Invisible No More: Campaigning for Asian American, Native Hawaiian, and Pacific Islander data equity

Little is known about the over 40 different ethnic groups comprising the Asian American (AA) community living in New York, despite numbering 1.3 million in New York City. The omission of the different AA ethnic communities in statewide and citywide reports leads to invisibility and masks the unique social, educational, and economic differences associated with diverse AA ethnicities. The Coalition for Asian American Children and Families (CACF) built a campaign on data improvements, convened conversations with its members, and launched the "Invisible No More" campaign. CACF implemented a multi-prong approach which included 1) analysis of existing models, bills, and laws; 2) conversations with colleagues engaged in data equity efforts nationally and in other states; 3) development of tailored messaging for target audiences; 4) a power analysis and identification of champions from the stakeholder and decision maker communities; 5) training for supporters; 5) community mobilization; and 6) creation of a communication plan with supporters. In 2012, CACF and its partners worked with local policymakers to introduce a bill calling for the standardization of data collection and reporting on AAs and Pacific Islanders in state agencies. Later that year, CACF and a NYC council member introduced a similar city bill. In January 2013, new policymakers re-introduced the state bills. The Invisible No More campaign demonstrated the importance in securing early buy-in from diverse stakeholders and implementing best practices from other jurisdictions doing similar work. In addition to applying these lessons learned, the project recommends establishing relationships with power players, particularly state and city agencies, to gain insight on the feasibility; outlining the financial impact of data legislation to ensure that the law would not become an unfunded mandate; and linking legislation to community impact and social justice to personalize data equity and prove it is achievable.