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    Who killed the knowledge analysts? A short history of Knowledge Working (KW) in a public sector agency

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    Author
    Davenport, Elizabeth
    Rasmussen, Louise
    Issue Date
    2006
    Submitted date
    2006-09-19
    Keywords
    Social Informatics
    
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    Citation
    Who killed the knowledge analysts? A short history of Knowledge Working (KW) in a public sector agency 2006,
    URI
    http://hdl.handle.net/10150/105860
    Abstract
    This is a submission to the "Interrogating the social realities of information and communications systems pre-conference workshop, ASIST AM 2006". The paper is one of a series by the authors that seeks to explain conflicts and contradictions in knowledge management discourse in organisations. The paper presents a study of knowledge networking within a public sector agency (PSA), where a number of knowledge management initiatives have been introduced since the inception of the UK â Modernising governmentâ programme of 1999. The study involves an observant participant (Czarniawska, 2001), as one of the authors has worked in the organisation as a Knowledge Analyst (â KAâ ). The case is an interesting one as it explicates the social and material consequences of a number of utopian KM visions that inspired senior managers in the organisation. For seven years (1999-2006), PSA maintained a knowledge network (the â Knowledge Workingâ (KW) initiative) across its 12 local subsidiary companies â the network was unstable, both a source and an outcome of discursive contests. Our study explores the life and death of this discourse formation, and its associated subject, the KA. A comparable study of a public agency was undertaken by Carter and Scarbrough in 2001, one of several that constitute a research agenda based on the work of Foucault (e.g. 1975) in Information Systems Research recently reviewed by Willcocks (2006). Following Schulze and Stabell, (2004), we identified five main discourse elements: â valueâ , â psychologyâ , â objectâ , â practiceâ and â structureâ . These elements have been used to analyse field data gathered in the past 3 years.
    Type
    Extended Abstract
    Language
    en
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