Model Minority Myth + Anti-Blackness

What is the “model minority myth” and “good vs. bad immigrant” narrative? The “model minority myth” holds that the AAPI community typically holds a higher degree of socioeconomic success than other racial groups. The “good vs. bad immigrant” narrative holds that a certain segment of immigrants are “good” and “deserving” to be in the U.S. and a certain segment of immigrants are “bad” and often seen as criminals.
Why must we counter these narratives? These narratives position the AAPI community as a racial wedge that pits other communities of color against each other and inhibits our ability to build cross-racial solidarity and coalitions. Especially in a time where the current administration spews hateful rhetoric against Latinx and Muslim immigrants, false narratives have serious implications for everyday people, such as the rise in hate crimes and hate violence and the decrease of refugee resettlement in the US.
Where does the term “anti-Blackness” come from? Why should we fight against it? Anti-Blackness stems from colonial America, where African slaves were forcibly brought to this country and dehumanized. Anti-Black sentiments has been ingrained into the fabric of our country, and these inhuman attitudes have seeped their away into AAPI communities. Anti-Blackness creates racial wedges between people of color, causes complacency amongst the AAPI communities towards the struggles of Black communities, and obstructs meaningful collective solidarity.
What is data disaggregation, and why is it important for the AAPI community? Data disaggregation is the breaking down of data into subcategories, such as ethnic subcategories like Chinese and Indian, to provide more insight in order to plan effective evidence-based actions. Looking at disaggregated data will help policy makers allocate resources to areas, where it is most needed and effective. Data disaggregation shatters the “model minority” myth that is unjustly applied to all AAPIs and is used as a racial wedge between communities of color. Furthermore, data disaggregation enables effective evidence- based policy around the distinct needs of the diverse AAPI communities and identification of specific barriers to access services and resources at the local, state, and federal level.