Jihadist terrorism: a protocol for evaluating the risk of radicalization and the perpretation of attacks
Bibliographic record
Abstract
The main purpose of this doctoral thesis is to make up a protocol of a complete examination of the risk of radicalism and perpetration of jihadist attacks. In order to achieve this goal, the research was structured in two different parts. The first one consists of a bibliographical revision of the international literature about the phenomenon of jihadist terrorism. A theoretical basis was carried out about the risk factors of radicalism and attacks, as well as the existing theoretical and empirical protocols on this matter. The second part of our research is based on an original empirical research. A large database was prepared, consisting of all the jihadist attacks commited in West countries from January of 2006 until May of 2018. This date was determined given that the year 2006 is considered the starting point of the terrorist organization ISIS. The sample was composed of 145 authors of 116 attacks, of which 74 were carried out in Europe (n=105 individuals) and 40 in the U.S.A. and Canada (n=42 individuals). The methodology used in our work required the research of information in numerous official and journalistic sources to verify the data in the most profound way. Each one of the attacks was analyzed individually and in detail to obtain specific information about the biography of the individuals who perpetrated the attacks, their personal characteristics and the circumstances surrounding the commission of the events. Concerning all the cases identified, 158 criminological variables were extracted, according to the characteristics of the attacks and its authors, on which the statistical studies were based. The first ones were related to the crime behavior (n = 33), while the second ones were related to the sociodemographic characteristics, lifestyle, personality of the subjects and the process of radicalization that they experienced (n = 125). Both types of characteristics were codified in two differentiated databases in which the information collected was recorded, on the one hand from European cases, and on the other, from U.S.A. and Canada. Some key variables that provided information about the authors profiles and risky behaviors related to the perpetration of attacks were identified. One of the outstanding contributions of this research has been the identification of a new figure that we can call pseudojihadist. This finding shed light on the profile of an author who has been unknown so far, and who requires a specific approach. The final result of our research was materialized in the preparation of the screening and alarm protocols in order to consider both the risk of radicalism and the perpetration of attacks. We did it by comparing the risk factors proposed in previous protocols with the ones obtained in our research; in addition, we achieved an innovative contribution with original and relevant factors. Therefore, the goal of this research is that protocols will have a practical utility in the struggle against terrorism, and owing to this we required the help, collaboration and supervision of a special unit of the Guardia Civil in order to implement these protocols in Spain as soon as possible.
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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 | 0.030 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.043 | 0.015 |
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".