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On Consensus, Consensusing and False ConsensusnessHorst, Maja; Irwin, Alan (Frederiksberg, 2010)[More information][Less information]
Abstract: In response to the recent troubled history of risk-related technological development in Europe, one institutional reaction has been to advocate public deliberation as a means of achieving broad societal consensus over socio-scientific futures. We focus on ‘consensusing’ and the expectation of consensus, and consider both their roots and their performative consequences. We argue that consensus should be seen not simply as the absence of disagreement but as a particular political and ideological formation. We consider and explore the Danish model based on the folkelig concept of the common good, before turning to the wider European movement towards consensus-building. As presented here, consensusing becomes a focus for political contestation but also for nation- and institution-building. Rather than evaluating deliberation solely in terms of its short-term instrumental effects, consensusing should also be understood as performative of national and inter-national identity. URI: http://hdl.handle.net/10398/8268 Files in this item: 1
Horst og Irwin 2010.pdf (120.8Kb) -
Madsen, Dorte (, 2010)[More information][Less information]
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Quantifying alignment units with keystroke dataCarl, Michael (, 2009)[More information][Less information]
Abstract: The paper discusses a method to triangulate process and product data. We suggest converting Translog data into a relational format which contains both process and product data. We outline how this representation allows us to retrieve and correlate the various dimensions of the data more easily. The concept of Alignment Unit (AU) is introduced and contrasted with that of Translation Unit (TU). While AUs refer to translation equivalences in the source and target texts of the product data, TUs refer to cognitive entities that can be observed in the process data. With an (almost) exhaustive fragmentation of the source and target texts into AUs, we are able to distribute and allocate the entire set of keystroke data to appropriate AUs. Using the properties of the keystroke data, AUs are quantified in a novel way which enables us to visualise and investigate the structure of translation production on a fine-grained scale. URI: http://hdl.handle.net/10398/8040 Files in this item: 1
keystrokes.pdf (940.0Kb)
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