The author argues for different methodological preferences for Comparative Political Theory (CPT), a subfield of political theory started by some of the leading political theorists in North America. He describes the need to adopt comparative theorizing because ideas about the Self are usually shaped as a result of an encounter with the Other. He also cites the most basic difference of his work with the mainstream works of CPT and criticizes CPT that is based on the centrality of globalization.
This article extends upon research about the politics of work and the digital mundane. It does this via an ethnographic study I undertook at a digital detox retreat located in North America. At this particular digital detox retreat, participants were invited to relinquish use of their digital devices, discussion of their professions and use of their ‘real names’ for a four-day period. I consider the pertinence of why a detox from the ‘digital’ and from ‘work’ were bound with one another and how the centrality that was accorded to ‘work’ at this retreat was tied in with a cultural framework of the digital mundane. I tie themes iterated in ‘digital detox’ literature with epistemological concerns, highlighting how the signifier of the ‘digital’ allows for an obscuring of high-tech politics and agendas. [ABSTRACT FROM AUTHOR]
Sarkar, Avranil, Fienberg, Stephen E., and Krackhardt, David
Subjects
PROFITABILITY, ESTIMATES, BRANCH banks, SOCIAL networks, EMPLOYEES, REGRESSION analysis, DATA analysis
Abstract
Abstract: The literature on social networks and their analysis has undergone explosive growth in the past decade. Network models have been used to study structures as diverse as the interaction of monks in a monastery, the links across the World Wide Web, and the structure of organizations. In much of this literature the network itself is viewed as the object of interest, and models are used to elucidate its structure. In this paper, we adopt a different perspective and we explore the role of network structure of organizations for prediction purposes. In particular, we work with data gathered on the advice-seeking habits of employees in 52 branches of a major North American bank corporation. We then use the network structure within each branch discovered via various exploratory analyses to predict the profitability of the individual branches. [Copyright &y& Elsevier]