Cognitive and Social Structure of the Elite Collaboration Network of Astrophysics: A Case Study on Shifting Network Structures [Book Review]
David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Minerva 49 (4):461-488 (2011)
Scientific collaboration can only be understood along the epistemic and cognitive grounding of scientific disciplines. New scientific discoveries in astrophysics led to a major restructuring of the elite network of astrophysics. To study the interplay of the epistemic grounding and the social network structure of a discipline, a mixed-methods approach is necessary. It combines scientometrics, quantitative network analysis and visualization tools with a qualitative network analysis approach. The centre of the international collaboration network of astrophysics is demarcated by identifying the 225 most productive astrophysicists. For the years 1998–1999 and 2001–2006 four co-authorship networks are constructed comprehending each a two year period. A visualization of the longitudinal network data gives first hints on the structural development of the network. The network of 2005–2006 is analyzed in depth. Based on cohesion analysis tools for network analysis, two main cores and three smaller ones are identified. Scientists in each core and additionally in structurally interesting positions are identified and 17 qualitative expert interviews are conducted with them. The visualization of the network of 2005–2006 is used in the interviews as a stimulus for the interviewees. An analysis of the three most often used keywords of the 225 astrophysicists is included and combined with the other data. The triangulation of these approaches shows that major epistemic changes in astrophysics, e.g. the discovery of the accelerating expansion of the universe, together with technical and organizational innovations, leads to a restructuring of the network of the discipline. The importance of a combination of qualitative and quantitative network analysis tools for the understanding of the interplay of cognitive and social structure in the sociology of science is substantiated
|Keywords||Scientific networks Cognitive structure Co-authorship network Astrophysics Scientific collaboration Elite network Social network analysis Epistemic culture Scientific disciplines Dark energy|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
Andrea Bonaccorsi (2008). Search Regimes and the Industrial Dynamics of Science. Minerva 46 (3):285-315.
Jan A. Fuhse (2009). The Meaning Structure of Social Networks. Sociological Theory 27 (1):51 - 73.
Thomas S. Kuhn (1957). The Copernican Revolution: Planetary Astronomy in the Development of Western Thought. Harvard University Press.
Thomas S. Kuhn (1962). The Structure of Scientific Revolutions Vol. The University of Chicago Press.
Rudolf Stichweh (1992). The Sociology of Scientific Disciplines: On the Genesis and Stability of the Disciplinary Structure of Modern Science. Science in Context 5 (1).
Citations of this work BETA
No citations found.
Similar books and articles
Barry Wellman (1983). Network Analysis: Some Basic Principles. Sociological Theory 1:155-200.
Shino Shiode (2008). Analysis of a Distribution of Point Events Using the Network-Based Quadrat Method. Geographical Analysis 40 (4):380-400.
Gaston Heimeriks, Marianne Hörlesberger & Peter Van den Besselaar, Mapping Communication and Collaboration in Heterogeneous Research Networks.
Sjoerd D. Zwart, Ibo van de Poel, Harald van Mil & Michiel Brumsen (2006). A Network Approach for Distinguishing Ethical Issues in Research and Development. Science and Engineering Ethics 12 (4):663-684.
Frédéric Vandermoere & Raf Vanderstraeten (2012). Disciplinary Networks and Bounding: Scientific Communication Between Science and Technology Studies and the History of Science. [REVIEW] Minerva 50 (4):451-470.
Ruth Meyer & Bruce Edmonds, Signatures in Networks Generated From Agent-Based Social Simulation Models.
Mark H. Johnson & Leslie A. Tucker, The Emergence of the Social Brain Network: Evidence From Typical and Atypical Development.
Herman Philipse (1990). The Absolute Network Theory of Language and Traditional Epistemology: On the Philosophical Foundations of Paul Churchland's Scientific Realism. Inquiry 33 (2):127 – 178.
Müge Ozman (2005). Interactions in Economic Models: Statistical Mechanics and Networks. [REVIEW] Mind and Society 4 (2):223-238.
Romain Boulet, Pierre Mazzega & Danièle Bourcier (2011). A Network Approach to the French System of Legal Codes—Part I: Analysis of a Dense Network. [REVIEW] Artificial Intelligence and Law 19 (4):333-355.
M. R. W. Dawson, D. A. Medler, D. B. McCaughan, L. Willson & M. Carbonaro (2000). Using Extra Output Learning to Insert a Symbolic Theory Into a Connectionist Network. Minds and Machines 10 (2):171-201.
Dan Lloyd (1994). Connectionist Hysteria: Reducing a Freudian Case Study to a Network Model. Philosophy, Psychiatry, and Psychology 1 (2):69-88.
Christopher Gauker (1993). An Extraterrestrial Perspective on Conceptual Development. Mind and Language 8 (1):105-30.
Merel Visse, Guy A. M. Widdershoven & Tineke A. Abma (2012). Moral Learning in an Integrated Social and Healthcare Service Network. Health Care Analysis 20 (3):281-296.
Added to index2011-11-24
Total downloads13 ( #130,128 of 1,168,031 )
Recent downloads (6 months)2 ( #85,406 of 1,168,031 )
How can I increase my downloads?