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  1. The Relevance of Language as a Predictor of the Will for Independence in Catalonia in 1996 and 2020
    Autor*in: Argelaguet, Jordi
    Erschienen: 2021
    Verlag:  SSOAR, GESIS – Leibniz-Institut für Sozialwissenschaften e.V., Mannheim

    Abstract: The Catalan secessionist parties, if added together, have won all the elections to the Parliament of Catalonia from 2010 to 2021. Their voters have been increasingly mobilized since the start of the controversial reform process of the... mehr

     

    Abstract: The Catalan secessionist parties, if added together, have won all the elections to the Parliament of Catalonia from 2010 to 2021. Their voters have been increasingly mobilized since the start of the controversial reform process of the Statute of Autonomy (2004-2010). The aim of this article is twofold. First, it intends to test whether language is the strongest predictor in preferring independence in two separate and distinct moments, 1996 and 2020. And second, to assess whether its strength has changed - and how - between both years. Only the most exogenous variables to the dependent variable are used in each of two logistic regressions to avoid problems of endogeneity: sex, age, size of town of residence, place of birth of the individual and of their parents, first language (L1), and educational level. Among them, L1 was - and still is - the most powerful predictor, although it is not entirely determinative. The secessionist movement not only gathers a plurality of Catalan native

     
    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    DDC Klassifikation: Politikwissenschaft (320)
    Weitere Schlagworte: Catalonia; effective number of language groups; independence; language; logistic regression; secessionism; subjective national identity
    Umfang: Online-Ressource
    Bemerkung(en):

    Veröffentlichungsversion

    begutachtet (peer reviewed)

    In: Politics and Governance ; 9 (2021) 4 ; 426-438
  2. Concept of peer-to-peer lending and application of machine learning in credit scoring
    Autor*in: Klimowicz, Aleksy; Spirzewski, Krzysztof
    Erschienen: 2021
    Verlag:  University of Warsaw, Faculty of Economic Sciences, Warsaw

    Zugang:
    Verlag (kostenfrei)
    Verlag (kostenfrei)

    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signatur:
    VS 427
    Fernleihe:
    keine Fernleihe
    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Schriftenreihe: Working papers / Faculty of Economic Sciences, University of Warsaw ; no. 2021, 4 = 352
    Schlagworte: artificial intelligence; peer-to-peer lending; credit risk assessment; credit scorecards; logistic regression; machine learning
    Umfang: 1 Online-Ressource (circa 53 Seiten), Illustrationen