The SDGs are a useful tool to measure and compare gender development in and across countries.
Many countries have failed to produce data on the SDGs disaggregated by gender, race, ethnicity, income, and other social characteristics, risking the exclusion of marginalised communities from datasets.
The Asia-Pacific region in particular suffers from data gaps and lack of reliable data overall, as well as disaggregated across gender and other characteristics.
SDGs are criticised for having failed to ‘leave no one behind’ in their exclusion of the LGBTQIA+ community and paying insufficient attention to issues surrounding larger goals.
Indicators are criticised for simplifying complex issues and being removed from the communities they study.
The Sustainable Development Goals (SDGs) are a set of 17 goals which were adopted by members of the United Nations in 2015 to be met by 2030. The 17 goals correspond to a wide range of development goals, from poverty, hunger, access to clean water and sanitation, to decent work and climate action. Goal 5 pertains to achieving gender equality, and includes a broad set of gender-related targets — including valuing care and domestic work, eliminating child and forced marriage and all types of exploitative practices against women and girls, greater participation of women in leadership roles, access to ownership and control over land, using information and communication technology to promote women empowerment, amongst others.1 The SDGs have thus provided a platform to monitor progress on and advocate for a number of interrelated but distinct gender developmental goals.
Several methods and tools have been developed to monitor the global, regional, and national state of gender equality in the SDGs. Developed by Equal Measures 2030, the Gender Advocates Data Hub allows users to measure the state of gender development with relation to 52 targets contained within 14 of 17 SDGs in a total of 129 countries.2 Through the use of data visualisation tools, the platform enables cross-country comparisons and filtering across indicators by thematic areas, and also showcases case studies of women leading advocacy efforts in their communities.3
Despite calls to mainstream gender across all 17 SDGs, only 6 of 17 goals are gender-sensitive, 5 are gender-sparse, while 6 are gender-blind.4 UN Women has identified 54 indicators from the 232 identified in the SDGs that are relevant to gender development.5 The Inter-agency and Expert Group on Gender Statistics (IAEG-GS) has proposed a Minimum Set of Gender Indicators containing 52 quantitative and 11 qualitative indicators endorsed by the 44th session of the UN Statistical Commission (UNSC).6 In their review of the SDGs in 2019, Open Data Watch identifies 73 indicators that require sex disaggregation, and 13 that apply only to women.7 The indicators that should be disaggregated along sex but are currently not include access to amenities such as safe drinking water, electricity, mobile network, and internet.8 The review further finds that many indicators lack the disaggregation that would allow intersectional analysis - race, ethnicity, disability, among others, rarely appear, and sex, income, age and education are not included as often as they should be.9
Countries have failed to measure several outcomes underlying their targets. According to a survey by the UN Statistical Division (UNSD) in 2011, “only 30-40 percent regularly produce sex-disaggregated statistics on topics such as informal employment, unpaid work, entrepreneurship, agriculture, child marriage, violence against women, and access to clean water and/or sanitation, as well as technology”.10 Most of the remaining 60-70 percent “tend not to collect data at all or only infrequently”.11 UN Women finds that adequate data is only available for 10 of 54 gender-specific indicators.12 Often even when data does exist, vulnerable groups such as gender, racial, and ethinic minorities or groups from certain geographical regions are missing from the data.13 In South Asia, for example, unmarried women are more likely to be counted than married women.
Further, only 13 percent of countries have allocated a regular budget for the collection and use of gender data in relation to the SDGs.14 Finally, countries find it difficult to collect new survey data - required for a number of indicators - in expected time periods.15 Poor technical and infrastructural capacities, combined with large populations and cultural diversity in the Asia-Pacific region make it exceedingly difficult to undertake cross-regional comparisons.16
On the subject of closing the digital gender gap as envisaged by targets in the SDG, the World Wide Web Foundation has developed a ‘Digital Gender Gap Audit Scorecard Toolkit’ with support from UN Women.17 This toolkit is an open source framework which includes 14 indicators to empirically measure progress of countries towards closing the digital gender gap until national gender and ICT indicators are developed, and therefore it can be used to fill prevailing gaps in information about women and ICT. 18 Similarly, the ‘Ready to Measure (R2M) Gender Data Query Tool’ developed together by Open Data Watch and Data 2x proposes 20 indicators to begin the process of the measurement of gender equality for the SDGs. 19 This tool also ensures readily available information on gender data, allowing users to identify data gaps and status of girls and women. 20
Since many of the SDG targets reflect articles of the United Nation Declaration on Rights of Indegenous People, data collected specifically for indigenous people can feed into monitoring SDGs from an indigenous people’s perspective. For example, The Indigenous Navigator, a tool for measuring the rights of indigenous people, collects data on 13 thematic domains which represent rights and development of indigenous people, and are also relevant to the SDGs.
The Asia and the Pacific Sustainable Development Goals Progress Report of 2019 by UN ESCAP talks about the progress of Asia Pacific regions towards the Sustainable Development Goals and identifies data gaps with the same.21 Dr. Armida Salsiah Alsjahbana acknowledges that across all the SDG goals, the biggest challenge facing Asia and the Pacific is the lack of reliable data and data gaps. 22 To prepare this report, data was used from the Global SDG indicator database and online databases of custodian agencies and it was found that only 83 out of the 232 SDG global indicators had sufficient data, such a lack of data impedes the assessment of progress. 23
The underlying goal of the SDGs is to ‘leave no one behind’. Despite claims of inclusion, Goal 5 glaring excludes LGBTQIA+ groups, not taking cognizance of discrimination based on sexual orientation and non-binary gender identity.24 Instead, violence and discrimination against LGBTQIA+ groups has been acknowledged in a separate UN statement endorsing end to all such violence to achieve SDGs.25 Problematically, the statement only makes specific reference to health programmes around HIV, risking deepening stigmas around non-conforming groups and ignoring all other dimensions of their development and wellbeing, including achievement of gender equality as set out in Goal 5.26 The treatment of gender as fixed and binary across the SDGs has led to national-level reporting systems producing binary data.27
Although SDGs have been a significant improvement over the Millenium Development Goals, they have faced criticism for providing a set of goals that have inconsistencies and contradictions,28 and are weakly worded allowing governments to draw attention away from political failure and human rights abuse by reporting SDG successes.29 They have also been criticised for being difficult to “quantify, implement and monitor.”30 Individual SDGs have also been critiqued for their inability to capture the issue they aim to address. For example, SDG 3 and 5 take a narrow view of sexual and reproductive health and rights.31 They overlook the availability of safe abortions and access to high quality sexual and reproductive health information for adolocents, men and sexual minorities, as well as the prioritisation of the needs of underserved populations.32
Finally, even though indicators are useful tools to measure progress towards achieving these goals, they are criticised for being reductionist analytical tools and oversimplify complex issues.33 The use of quantified indicators to assess gender development and equality has been critiqued as representing auditing techniques of corporate “management and control”. To address such criticisms, data-driven systems should be designed in ways that are locally useful and empower community-based workers and advocacy groups rather than fulfil agendas of international development actors.34 UN Women further recommends a rights-based approach to data, critically including aspects of community participation, appropriate levels of disaggregation, self-identification, transparency, privacy, and accountability.35