Framing and Contesting a Revolution: Identity Construction, Gender, and Rebel Group Cohesion in Columbia
Notice bibliographique
Résumé
The literature on rebel group cohesion and desertion from armed groups offers a variety of explanations for patterns of disengagement from armed violence, including government pressure, in-group violence, disillusionment in the group's cause, networks, and trauma.But most of the disengagement literature focuses on men who have deserted their groups, with much less information on those who stay until ordered to disarm-and almost no analysis on women who disarm.The lack of comparative analysis between deserters and loyalists limits what we understand or can predict about rebel group cohesion.In addition, this literature has failed to adequately explore the role of gender norms, even though hypermasculinity, narratives of brotherhood, and feminization of the enemy are well-established mechanisms for increasing troop cohesion in militaristic groups.Based on over 100 in-depth interviews with former guerrillas and paramilitaries in Colombia, this dissertation argues that framing contests and related identity constructions are critical in insurgencies and civil war, and that the outcome of these contests influences individual decisions to disengage from violence and the experiences of ex-combatants after demobilization.Second, I argue that how these competing frames operationalize gender norms influences not only troop cohesion but also the way combatants calculate their investments in the group and possible alternatives.As a result, even recruits that are not fully committed may stay for lack of alternatives.Conversely, recruits may desert their group only to face the stigmatizing consequences of government narratives in civilian life.This study examines what variables produce these outcomes, emphasizing the role of framing contests and arguing that ignoring gender in rebel group cohesion has left a significant gap in our understanding of both desertion and post-conflict reintegration.my access to these sites, which were the jumping off point for this work.I am indebted to my hard-working transcribers, Alejandro Reverend and Jorge Soto (without whom I would no doubt still be transcribing), and to my beloved Spanish teacher, Mauricio Hoyos and his family, who ensured that I was well-versed in Colombian slang and provided a place to rest in the midst of my intense fieldwork.And I do not even know how to thank Alejandro Carlosama, who worked beyond all expectations as my research assistant, fixer, and confidante.Alejo, estoy muy agradecida por lo que has hecho y siempre te tendré a ti y a tu familia en mi corazón.Many wonderful friends kept me sane during this process, especially those who tolerated hearing about my dissertation endlessly: Julie Stonehouse, Maya Dafinova, Gaëlle Rivard Piché, Mia Schöb, and my runner girl gang.I will also always be grateful to my parents for fostering curiosity and a lifelong passion for learning, and for flying across the country many times to help with childcare.My dear children, Jesiah and Calia, showed incredible courage and tenacity throughout this long process and endured a lot of upheaval.And my husband, Jon, whose unfailing loyalty, flexibility, and encouragement-even when I made highly questionable decisions-allowed all of this to happen.Thank you for being a rock when I was the storm.Lastly, I owe my life to someone whose name I do not know.In 2012, a
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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 | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,018 | 0,012 |
| Communication savante | 0,010 | 0,002 |
| Science ouverte | 0,001 | 0,006 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 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 ».