A Crime–Terror Nexus? Thinking on Some of the Links between Terrorism and Criminality<sup>1</sup>
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
Decreasing state sponsorship for terrorism in the post-9/11 environment has pressed terrorist groups to find alternative sources of financial support. Some groups have created their own “in-house” criminal capabilities, for example FARC, the LTTE, and Al Qaeda. Several analysts have argued that this “mutation” in organizational form may lead terrorist groups to ally with organized crime, whereas others have suggested that distinct organizational and ideological differences between the two will preclude cooperation. Drawing on both accounts, it is argued in this article that the degree of a terrorist group's organizational capacity and need are key predictors of the types of crime they will engage in, while ideological (political) distinctiveness will preclude fully symbiotic cooperation between terrorists and organized crime groups.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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