à 
Prix: Entrée libre
Local C-2059
3150, rue Jean-Brillant
Montréal (QC) Canada  H3T 1N8

Guest speaker : Conor O'Reilly


Conor O'Reilly is Associate Professor in Transnational Crime and Security at the Centre for Criminal Justice Studies, University of Leeds. He has published widely on themes including: transnational policing; high policing; branding security; colonial policing; and, Lusophone policing. At present he is working on two large research projects: the Newton Fund project 'Mobile Solutions to the Mexican Kidnapping Epidemic' (PI); and, the ESRC Transformative project 'Data Justice in Mexico's Multiveillant Society' (Co-I).



Summary


This conference presents findings from the Newton Fund project, ‘Mobile Solutions to the Mexican Kidnapping Epidemic: Beyond Elite Counter-Measures, Towards Citizen-Led Innovation’. It draws upon fieldwork conducted in the US-Mexico borderland settings of Juarez-El Paso and Tijuana-San Diego. Whilst it is a given that kidnapping disrupts normal life patterns and tears at the social fabric of affected communities, our research in the US-Mexico borderlands has uncovered other interruptions to the everyday intimacies of personal and business life in this region that stem from kidnapping. In arrangements that I term the ‘intimacy-distance paradox’, ever-present kidnap risk has created the strange situation whereby the protection of those with whom citizens are closest, often necessitates the fashioning of (somewhat contradictory) arrangements that instil distance as a key element in security arrangements and protocols to preserve and secure those same relationships. This paper spotlights how intimacy, its betrayal, its loss, its creation, its preservation, and (potentially) its restoration, are important considerations within examination of kidnapping in Mexico’s Northern borderlands, and indeed further afield.


Information


Conférence organisée par le Centre international de criminologie comparée

Kidnapping in the US-Mexico Borderlands and the 'Intimacy-Distance Paradox'