You are kindly invited to follow TALKS ON MIGRATION SERIES: Spring 2020-2021 organized by Jean Monnet Module on European and International Migration Law
Speaker: Dr. Verónica Ruiz Abou-Nigm (senior Lecturer in Private International Law at Edinburgh Law School and the principal investigator of the GCRF funded project Migration in Latin America (MiLA))
Title: “Regional Migration Governance: Soft Law and the Diffusion of Policies on Integration and Inclusion (Focus on South America Regionalism)”
Date: March 9, 2021, Tuesday
Time: 12.30- 13.20
This is an online seminar. To request the event link, please send a message to the department.
Abstract:
Migrant populations in South America are increasing faster than the world average due to rapid growth of intra-regional migration. South America has a distinctive regional liberal discourse, and migration-related projects, processes and products (Van Lagenhove 2012) that are the most developed after those in the European Union (Brumat & Acosta 2019). Yet, this ‘new’ south-south migration generates various and diverse challenges for migrants and their host societies in the region. These challenges also offer opportunities for the development of integration and inclusion policies that can respond locally to the regional experience which is in turn part of a global phenomenon. The presentation will focus on soft law mechanisms, particularly (i) the UN 2030 Agenda for Sustainable Development (2015), (ii) the UN Global Compact for Safe, Orderly and Regular Migration (2018) and (iii) the IACHR Inter-American Principles on the Human Rights of Migrants, Refugees, Stateless Persons and Victims of Human Trafficking (2019). These instruments, despite their non-legally binding nature, may contribute towards local design and implementation of migrant inclusion and integration policies, and to their diffusion, providing an understanding of what ‘well-managed migration polices’ entail, and informing how such policies can be implemented, monitored and evaluated by using indicators to support data collection.