Participation and Democracy
Ross Campbell, PhD
In this module, I will run seven interactive sessions which mimic the flow of how political scientists conduct research on political participation. Each session will take a separate form of participation. We will analyse how many people participate in that form, compare the levels across different countries and political systems and then probe into the factors that influence it.
What technology will we use to do this?
We are going to use an online computational environment that can be accessed from the "launch binder" icon below. After you click on it, you will go into a bespoke learning environment that I created for these sessions. This might take some time to load, possibly 4-5 minutes, depending on the speed of your network. Because of this, it might be tempting to assume it isn't working and try again. Please don't do this. Instead, be patient and you will get there. In all the times I've tried to access the site, it has never failed outright.
The software we'll be using is RStudio and you can fine more information about it here. RStudio is an open-source programme for analysing data and is one of the leading programming languages. You don't need to be a computer programmer; I've written the code for you and will show you how to execute it.
What data will we use?
This course uses an abbreviated verison of the European Social Survey. The survey is too big to use in full, so I've reduced the number of countries and variables to make it more accessible. As you'll see when we look at the questions it asks, it is a really good data source to investigate how and why people participate in politics. Rather than just ask questions, in this module we want to get some answers.
You can find out more about the survey here
Why are we using data?
This is not a course on statistics and students do not need to have mathematical skills to complete the lab exercises. But surveys frequently include data on forms of political participation, and this can provide helpful, but qualified, answers to the questions guiding this module. Most commonly, these surveys come in cross-national form; i.e., they are collected in multiple countries simultaneously. This enables us to examine and compare levels of participation in regions within countries, and/or across countries. In doing this, the data contradict your assumptions. The lesson here is to be cautious about approaching this module with assumptions. Not everything that you think is happening is actually happening. Let the data guide you, but be critical of it too.
Do I need to be able to programme?
No - all of the code will be prepared for you and you will be guided in how to run it. You will then get results in tables, graphs and charts. We can discuss what these mean. This is the central point of the sessions: looking at the data for yourself and thinking through what it means. At times, this won't be straight-forward, but such is life in social science.
Where can I get help with R/RStudio?
If you find that you want to build your skills, there are lots of resources for using R and RStudio. All of the following are free of charge:
Presentations on YouTube
Blogs explaining the Tidyverse
Can I run the analyses on my own?
Yes - practice makes perfect! These materials have been produced to develop your knowledge and you should feel free to enter the data environment when you want. This will help you understand more about participation than simply reading someone's evidence - and this is an important part of being a social scientist. For as interesting as books and articles are, you need to examine the evidence on your own at some point. And the skills and techniques you'll acquire in doing so will benefit you in the long-term.