Testimony

Data Disaggregation Gives Lawmakers a Full Picture of Communities and Advances Equity


Testimony from NJPP Policy Analyst and State Policy Fellow Marleina Ubel in support of implementing data disaggregation.

Published on Nov 7, 2022 in Immigrants' Rights

Good morning, Chair Beach and members of the committee. My name is Marleina Ubel and I am a policy analyst at New Jersey Policy Perspective (NJPP), a nonpartisan think tank focused on advancing economic, social, and racial justice. Thank you for the opportunity to testify today.

One of New Jersey’s great strengths is its diversity, which, as recent Census data show, continues to grow with increasing Asian American and Pacific Islander populations. To advance equity and effectively allocate resources, policymakers need a full picture of the needs of their residents. But without complete data, especially about New Jersey’s Asian American, Pacific Islander, Middle Eastern, and North African populations, policymakers are in the dark.

Unfortunately, when it comes to health, social services, the criminal legal system, housing, or education, many of the data collected for these populations lumps all of these communities into a single category as “Asian”, “AAPI”, or sometimes simply “Other” or “Unknown.”

These vague categories mask socioeconomic differences between and within national-origin and ethnic groups. The continent of Asia comprises more than half of all people on earth. One catch-all category of “Asian American” fails to capture the diverse backgrounds, let alone the separate experience of Pacific Islanders.

Perhaps the clearest example of the hazards of this one-size-fits-all approach has been the COVID-19 pandemic response. Although Asian Americans overall had lower mortality rates, specific populations, especially Filipino and South Asian national-origin groups, were overrepresented in COVID-19 deaths.

A-3092 would take an important step towards ensuring that when New Jersey policymakers, leaders, and community members look at state-collected data, they are seeing a complete picture, not one that erases entire communities.

Thank you.

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