Today’s installment of “Research you should read” comes to us from Educational Researcher. The paper is “Uneven playing field? Assessing the teacher quality gap between advantaged and disadvantaged students,” and it’s by Dan Goldhaber and colleagues. This is a beautifully done analysis that accomplishes several goals:

1. It quantifies the degree of teacher sorting based on multiple teacher characteristics, including both input (e.g., credentials) and output (e.g., estimates of effectiveness) measures.
2. It examines that sorting across multiple indicators of student disadvantage.
3. It does (1) and (2) for an entire state.
4. It identifies the sources of the inequitable distribution (e.g., is it mostly due to between-school or within-school sorting?).

The results are intensely sobering, if not at all surprising:

We demonstrate that in Washington state elementary school, middle school, and high school classrooms, virtually every measure of teacher quality—experience, licensure exam score, and value-added estimates of effectiveness—is inequitably distributed across every indicator of student disadvantage—free/reduced-price lunch status (FRL), underrepresented minority (URM), and low prior academic performance (the sole exception being licensure exam scores in high school math classrooms).

In short, poor kids, kids of color, and low-achieving kids systematically get access to lower quality teachers, any way you define “quality” [1].

The authors also note that most of the sorting is between schools and between districts, rather than within schools, at least for most of these measures. This is also not surprising, but it of course makes addressing this problem all the more difficult. It’s one thing to reassign teachers within schools (though even that is probably much easier said than done). It’s an entirely different thing to find ways to redistribute teachers across schools or districts without raising the hackles of the broad swath of the electorate who wants government to get their hands off the public education system.

There are undoubtedly many causes of this (frankly, abhorrent) set of findings. The authors list or suggest several:

• Higher-quality teachers are more likely to leave districts serving more disadvantaged kids, likely because of both pay and working conditions.
• Existing pay structures create little incentive to work in more disadvantaged settings (often it’s the opposite–the more disadvantaged districts pay less than the tonier suburban districts).
• Student teaching may contribute to sorting, with the most advantaged districts snatching up the most qualified candidates.
• Collective bargaining agreements often give more senior teachers preference in terms of teaching assignments, which they use to make within-district transfers from more to less disadvantaged schools.
• School leaders may give their best or most experienced teachers within-school preferences in terms of teaching assignments.

These are not easily remedied, but certainly there are policy innovations that might help. The most obvious is that we should pay teachers who teach in more disadvantaged settings more, not less. This certainly is true between districts, but it ought to be true within districts as well. The authors cite evidence that these bonuses can induce desirable behaviors. Another is that we really need to work on the underlying challenges of working in more disadvantaged schools, including working conditions. Several recent studies have shown the powerful influence of working conditions on teachers’ employment decisions and their improvement as professionals.

I do not know whether state or federal policymakers should get involved in this issue. As a big government guy who is concerned about the way our school system treats those who are most disadvantaged, my inclination is to say yes. My hope is that some states can lead the way, creating new laws and systems that, at a minimum, make it equally likely that a poor kid and a rich one in a public school can get access to a good teacher. The status quo on this issue clearly is not working for our most disadvantaged kids.

[1] Of course there could be some other undefined measure of quality that’s not distributed this way, but I’ve not seen any evidence of that.