Frédéric Lebaron: Geometric Data Analysis as a Tool for Reflexivity. [Abstract]
In this article, I propose a reflection on the use of geometric data analysis (GDA) as a tool allowing for a higher degree of reflexivity regarding data collection, data analysis, and their sociological interpretation in the case of “social space” studies. I will especially stress the fact that the subject of observation and of analysis can be integrated in the constructed objects dealt with in GDA studies (namely clouds of points). Hence, subjects of observation or analysts can be visualized as projections in a geometric sense in the constructed space(s). This simple geometric technique can allow for a more systematic and relational appraisal of various potential biases at various stages. These biases usually relate to the sociological trajectory – and hence internalized and largely unconscious dispositions – of the analyst, which can also be seen by that way as relational properties in a multidimensional space. I illustrate this epistemological and methodological perspective with examples taken from my proposographical study on the field of French economists and an analysis of European surveys on social inequality.