Encouraged by Weiwen, I am posting my comments as an answer.
Your unit of analysis is high school? If I understand things correctly, each high school would give rise to 7 race/ethnicity percentages and the 7 percentages would add up to 100%. So you can't add all 7 percentages as control variables in your model, as you would have perfect multicollinearity between them. You could add just 6 of them perhaps and leave one out of the model entirely. Which one you leave out depends on what you are most interested in.
The other thing you could do is to identify a subset of race/ethnicity categories you are most interested in (e.g., white and hispanic ) and define a percentage that reflects that subset (e.g., 60% white + 20% hispanic = 80% white or hispanic). Then you can include that percentage in the model. In that case, you'll be able to control for the combined percentage of white and hispanic students in your modelling.
Or you could use a mixture of percentages: "60% white" and "10% black or hispanic" (as long as they don't add up to 100%). In that case, you'll be able to control for both the percentage of white and the combined percentage of black or hispanic students in your modelling.