In the wake of recent murders of Black citizens, like George Floyd, and subsequent protests, there has been a lot of attention being paid to the concept of implicit bias and how to combat it.
There seem to be far fewer people questioning the existence of implicit bias than when Mike Pence was very confused about it at the Vice-Presidential debate. You can see tons of resources about how it affects teachers at We Should Be Obsessed With Racial Equity.
The typical response to dealing with implicit bias in most professions, including in teaching and in police, is through having implicit bias trainings. Unfortunately, research has been pretty clear that any positive impacts of these trainings are all very short-term (see ‘Implicit Bias’ Trainings Don’t Actually Change Police Behavior and Making people aware of their implicit biases doesn’t usually change minds. But here’s what does work).
I think that a lot can be achieved just by collecting data to document disparities that are occurring as a result of bias. And maybe an easy example is police operations, although it can be applied in many settings.
Here’s what Ladson-Billings suggests:
You have to be able to look at your specific and local context, so for these teachers in Green Bay, I told them, “Well, why don’t you guys do this? Why don’t you go back and just pull your data, look at your suspension rates and who’s being suspended, look who’s being assigned to special education, look who gets into advanced placement class, look who’s in honors — just document that, and then share that with each other and say, ‘How do we explain it?’”
In the same interview, Ladson-Billings continues by saying:
People’s explanations will help you understand why certain things are happening. If their explanation is, “Well, you know, we have all these poor kids,” OK, the poverty is not gonna stop next week. Are we saying because the children are poor, they are incapable of X, Y or Z?
Greenwald, on the other hand, moves in a different direction with what he calls “discretion elimination”:
This can be applied when people are making decisions that involve subjective judgment about a person. This could be police officers, employers making hiring or promotion decisions, doctors deciding on a patient’s treatment, or teachers making decisions about students’ performance. When those decisions are made with discretion, they are likely to result in unintended disparities. But when those decisions are made based on predetermined, objective criteria that are rigorously applied, they are much less likely to produce disparities.
I’m not sure how well Greenwald’s suggestion would work in a K-12 environment – we’ve seen how a lack of discretion can result in harm to children with “no-excuses schools.” And the dangers in education of being “data-driven,” instead of being “data-informed,” are well-documented.
And we’ve also seen examples in education of where there has been discretion elimination (for example, restricting suspensions when data shows that African American students are suspended more often), some schools then have just faked data. And others have just called suspensions something else.
If there’s agreement that teachers, particularly White ones, have implicit bias, and there’s agreement that implicit bias trainings aren’t very effective ways to deal with it, and there is agreement that analyzing data to identify how those biases “play-out” is an important next step, what do you think are effective institutional processes to use in order to then act on that data? What are strategies to then have useful conversations about what the data shows?
At our school, under the leadership of our English Department Chair, Antoine Germany, we’ve been analyzing the data and starting those conversations, though COVID-19 interrupted them. I’m sure we’ll re-engage later in the summer and in the fall.
I’m all ears to hear your thoughts.