Mapping Ethnic Representation Scores in R

Here’s a demonstration of how easy it is to map with the R package rworldmap by Andy South. I map the ethnic representation scores in my 2009 JLS article, available from my Dataverse. I used the tab-delimited file, which contains the country name, Q-scores, R-scores, and a binary indicator of minority presence. I searched&replaced the tabs with commas, and added a new column for the ISO3 country codes.

After that, it’s just a few lines in R:

library(rworldmap)
dta <- read.csv("Representation.csv") # these are the data described above.

> head(dta) gives:
Country ISO3 QScore RScore Present
1 Afghanistan AFG 0.803 0.697 1
2 Albania ALB 0.980 0.510 1
3 Algeria DZA NA NA 1
4 Andorra AND 0.980 0.000 0
5 Angola AGO NA NA 1
6 Antigua & Barbuda ATG 0.910 0.000 0

Next we have to identify the countries. joinCode specifies that I used ISO3, nameJoinColumn specifies the variable with the country abbreviations:

jcd <- joinCountryData2Map(dta, joinCode="ISO3", nameJoinColumn="ISO3")

Next a line from the package vignette that makes the plot use the space available.
par(mai=c(0,0,0.2,0),xaxs="i",yaxs="i")

Now, while mapCountryData(jcd, nameColumnToPlot="QScore") would suffice to draw a map, I used some of the options available (e.g. a blue ocean, light grey for missing data), and drew the legend separately for a little extra control:

mapParams <- mapCountryData(jcd, nameColumnToPlot="QScore", addLegend=FALSE, mapTitle="Ethnic Representation Scores", oceanCol="light blue", missingCountryCol="light grey")
do.call(addMapLegend, c(mapParams, legendWidth=0.5, legendMar = 4))

The title is a bit off, but other than that, I’m pretty happy for a first cut with so little coding.

ers-map
Ruedin, Didier. 2009. ‘Ethnic Group Representation in a Cross-National Comparison.’ The Journal of Legislative Studies 15 (4): 335–54. doi:10.1080/13572330903302448.

Explaining MIPEX Scores with Patterns of Democracy

I’m always happy to see research published that I hoped to get done ‘one of theses days’. A recent paper in West European Politics uses a sophisticated model to statistically explain immigration policies using patterns of democracy. Different aspects of democracy are associated in different ways, but I’m a bit puzzled by the decision of the authors to downplay the influence of GDP. Perhaps there’s still a difference between political science and sociology after all, and institutional differences count more, so to speak, than for example a modernization thesis.

Wasn’t it already published, I’d include this paper as an example in my recent paper on recombining MIPEX. It’s just one of these instances where aggregated MIPEX scores (and in the supplementary material MIPEX dimensions) are used. Well, if you’re not into recombining MIPEX, a look at a pure reliability assessment of MIPEX might have helped making a slightly stronger case. With just 30 countries, more sensitivity analysis would also help. For instance, is there something about “settler legacies” or is it just Anglosaxon countries with a longer tradition of regulating race and ethnicity — something that MIPEX honours?

Future efforts should make use of the fact that MIPEX data have been collected over time, which makes for stronger conclusions (institutions or otherwise). They may also use theory other than the empirically refuted assumption that proportional systems are good for all kinds of minorities under all circumstance. Irrespective of these quibbles, with the paper by Anita Manatschal and Julian Bernauer we have a good basis to build on.

On Immigrant Backgrounds

In the social sciences and in day-to-day politics we often operate with the concept of immigrant background. It’s a loose concept, and often used without adequate consideration. In the social sciences, we often define anyone who has at least one foreign parent as having an immigrant background. This is systematic, but not the solution.

Following this approach all “mixed” children of one native parent and one foreign parent are considered “foreign”. In some way, that’s akin the one drop of blood used to define what counts as black in the US; a reflection of concerns over purity and boundary-making rather than attempts to create an empirically useful category.

We should simply get away from the idea that a single definition fits all our concerns. Mixed children are native speakers and are fully part of the local culture. The fact that one of their parents is “foreign” is not a deficit, but something they have in addition. This is a different case from having two foreign parents where something (language, attitudes, culture) might be missing. In a different situation, however, having a single foreign parent might be equivalent to having two. For instance, if we’re looking at discrimination, one foreign parent might be a relevant negative marker making the individual more susceptible to discrimination.

Women’s Representation in Multi-Ethnic Countries

A new paper by Leonardo Arriola and Martha Johnson examines women’s representation in multi-ethnic countries. They focus on ministerial appointments to executive cabinets in 34 African countries. They find that fewer women are appointed to cabinets in countries where ethnic groups are more politicized. Although my research focuses on representation in national legislatives, it shows that this mechanism seems to be at work more generally. My research argues that the salience of social divisions is relevant here: sometimes gender differences are relatively more important, sometimes ethnic differences are relatively more important.

In fact, when Arriola and Johnson note that there are more appointments for women in countries where there are more women in the legislature, they hint at the above, but never make it explicit. It is encouraging to see research by others corroborating findings, especially if they use different methods and a different focus.

Arriola, Leonardo R., and Martha C. Johnson. 2013. “Ethnic Politics and Women’s Empowerment in Africa: Ministerial Appointments to Executive Cabinets.” American Journal of Political Science. doi:10.1111/ajps.12075.

Ruedin, Didier. 2010. “The Relationship between Levels of Gender and Ethnic Group Representation.” Studies in Ethnicity and Nationalism 10 (2): 92–106. doi:10.1111/j.1754-9469.2010.01066.x.

Ruedin, Didier. 2013. Why Aren’t They There? The Political Representation of Women, Ethnic Groups and Issue Positions in Legislatures. Colchester: ECPR Press. ISBN: 9780955820397