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.
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.
It’s been in the works for a long time, but I have the pleasure to announce the publication of my monograph.
Why 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.
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):
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.
In his 1993 paper, Richard Matland argues that party magnitude — the district magnitude divided by the number of parties — is causally closer to levels of political representation than the underlying district magnitude. The concept of party magnitude is used from time to time in the literature, but usually little attention is paid as to how it works.
In addition to the effects of district magnitude, assuming that men are more likely to take the top spot of party lists than women are, where there are fewer parties competing, the likelihood that a woman is elected is increased by reaching further down the party list. Combining the two effects, it is also apparent why, as Matland acknowledges, the effects of party magnitude are temporarily limited. The association is weak where the proportion of women in parliament is low. In this case the likelihood of that a woman is elected is low in any case. As the proportion of women in parliament increases, so does the association. Once women are as common as candidates as men are, and they are equally likely to appear at the top of party lists, the association once again decreases. The likelihood that a woman is elected in this case approaches 50%.
Matland, R. (1993). Institutional variables affecting female representation in national legislatures: The case of Norway. Journal of Politics, 55, 737-55.