MultiRacial Erasure in Academia 3
Ideas for updating the student data for Multiracial Inclusion
UCSD’s Mixed Student Union believe offering a “Multiracial” category should be part of the solution. In fact, in Spring 2021, we (along with my my independent study lab) successfully had the subject pool here in UCSD’s Psych department add a Multiracial option, a disaggregated option for Asian students (so now we have East Asian & South Asian Indian), & an option for Middle Eastern students who previously were left with choosing one of two incorrect answers (Other or White). The research subjects that select Multiracial are shown an additional webpage where they can specify how they identify by selecting pre-chosen items, or typing/ filling in the blank if the preset list isn’t sufficient. Given my lab’s focus on Multiracial research, this was a long awaited update (see image below titled aMorePerfectSONA).
There may be an opportunity to have the data/ IT/ admissions teams update the way they code Multiracial students sometime soon. Thus, having a proposal ready from the start means they’ll know exactly what we’re seeking, they can begin building the new admissions data with the updated format, & it’d be easier than trying to revise it in the future.
Here are a couple of approaches we may propose (reflective of the SONA research solution):
1. Group Specificity List
Create a Multiracial option for all current & future students & have that selection reflected in the demographic information universities publish. Importantly, the Multiracial students in this data should NOT be double counted among the monoracial population.
Thus, if Hogwarts University had 35 monoracial Indian students & 30 monoracial Vietnamese students in Autumn, then enrolls 19 Multiracial Indian-Vietnamese students in Spring, the number of Indian & Vietnamese students shouldn’t increase to 54 & 49 (respectively). The numbers would remain at 35 & 49, and the 19 Multiracial students would be counted as 19 Multiracial students.
2A. Multiracial Specificity List
Create another dataset based on the identities selected from the Multiracial student population. There are two different ways in which this data could be portrayed.
For instance, if a student indicated they are part Hispanic, part Black, & part Filipino, the data could have:
Monoracial Hispanic 2,759 students
Multiracial Hispanic 483 students
Monoracial Black 1,806 students
Multiracial Black 391 students
Monoracial Filipino 617 students
Multiracial Filipino 162 students
As with the Group Specificity List, the monoracial numbers are kept completely separate from the Multiracial numbers.
The way it’s currently done is that the Filipino student population would be counted as 779 students (617+162) without specifying the actual number of Multiracial & monoracial individuals.
This approach would fix that.
This approach means that Multiracial students would be represented by multiple counts within the dataset. For instance, the Black-Filipino-Hispanic student from the previous example would be counted 3 times: once within the Multiracial Filipino group, once within the Multiracial Black group, & once within the Multiracial Hispanic group.
That helps provide an overall count of Multiracial students who happen to be composed of ANY identity.
2B. Specific Multiracial Categories
In addition, it would be nice to have literal Multiracial identities provided. For example
Black-Taiwanese 238 students
Hispanic-White 364 students
Filipino-Hispanic-Indian 17 students
Ensuring that students are counted/ officially included in lists associated with each of their identities ensures that they don’t have a portion of their potential college experience taken from them due to an arbitrary coding system.
Backstory on Multiracial Erasure
“A student who identifies as Black & Hispanic & Japanese on enrollment forms is counted as a monoracial Black student. Their Japanese & Hispanic ethnoracial identities won’t exist & they’ll never be included in batch emails about Hispanic student aid/networking/etc because universities only acknowledge them as Black.
If you’re a MultiRacial Hispanic & Vietnamese & White student, you will never be in the university’s email lists for Vietnamese student organization updates/info because universities only acknowledge you as Hispanic.
If you’re a MultiRacial student of any background → you will never be directed to a plethora of opportunities that would recognize & benefit the fullness of who you are.
Importantly, this isn’t due to malice, hateful prejudice, or any ill-intent. Unfortunately, it’s due to how the coding & reporting of student demographic information is requested by the US Department of Education — an example of which is the Primary Ethnicity Hierarchy. Given that preference at the macro-educational level, the data collected at the micro-educational levels of university systems is going to be coded & structured in a manner that results in the erasure of MultiRacial students. As always, the impact matters more than the intent.
Imagine there was a freshman named Kamala Devi Harris starting college with the class of 2025 this Fall. Given that the Primary Ethnicity Hierarchy places Indian in position #8 & Black in position #1, she would receive all the same emails/ offers/ invites as her monoracial Indian peers because she would only be in the system as a Black student.
She would be at risk of completely missing out on enriching experiences & opportunities as it pertains to her cultural identity as an Indian student.
Thus, if we succeed in this endeavor & more universities change how they report demographic information for multiracial students, it will significantly enrich the college experience of thousands of current students & countless students in the years to come.”
I think this sounds strange to people sometimes, but there SHOULD be networking/ event/ scholarship-grant/ etc opportunities specifically for Multiracial individuals… just like all other groups.
Linguistic Hierarchy of Mate Preferences
It’s not a strong hypergamy pattern (i.e., height & age preferences) but there appear to be some gendered trends worthy of further investigation.
@DrEricDing · Jul 23
ANOTHER EFFICACY DROP — Not good — Israel Ministry of Health just released another vaccine efficacy update due to #DeltaVariant — only 39% Pfizer VE for #COVID19 infection, 40.5% for symptomatic, 88% for hospitalization, 91% for ICU/low oxygen/ death. More — waning efficacy too —
Folks- it’s been a long 2 months of yelling at the CDC on reinstating masks. Thank you those who stood by & supported. We should teach that what is popular is not always right, and what is right is not always popular. It’s not being contrarian — it’s being precautionary. Stay safe.
· Jul 14 — Warning sign
I’m doubling down — @CDCgov most definitely made a *grave mistake* in May dropping mask rules for vaccinated & lending momentum to anti-maskera. I said it before, and I’ll say it again — @CDCDirector needs to reinstate the mask rules to fight #DeltaVariant ASAP!