Earlier quoted context omitted.
It's not impressive if you don't understand statistics I guess. You want to measure the impact of educational policies on students. So you control for other factors that influence educational outcomes, and you try to eliminate those effects. Girls do better than boys on most testing. Asians do better than other races. Free & reduced lunch kids do worse. Special education and ESL students obviously do worse. So of cou…
But unless you control for it very, very carefully, you end up with results like "free and reduced lunch programs cause kids to do worse" - which isn't supported by the evidence, because there may be other factors that coincide with those who are eligible for them. You'd have to do something like take the high-performing SF district and give half the students, randomly selected, free lunches.
Nonsense, you end up with results like "free and reduced lunch programs are correlated with kids who do worse", which they absolutely are!