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The Biased State of Gender Disaggregated M&E Data

By Guest Writer on December 12, 2016


Recently, we sent out a survey on international development experiences with gender data to help inform the MERL Tech conference. We asked whether international development staff collected it in their work, how they collected it, what they collected and challenges they faced. 138 people responded, offering key insights on the reality of collecting meaningful sex-disaggregated data.

“I am always surprised — and I should not be —that data collection on women and girls is considered an extra, even by people who know better. That is how it is discussed. Women and girls — and boys are considered secondary to men, that is the dominant attitude. “- Survey respondent

The good news is that the survey showed that 96% of respondents collected data on their gender activities, with almost 83% collecting both qualitative and quantitative data. The bad news is that the data collection process is often imperfect and not comprehensive, with 88% of respondents facing challenges in collecting data. The number one barrier to collection was social and cultural barriers, with over 75% of people citing this as the key barrier to gathering useful gender data.

“We should be asking ourselves what we *think* the gender dynamics of the activity might be and then designing data collection to find out what really happened and whether we were right or not.” – Survey respondent.

The challenge with collecting data in a fair and non-partial way is that we don’t know what we don’t know. Too often, only when we are in the midst of data collection does it start to become clear that the process is biased, but at that point it is already too late to adjust survey instruments, budgets and timelines in the data collection process.

However, it is possible the very data we might be looking for already exists. We commonly re-invent the wheel to design questions and instruments, due to the siloed nature in which we work. This means we often overlook the wealth of public resources available in our own sectors (in this case digital development), which could provide a benchmark or landscape of the geography we are looking to research.

Yet, even within the same country, data and definitions can vary greatly. For example, several studies in Bangladesh have found different statistics for women’s mobile access, depending on the particular segment of women, and how they define access (own a mobile, have access to a mobile etc.)

Where the data or standards don’t exist, we’re working towards a solution to make data collection fair, non-partial and non-duplicative. At mSTAR we are developing a toolkit with the Digital Inclusion team at the USAID Global Development Lab to focus explicitly on examining gender and ICT access and use.

The toolkit will provide resources for USAID staff and implementing partners to assess the gender and ICT landscape in any given community, country or region in which they work, and interpret the data for programming. We believe this toolkit will help in the continued effort to move our industry towards unbiased and equal data collection.

While the toolkit will be launched shortly, please do add your additions to the Google sheet in the meantime, feel free to start a tab for your specific sector. Let’s step out of our silos, use resources wisely and share information with each other.

By Katie Highet and Sara Seavey.

Filed Under: Data
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