The Inter Parliamentary Union release a report each year detailing changes in the representation of women across the world. In 2017, women represented 23.4% of all MPs – which is less than half of the proportion of women in the population at large.
While the picture for the last decade shows a positive trend, there is nothing inevitable about ever-increasing representation of women. The IPU report notes that while Albania and France’s representation of women rose by 10% and 12% respectively, other countries saw a decline. Improved representation of women is often a result of decisions deliberately taken to improve representation, rather than being a natural outcome of unstoppable social forces.
One of the pitfalls of international comparisons is that it obscures some of the drivers of good and poor representation. Increased representation of women is often uneven, and concentrated more in some parties rather than others. As Miki Caul points out, international comparisons of relative representation of women overlook “the fact that individual parties vary greatly in the proportion of women MPs within each nation”. Similarly, Lena Wängnerud argues “cross-country studies tend to miss variations between parties within a single system. Variations in the proportion of women to men are even greater across parties than across nations”.
To understand more about this, we’ve built an experimental mini site to examine the roles of parties in driving the representation of women. Using data from EveryPolitician.org (which contains gender and party information for a number of countries), we can explore the respective contributions of different parties to representation of women.
For this it’s not enough to look at the gender ratios of all the parties individually, as those with the best proportional representation of women are often quite small — for instance, the Green Party in the UK has 100% female representation, in the form of its one MP.
Instead, what we look at is the respective contributions to the total gender ratio. For each party we look at how much better or worse the proportional representation of women would be if you ignored that party’s MPs.
For instance in the UK, while the gender ratio of the current House of Commons is around 32%, the Labour Party’s ratio is around 44%. If you take out the Labour Party the representation of women in the House of Common as a whole drops to 23%.
For our purposes, the Labour Party is the UK’s Most Valuable Party (MVP) — ignoring it leads to the largest reduction in the representation of women. For each country, the gap between the ‘gender ratio’ and the ‘gender ratio ignoring the MVP’ gives a new metric of how to understand the gap in gender representation. Where this number is high, it means that the role of individual parties is very important; where it is lower it means that the ratio is not strongly driven by party effects. For instance, the gender ratio in the United States is strongly driven by party effects, while in Bolivia it is not.
Countries with a wide gap between the ‘ratio ignoring the best party’ and ‘ratio ignoring the worst party’ tend to be countries that use majoritarian electoral systems, like the UK. Pippa Norris shows that systems using majoritarian electoral systems tend to have a poorer representation of women than those using proportional representation, but also that there is a lot of variation within each family of electoral systems and “the basic type of electoral system is neither a necessary nor a sufficient condition to guarantee women’s representation”.
Our analysis shows that parties have different levels of agency to improve the overall representation of women depending on the party structure created by the electoral system. Countries that use proportional representation tend to show smaller party effects because there are usually more parties with fewer MPs — and so the ability of any one party to shift the overall representation is reduced. Conversely, in FPTP parliaments with only a few major parties, a large amount of change can happen by only one of these major parties taking measures to improve their internal representation of women.
For example, while Germany’s CDU and the UK’s Conservative party have a similar representation of women at the national level (20.5% and 21.14% respectively), the Conservative party has more than twice the leverage to affect the overall representation of women simply by changing their own policy.
There are limits to using the proportional representation of women as a single measure for the political representation of women. As mySociety’s Head of Research Rebecca Rumbul has previously shown, even bodies with relatively good representation of women like the National Assembly for Wales can then fall down on other areas – with a low proportion of oral evidence to consultations and committees coming from women. While the UK’s Conservative party performs poorly on the proportion of MPs, it has conversely selected more female party leaders and Prime Ministers.
Importantly, looking at the representation of women as a single figure also obscures the important role of social factors as such class or race in shaping which women are represented. Creating a metric for comparison across many different countries is inherently reductive and discards important information about local context in every instance.
Our goal with this website has been to re-complicate the international comparison by moving away from a single national statistic for representation in a way that assigns agency to political actors within each country. Variations among these parties (and international variations in this variation) reflect that representation of currently under-represented groups isn’t a natural fact of life in a given country, but reflects choices made – and that other choices can lead to different outcomes.
This is still a work in progress and we acknowledge there will be holes in how this data has been applied. Lack of gender information for all countries means that some countries that have high representation of women (such as Rwanda) are not addressed. This means that it shouldn’t be taken as a comprehensive ranking — but we hope it is useful as a jumping off point for thinking about the representation of women in parliaments across the world.
We have detailed our methodology here, including known issues with the data. This is an early experiment with the data and we welcome feedback on the website here; or get in touch through the contact details here.
The data the site is built on can be downloaded from everypolitician.org.
A key part of mySociety’s research agenda is understanding how Civic Technology is (or isn’t) helping under-represented groups in society access government services and their representation. In 2015 we released a report Who Benefits from Civic Technology, that explored variations in usage of Civic Tech in various countries and demographics. You can read or download it here.
In this blog post I’m going to talk a bit about how we’ve internally tried to apply our data to understanding the under-representation of women in politics and as users of our services, as well as some interesting things that external researchers have found using our data.
Our EveryPolitician dataset contains information on current (and in some cases historical) politicians for a large number of countries around the world. For a large number of representatives, this includes gender information.
However, a key problem of international comparisons of the representation of women is, as Miki Caul points out, that it “overlooks the fact that individual parties vary greatly in the proportion of women MPs within each nation”. Similarly, Lena Wängnerud argues “cross-country studies tend to miss variations between parties within a single system. Variations in the proportion of women to men are even greater across parties than across nations”.
Fortunately, this is exactly the kind of problem that an international dataset like EveryPolitician is well placed to examine – on Thursday we’ll be using a new mini-site to explore the gender and party information contained in EveryPolitician to give a sense of the international picture and the party-level differences within each country. Stay tuned! Or you can download the data yourself (there are APIs for Python, Ruby and R) and try and beat us to it.
TheyWorkForYou makes it easy to search through the history of what has been said in Parliament, and we make the data (based on the Hansard dataset but more consistently formatted) freely available to download. As essentially a download of a very large amount of text, getting insights from this dataset is a bit more complicated, but potentially very rewarding.
Jack Blumenau has a paper based on TheyWorkForYou data using language to analyse whether appointing female ministers changes how other female MPs participate in debates. Looking at “half a million Commons’ speeches between 1997 and 2017, [he demonstrates] that appointing a female minster increases the participation of women MPs in relevant debates by approximately one third over the level of female participation under male ministers” – and that “female MPs also became more influential in debates under the purview of female ministers […] female ministers respond in a systematically different fashion to the speeches of female MPs.” In this case, influence is a measure of whether the language an individual used is then taken up by others, and this kind of analysis shows how the TheyWorkForYou dataset can be used to demonstrate not just counts of how many women were in Parliament, but the substantive effects of women holding office on the political process.
As Myf talked about yesterday, TheyWorkForYou’s Commons content now extends back to 1918, and so includes every speech by a female MP ever made. We hope this is a useful resource for anyone interested in exploring the history of the representation of women in the UK and have plans for a small project in the upcoming months to show in a simple way how this data can be used (please sign up to our mailing list if you’re interested in hearing about this when it’s completed).
FixMyStreet and WriteToThem
Understanding the under-representation of women is important across our services. Where men and women are experiencing different issues and concerns, imbalances in access (or use of access) potentially lead to differences in resource allocation.
The majority of reports on FixMyStreet.com are reported by men – but to make things more complicated, it’s not just that women make fewer reports, but women report substantively different kinds of reports.
Reka Solymosi, Kate Bowers and Taku Fujiyama investigated FixMyStreet reports and found (by determining gender from names of problem reporters) that different kinds of reports are more likely to be reported by men and women – they suggest that at “first glance it appears that men are more likely to report in categories related to driving (potholes and road problems), whereas women report more in categories related to walking (parks, dead animals, dog fouling, litter)”.
If different kinds of reports are differently gendered, this complicates thinking about how to improve how women use the website – as potential users are having substantially different experiences of problems in the real world well before they interact with the site. We have to engage with the nuance of this kind of finding to understand how to redress issues of access to services.
We’re currently in the process of extending this kind of analysis to our other service. For WriteToThem, we’ve learned that while the majority of people using the service to write to MPs are male (around 60%), this picture is different depending on the level of government – for instance the gender balance for people writing to councils is pretty close to 50/50.
As part of this, we’re investigating whether having the same gender as their representative makes people more likely to make contact. This has some interesting preliminary findings, and we hope to have more to say about this towards the end of the year.
Our research in this area is ongoing, and we’re keen to help people use our data to investigate under-representation – especially where you have expertise or knowledge that we don’t. If you’d like to discuss potential uses of the data please get in touch, or sign up to our mailing list to hear about future research releases.