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Two political science students participate in ICPSR Summer Program

Inter-university Consortium for Political and Social Research (ICPSR), established in 1962 by the University of Michigan Institute for Social Research, maintains a data archive of more than 250,000 files of research in the social and behavioral sciences.

ICPSR’s educational activities include the Summer Program in Quantitative Methods of Social Research, a comprehensive curriculum of intensive courses in research design, statistics, data analysis, and social methodology. The 2020 Summer Program was held online. Two students from the Graduate School of Political Science at Waseda participated in the program.

ICPSR Summer Program Overview
https://www.icpsr.umich.edu/web/pages/sumprog/

 

 

Name: Takahiro Katayama
Affiliation: M2, Graduate School of Political Science
Course: Network Analysis II

My name is Takahiro Katayama of Graduate School of Political Science. I enrolled to GSPS to learn quantitative methods in Security Studies. From 27 July to 13 August, I participated in ICPSR Summer School. I would like to take this opportunity to share some of my experience in ICPSR.

Motivation

My master thesis is on DCA (Defense Cooperation Agreement) and Alliance using Network analysis, and I had been looking for classes and workshops for ERGM (Exponential Random Graph Model), a model which I will be using for Network analysis. I found out that there will be a course on ERGM for ICPSR and that it was going to be online this year due to the COVID-19 outbreak. I had known about ICPSR and have wanted to participate, but due to family reasons, spending 4 weeks in Michigan was not an option. So when I found out that ICPSR was going to take place online this year, I decided to take this golden opportunity.

Course Overview

I enrolled in “Network Analysis II.” The instructor was Olga Chyzh, Assistant Professor of Toronto University. The course covered the fundamentals of ERGM along with other advanced models, such as TERGM, Ego ERGM, Latent Space Model and Local Structure Graph Model. Also, a considerable amount of the time was allocated for Lab, where I was able to obtain hands-on experience on the application of ERGM and other models.  The class was taught using zoom video conference. Due to the time difference, the class took place at midnight in Japan. But a recorded video of the lecture was provided, so I was able to proceed with my own pace.

Networking

I assume that one of the biggest excitement of participating in summer school is you get to meet other students and teachers of the same research field in person. But, obviously, none of these couldn’t be expected this year. Some online meetings for socializing seemed to be held occasionally.

Message for the future participants

ICPSR summer school provides a wide variety of quantitative method classes where you can learn the latest subject matters taught by promising young scholars. Unfortunately, I had to limit myself to only 1 course because I wanted to concentrate on network analysis but there were many other courses that I found interesting. At this point, the format of the next year’s ICPSR is not clear yet. But if it were to be held online, I assume there will be people like myself who are limited to onsite participation but could attend online. If you find a course that is of your interest, I strongly recommend that you attend the ICPSR next year!

Lastly, I would like to express my sincere appreciation to Center for Positive/ Empirical Analysis of Political Economy for their generous support.

 

 

Name: Shusuke Ioku
Affiliation: M1, Graduate School of Political Science
Course: Causal Inference in Social Science/Bayesian Statistics in Social Science (Advanced)

Reason for attending the course
It was recommended by a friend who had taken the course in the past, and I thought it would be a good opportunity to update my knowledge of empirical methods.

What’s so special about the course?
I took a course on causal inference and Bayesian inference. What was particularly appealing to me was that the structure of the courses went beyond the mere impartation of textbook-like knowledge to include the application of each method to the students’ own research. The instructors and TAs often gave us advice on application based on their own experiences, and students were given the opportunity to receive comments on their own research plans. This kind of practical information is very useful in research activities, but it is not always available in textbooks or introductory lectures.

Interaction with other students
Since the class was held online, there were few opportunities to interact with other students before and after the class, which was disappointing. However, there were some efforts to promote interaction between students, such as the courses’ Slack channels where students frankly talk with each other and discuss homework problems. Also, during classes there were some group works with Zoom breakout sessions.

Advantages of online courses
The biggest advantage for me was that I could take the course at home. Of course, there should be a great deal of fun in participating at Michigan, but the ease of not having to make any travel or accommodation arrangements was very comfortable.

A message for future participants
How students can adapt to online learning environment will vary from person to person. But regardless of whether future programs are held online or not, I would still recommend participating if you are seeking an opportunity to gain practical knowledge about relevant methods in our field.

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