This paper analyzes the resistance to the neoliberal discourse supporting privatizations in the Italian sociopolitical field: we address the change from a state control over economy to a situation where most of the state owned enterprises are sold and neoliberal principles are widely adopted and accepted. We focus on resistance, which builds on two frames that differ according to the period when they arise, the words they are composed of, the meanings they bear upon. The first one, which is more prevalent in the period 1984-2000, and that we called “values of developmental state”, opposes privatizations from a technical point of view: it is used in quotes that rationally support state intervention in economy. The second frame, that we called “stigma privatizations”, becomes prevalent starting in 2000 and appears mainly in articles that deal with societal issues, literature, movies and the wider sociocultural debate. Here influential speakers blame privatizations as something that eroded societal cohesion. To explain the transformation, we mobilize the concept of capital as described by Bourdieu: as economic capital attached to delegitimized institutions erode, discourse on resistance does not disappear but is framed within the fields that are less dependent on economic capital. As a connected contribution, the key role played by cultural capital in preserving areas of resistances revives the debate on the role of intellectuals within power dynamics as described by Antonio Gramsci. From a technical point of view, we study the evolution of the vocabulary of privatizations by analyzing almost 70.000 articles in the period 1984-2014. we use Topic Modeling, that is an automated text analysis technique that elicits topics, which are the sets of words that constitute discourses. We then reconstruct frames starting from these topics.
Pareschi, L., Mollona, E. (2016). No country for neoliberalism: a topic modeling approach to protean discourses to resist privatizations in Italy. In Working paper series (pp. 1-42). ITA : Department of Management, Università Ca' Foscari di Venezia.
No country for neoliberalism: a topic modeling approach to protean discourses to resist privatizations in Italy
Luca Pareschi;
2016-01-01
Abstract
This paper analyzes the resistance to the neoliberal discourse supporting privatizations in the Italian sociopolitical field: we address the change from a state control over economy to a situation where most of the state owned enterprises are sold and neoliberal principles are widely adopted and accepted. We focus on resistance, which builds on two frames that differ according to the period when they arise, the words they are composed of, the meanings they bear upon. The first one, which is more prevalent in the period 1984-2000, and that we called “values of developmental state”, opposes privatizations from a technical point of view: it is used in quotes that rationally support state intervention in economy. The second frame, that we called “stigma privatizations”, becomes prevalent starting in 2000 and appears mainly in articles that deal with societal issues, literature, movies and the wider sociocultural debate. Here influential speakers blame privatizations as something that eroded societal cohesion. To explain the transformation, we mobilize the concept of capital as described by Bourdieu: as economic capital attached to delegitimized institutions erode, discourse on resistance does not disappear but is framed within the fields that are less dependent on economic capital. As a connected contribution, the key role played by cultural capital in preserving areas of resistances revives the debate on the role of intellectuals within power dynamics as described by Antonio Gramsci. From a technical point of view, we study the evolution of the vocabulary of privatizations by analyzing almost 70.000 articles in the period 1984-2014. we use Topic Modeling, that is an automated text analysis technique that elicits topics, which are the sets of words that constitute discourses. We then reconstruct frames starting from these topics.File | Dimensione | Formato | |
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