K. Reed

Last fall I posted an assessment of VCU’s mention in recent studies charting the success of minority students in higher education. 

You can read the full post here, though I’ll quote the relevant passage below. My response to that report was simply: there’s good news and there’s bad news. The good news is I do believe VCU is doing a tremendous amount to support minority students. The bad news is I don’t believe we’re using the right datasets to chart this. To wit:

“African-America” and “Hispanic” offer us somewhat misleading categories either of which might translate to: [racial v cultural] v [racial . cultural]*, where “cultural” might or might not include language considerations, which in the definitional constraints of our study might or might not target one or both groups. Thus a recent immigrant from Nigeria, who might share many of the same learning challenges facing Hispanic students (like language adjustment), runs the risk of being lumped with African American students out of a coincidence of race, which when we take into account racial discrimination in the American educational system might not be entirely inappropriate.

*notation

I chose Nigeria for my example because I have a large number of first and second-generation Nigerian students (followed closely in African nations by students from Ethiopia, Egypt, and Sudan).

The national language of Nigeria, of course, is English. On their language survey, however, my Nigerian students report speaking primarily Bantu or Yoruba for most of their lives. This is true even for those students born  in the US to Nigerian parents, because most young people live most of their lives at home.

These students, I fear, get doubly overlooked in the data: either they are “African-American” and are assumed to fit the pattern of most African-American teens in Virginia (native and home English speakers) or they are seen as immigrants from a nation whose native language is English, as if Nigeria is linguistically analogous to the UK. Usually, datasets treat these students as African American. 

Here’s where things get interesting: there may be reason to believe that first and second generation Nigerian immigrants academically out-perform African-American students who are the descendants of slaves in the US. See coverage from The Houston Chronicle, from The San Francisco Chronicle, and from The New York Times. 

This would mean that even in cases where Nigerian-American students face language barriers that go overlooked they are at an advantage over students whose ancestors are the survivors of slavery (and who are them selves survivors in a very real way).

Let’s jump, for a second, to a piece on the legacy of post-slavery racial segregation by Ta-Nehisi Coats in The Atlantic recently. He writes:

Last night I had the luxury of sitting and talking with the brilliant historian Barbara Fields. One point she makes that very few Americans understand is that racism is a creation. You read Edmund Morgan’s work and actually see racism being inscribed in the law and the country changing as a result. 

If we accept that racism is a creation, then we must then accept that it can be destroyed. And if we accept that it can be destroyed, we must then accept that it can be destroyed by us and that it likely must be destroyed by methods kin to creation. Racism was created by policy. It will likely only be ultimately destroyed by policy. 

This is precisely the problem with university datasets. They see racism as a habit, but they fail to understand it as a creation. For a survey of what the creation of racism means in Richmond (where many of our students are born and raised) glance through the mayor’s anti-poverty report, where you will see one of the nation’s largest wealth-redistribution programs in the practice of red-lining. Red-lining took neighborhoods inhabited by the descendants of slaves and systematically striped them of wealth through discriminatory home finance practices (pgs 27-29). When we talk about “wealth redistribution” in the US, we never talk about that. 

What does this have to do with education? My Nigerian-American students and my African-American students face some of the same challenges (habitual racism) and some different challenges (generational inheritance of racism as educational, financial, zoning, correctional, and health care policy, just for a start). This is not to say Nigerian-American students won’t come to inherit those additional challenges. I fear they will. I just don’t know because I can’t find studies that assess it. Does policy catch up with new immigrants from Africa? Why or not? If so why, if not why not? 

Finally, what should a dataset look like to start to address any of this complexity? We have to decide who we are targeting with Minority Success Programs, and we have to decide how we want them to be impacted. Were I to choose I would chose both Nigerian-American and African-American students, but I would need to first study whether their educational support needs might be different. All the data I read this morning suggests that it is. If it is, I need to measure their success outcomes separately to ensure I’m actually meeting the needs of both students. Of all students, really. 

Much to the dismay of those who would decry language specificity as political correctness, I think the problem has to do with how we categorize, and I think that problem comes from habits of speech. 

——

Coats, Ta-Nehisi. “Good People, Racist People.” theatlantic.com. Atlantic Media. 8 Mar. 2013. Web. 12 Mar. 2013. 

Mayor’s Anti-Poverty Commission. “Mayor’s Anti-Poverty Commission Report.” Richmond City Government (richmondgov.com), 18 Jan 2013. Web. 12 Mar. 2013. 

Me, here.