A guiding principle of the 2030 Agenda for Sustainable Development, “leaving no one behind” is one of the main themes of this year’s World Data Forum (19–21 October). Zeroing in on gender statistics in particular, I’d like to focus on three interrelated trends that have emerged in this regard – intersectionality, the environment and technology.
Inequalities often overlap or ‘intersect’ in ways that create and compound deprivation and disadvantage. As such, the specific needs of the most marginalized populations need to be identified and measured so they can inform political discourse and spark necessary change.
However, when the data used to inform policies fail to capture such inequalities, decisions are likely to leave people behind. Put differently, if data are incomplete, responses will be incomplete. It is our duty to ensure this does not happen.
Capturing intersecting inequalities requires disaggregating data by sex, age and other characteristics (class, race, location, disability, educational level, migratory status, etc.) It also means carefully deliberating, choosing topics and asking questions about how different groups of people may be differently affected.The process of deliberating and choosing topics, which must involve participation from marginalized groups, is particularly important yet often missing, making data less relevant.
Even at the best of times, prior to COVID-19, only 31% of gender-specific Sustainable Development Goal (SDG) indicators could be reliably monitored at the global level. If we add characteristics such as age, race or disability, even fewer data are available.
Since the pandemic began, most countries’ regular statistical activities have been disrupted, making it extremely difficult to assess the pandemic’s impact or to target policies accordingly, particularly for the most vulnerable. It is thus critical for governments to collect such data and make it available in a timely manner.
Through our Women Count global programme, UN Women has been working in select countries, including conducting 40 rapid assessment surveys and an additional 30 planned or underway to provide timely data about the impact of COVID-19 on gender equality and women’s empowerment.
Amid the pandemic, we’ve also been producing and compiling data through interactive dashboards and special reports. For example, From Insights to Action reveals that Black women are 4.3 times more likely than white women to die from COVID-19 in the United Kingdom. Yet, it points out that only 60 of 193 countries (31%) are currently reporting data on infections by sex and age to the World Health Organization and even fewer report infections by gender and race or other characteristics. The report also highlights new data on the rise of extreme poverty, which will hit women and girls hardest – especially women in prime reproductive years (ages 25–34).
The UN-Women/UNDP COVID-19 Global Gender Response Tracker which monitors policy measures enacted by governments worldwide to tackle the COVID-19 crisis, highlights that responses so far have failed to fully address the challenges faced by women. While 704 in 135 countries have taken measures to address the crisis-related spike in gender-based violence, only 10 per cent of fiscal and economic measures taken by 130 countries to help businesses weather the crisis support women’s economic security.
There is also precious little data on gender and the environment. Research has shown that women and children are 14 times more likely than men to die during a disaster. According to the 2020 SDG Gender Snapshot, the lack of clean cooking fuels and technologies is causing the premature death of nearly 2 million women a year; and only 21% of UN Climate Change Conference delegations were headed by women in 2019.
Yet, analysis reveals that of the 231 unique SDG indicators, only seven currently measure the connections between gender and the environment explicitly.
To address such data gaps, UN Women and the United Nations Economic and Social Commission for Asia and the Pacific partnered with UN Environment and the International Union for Conservation of Nature to propose an Environment-Gender Indicator Set for Asia-Pacific countries. UN Women and partners have been working to refine the set and develop a model questionnaire for environment-gender surveys, which will be tested in Bangladesh and Mongolia this year. This is a good start.
Still, environmental data with intersectionality is almost nonexistent, despite mounting evidence that climate change, clean water access, forest management and other key sustainable development issues have important gender and intersectional dimensions , including for indigenous communities, migrants and other groups. So, gender-environment data must be further disaggregated, and questions should assess the different impacts for different groups.
Artificial intelligence, Big Data and geographic information systems (GIS) are revolutionizing the way data are collected, analysed and disseminated – often with great insights, cost-savings and time and efficiency benefits.
However, we know that algorithms can be biased, Big Data can be exclusionary, and individuals’ privacy and confidentiality can be violated. New technologies are also raising concerns about safety and privacy, with more women and girls facing cyberviolence and abuse.
In keeping with the human rights principle of ‘do no harm’, another consideration in capturing intersectionality is that data-collectors should not create or reinforce discrimination, bias violence or stereotypes.
To harness technological change to advance gender equality, organizations must carefully consider how to protect the data they collect. Algorithmic transparency, including our ability to scrutinize them to understand underlying assumption, model and data limitations, will also be key. This is all the more important for data on vulnerable or at-risk groups. Greater accountability is needed in this field and legal frameworks such as Europe’s 2018 General Data Protection Regulation can help.
The way forward
The paucity of data on gender and intersectionality requires greater attention, investment and prioritization. We need to ensure that it is a default approach rather than an afterthought. This requires laws and policies to support the production and dissemination of disaggregated data – including on the environment – to ensure that no one is left behind.
Such efforts should also harness the power of new technology, while taking pains to do no harm, and respect and protect people’s data privacy.
Finally, intersectional gender data must be analysed and shared effectively in order to shape policies. It is only through better measurement and evidence that we can start to generate better solutions. And decision-makers must demand and have this evidence in order to use it.