We live in an age of unprecedented access to data and information. For those who care about the situation of women worldwide, this has been a tremendous boon. A wide variety of sources can be tapped to learn about the challenges women face, from the UN’s Wistat, the World Bank’s GenderStats, the World Economic Forum’s Gender Gap Report, and many others, as well as a plethora of indices such as UNDP’s Gender Inequality Index, the OECD’s SIGI index, and the WomanStats PSOW scale, to list but just a few.
In addition to these more traditional data efforts, we also now have the capability to crowdsource data on what is happening with women in real time. For example, HarassMap in Egypt and the Women Under Siege project receive, report, and map incidents of assault and rape as they occur. The Polaris Project tracks calls and emails to the trafficking hotline in the US, and is capable of generating data in real time, as well. Google has stepped in to help anti-trafficking organizations share and visualize the data they collect.
In fact, there’s so much information that it is time to recognize that there are problems to address. It’s time to be smarter about collecting, compiling, and using data concerning women.
First of all, there are still gaps. For example, you can quickly obtain the number of women holding seats in national legislatures by checking out the Inter-Parliamentary Union’s dataset on the subject. But perhaps you are interested in the number of women in state, local, and municipal governments? Good luck finding such figures. And good luck finding any information on how many women judges there are; the judicial branch get markedly less attention than executive or legislative branches of government. Such statistics should be kept at the national level, but are not. Furthermore, these statistics should be easy to get; there are other persistent gaps in information that we know at the outset will be very hard to collect; data on intimate violence, gender-disaggregated nutrition, percentage of housing titles held by women, average number of hours spent in reproductive labor, and so forth. It’s time to inventory these gaps and develop mechanisms to overcome them.
Second, “data” is not just numbers; there are quite a number of important dimensions of women’s lives that will never be captured quantitatively. One of these dimensions is law; there are still very few informational resources on laws and regulations affecting women. For example, what if you wanted to know the laws on child custody in the event of a divorce in Sri Lanka? Again, good luck. There would be very few sources you would find to consult. The IMPOWR Project is one; WomanStats is another. There appear to be two distinct types of barriers to collecting this information: one is that many of the larger datasets do not handle qualitative information at all--they don’t collect such information on laws affecting women because they feel the very structure of the data does not fit their template. Another barrier is that there is no systematic way to track changes to the law over time, meaning that it will be very difficult for a data project to know when their information has become outdated.
Many other important qualitative dimensions of women’s situation besides law are not generally captured by the large data sets, either. Social mores, social pressure, customs and traditions, implementation and enforcement of the law—you will not find any information on these phenomena in a dataset like GenderStats. There are some datasets that embrace this type of qualitative information—for example, the WomanStats Project—but most do not. The closest that some projects get to this type of qualitative information is through survey data. Survey data is a “quantitative” approach to attitudinal data, because what you are recording is not the attitudes per se, but rather percentages of people surveyed holding a particular attitude. Even so, there are very few survey instruments asking gender questions on a truly cross-national basis: the World Values Survey is one; the DHS surveys are another. The challenge of qualitative data is thus another task needing focused attention.
Third, data is still not informing policy to the degree that it should. Indicators related to women’s situation have not, generally speaking, been used to monitor, benchmark, or evaluate policy. This is beginning to change as governments and organizations at last incorporate indicators on women into their planning and evaluation mechanisms. For example, during the time Hillary Clinton was US Secretary of State, nine gender-relevant indicators were added to the Master Indicator List that State and USAID use to evaluate their own performance. UNWomen has recently prodded the UN Statistical Commission to adopt a set of nine indicators on violence against women as well as 52 additional indicators of women’s economic situation.
Even with this very promising start, there is still more to be done on this front. For example, the first of the nine US indicators is, “Number of laws, policies, or procedures drafted, proposed or adopted to promote gender equality at the regional, national or local level.” This formulation once again is steadfastly quantitative in nature, even though what we would hope to see is some indicator of impact, and not merely of output. It’s always easier to count something countable than analyze situations for real change, but that may not give us the information we really need. For example, if this number went up over the course of a year, does that mean anything has actually changed in a positive direction for women? Afghanistan’s EVAW Law was debated in parliament this past summer—but the debate nearly resulted in the law’s undoing, and the bill had to be pulled from the floor and placed back into committee lest it be completely eviscerated. No doubt this parliamentary debate will “count” towards this indicator, even though the episode suggests a worsening situation for Afghan women’s rights, not an improved situation. This suggests we need to be smarter about the way we develop and use indicators in the policy realm.
Fourth, the data projects’ outputs may not be comparable, in part because of a lack of transparency. Oftentimes it can be very difficult to tell how a score was assigned, or what information was used to make the assignment. In some instances, this is because unidentified country experts were the ultimate arbiter. For example, if one is told that women’s access to land ownership in Albania is 0.50 on a 0-1 scale, it may be hard to discern what information was used to inform the score and even what the score really means. It is also hard to determine how this scoring of women’s land ownership compares with coding of the same concept by other data projects. This situation cries out for a comprehensive inventory and meta-analysis of efforts across projects.
Fortunately, there are some initiatives underway to tackle some of these problems. One is the Data 2X Initiative, announced in 2012, partnering the US State Department, the UN Foundation, and the Hewlett Foundation, which initiative is intended to “address the gap in global sex disaggregated data through a combination of data review and assessment, partnership and advocacy. Improved gender data will guide policy, better leverage investments, and inform global development agendas.” Since stepping down as US Secretary of State, Hillary Clinton has also launched the No Ceilings Project, which will “work with leading technology partners to create a comprehensive and accessible global review that will bring together and widely distribute the best data on the status of women and girls and their contributions to prosperity and security. Advocates, academics and leaders will be able to see the gains we’ve made, as well as the gaps that remain, and access and share this information across platforms in order to design reforms and drive real change.” These are both very promising developments, and we look forward to seeing their efforts unfold.
This is an exciting time to be in the business of collecting and utilizing data on women; even so, it’s also time to work smarter than we have to date. The next few years will bring meaningful progress on the issues raised here, enabling better, more effective policy and programming for women worldwide.
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