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Berkeley law professor tells SF school committee data link school composition and achievement gap
Summary
Professor Goodwin Liu presented research showing correlations between school racial composition and lower API scores and highlighted teacher experience and turnover as likely mechanisms; board members and parents pressed staff for local subgroup analyses and simulations.
Professor Goodwin Liu, a visiting scholar at Berkeley Law, told a San Francisco Unified School District ad hoc student assignment committee in December that district and national research show a strong correlation between a school’s racial composition and its academic performance.
Liu told board members the district is demographically diverse overall but that many individual schools are racially identifiable: “half the schools are around that number are racially identifiable in the district,” he said. He showed district graphs and national studies — including the Moving to Opportunity experiment and a Texas longitudinal study — that he said suggest higher concentrations of Black or Hispanic students correlate with lower Academic Performance Index (API) scores for those student groups.
Liu cautioned that correlation is not causation and said a fuller analysis would require student-level subgroup data. He recommended examining Black and Hispanic students’ outcomes…
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