Giving Compass’ Take:
• Jay Cassano reports that students are working to address segregation in NYC’s specialized high schools by creating a new admissions algorithm that accounts for students’ disadvantages.
• Does it make sense to move away from a neutral algorithm? How can these schools best be integrated?
• Learn more about NYC’s specialized schools.
Students rank-pick up to 12 schools, in order of preference. Schools are then allowed to set up screens to filter out students that do not meet their requirements. Most screens include academic performance and standardized test scores, but others judge a portfolio of writing or art, or may include an interview, audition, or some combination thereof. Then schools rank the students they would like to admit.
From there, a matchmaking algorithm does the rest. The New York City high school admissions process was revamped in 2004 when that algorithm, created by three economists, replaced how students were admitted to schools. The algorithm uses game theory to go through “rounds” of matchmaking, guaranteeing that no student ends up at school that is lower on their preferences than another school that would take them, given the students still available to that school. It eliminated so-called “sub-optimal” matches, and one of the creators, Alvin Roth, went on to win a Nobel Prize in economics for his work on the subject.
The problem with that algorithm, students and experts today argue, is that it fails to account for disparities along racial lines. Because students are frequently screened by test scores, in which white and Asian students consistently perform better than black and Hispanic students, it ends up reinforcing existing inequality.
The solution students came up with was to create a new matchmaking algorithm that prioritizes factors highly correlated with race such as a student’s census tract, whether they receive free or reduced-price lunch, and whether English is their second language. Such an algorithm would boost disadvantaged students higher up in the matchmaking process, provided they have already passed a school’s screening process.
“There’s nothing wrong with a neutral algorithm fundamentally, but because we’re overlaying it on a system that’s predicated on racist and classist measurements of our students, it’s just replicating that kind of system,” said Yana Kamlyka, IntegrateNYC’s research director and a current undergraduate student at Cornell. “It’s essential to include equity-prioritizing elements in the process. I think it’s important that our education policies are deliberately anti-racist instead of neutral.”
Read the full article about students working to address segregation by Jay Cassano at FastCompany.
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