What defines a good civil servant is not self-evident. In fact, when you ask civil servants what it means “to be a good civil servant” and “to do a good job,” you receive differing responses based on the various values that guide the way each individual approaches their job. The differing values can be traced to well-established perspectives in the literatures of public administration, governance, and political science. Each perspective defines “good government” and “being a good civil servant” in different ways, elevating differing values in the process. These perspectives are institutionalized and internalized in the present-day reality of public administration. Therefore, a present-day civil servant works amid a variety of competing perspectives about what “good government” and “being a good civil servant” mean. It is interesting how various perspectives on “good governance” and “being a good civil servant” play out in the working-practice of civil servants: How do values from the various governance perspectives guide the practical actions of civil servants? To answer this question, we conducted a research project to look for patterns in the values that guide the work of civil servants. We distinguished four governance perspectives from literature on governance. We translated these four governance perspectives into typical value statements that guide practical action, and used Q-methodology to survey civil servants with these perspectives as options. We found four distinct profiles of combined values that apparently guide the practical actions of civil servants. The profiles help us better understand the variety of values that guide practical actions of civil servants.

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The values and opinions of the stakeholders involved in a decision making process are the key to its outcome. Reflection on how stakeholders perceive a situation, and on the consequences of these perceptions for the decision outcome is a intellectually demanding exercise. To support analysts, we have developed a conceptual modeling tool called DANA (Dynamic Actor Network Analysis). The modeling language is based on the policy network paradigm and embodies concepts from cognitive mapping and linguistic approaches to approximate reasoning. In this paper, we investigate how certain interesting properties of stakeholder networks modeled with DANA can be determined algorithmically. Automatic detection of the factors most relevant to a policy situation, and of disagreement and conflict among stakeholders may help the analyst in focussing her 1 analysis.