Bibliographic record
Abstract
Following the 9/11 attacks on New York and Washington, DC, there has been an increasing interest among scholars, students, and the interested public to study and learn about the Islamist-oriented terrorist organizations called Jihadi Salafi Groups (JSGs). Considering that these organizations emerged in highly fragile states, S. Yaqub Ibrahimi asks: how and why is state fragility linked to the emergence of JSGs? Ibrahimi bases his study on three events: the establishment of al-Qaeda in Afghanistan in 1998, the rise of Islamic State in the post-Saddam Hussein Iraq, and the failed al-Qaeda effort to establish a base in Saudi Arabia in 2003. These case studies contain major aspects and features of the rise of JSGs and, together, explain the contribution of state fragility to the process of the formation and expansion of these terrorist organizations. International Security in a World of Fragile States stands out as a pivotal work on the interconnection between the root causes of JSGs and state fragility conditions and their amalgamated role in the formation and evolution of these organizations. It contributes to IR and international security debates by developing a comprehensive but readily understandable narrative of the rise of JSGs in Islamic countries, and examining them in an analytical framework in which their root causes are categorized on individual, group, and international levels.
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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 | 0.010 | 0.023 |
| Scholarly communication | 0.011 | 0.014 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".