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A methodological framework for policy design & analysis focusing on problem identification & investigation

Teehan, Catherine 2018. A methodological framework for policy design & analysis focusing on problem identification & investigation. PhD Thesis, Cardiff University.
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Abstract

Traditional public policy decision making has been supported with a cyclical framework based on the rational model, first introduced in the 1950s by Harold Lasswell. However, public policy problems are intrinsically complex and are usually inherently multi-disciplinary and critics of the cyclical model call for more holistic approaches to public policy decision making to address this complexity. This means methodologies, tools and techniques that support multiple perspectives, involve multiple stakeholders and require multiple sources of information are essential for the investigation, analysis and support of public policy decision making. The proposed framework presented in this thesis has been developed to address the issues arising when investigating public policy problems. It addresses the complexity and multiplicity that is public policy decision making, concentrating on problem identification and definition. There is a presentation of the existing frameworks for policy decision making and their limitations. It discusses issues with problem recognition and definition and proposes a methodological framework that provides a thorough investigation into the problem domain to identify areas for policy actions, critical information needs and enables simulation and experimentation to identify unintended consequences. Traditional approaches to policy decision making have been criticised for failing to take into account the wealth of information generated and used by the policy process. This has led to the emergence of Policy Informatics as a new field of research. This thesis shows that a methodological framework for policy design and analysis can be created, based on the core concepts of Policy Informatics and Systems Thinking, that more thoroughly investigates the problem space than previous approaches and addresses common issues with problem recognition and definition that exist in more traditional policy decision making frameworks.

Item Type: Thesis (PhD)
Date Type: Submission
Status: Unpublished
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Date of First Compliant Deposit: 22 November 2018
Last Modified: 22 Nov 2018 09:54
URI: http://orca-mwe.cf.ac.uk/id/eprint/116973

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