To be or not to be: How the Luxembourgish government is preparing for Brexit

This article summarizes the potential impact of BREXIT on Luxembourg (as seen by April 2019)

Double transition of young migrants in Luxembourg: vulnerable, resilient and empowering integration trajectories in the period of youth

peer reviewedMigrant integration trajectories have become more complex, open, uncertain, and continuously changing, over time. For young migrants, their integration endeavour intersects with their process of transition to adulthood, a double transition that poses additional challenges. Recent theoretical perspectives such as “liquid integration” aim at focusing on the dynamic, processual, and temporal nature of migrant integration. The present article focuses on the dynamic interplay of obstacles and enablers that, over time, interact to construct complex, often non-linear, and open-ended integration and coming of age trajectories of young migrants (aged from 18 to 30 years) coming from outside the European Union (EU) to EU countries. Empirical results from the H2020 MIMY (Empowerment through liquid Integration of Migrant Youth in vulnerable conditions) research project in Luxembourg will be presented. In order to address the goal of the research, qualitative data were gathered by means of N = 38 interviews with young migrants with different migratory paths, characteristics and experiences, and specifically included: young migrants from non-EU Portuguese-speaking countries (N = 16), refugees living in reception centres (N = 15), migrants who since arriving in Luxembourg have become publicly visible (N = 7). Content analysis of the interviews allowed a twofold purpose: (1) capturing the unfolding of intersectional integration obstacles that over time play a decisive role in the building of conditions of vulnerability of the double transition under analysis; (2) capturing the multidimensional resources that interactively build up to give rise to resilient and empowering integration and coming of age experiences. The identification of decisive multidimensional obstacles and resources present in the integration endeavour during the process of coming of age allowed us to capture differentiated routes of vulnerability, on the one hand, and resilience/ empowerment on the other. Key ingredients of both vulnerable and more resilient and empowering integration and coming of age trajectories are identified as well as their relational dynamics, enabling to address key challenges for the resilience and empowerment of young migrants in the process of negotiating their transition to adulthood amidst their integration challenges in the Luxembourgish society.11. Sustainable cities and communitie

Why is it so hard? And for whom? Obstacles to intra-European mobility

Even though intra-European youth mobility is valued as a boost for personal and professional development, few opt for it. While obstacles preventing young people to become mobile have been discussed broadly, less attention has been paid to the obstacles for the youth who are already on the move. We offer this rare perspective in regard to intra-European mobility. We focus on youth in four types: pupil mobility, vocational (education and training) mobility, higher education student (degree and credit) mobility and employment mobility, in six countries: Germany, Hungary, Luxembourg, Norway, Romania and Spain. Our analysis, based on qualitative (140 interviews) and quantitative (N=1.682) data, reveals that the perceived obstacles vary between the mobility types, with the greatest divergence between the educational and work-related mobilities. Obstacles such as lack of financial resources and guidance, the perceived incompatibility of institutional regulations within Europe, are shared by all mobile youth

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Brexit: Mind the gap! The significance of regional disparities in political decision making

Die Ergebnisse des Referendums am 23. Juni 2016 im Vereinigten Königreich (VK) sind ein Beweis dafür, dass regionale Disparitäten und der territoriale Zusammenhalt innerhalb eines Landes politisch relevante Faktoren darstelle

Mixed Methods to Empower Migrant Youth in Vulnerable Conditions: a place-based, migrant-centered international project

In this methodological paper, we will present a newly established international and interdisciplinary research project focusing on empowering young migrants in vulnerable conditions and supporting integration strategies within the EU in a unique and comprehensive mixed methods research design combining secondary analysis with qualitative empirical data. The triangulation of results from different sources and methods will help to provide a deeper insight into the integration processes from the perspectives of migrants, host nationals and experts. In the framework of MIMY, financed by H2020 and comprising 12 consortium members from 11 disciplines and 9 European countries, we will focus on various challenges of integration strategies of young migrants in vulnerable conditions, considering different sectors from the perspective of different actors, at macro-, meso- and micro-levels. This will help to explain the successes and failures of integration over migrants’ life courses as well as the long-term consequences for migrant communities and the hosting society. The research design of MIMY follows several steps: 1) desk research - literature review, content analysis, mapping exercises, 2) quantitative secondary data analysis, policy and discourse analysis, 3) qualitative empirical studies, and 4) synthesizing and synergizing all findings and drawing policy recommendations. The present paper will outline how this project integrates qualitative and quantitative methods by using an innovative, multi-method approach (e.g. policy analyses, delphi study, focus groups, in-depth qualitative interviews, participatory action research) in order to explore vulnerability and resilience of young migrants in cross-national perspectives combining policy analysis with demographic, sociological, psychological, discursive, and ethnographic analysis

Was bedeutet jung und mobil? Ergebnisse aus dem Projekt MOVE

MOVE (Mapping mobility - pathways, institutions and structural effects of youth mobility in Europe) dealt with intra-European mobility (May 2015 - April 2018). The text sets out recommendations for action on youth mobility