The radicalization of homegrown terrorists: A social-personality model
Notice bibliographique
Résumé
A new type of terrorist has emerged in the last decade. Inspired by jihadi ideology, these individuals are born and raised in the very country they wish to attack. Such homegrown terrorism has become the primary concern of security agencies in Western countries. While many theories purport to describe the exact stages involved in the radicalization leading to homegrown terrorism, very little empirical data exists on the psychology of those who become radicalized. In the present dissertation, I propose and test a novel model of the social psychological factors contributing to radicalization: the two-factor model of homegrown terrorism. The origins of the two-factor model are discussed in Manuscript 1, where I reviewed five major models of radicalization and analyzed them through the lens of terrorism studies and social psychology. This analysis yielded several avenues for future research, including the importance of the jihadi narrative and of personality traits. These two themes then formed the basis of the two-factor model of homegrown terrorism tested in Manuscript 2. In order to derive specific, testable hypotheses, social identity theory was used to deconstruct the jihadi narrative and social dominance theory was used to inform the theme of personality. I hypothesized that the jihadi narrative, which underscores a threat to Islam, is interpreted on an individual level as a threat to collective pride, and that low social dominance orientation (SDO) is linked to increased support for the use of violence. Together, a threat to collective pride and low SDO formed the two-factor model of homegrown terrorism. The initial test of the two-factor model consisted of a survey conducted with Canadian Muslims. Results supported one factor in the model but not the other. Respondents who perceived a greater threat to Islam reported less collective pride, which in turn lead to more aggressive action tendencies towards non-Muslim Canadians. Moreover, it was high SDO, rather than low SDO, that were linked to more aggressive action tendencies towards non-Muslim Canadians. A similar pattern of results was found in two laboratory experiments where participants were deceived into thinking that group members had either truly planned, or successfully carried out, acts of terrorism. When this violence was presented as a response against a threat to group pride, strongly identified group members viewed terrorism more positively. Moreover, during these experiments, higher levels of SDO were associated with more positive appraisals of terrorism. Manuscript 3 describes additional testing of the link between high SDO and terrorism. Capitalizing on an annual large-scale civil-war simulation, I investigated if participants' personality characteristics predicted their selection of simulation role. For two consecutive years, students who requested to enact terrorists and insurgents rated significantly higher on SDO than students requesting other roles. Overall, the results identify collective pride and high SDO as key factors in the radicalization process leading to terrorism. Implications for future research and counter-terrorism strategies are discussed.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,003 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».