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4 Get on Your Feet, Get Happy: Happiness and the Affective Governing of Young People in the Age of Austerity

  • Deirdre Duffy
Chapter

Abstract

Happiness is a central theme in the current well-being agenda both implicitly—when couched in the language of therapy and ensuring contentment (Ecclestone and Hayes 2009; Brunila 2012)—and explicitly—through the adoption of ‘happiness measures’ and the emergence of Happiness Studies (Ahmed 2007/08). However, this chapter suggests that the happiness agenda, which dominates neo-Liberal well-being discourses, operates not as vague well-intentioned support but as a form of affective governance. The happiness project represents the production and regulation of neo-Liberal subjects through the manipulation of emotion and futurity. The term affective refers to the ‘pre-reflexive and preconscious [...] embodied encounters that influence the capacity of the mind and body to act’ (Pimlott-Wilson 2015, p. 3). This form of governing orients subjects towards objects or ways of being by connecting them to desired emotional states (e.g., joyfulness, pride, happiness) that are felt viscerally before they are subjected to reflection. The actions of subjects are thus pre-consciously governed by the potential possessions or ways of being of the future (Berlant 2011; Staunæs 2011; Sellar 2014; Bjerg 2013). Under neo-Liberal austerity these ‘happy objects’ are principally financial stability, employment and economic success (Ahmed 2007/08)—artefacts of the moral economy. Young people, the chapter proposes, are particularly susceptible to this phenomenon, as their ways of being in the present are already oriented towards ways of being in the future. As a result, the chapter concludes, the promotion of happiness under the discourse of well-being is part of a strategy of both orienting young people towards particular ways of being and, in doing so, regulating young people in the present.

Keywords

Young People European Union Good Life Financial Stability Term Affective 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© The Author(s) 2017

Authors and Affiliations

  • Deirdre Duffy
    • 1
  1. 1.Manchester Metropolitan UniversityManchesterUK

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