Back to News

Counted and visible: Global conference on the measurement of gender and intersecting inequalities

New York
Counted and Visible

26-27 February 2020

Conference Room 4, United Nations HQ, New York



The 2030 Agenda pledges to leave no one behind and to ensure that the SDGs are met for all. Leaving no one behind means that the benefits of sustainable development reach everyone. But women and girls who experience multiple and intersecting forms of discrimination are often the furthest behind.

In order to truly leave no one behind and address how gender intersects with other inequalities, we need data to be disaggregated by income, gender, age, race, ethnicity, migratory status, disability, geographic location and other characteristics. But data disaggregation alone is not enough – the specific needs of the most marginalized populations need to be identified, and measured, so that they can inform political discourse and spark necessary change. 

Counted and Visible: The global conference on the measurement of gender and intersecting inequalities will create a common understanding among data users and producers on how to measure intersecting inequalities from a gender perspective in order to ‘leave no one behind.’ It will contribute to current work on data disaggregation to better inform policies and advocacy on gender equality and women’s empowerment. The conference will also be a space for dialogue on gender and intersectionality, to have a better understanding on the needs of the most marginalized groups. 

Speakers and participants: Staff from UN Agencies, government officials, leaders from private foundations and civil society organizations, feminist researchers and economists.

Organizers: UN Women, in collaboration with the UN Statistics Division





 Wednesday, 26 February 2020

 09:00 – 10:00
Registration and check-in
 10:00 - 10:30
Session 1: Welcome and Opening remarks

Opening remarks will be delivered by the Conference co-hosts, UN Women and UN Statistics Division

 10:30 – 11:45
Session 2: What does gender, intersectionality and LNOB mean for realizing the SDGs?

This session will aim to develop a common understanding of what ‘gender’, ‘intersectionality’ and ‘Leave no one behind’ means for measuring and achieving the Sustainable Development Goals.

 11:45 - 13:00
Session 3: From theory to practice – how is gender, intersectionality and LNOB translated into data production and analysis?

This session will explore how data systems and data collection, analysis and dissemination mechanisms are currently set up to prioritize the measurement and reporting of challenges that marginalized groups face, exchange best practices and current limitations of data systems to measure gender, intersectionality and LNOB.

 13:00 - 15:00
Lunch Break
 15:00 – 16:15
Session 4: Missing Figures: Who is being left behind?

This session will be broken into 4 parallel sessions focusing on different vulnerable groups that are traditionally rendered invisible in official statistics. Each session will allow for sharing of country experiences on how to improve data availability on vulnerable populations, analysing challenges, opportunities and good practices.

 16:15 – 16:30
Break *Move to Conference Room 4*
 16:30 – 17:30
Session 5: Plenary session – Completing the picture: Improving Data Availability to leave no one behind

Moderators from the parallel sessions will report back into plenary and open it up to discuss other types of intersecting inequalities not covered, where data is also scare (i.e. race and ethnicity, urban/rural, employment, indigenous groups, individuals with diverse gender identity etc.) Knowing these gaps: how can we operationalize LNOB in data collection and data analysis?

  • Moderator: Haoyi Chen (Intersecretariat Working Group on Household Surveys, UNSD)
 17:30 – 17:45
Closing Remarks


 Thursday, 27 February 2020

 09:30 – 10:00
Registration and welcome
 10:00 – 11:30
Session 6: Data quality, sources, good practices and constraints

This session will explore the opportunities and challenges of gender data disaggregation using different data sources including DHS, Census, administrative data, household surveys etc.

 11:30 – 13:00
Session 7: Filling the Gaps: Does non-official data hold any promise?

This session will aim to explore if there a role for non-official data producers to help fill current data gaps. What needs to happen to ensure that alternative and complementary gender data sources, including qualitative evidence, become a tool for accountability.

 13:00 – 15:00
 15:00 -16:30
Session 8: Gender Data Governance in the Digital Era – what does this mean for LNOB?

In keeping with the human rights principle of ‘do no harm’, data collection exercises should not create or reinforce discrimination, bias or stereotypes against population groups, and objections by these groups should be taken seriously by data producers. How can privacy, confidentiality and data protection be ensured and how can legal frameworks help, particularly in the Digital Era (i.e. Big Data, AI, GIS etc)?

 16:30 - 17:30
Session 9: Translating statistics on gender and intersectionality to actions and positive changes

This session will highlight “stories of change”- examples of how data on gender and intersecting inequalities can be strategically used to inform policies and advocacy on gender equality. What led to success? Is an intersectional perspective also needed when advocating for policy change?

 17:30 - 18:00
Closing remarks

(Part 1) Counted and visible: Global conference on the measurement of gender and intersecting inequalities

(Part 2) Counted and visible: Global conference on the measurement of gender and intersecting inequalities

(Part 3) Counted and visible: Global conference on the measurement of gender and intersecting inequalities

(Part 4) Counted and visible: Global conference on the measurement of gender and intersecting inequalities




Related stories

show filters hide filters

Explore the Data

Learn more about our data resources, why data is missing, and explore our multiple data dashboards to learn more about gender statistics.