When They Look at us, They Don't See Future Colleagues

When I look at the cartoon picture for this blog, I'm pretty sure that George Cantor isn't looking at the African native and thinking, "future colleague material!"  Of course, the picture was actually drawn by George Gamow so perhaps it is unfair to pick on Cantor.

As usual, the above short pithy title should be a bit longer and be

"My theory is that when they look at us, they don't see future colleagues."

Also, I need to define terms. The "They" in this context refers to MOST (not ALL) STEM faculty.

This seems to be experimentally self evident based on the past 60 -70 years of data, but I am sure that there are those that would suggest that they tried really hard to make us colleagues, but, alas, we just weren't the quite the right fit. Or something like that.

It's not really a giant mystery as to what the operating mechanism is: 

-We are not their current colleagues.

-So they don't see us as future colleagues. 

-So they don't REALLY invest in us as students 

-So we don't become their future colleagues.

and repeat. 

It's sort of an example of both loops and induction actually.

Of course, this is just my theory, but I have looked at the data and gathered some of my own.

If you are interested, I refer you to my seminal monograph on the topic

https://www.johnerickson.us/teaching-and-researchprojects/researchprojects/the-lightness-dist-in-stem

There are two versions of the doc now. One with math and one without.  On one level, there is nothing earth shattering about some of this. Everybody talks about "the diversity problem in STEM".  In fact, until recently, it's been nauseatingly non-stop.

What is new in this document is the effort to quantify it, and perform a mildly novel analysis and visual representation.

One conclusion that came out of this work is that while underrepresented populations are, not surprisingly, underrepresented, blacks are probably doing significantly worse than Latinx people and Native American populations are also doing really terrible. Finally, all of these groups are doing significantly worse than women, who have made some progress in recent years, but it has mainly been white and Asian women however.

Probably the most genuinely surprising conclusion of my research is that it appears that math may be measurably and significantly worse than other parts of STEM. I actually did not see this coming and figured it was all just equally bad.

This is what we found, but the sample size should be larger so I would encourage other researchers to investigate this.

Note: we don't believe that the subject of math is intrinsically racist. That's ridiculous, and in fact makes no sense, but we do believe that the racist ideas about the abilities of Africans and those in the diaspora fully penetrated the culture of mathematicians more than other subjects apparently and this is nicely illustrated by the picture of Cantor trying to teach an African native to count.

What is a student interested in STEM, especially math, supposed to do with this grim information? These subjects are interesting and these skills are still valuable. Off hand, I would say the following:

• I would suggest that you consider other options outside of academia. There is still plenty of racism in industry, but this will broaden your options.
• As for math in particular, learn as much as you can, as it is almost always useful, but try and find other subjects you are interested in that leverage mathematics so that, again, you have more options.
• Follow up to the previous point. If you have only studied pure math, you might want to add some applied math to the mix as well as programming skills.

If I think of anymore ideas, I will let add them.

Also, on second thought, I would say that maybe the extended title of this post should have been

"My theory is that when they look at us, they don't see future colleagues...or even current colleagues."