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Debus, Marc, und Martin Gross (2017): Positions on and issue emphasis of European integration and EU Cohesion policy: Analysing (sub-)national party manifestos. [COHESIFY research paper; 4] mehr
Debus, Marc, Jale Tosun und Marcel Maxeiner (2017): Support for Policies on Entrepreneurship and Self-Employment among Parties and Coalition Governments. Politics & Policy, 45, Heft 3, S. 338-371. mehr
Dollmann, Jörg (2017): Positive choices for all? SES-and gender-specific premia of immigrants at educational transitions. Research in Social Stratification and Mobility, 49, S. 20-31. mehr
Dollmann, Jörg (2017): Presentations of migration data sources: CILS4EU. [CESSDA Data Discovery Workshop and Workshop on Methodological Issues in Surveying Immigrant Populations, GESIS, Köln, 13. bis 14. November 2017] mehr
Dollmann, Jörg, und Frank Kalter (2017): Positive choices everywhere? System-specific premia for immigrants at educational transitions. [25th Annual Workshop Transition in Youth (TIY), Brüssel, 13. bis 16. September 2017] mehr
Dollmann, Jörg, und Frida Rudolphi (2017): Classroom composition and achievement: Do class context or friends in class matter more?. [Summer Meeting of the Research Committee on Social Stratification and Mobility (RC28), New York, 08. bis 10. August 2017] mehr
Däubler, Thomas (2017): Constituency Representation under Districted PR Systems. [Workshop "Responsivität", University of Duisburg-Essen, 20. Januar 2017] mehr
Däubler, Thomas (2017): Links-Rechts und darüber hinaus - eine Neuvermessung der deutschen Parteienlandschaft mit einem auf die MARPOR/CMP-Daten angewandten IRT-Modell. S. 57-88 in: Sebastian Bukow, Uwe Jun (Hrsg.) Parteien unter Wettbewerbsdruck. Wiesbaden: Springer VS. mehr
Däubler, Thomas (2017): National Policy for Local Reasons. [Workshop "Micro-foundations of party democracy: The re-inforcing and cross-cutting consequences of party membership and non-party affiliation", University of Bremen, 20. bis 21. Juli 2017] mehr
Däubler, Thomas, und Kenneth Benoit (2017): Statistical Scaling Meets Classic Content Analysis: Using Bayesian IRT-Modelling to Infer Latent Variables from Hand-Coded Texts. [The 3rd Annual International Conference on Computational Social Science, Cologne, 10. bis 13. Juli 2017] mehr