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New publication by Hjellbrekke and Korsnes

Field Analysis, MCA and Class Specific Analysis: Analysing Structural Homologies Between, and Variety Within Subfields in the Norwegian Field of Power

In this chapter, Hjellbrekke and Korsnes discusses how the homology thesis can be investigated statistically by turning to two variants of geometrical data analysis: MCA and class specific MCA (Le Roux og Rouanet 2010). In particular, class specific MCA (herafter CSA ) is a methodological innovation that allows us not only to explore the relation between the field of power and its subfields, but also to discuss how Bourdieu’s homology thesis may be scrutinized.

Hjellbrekke og Korsnes
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In the social sciences, multiple correspondence analysis (MCA) owes much of its fame to the work of the late Pierre Bourdieu (1930–2002). Now classic works like L’anatomie du gout (Bourdieu and de St. Martin 1976), Le patronat (Bourdieu and de St. Martin 1978), Distinction (Bourdieu 1984 [1979]), Homo Academicus (Bourdieu 1984) and State Nobility (1996 [1989]) all relied heavily on the use of either simple correspondence analysis (CA) or multiple correspondence analysis (MCA). By subjecting data on various forms of capital distributions to CA or MCA, field structures were objectified and the homology thesis, i.e. that fields in the modern French society were structured in similar ways, could be formulated. The problem of homology has been a returning question in the reception and the attempts of replicating Bourdieu’s work, both within and outside of France. In this chapter, we’ll discuss how this hypothesis can be investigated statistically by turning to two variants of geometrical data analysis: MCA and class specific MCA (Le Roux og Rouanet 2010). In particular, class specific MCA (herafter CSA ) is a methodological innovation that allows us not only to explore the relation between the field of power and its subfields, but also to discuss how Bourdieu’s homology thesis may be scrutinized.

 

For more information and access to the article, visit SpringerLink.