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Addressing the Achievement Gap: Updates on Poverty Funding Calculations in Oregon

This document presents recent updates to the poverty funding calculation methods used by the Oregon Department of Education to address the achievement gap. It discusses the implications of HB 2098, the use of large district census data, and the challenges faced in accurately determining the poverty levels among school-aged children. The analysis includes case studies from various school districts, specifying how changes in poverty rates directly impact funding, while also emphasizing the importance of accurate data transparency and legislative intent.

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Addressing the Achievement Gap: Updates on Poverty Funding Calculations in Oregon

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  1. Closing the Achievement Gap: Poverty Funding Calculation Update Michael Elliott State School Fund Coordinator Oregon Department of Education Michael.s.elliott@state.or.us

  2. Previous Calculation • HB 2098 • Data Set • Calculations • Case Study • Data Runs Overview of Poverty Calculation

  3. Two Sets of Data: • Large districts (greater than 2,500 ADMr) • Census Data • Change in ADMr Current Data

  4. Small Districts (less than 2,500 ADMr) • Greater of • Census Data (see Large Districts) • Portion of County’s Free and Reduced Lunch count Current Data

  5. Problems • Accuracy • Severity Changes Current Data

  6. Rulemaking Authority • Maintains 0.25 Weight HB 2098

  7. Accurate Data • Generally accessible and accepted data • Use U.S. Census Bureau data HB 2098: Legislative Intent

  8. No additional data collections HB 2098: District Concerns

  9. Transparency • Accuracy HB 2098: ODE Goals

  10. Different Definition • Known underreporting • Accuracy concerns What about Free and Reduced Lunch Data?

  11. U.S. Census Bureau data • http://www.census.gov/did/www/saipe/ • Updated annually • District level data Small Area Income Poverty Estimate (SAIPE)

  12. Statistical Model • SNAP from U.S. Department of Agriculture • IRS Data • American Community Survey data SAIPE

  13. Data provided: • Population of district • Population age 5-17 in district • Population of age 5-17 in families in poverty SAIPE

  14. Start with SAIPE Data • Total Population age 5 to 17 in school district Poverty Calculation

  15. Problem: • Not all children attend public schools • Need accurate population in public schools Poverty Calculation

  16. Solution: • Use ADMr • Percentage of children attending public school Poverty Calculation

  17. 2 Steps: Poverty Calculation

  18. Problem: • Some ADMr to SAIPE 5 to 17 ratios will be greater than 100% • Charter School enrollment • Inter-district transfers • Open Enrollment Poverty Calculation

  19. Solution: • Cap ADMrto SAIPE 5 to 17 ration to 100% • District gets SAIPE maximum • Charter schools receive district percentage Poverty Calculation

  20. Salem Keizer: • SAIPE population age 5 to 17 = 45,269 • ADMr = 37,999.07 • SAIPE Poverty = 12,572 Does this work?

  21. Salem Keizer: • ADMr÷ SAIPE • 37,999.07 ÷ 45,269 = 83.94% • ADMr-SAIPE ratio × SAIPE Poverty • 83.94% × 12,572 = 10,553.01 • Change in weights = 904.66 increase Does this work?

  22. DHS and OHA published report on poverty hotspots • Hotspot is a high concentration of family in poverty Does this work?

  23. Data Used: • Oregon SNAP data • Oregon Employment Data • DHS client data • Available at: http://www.oregon.gov/dhs/ofra/ofradocuments/High%20Poverty%20Hotspots%202013.pdf Does this work?

  24. SAIPE v. Free and Reduced Lunch Does this work?

  25. Two data sets: • 2014-15 v 2014-15 Poverty Change • 2012-13 v 2013-14 ADMw Data Sets

  26. First Data Set • Compares change in poverty • Change in weights • Change in projected funding Data Sets

  27. Second Data Set • ADMw for 2012-13 compared to 2013-14 • Shows extended ADMw interaction with poverty weights • Extended ADMw calculation Data Sets

  28. Outcome #1: Redmond SD • Poverty increased • Total funding increased Data Set #1: 3 Outcomes

  29. Outcome #1: Redmond SD • Poverty increased • Increase of 273.53 to 443.49 • Extended ADMw increased • Increase of 273.53 to 8,166.64 • Increase weights more than loss of $$/wt • Increase of $1,940,717 • $$/wt loss of $336,302 Data Set #1: 3 Outcomes

  30. Outcome #2: Bandon SD • Poverty decreased • Total funding decreased Data Set #1: 3 Outcomes

  31. Outcome #2: Bandon SD • Poverty decreased • Decrease of 14.43 to 36.77 • Extended ADMw remained the same • Increase weights less than loss of $/wt • Same weights • $/wt loss of $38,602.69 Data Set #1: 3 Outcomes

  32. Outcome #3: Corvallis SD • Poverty increased • Total funding decreased Data Set #1: 3 Outcomes

  33. Outcome #3: Corvallis SD • Poverty increased • Increase of 36.4 to 254.93 • Extended ADMw increased • Increase of 0.43 to 7,128.17 • Increase weights less than loss of $/wt • Increase of $3,049 • $/wt loss of $293,965 Data Set #1: 3 Outcomes

  34. Outcome #3: Corvallis Breakdown extended ADMw: • Greater ADMw between 2013-14 and 2012-13 • Charter school ADMw counted separate Data Set #1: 3 Outcomes

  35. Outcome #3: Corvallis Extended ADMw • Non-charter ADMw Difference: 160.20 Data Set #1: 3 Outcomes

  36. Outcome #3: Corvallis Extended ADMw • 2013-14 ADMw has to increase by more than 160.2 to affect funding level Data Set #1: 3 Outcomes

  37. HB 2098: more accurate and up-to-date • SAIPE: district level with annual updates • Calculation: (ADMr/SAIPE Pop)* SAIPE Poverty • 3 outcomes • Next Steps Summary

  38. QUESTIONS?

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