Les dimensions émotionnelles du terrorisme : Émotions, radicalisation violente et engagement terroriste
Bibliographic record
Abstract
Par une volonté louable de rompre avec des approches psychologisantes du phénomène terroriste dominantes au cours des années 1960-70, les recherches contemporaines en matière de terrorisme(s) et de violence(s) politique(s) ont très largement mis l’emphase sur la figure du « terroriste » comme acteur rationnel et stratégique. Face aux limites des approches rationalistes de l’engagement radical qui envisagent de manière réductionniste les individus au travers d’un calcul rationnel univoque en terme de coûts et d’incitatifs à l’action, il nous apparaît important de réintégrer dans les réflexions théoriques sur les phénomènes terroristes, les émotions afin d’en interroger le rôle dans la production d’une trajectoire violente et/ou terroriste Notre article se propose donc ici d’effectuer une revue de la littérature non-exhaustive des travaux actuels autour du rôle des émotions en matière de terrorisme, et d’éclairer les voies de recherches futures à la lumière de travaux déjà engagés dans le champ de la sociologie des mouvements sociaux, des nouveaux mouvements religieux ou encore de la sociologie cognitive. Au travers de ce « retour des émotions » qui traverse les sciences sociales et plus globalement le champ de la connaissance contemporaine, nous pensons qu’il s’avère en effet possible de dégager des pistes de recherches fructueuses permettant d’affiner notre regard sur les phénomènes terroristes et les logiques de radicalisation violente.Contemporary research on terrorism(s) and political violence(s) have largely put the emphasis on the figure of the "terrorist" as rational and strategic player, in a break with psychoanalytical approaches to terrorism that were dominant from the 1960-1970’s. Giventhe limitations of rationalist approaches to radical commitment, and considering how reductionist is the understanding of individual participation to terrorism related activities through a rational calculation framework in terms of costs and incentives to action, it is important to reintegrate in the theoretical reflections on terrorist phenomena how emotions can play a role in leading potential terrorists down a violent path. This paper presents acritical assessment of current academic work surrounding the issue of violent radicalization and involvement in terrorism, and engages in a theoretical debate thathighlights potential future research that could better integrate a prominent role foremotions in our understanding the process of terrorist radicalization and clandestine political violence.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".