Photo
Office Location
224 McCone

Email Address
philip.murphy@miis.edu

Phone Number
831.647.4600

Language(s)
Македонски јазик

Philip J. Murphy

Assistant Professor, GSIPM-MAIPS/Mixed-Methods Evaluation,Training & Analysis


Dr. Murphy earned his PhD in Public and International Affairs from the University of Pittsburgh, where he recently held the position of Senior Policy Fellow at the Matthew B. Ridgway Center for International Security Studies. He has taught distance education courses in a Master of Public Policy and Management program targeted at mid-career public and private sector professionals in Macedonia. He has also been an Adjunct Professor at the Graduate School of Public and International Affairs and a visiting faculty member in the Faculty of Public Administration at South East European University, a university in Macedonia that is dedicated to increasing ethnic inclusion and improving the quality of the country’s public higher education.

His research interests include the application and advancement of innovative methods for detecting and discerning “dark” networks and other difficult to identify social, identity, or interest groups. He is particularly interested in the ideas of distributed cognition and shared identity (i.e., shared perceptions, overlapping frames of reference). The ability to identify – or perhaps promote – shared identities in a population, especially those that bridge disparate religious and ethno-cultural communities, holds great promise for enhancing policymaking, increasing stability, and implementing policy in developing and divided societies. He is currently involved in research projects in the fields of network analysis, public health, and security studies.

Expertise

Public Policy, Research Methods, Quantitative Methods, Network Analysis, International Development

Education

Ph.D University of Pittsburgh; MA East Tennessee State University; BS Appalachian State University

Selected Publications

"Knowledge Hub and Inventory of Opportunities."

"Getting it Done: A Brief Overview of Critical Junctures in the Study of How Policy Translates into Practice."

"Public Administration Education in Macedonia: Accelerating the Process."

"Social Policy and International Interventions in South East Europe."

"Models, Methods, and Stereotypes: Efforts to Maintain, Reify, and Create Macedonia's Ethnopolitical Identities and how Research can Move beyond Them."

"Public Policy Analysis and its Importance to Public Administration Reform."

Courses

Courses offered in the past four years.
indicates offered in the current term
indicates offered in the upcoming term[s]

IPSG 8501 / IPOL 8501 - Policy Analysis      

This course introduces students to the theory and practice of policy analysis. Students will be introduced to the stages of the public policy process, including agenda setting, formulation, implementation, and evaluation. Students will also develop basic policy analysis skills, including problem structuring, stakeholder identification, summarization of current policy, development of policy options, elaboration of criteria for selection, and recommendation of course of action. These concepts are illustrated by examples policies that fall within students' range of interests. This course also introduces students to scientific methods that are used as a means for structuring policy inquiry. A series of research approaches and techniques are presented in the context of forecasting, monitoring, and evaluation for the analysis of domestic and international policies.

Fall 2010 - MIIS, Fall 2011 - MIIS, Spring 2014 - MIIS

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IPSG 8504 / IPOL 8504 - Data Analysis for Public Polcy      

The course is an introduction to inferential statistics with an emphasis on Policy Analysis applications. Topics to be covered include sampling, estimation, hypothesis testing, analysis of variance, and simple and multiple regression analysis. The course will also include an introduction to the use of the computer as a tool for data analysis using leading statistical packages, as well as Excel statistical functions.

Fall 2010 - MIIS, Spring 2011 - MIIS, Spring 2012 - MIIS, Fall 2012 - MIIS, Fall 2013 - MIIS, Fall 2014 - MIIS

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IPSG 8565 / IPOL 8565 - Intro to Network Analysis      

This course introduces students to the skills and concepts at the core of a dynamic and rapidly developing interdisciplinary field. Network analytic tools focus on the relationships between nodes (e.g., individuals, groups, organizations, countries, etc.). We analyze these relationships to uncover or predict a variety of important factors (e.g., the potential or importance of various actors, organizational vulnerabilities, potential subgroups, the need for redundancy, social and economic ties, growth within a network, …). Although the security field has received the greatest amount of recent attention (covert or terrorist networks), these tools can offer valuable insight into a variety of disciplines. The combination of – often stunning – visual analytic techniques with more quantitative measures accounts for much of the increasing worldwide popularity of this field.

Course Objectives

At the end of the semester, students will be able to:
Explain and apply a number of the concepts that underpin network analysis Apply concepts such as centrality, brokerage, equivalence and diffusion to network data Critically evaluate structures and substructures within a network Perform a variety of approaches to clustering and cohesion to networks Analyze networks using a variety of software packages

Spring 2011 - MIIS, Spring 2012 - MIIS, Fall 2012 - MIIS, Fall 2013 - MIIS, Fall 2014 - MIIS

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IPSG 8673 - Advanced Data Analysis      

The advanced data analysis course was designed to provide students with the opportunity to expand upon the skills developed in the introductory course (IPSG 8504), and introduce new skills that address a greater range of analytic needs. This is a project-based, applied course. Class discussions will include both how and why to use these tools, with a strong emphasis on policy applications. Among others, the course covers modules on Factor Analysis, Non-Linear Regression, Spatial Analysis and Time Series Analysis, and its design has a strong emphasis on policy applications. Multiple data sets will be used, but students are encouraged to use their own data and background knowledge.

Spring 2013 - MIIS, Spring 2014 - MIIS

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IPSG 9507 - QualitativeDataAnalysisMash-Up      

This lively, hands-on course focuses on analysis of qualitative data. By “data”, we mean interview, focus group, written reports and visual records, hundreds of pages of them. Students will have a choice of qualitative data sets – there is no time in this short course to engage in primary data collection -- and our entire focus will be on a) deciding how to interrogate the data (what is it you wish to know, demonstrate, reveal, test?), b) developing code books and coding, c) inter-coder reliability, and d) a wide variety of analytical approaches you can use, once you have qualitative data reduced and organized. The first seven weeks of the course focus on a-c. Then, during a final weekend workshop, students will engage in hands-on analysis, using techniques introduced rapid fire during the workshop: expect to practice no fewer than 20 qualitative analysis techniques over three days. This course emphasizes the importance of studying/reading high quality qualitative research studies as fundamental to learning – we will dissect one study each week to understand how the researchers put it together – while also emphasizing learning-through-doing, making mistakes, and collaborative analysis (qualitative inquiry is almost always improved through collaboration). Your final product will be a 10-page analysis, due two weeks after the final workshop.

Fall 2014 - MIIS

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MPAG 8507 - QualitativeDataAnalysisMash-Up      

This lively, hands-on course focuses on analysis of qualitative data. By “data”, we mean interview, focus group, written reports and visual records, hundreds of pages of them. Students will have a choice of qualitative data sets – there is no time in this short course to engage in primary data collection -- and our entire focus will be on a) deciding how to interrogate the data (what is it you wish to know, demonstrate, reveal, test?), b) developing code books and coding, c) inter-coder reliability, and d) a wide variety of analytical approaches you can use, once you have qualitative data reduced and organized. The first seven weeks of the course focus on a-c. Then, during a final weekend workshop, students will engage in hands-on analysis, using techniques introduced rapid fire during the workshop: expect to practice no fewer than 20 qualitative analysis techniques over three days. This course emphasizes the importance of studying/reading high quality qualitative research studies as fundamental to learning – we will dissect one study each week to understand how the researchers put it together – while also emphasizing learning-through-doing, making mistakes, and collaborative analysis (qualitative inquiry is almost always improved through collaboration). Your final product will be a 10-page analysis, due two weeks after the final workshop.

Fall 2014 - MIIS

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