Unlocking Luhmann

A Keyword Introduction to Systems Theory
1. Auflage 2021
ISBN: 978-3-8376-5674-9
Verlag: transcript

Buch, Englisch, 276 Seiten, Kartoniert, Format (B × H): 148 mm x 225 mm, Gewicht: 432 g

Reihe: BiUP General

Luhmann's theory is fascinating and complex. It offers incomparably enlightening insights, references and research opportunities, but reveals its utility only after a quite high competence threshold. Using the reticular form of the glossary, this book makes the theory accessible while maintaining its complexity. Without being obstructed by knowledge gaps or by references to concepts presented elsewhere, readers inside and outside sociology get the required support to explore sociological systems theory and to engage with it. Luhmann himself, in his introduction, praises the form of the glossary to cope with the challenges of the theoretical description of our highly complex society.

Autoren/Hrsg.

Baraldi, Claudio

Corsi, Giancarlo

Esposito, Elena

Weitere Mitwirkende

Walker, Katherine

Fachgebiete

• Mathematik | Informatik Mathematik Mathematik Interdisziplinär Systemtheorie
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Kybernetik, Systemtheorie, Komplexe Systeme
• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Gesellschaftstheorie

Über Autor(innen)

Claudio Baraldi published several works in international books and journals on communication systems. His research concerns interaction systems related to facilitation of children's participation, interlinguistic and intercultural mediation, conflict management.
Giancarlo Corsi worked and published intensely on the theory of social systems, public opinion and communication media, education, career and social inclusion. His current research deals with the relationship between public sphere, mass media, and new communication technologies.
Elena Esposito published many works on the theory of social systems, media theory, memory theory, and sociology of financial markets. Her current research on algorithmic prediction is supported by a five-year Advanced Grant from the European Research Council.