Dr. Luana Martin-Russu
- Post-accession Europeanization
- European Integration
Dr. Luana Martin-Russu is a postdoctoral researcher at the New School of Digital Studies (ENS) of the European University Viadrina, Frankfurt (Oder). Her current research focuses on the use of digital data analysis for measuring de-Europeanization. Her main research interests include European Union politics, EU enlargement and conditionality, democracy and rule of law observance in Eastern Europe.
Luana has been invited to give input presentations and workshops in Germany, France, Italy, Switzerland and the UK. She is active in the non-governmental sector and leads a project on environmental and global citizenship education.
Luana has taught a wide range of classes in Europeanization, European Politics and International Relations at the European University Viadrina, Frankfurt (Oder).
Transparency Made Useful: Employing Digital Data Analysis to Measure and Prevent de-Europeanization
Digital data analysis to measure de-europeanization: the manner and extent to which the European Union produces domestic change in its member- and accession-states. It starts from the empirical observation that several European member states allow their legislation to slide away from either European or democratic standards after having gained EU membership. It postulates that it depends primarily on lawmakers whether or not a state pursues a European and a democratic agenda. Therefore, it is at the level of legislative decision-making that this project decides to observe when and where there is a decrease in the level of compliance and when and where the rule of law is not de facto realized. It takes up the challenge to develop a longitudinal study across policy fields and over longer periods of time in order to reveal subtle patterns of legislative instability and abusive law-making practices. It starts from the research question: How can de-Europeanization be effectively measured? It sets off to answer this question by employing a new method of analysis based on computer driven data acquisition (Python-based algorithms) and natural language processing (NLP).
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