The myth of global Islamic terrorism and local conflict in Mali and the Sahel
Bibliographic record
Abstract
IN THE WAKE OF THE RAPID escalation of the conflict in Mali, analyses and articles seeking to make sense of the situation and its actors have proliferated.1 Nevertheless, political figures, policy makers, and researchers continue to fall back on simplistic narratives in their attempts to explain the intensification of violent Islamist activity in the region. Without a finely tuned understanding of diverse groups – their structures, objectives, and modalities of violence – analysts risk recycling dangerously misleading narratives about Islamist violence in Africa and its consequences. This briefing draws on empirical evidence of violent Islamist activity, strategy, and structure to highlight the differentiated nature of groups operating in the Sahel region and further west, in what has come to be known as Africa's ‘arc of instability’.2 It contends that violent Islamist groups emerge in and are shaped by distinct domestic contexts and issues, a feature that is obscured by a totalizing narrative of global Islamic terrorism. In turn, leaders seek to cast opposition threats as extreme and associated with Al-Qaeda in order to locate the blame for violence elsewhere, away from poor records of governance, state capacity, and representation.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.029 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".