni’s residual-based panel cointegration test and the error correction model-based panel cointegration test developed by Westerlund. In order to obtain more robust results, we use two different measures of corruption which are Corruption Perceptions Index (CPI) and Worldwide Control of Corruption Indicator (CC). The results of both tests reject the null hypothesis of no cointegration. we conclude that corruption and terrorism converge. Our findings corroborate results of previous studies.</p>
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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