Looking beyond the binary: How data for development impacts gender justice?

Description

Assuming that a given database collects the data of individuals with the intent of serving the same group with specific services, then designing this database would require an understanding of this set of individuals. Among the different kinds of data collected about these individuals, suppose only the gender of every individual were to be considered, data collection processes (especially in a developing country) need to collect data about individuals of all genders.

According the UN, in its report titled, “Gender Equality in the 2030 Agenda for Sustainable Development 2018,” there’s no international standard for collecting and measuring gender-identity data. This has resulted in a lack of data about those who are vulnerable to discrimination and inequality because they identify outside the binary genders of male and female. This often translates to a lack of standard at the national level in different countries and the lack of correct data about individuals who may identify outside the binary genders.

“Gendering of Development Data in India: Beyond the Binary” is a qualitative study done by Brindaalakshmi K for the Centre for Internet and Society as part of the big data for development networks backed by the International Development Research Centre (IDRC), Canada. This study looked into the development of data collection initiatives in India to question the inherent assumption that large-scale datasets are the best reference points for designing development solutions such as welfare schemes, especially for marginalized groups like the transgender community.

This study attempted to understand how transgender communities want to be included in state, national, and global enumeration processes so that they can effectively access necessary services and the opportunities of responsible enumeration and representations offered to them by digital technologies.

Using the findings from this study, you’ll look at the gaps in data collection processes, especially for a large-scale process like the census and its effects on designing services and the processes to access these services. With gendering of development data in India as a case study, you’ll explore the design of an identity marker, digitization of the identification process, and the resulting data.

Brindaalakshmi dives into areas such as healthcare, financial services, and education, among others, in which individuals outside the binary genders get excluded due to the lack of an inclusive data collection process. This session seeks to answer some questions including if this lack of inclusion in data collection is limited to public services, if private sector services are more inclusive of all genders, how individuals outside the binary want to be enumerated into different data systems, if digital technologies are the solution to the problems of data exclusion, if digital technologies have really solved the problem of marginalization for a marginalized group, the role privacy plays with such a group, if data systems are stuck in a vicious cycle that emphasizes on the need for more data which only results in more bad quality data, and if this vicious cycle of “the need for data” sidesteps the responsibility of service providers to meet the needs of users and, in case of governments, its citizens.