Limits of Descriptive Representation

Having spent quite a bit on trying to understand political representation, I know how easy it is to forget the wider context. Here I want to highlight just two things.

First, even if the political representation of different groups is a good thing, we mustn’t forget that most political systems do not revolve around ethnic difference or gender, but about economic growth, the availability of jobs, or security and stability more widely.

Second, there’s a paper Robert Goodin that neatly outlines the limits of descriptive representation in representing diversity — whilst maintaining legislatures where deliberation and debate remains possible. While he may not account enough for multiple group membership and the fact that not every legislator needs to take part in every debate, Goodin’s argument is a good reminder to keep in mind the bigger picture: why do we care about political representation? After all, with opinion polls we have a good instrument capturing the preferences of the population…

Goodin, Robert E. 2004. “Representing Diversity.” British Journal of Political Science 34 (3): 453–468. doi:10.1017/S0007123404000134.

Measuring Descriptive Representation

In the last two weeks I had several conversations on how to best measure descriptive representation (i.e. the numerical representation of groups). I treated this in my recent monograph, but also in a conference paper in 2011. In my view, there are three important points: (1) What’s best depends on your research question. (2) It is important to include the population and the representatives. (3) I recommend two measures as follows: Ri / Pi for measuring the representation of a single group (e.g. a specific minority group, or all minorities combined as opposed to the majority population); for the situation at the national level, I prefer the Rose index (1 – 0.5 * |Ri – Pi|) over the Gallagher index (but following recent simulations I have undertaken, less strongly than previously). Ri stands for the proportion of a group among the representatives, Pi for the proportion among the population.

Why Aren’t They There: Additional Figures

There’s always more to say, and many potential figures did not make it into my research monograph on political representation. I have added some additional figures on Figshare. I have added additional plots on the distributions of representation scores in different policy domains, but also included some of the figures in the book, including the theoretical framework of political representation developed in the book.

‘Why Aren’t They There?’ A Study of Political Representation

It’s been in the works for a long time, but I have the pleasure to announce the publication of my monograph.

9780955820397_cvr.inddWhy Aren’t They There? is a comprehensive study of political representation in a cross-national format. It examines the representation of women, ethnic groups, and policy positions in a cross-country comparison.

The book includes an analysis of the representation of women over time, and presents a critical view of the effectiveness of quotas. Using new data on ethnic groups in legislatures, the book is a significant step forward in the analysis of political representation. The representation of issue positions is examined in eight policy domains. The systematic approach of the book allows a ground-breaking examination of how different forms of representation – women, ethnic groups, issue positions – are interlinked.

It examines aspects that are unattainable in studies focusing on only a single form of representation. This results in a comprehensive understanding of political representation, and leads to important and policy-relevant insights for electoral engineering.

Link to ECPR Press | Table of Contents | Sample Chapter

Women in Claims-Making

In the project SOM we use a large media analysis to examine claims-making in the news. I looked at the gender aspect. Since the original data does not record the gender of the claimant, I used the first name of the 200 most common first names and manually assigned the gender.

This gives me 531 claims by women (16%), and 2729 claims by men (84%).

I find significant differences across countries in the proportion of claims made by women (as opposed to men):

Women 23.5% 9.4% 17.2% 24.7% 18.5% 16.9% 5.55%
Men 76.5% 90.6% 82.8% 75.3% 81.5% 83.1% 94.5%

My initial thought was that these differences are just another reflection of the different levels of descriptive representation. This isn’t the case, though (r=0.08):

I also looked at the frames used in political claims; men tend to use identity frames a bit more often, women moral arguments more often and instrumental frames. Instrumental frames are dominant for men and women.