Separatism and Jihadism: Interaction in the Context of Terrorist Activity
Bibliographic record
Abstract
According to the well-known concept of consequential waves of terrorism, proposed by American researcher David C. Rapoport, since 1979, the world has encountered a wave of religious terrorism. Religiously motivated terrorists are the most dangerous and cruel terrorists who continue to lead the world. All four terrorist groups responsible for 55 per cent of total deaths in 2019 are jihadists (Global Terrorism Index 2020). The Taliban, Boko Haram, ISIL, and Al-Shabaab all fight for the establishment of their own quasi-state entities within the borders of existent sovereign states. This political objective associates the jihadists with another ideological movement – separatist-terrorists – in Rapoport’s model. Despite apparent distinctions in ideological foundations and political agendas, these two movements are similar in their struggle for self-determination within the borders of sovereign states. In this article, we use data from the Global Terrorism Database to compare how these two ideological movements with similar political objectives influence each other in the area of terrorist activity. Having analysed and reviewed information about 3,617 terrorist organisations that committed at least one terrorist attack from 1970 to 2018, we check how jihadist and separatist-terrorist activities were interrelated and how this interrelation manifested itself in different countries.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".