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Superintendent says state changes to compensatory revenue counting could undercount some students; district to explore data-match alternatives
Summary
Superintendent Matt told the board the compensatory revenue task force met with New Mexico officials who use state income and benefits data plus census-tract proxies to identify students in poverty; Matt warned that a direct-certification-only state approach risks undercounting reduced-price students and said the district will research available state data matches.
Superintendent Matt updated the board on the compensatory revenue task force’s recent work, including a briefing with New Mexico officials about that state’s method of identifying students for at-risk funding.
"They are using state-level data matches — income tax records and Department of Human Services matches — to identify most students," Matt said, reporting that New Mexico’s approach produced high match rates and left only a very small number of students unmatched. The district’s task force is exploring whether similar data relationships exist in Minnesota and what the legal and technical implications would be.
Matt warned of a potential pitfall if the state moves to a direct-certification-only model for counting students in compensatory funding formulas: districts that historically relied on family-submitted forms and those with many reduced-price students may be undercounted. "I don't think it was a good idea," he said of a direct-certification-only approach, explaining that it can undercount reduced-price students and that multiple measures are more accurate.
Board members discussed the federal requirement to continue collecting family forms even if state counting changes, and Matt noted that changes in federal program eligibility and family participation dynamics (including reluctance to share information with outside agencies) could influence direct certification counts.
The district will continue task force work to inventory state data matches, consult legal and technical partners, and consider multi-measure approaches to ensure compensatory revenue counts are accurate.
