Data Disaggregation: A Critical Tool for Measuring Success in Eliminating Systemic Racism and Achieving the UN Sustainable Development Goals (SDGs)
Yasmin Hussein, Fordham University
On July 14th, 2022, SPSSI’s UN/NGO team hosted a High-Level Political Forum (HLPF) side event, co-sponsored by the missions of Costa Rica, Mexico, and South Africa. This event was held to address the critical need for disaggregated data as a tool for identifying and eliminating systemic racism that may hamper achievement of the UN Sustainable Development Goals (SDGs). The event was introduced by Dr. Corahann Okorodudu, Co-Coordinator of the Anti-Racism Campaign of the SPSSI UN/NGO Team, moderated by SPSSI President Dr. Linda Silka and included five panelists: H.E. Maritza Chan, Chargé d’Áffaires, A.I. of the Permanent Mission of Costa Rica; H.E. Xolisa Mabhongo, Deputy Permanent Representative of Mission of South Africa; Mr. Edgar Vielma-Orozco, Director General of Sociodemographic Statistics at Mexico’s National Institute of Statistics and Geography (INEGI); Dr. Gay McDougall, Vice Chair of the UN Committee on the Elimination of Racial Discrimination and International Human Rights Expert; and Dr. Mai Phan, an Equity Data Expert at the Toronto Police Services. Closing remarks were provided by Dr. David Livert, SPSSI UN/NGO Main Representative, and Dr. Amanda Clinton, Senior Director of International Affairs, APA.
Each speaker highlighted the importance of disaggregated data to understand how diverse populations were impacted by efforts to address the SDGs. H.E. Chan discussed how, with the use of census data, Costa Rica has worked to provide visibility to issues and inequalities that are not readily visible. Costa Rica passed a law in 2021 to work towards increasing access to employment, education and cultural diversity. This need for increased access to opportunities was echoed by H.E. Mabhongo, who examined the role of racial discrimination in areas such as education and environment as contributors to a generation of disparities. H.E. Mabhongo noted that ending racism is not solely based on changing attitudes, but rather changing the system that separated people and caused these disparities. With the COVID pandemic highlighting the racial inequalities faced by marginalized groups, as noted by Dr. Phan, it is necessary to collect further data and to use such data to enact change, such as the passing of legislation in the province of Ontario in 2016 to address systemic racism and racial barriers.
Despite the need for disaggregated data to eradicate racism, there are still many barriers that preventing action. One such barrier is the measurements used. Mr. Vielma-Orozco discussed the need for proper measurement tools for data collection in order to disaggregate and provide further visibility to marginalized groups. Furthermore, Mr. Vielma-Orozco demonstrated how disaggregated data can yield critical information on distinct populations in targeted geographic areas. Dr. Phan also noted that a key barrier in collecting race-based data is fear that collecting racial data was itself racist, with some preferring racial blindness, but emphasized the need for an active rather than passive approach to anti-racism. For some, the biggest barrier is the lack of awareness for the necessity for this data, as Dr. McDougall explained, and the belief that it is unnecessary, when in actuality, disaggregated, comprehensive data can reveal inequalities and discrimination that marginalized groups are facing, even when it is not readily visible.