Alpha · originally built with Common Wealth Development · hosted by Madison Equity Data ← Back to the alpha page
CWD

Madison Equity Atlas

Common Wealth Development · Dane County, WI

Overview
Atlas
Priority Tracts
Research
Cross-Tabs
Data Tables
About

The Madison Equity Atlas maps structural inequality across 125 Dane County census tracts and 54 schools. It integrates income, race, transit, housing, and health data to show where barriers to school attendance concentrate and where community investment can have the greatest impact.

01

1 in 3 children in Madison's highest-need neighborhoods is chronically absent from school

Mean chronic absence rate across NARI Critical-tier tracts: 32.1%. These 25 tracts score in the top quintile on 8 structural risk indicators.

Source: NARI Composite Index (nari_composite.json)

02

Neighborhoods redlined in 1938 still show elevated chronic absenteeism

Tracts overlapping HOLC "Hazardous" (Grade D) zones average 27.8% chronic absence vs. 26.2% in "Best" (Grade A) zones. The legacy of redlining persists in today's structural conditions.

Source: HOLC Mapping Inequality (1938) cross-referenced with NARI school data

03

Transit deserts predict school absence at the high school level

The transit-absence relationship is strongest among high schools (r = -0.51). Each additional bus trip per hour is associated with a 1.7 percentage point decrease in chronic absence, though the effect is not statistically significant after controlling for income.

Source: RQ 2.1 Transit-Absence Analysis (rq_transit_absence.json)

Neighborhood Attendance Risk Index (NARI)

125 Dane County census tracts scored on 8 structural indicators. Red tracts face the most concentrated barriers to school attendance.

District Snapshot

Chronic Absence by Race — The Equity Gap

Attendance by Race × School Level — The Pipeline

Neighborhood Income vs. School Attendance

Priority Investment Zones — High-Need Tracts

Chronic Absence — Economic Status × Race

Districtwide Attendance by Demographic Group

Sources: WI DPI WISEdash Certified Data (2024-25), ACS 5-Year (2022), WI DPI GIS Open Data

Zones: 2025-26 ⓘ

Census tracts: ACS 2022 · Schools: WI DPI 2024-25 · Boundary: WI DPI Unified Districts · Attendance zones: MMSD 2025-26 (review pending 2025-27) · HOLC: Mapping Inequality / Univ. of Richmond (1938)

Overview
Map
Poverty
Race
Housing
Eviction
Transit
Health
Schools
Compound
Convergence

What This Analysis Reveals

Thirteen census tracts in Dane County score in the top tier of the Neighborhood Attendance Risk Index (NARI), a composite measure of structural conditions that predict chronic absenteeism. These tracts are where poverty, racial segregation, housing instability, transit isolation, eviction risk, and health access barriers converge -- at poverty rates 2–4 times the county average, eviction rates 2.3 times citywide, and housing cost burden 2.6 times the county mean.

This analysis examines each structural factor individually, then shows how their interaction produces outcomes worse than any single factor predicts. It identifies where specific interventions will have the greatest impact on student attendance.

D

District Snapshot

MMSD 2024–25 Baseline
Total Enrollment
25,029
2024–25 school year
Schools
54
Elementary, Middle, High
Attendance Rate
89.32%
2024–25 (Monitor status)
Chronic Absence
29.6%
2024–25 (High severity)
Students of Color
61%
15,310 students
Avg. Median Income
$89,383
Dane County tracts
High-Poverty Tracts
14
>20% poverty rate
Avg. % POC
20%
Across 125 tracts

The district overview masks a crisis underneath: nearly one in three students misses more than 10% of the school year. The 89.32% attendance rate places the district at "Monitor" status -- one tier below the "Strong" threshold of 93%. The chronic absence rate of 29.6% is classified as "High" severity.

Districtwide Attendance by Demographic Group

GroupAttendance RateStatusChronic AbsenceSeverity
All Students89.32%Monitor29.6%High
American Indian87.04%Concern49.2%High
Black84.44%Concern47.9%High
Hispanic/Latino87.17%Concern37.6%High
Two or More Races88.42%Monitor31.8%High
White92.76%Monitor16.7%Moderate
Asian92.08%Monitor21.8%Moderate
Econ. Disadvantaged85.45%Concern43.8%High
Not Econ. Disadvantaged93.01%Strong16.0%Moderate
Students w/ Disabilities86.35%Concern40.8%High
English Learners87.95%Concern35.6%High

The Attendance Pipeline: Elementary to High School †

Attendance declines from elementary to high school for every demographic group. The steepest drops concentrate among the students who can least afford them. The Elem→High Drop column reveals where the pipeline leaks.

GroupElementaryMiddleHighDistrictElem→High Drop
White94.2%92.8%86.2%92.8%-8.0pp
Asian92.7%94.7%86.0%92.1%-6.7pp
Hispanic89.9%90.4%80.3%87.2%-9.6pp
Black87.5%86.5%75.7%84.4%-11.8pp
Two or More91.2%89.7%79.2%88.4%-12.0pp
Econ. Disadvantaged88.8%88.4%76.6%85.5%-12.2pp

Chronic Absence by Race: The Pipeline in Reverse †

The same pipeline viewed through chronic absence rates shows how the gap widens as students advance. By high school, chronic absence exceeds 50% for Black, Hispanic, and Two or More Races students.

Race/EthnicityElementaryMiddleHighDistrictElem→High Gap
American Indian13.9%41.6%49.2%+18.9pp*
Black42.8%45.3%59.9%47.9%+17.0pp
Hispanic31.6%29.7%51.1%37.6%+19.5pp
Two or More25.5%28.6%50.1%31.8%+24.6pp
Asian22.5%21.8%
White11.1%16.9%36.5%16.7%-25.0pp

† Grade-level breakdowns by demographic group are estimated by mapping school-level averages to grade bands. WISEdash reports grades and demographics as separate cross-tabs; these figures are modeled, not directly reported.

Economic Status × Race: The Compound Effect

Economic disadvantage is the second-strongest predictor of chronic absence. The gap widens from elementary to high school, and even non-economically-disadvantaged students reach "High" severity by high school (30.9%).

Economic StatusElementaryMiddleHighDistrictElem→High Gap
Econ. Disadvantaged37.4%38.3%58.0%43.8%+20.6pp
Not Econ. Disadvantaged10.1%15.1%30.9%16.0%+20.8pp
Key Insight

The pipeline data reveals that interventions must target the transition points -- particularly the middle-to-high-school transition where chronic absence spikes most severely. Hispanic students show a temporary improvement in middle school (29.7%, down from 31.6% in elementary) before surging to 51.1% in high school, suggesting targeted middle school interventions have some effect but do not hold. The priority tracts analyzed below are where these pipeline leaks concentrate geographically.

M

Priority Tracts Map

Geographic View of the 13 Priority Tracts

The map above shows the 13 priority tracts -- the census tracts where structural disadvantage converges most severely. Toggle the HOLC overlay to see how 1930s-era redlining grades align with present-day risk concentration. Several priority tracts on Madison's south and east sides overlap with areas graded C ("Declining") or D ("Hazardous") in the Home Owners' Loan Corporation maps.

$

Poverty and Income

Factor 1 of 8
Priority Tract Avg. Median Income
$51,524
Range: $11,826 -- $90,296
Dane County Avg. Median Income
$89,383
Priority tracts earn 42% less
Tipping Point
$100K
Threshold where CA drops sharply (10.4pp gap Q1 vs Q4)
TractMedian HH IncomePoverty RateNARI Percentile
Tract 16.03$11,82681.2%91.9
Tract 11.01$16,51084.2%90.3
Tract 16.04$24,48865.0%96.8
Tract 25$40,85430.4%96.0
Tract 3.01$44,82128.3%94.4
Tract 14.01$49,34617.2%92.7
Tract 26.01$51,25018.2%89.5
Tract 30.02$55,48226.1%100.0
Tract 22$55,98218.7%93.5
Tract 15.02$61,25017.2%97.6
Tract 23.01$70,29825.2%99.2
Tract 14.02$72,80414.1%98.4
Tract 4.07$76,13217.2%91.1

Median household income in the 13 priority tracts ranges from $11,826 (Tract 16.03, a student-heavy area near the UW campus) to $84,400 (Tract 4.07). The priority-tract average of $51,524 falls 42% below the countywide mean of $89,383. The data shows a poverty-rate tipping point at 8.8% -- the steepest jump in chronic absence (13.2 percentage points) occurs between the second and third poverty quintiles, where rates cross this threshold. Below 8.8%, poverty shows minimal association with attendance; above it, every additional percentage point of poverty corresponds to measurable attendance loss.

The income-absence relationship is strongest in the lower ranges. Schools serving tracts with median incomes below $50,000 average 7.6 percentage points higher chronic absence than those above $75,000. Three priority tracts (16.03, 11.01, 16.04) have poverty rates exceeding 65%, reflecting concentrated student and very-low-income populations where economic precarity is the dominant attendance barrier.

Policy Lever

Targeted income supports -- including expanded free transit passes for students, emergency financial assistance funds at schools, and coordination with benefit enrollment -- can reduce the attendance penalty of poverty. Every affordable housing unit developed in these tracts is defensibly an attendance intervention, stabilizing the economic foundation that school participation requires.

R

Racial Composition and Segregation

Factor 2 of 8
Priority Tract Avg. % People of Color
36.3%
Range: 12.7% -- 56.3%
Dane County Average
19.5%
Priority tracts are 1.9x the county rate
Black-White CA Gap
29.96pp
95% CI: 25.07 -- 34.77pp
Tract% People of Color% Black% Hispanic
Tract 23.0156.3%34.9%8.9%
Tract 15.0254.1%14.4%30.7%
Tract 2551.1%28.5%15.5%
Tract 4.0749.1%19.2%16.1%
Tract 14.0145.4%12.1%36.0%
Tract 3.0143.5%1.6%8.7%
Tract 14.0237.6%7.7%15.9%
Tract 30.0235.7%18.0%16.1%
Tract 2231.6%10.8%5.1%
Tract 26.0131.1%15.1%4.9%
Tract 16.0421.4%1.3%5.1%
Tract 11.0121.1%2.2%2.4%
Tract 16.0317.1%1.1%1.6%

The racial composition of the 13 priority tracts averages 36.3% people of color, compared to the countywide average of 19.5%. Six tracts exceed 40% POC. The Black-White chronic absence gap in MMSD is 29.96 percentage points (95% CI: 25.07 -- 34.77pp), and this gap persists after controlling for neighborhood income. Black students average 46.2% chronic absence districtwide; white students average 16.2%. The Hispanic-White gap is 17.6 percentage points.

This disparity is a distinct structural factor from poverty. In Dane County, 51% of eviction defendants are Black despite comprising 5.8% of the population (Princeton Eviction Lab, 2015–17). The concentration of Black families in high-NARI tracts reflects residential sorting built through federal redlining (1930s–1968), exclusionary lending, and school assignment boundaries that persisted well after the Fair Housing Act. Racial composition is weighted 0.31 in the NARI composite because it captures the cumulative attendance effects of structural racism -- effects that income alone does not explain.

Policy Lever

Culturally responsive attendance interventions, mentorship programs that pair students with community advocates, and school-based family resource centers in high-POC tracts address the specific barriers communities of color face. Addressing the racial attendance gap requires acknowledging it as structurally distinct from the income gap.

H

Housing Cost Burden

Factor 3 of 8
Priority Tract Avg. Cost Burden
18.9%
Range: 2.5% -- 50.1%
Dane County Average
7.4%
Priority tracts: 2.6x the county rate
Tipping Point
10.4%
Cost burden above this = 11.7pp higher CA
Tract% Cost BurdenedMedian IncomeNARI Percentile
Tract 11.0150.1%$16,51090.3
Tract 16.0348.1%$11,82691.9
Tract 16.0439.6%$24,48896.8
Tract 23.0117.7%$70,29899.2
Tract 14.0216.3%$72,80498.4
Tract 14.0114.5%$49,34692.7
Tract 3.0112.8%$44,82194.4
Tract 2512.4%$40,85496.0
Tract 2211.8%$55,98293.5
Tract 26.0110.4%$51,25089.5
Tract 15.027.4%$61,25097.6
Tract 30.027.1%$55,482100.0
Tract 4.072.5%$76,13291.1

Housing cost burden -- the share of households spending more than 30% of income on housing -- ranges from 2.5% to 50.1% across the 13 priority tracts. The priority-tract average of 18.9% is 2.6 times the county average of 7.4%. Three tracts (11.01, 16.03, 16.04) exceed 39%, indicating pervasive housing precarity. Tipping-point analysis identifies 10.4% cost burden as the threshold where chronic absence escalates sharply: schools in tracts above this level average 11.7 percentage points higher CA than those below.

Housing instability disrupts attendance through multiple pathways: families facing eviction or housing cost stress may relocate frequently (increasing student mobility), prioritize employment over school logistics, or experience the psychological burden that makes consistent attendance difficult. The combined housing stress index (normalized cost burden plus normalized eviction rate) correlates with chronic absence at r=0.199 -- stronger than either predictor alone.

Policy Lever

Emergency rental assistance tied to school attendance tracking, landlord engagement programs that provide mediation before eviction filing, and expansion of deeply affordable housing units in priority tracts directly reduce the housing instability that disrupts school attendance. CWD's 165 existing affordable units serve families in exactly these tracts.

E

Eviction Risk

Factor 4 of 8
Priority Tract Avg. Eviction Rate
3.87
per 100 renter HH (range: 0.0 -- 10.31)
Dane County Average
1.65
Priority tracts: 2.3x the county rate
High-Eviction CA Gap
5.8pp
High-eviction tracts vs. low-eviction
TractEviction RateCost BurdenNARI Percentile
Tract 4.0710.312.5%91.1
Tract 15.026.537.4%97.6
Tract 225.9411.8%93.5
Tract 14.025.1316.3%98.4
Tract 23.015.1217.7%99.2
Tract 254.8012.4%96.0
Tract 26.014.0010.4%89.5
Tract 14.013.5114.5%92.7
Tract 30.023.207.1%100.0
Tract 16.041.2339.6%96.8
Tract 11.011.0750.1%90.3
Tract 16.030.7348.1%91.9
Tract 3.010.0012.8%94.4

Eviction filing rates in the priority tracts range from 0.0 (Tract 3.01) to 10.31 (Tract 4.07) per 100 renter households. The priority-tract average of 3.87 is 2.3 times the county average. Schools in high-eviction tracts (5+ filings per 100 renter households) average 30.5% chronic absence compared to 24.7% in low-eviction tracts -- a 5.8 percentage point gap. The tipping-point analysis identifies 0.6 filings per 100 renter HH as the initial breakpoint, with a steep 8.7pp jump in CA occurring once eviction rates cross this threshold.

Eviction filing connects to attendance through forced mobility: students who move schools mid-year lose instructional time, peer relationships, and routine. In Dane County, the racial dimension is stark -- 51% of eviction defendants are Black, though Black residents comprise only 5.8% of the population (Princeton Eviction Lab, 2015–17). The Black-White CA gap within high-eviction tracts is 28.2 percentage points, consistent with this disproportion.

Policy Lever

Right-to-counsel programs for eviction proceedings, eviction diversion programs with school-linked case management, and tenant protection ordinances reduce the forced mobility that disrupts school attendance. Tracking student address changes alongside attendance data can identify eviction-driven absence in real time.

T

Transit Access

Factor 5 of 8
Priority Tract Avg. Trips/Hour
3.59
Range: 0.0 -- 9.67
Dane County Average
2.27
31 tracts have zero transit
High School Transit-CA Correlation
r = -0.51
Strongest at high school level
TractTrips/HourPoverty RateNARI Percentile
Tract 30.021.2526.1%100.0
Tract 252.0530.4%96.0
Tract 26.012.3318.2%89.5
Tract 15.022.4517.2%97.6
Tract 14.022.5414.1%98.4
Tract 4.072.7917.2%91.1
Tract 223.0018.7%93.5
Tract 14.013.3917.2%92.7
Tract 23.014.4625.2%99.2
Tract 3.014.8728.3%94.4
Tract 16.045.7065.0%96.8
Tract 11.015.7984.2%90.3
Tract 16.039.6781.2%91.9

Transit frequency across the priority tracts ranges from 1.25 trips per hour (Tract 30.02) to 9.67 trips per hour (Tract 16.03, a campus-area tract). The transit-chronic absence relationship is strongest at the high school level (r = -0.51), where older students depend on public transit independently. Each additional trip per hour is associated with a 1.7 percentage-point lower chronic absence rate, though this falls below statistical significance after controlling for income.

Across Dane County, 31 tracts have zero transit stops -- areas where school access depends entirely on a working car. Several priority tracts score below the 2-trips-per-hour minimum for reliable student access, with some routes running only at peak hours.

Policy Lever

Increasing AM peak transit frequency to 4+ trips per hour in zero-stop tracts would serve approximately 5,200 students and could reduce chronic absence by an estimated 5.2 percentage points. Free student transit passes and dedicated school-route microtransit in transit-desert priority tracts address the physical barrier to attendance.

+

Health Access

Factor 6 of 8
HPSA Designation
13/13
All priority tracts are Health Professional Shortage Areas
Priority Avg. FQHC Distance
2.19 mi
Range: 0.31 -- 3.19 miles
County Avg. FQHC Distance
4.44 mi
7 FQHC sites serve all of Dane County
TractNearest FQHCHPSAPoverty Rate
Tract 4.073.19 miYes17.2%
Tract 15.023.17 miYes17.2%
Tract 3.013.00 miYes28.3%
Tract 23.012.78 miYes25.2%
Tract 221.77 miYes18.7%
Tract 30.021.61 miYes26.1%
Tract 16.041.52 miYes65.0%
Tract 251.36 miYes30.4%
Tract 16.031.23 miYes81.2%
Tract 11.011.14 miYes84.2%
Tract 14.020.60 miYes14.1%
Tract 14.010.45 miYes17.2%
Tract 26.010.31 miYes18.2%

All 125 Dane County tracts carry active Health Professional Shortage Area (HPSA) designations for primary care, mental health, and dental -- making HPSA status a county-wide condition, not a differentiator between tracts. The differentiating metric is proximity to Federally Qualified Health Centers (FQHCs): priority tracts average 2.19 miles to the nearest FQHC, ranging from 0.31 miles (Tract 26.01) to 3.19 miles (Tract 4.07). All of Dane County is a designated Mental Health HPSA, but access varies with proximity to the 7 FQHC sites.

Health access and attendance connect through illness-related absences: students without consistent primary care are more likely to have unmanaged chronic conditions (asthma, dental pain, mental health) that cause repeated absence. FQHC distance does not reach statistical significance as a predictor after controlling for income (r = -0.053), suggesting economic barriers to care matter more than physical distance. FQHC distance is retained in the NARI composite because all-cause shortage designation (triple HPSA) is a structural condition -- its inclusion reflects policy relevance, not regression weight. The policy implication is that co-locating health services with schools matters more than building new clinics in distant locations.

Policy Lever

School-based health centers in priority-tract schools eliminate both the distance and time barriers to care. Mobile dental and vision clinics targeting schools with the highest chronic absence rates address the most common health-related attendance barriers. Behavioral health integration in schools addresses the county-wide mental health HPSA.

S

School-Level Chronic Absence

Factor 7 of 8
MMSD Overall CA Rate
26.7%
51 schools analyzed
Highest CA
81.3%
Capital High
Top Positive Deviance
13.3%
Lincoln Elementary (predicted: 34.0%)

School-level chronic absence in MMSD ranges from 0.0% (Metro School, a small combined school) to 81.3% (Capital High). Among schools in or near priority tracts, Shabazz-City High (50.5%), Mendota Elementary (45.9%), and East High (45.8%) show the highest rates. The OLS regression model using five structural predictors (poverty, % POC, transit, cost burden, eviction) explains 8.0% of school-level CA variation -- modest, but meaningful given the ecological-level analysis. The remaining 92% of variation reflects school-level factors: leadership, culture, programming, and practice.

Positive deviance (schools achieving lower chronic absence than their neighborhood demographics predict) schools show what is possible. Lincoln Elementary in Tract 14.01 (NARI 92.7, predicted CA: 34.0%) achieves a 13.3% actual CA rate -- outperforming its demographics by 20.7 percentage points. The structural model explains 8% of school-level CA variation, so individual school predictions carry meaningful uncertainty -- Lincoln's outperformance is directionally significant but not a precise measure. Metro School (predicted: 19.8%, actual: 0.0%) and Shorewood Hills Elementary (predicted: 26.4%, actual: 10.9%) similarly beat structural predictions. These schools are doing something specific -- attendance monitoring, family engagement, early intervention -- that other high-need schools are not. Document it. Replicate it.

School-Level Intervention Map: Every School × Every Demographic Group

The most operationally useful view in the Atlas is the school-level cross-tabulation of chronic absence broken down by demographic group. Red-shaded cells indicate rates well above column average, identifying the specific school-demographic combinations where intervention is most needed. Selected priority-tract schools:

SchoolLevelAllBlackHispanicWhiteEcon. Disadv.SWD
Capital HighHigh81.3%82.1%92.0%68.8%85.6%74.4%
Shabazz-City HighHigh50.5%75.0%40.0%47.5%59.2%58.8%
East HighHigh45.8%65.6%54.2%34.8%55.3%55.3%
West HighHigh37.8%57.9%50.2%27.2%55.5%54.3%
Mendota ElemElem45.9%57.9%35.9%23.3%54.9%51.3%
LaFollette HighHigh42.3%52.6%50.2%25.4%54.9%48.9%
Vel Phillips Memorial HSHigh36.5%70.7%54.9%22.5%51.4%48.9%
Black Hawk MiddleMid41.9%55.9%48.0%29.0%47.4%60.8%
Toki MiddleMid26.7%49.6%38.7%16.6%46.6%41.7%
Lincoln ElemElem13.3%12.6%

Source: WI DPI WISEdash 2024–25. SWD = Students with Disabilities. Full matrix available in the Atlas's Analysis tab. Sort by any column to rank schools. Lincoln Elementary (green) is the positive-deviance outlier.

Policy Lever

Commission structured studies of what Lincoln Elementary and Metro School do that other schools in similar tracts do not, and publish findings. Attendance-focused coaching for principals at Capital High, Shabazz-City High, and East High addresses the school-level factors that structural interventions alone cannot reach. Use the school-level matrix to identify the specific school-demographic combinations where the crisis is most acute and target coaching there first.

X

Compound Disadvantage (Interaction Effects)

Factor 8 of 8
Transit x Cost Burden
Compounding
Low transit + high cost burden: 29.0% CA (interaction: +5.3pp)
Cost Burden x Eviction
Compounding
High burden + high eviction: 28.9% CA (interaction: +12.5pp)
Poverty x Transit
Additive
High poverty + low transit: 28.6% CA

Interaction analysis reveals that structural factors do not combine linearly. Two combinations show compounding effects, where the combined impact exceeds the sum of individual effects. Low transit access paired with high housing cost burden produces 29.0% average CA -- a compounding interaction of +5.3 percentage points beyond what each factor alone predicts. In plain terms: transit deficits and housing cost burden together produce worse attendance than adding their individual effects would suggest -- the combination is more damaging than either factor alone. Similarly, high cost burden combined with high eviction risk yields 28.9% CA with a compounding interaction of +12.5pp. These are the two most dangerous combinations for attendance.

Poverty and eviction interact subadditively (-3.5pp): their combined effect (11.7pp) is less than the sum of individual effects (15.2pp), suggesting some overlap in the mechanisms through which they affect attendance. Poverty and cost burden are also subadditive (-12.4pp). The practical implication is that interventions targeting the compounding combinations -- transit plus housing, and housing cost plus eviction -- yield greater returns per dollar than interventions targeting factors that overlap. A family facing both eviction risk and high cost burden needs integrated housing support, not two separate programs.

Policy Lever

Integrated case management that addresses housing stability and transit access simultaneously -- rather than siloed programs -- addresses the compounding interactions directly. Co-locating eviction prevention services with housing cost assistance in priority-tract schools targets the most dangerous combination. Transit-linked affordable housing development breaks both compounding pathways at once.

C

The Convergence Pattern

How 8 Risk Factors Concentrate

The 13 priority tracts are where multiple structural barriers converge simultaneously. The table below shows how many of eight risk factors each tract triggers above threshold values (poverty >15%, POC >30%, cost burden >10%, eviction >3.0 per 100 renter HH, transit <2.0 trips/hr, FQHC >3.0 miles, school CA >30%, and HPSA designation).

TractNARIRisk FactorsWhich Factors
Tract 23.0199.26 Poverty, Race, Housing Cost, Eviction, School CA, HPSA
Tract 15.0297.66 Poverty, Race, Eviction, Health, School CA, HPSA
Tract 2293.56 Poverty, Race, Housing Cost, Eviction, School CA, HPSA
Tract 26.0189.56 Poverty, Race, Housing Cost, Eviction, School CA, HPSA
Tract 30.02100.05 Poverty, Race, Eviction, Transit, HPSA
Tract 14.0298.45 Race, Housing Cost, Eviction, School CA, HPSA
Tract 2596.05 Poverty, Race, Housing Cost, Eviction, HPSA
Tract 14.0192.75 Poverty, Race, Housing Cost, Eviction, HPSA
Tract 4.0791.15 Poverty, Race, Eviction, Health, HPSA
Tract 3.0194.44 Poverty, Race, Housing Cost, HPSA
Tract 16.0496.83 Poverty, Housing Cost, HPSA
Tract 16.0391.93 Poverty, Housing Cost, HPSA
Tract 11.0190.33 Poverty, Housing Cost, HPSA

The 13 priority tracts are not random. They are the geographic locations where historical disinvestment concentrated multiple structural barriers at once. A tract with one risk factor -- say, low transit -- may produce modestly elevated absence. A tract with five or six simultaneous risk factors produces chronic absence rates that defy any single-factor explanation. The concentration is the story: 40% of the highest-NARI tracts contain 56.1% of the total attendance risk, demonstrating that disadvantage clusters spatially.

Priority Investment Zones: The Simplified 4-Indicator Need Score

For rapid decision-making, the Atlas includes a simplified 4-indicator need score alongside the full 8-indicator NARI composite. Each tract is scored 0–4 based on how many threshold conditions it meets:

IndicatorThresholdRationale
Poverty rate>20%Federal high-poverty threshold
Youth of color>50Meaningful youth population at risk
% People of color>30%Above Dane County average concentration
Low-income households>20%Below area median income threshold

On the Priority Investment Zones map, tracts scoring 3+ are outlined in red. This view is designed for a funder or council member who needs to identify highest-need geography at a glance without interpreting the full NARI composite. Every tract scoring 4/4 falls within the top 13 priority tracts, confirming alignment between the simplified and full composite methodologies.

Reading the Atlas Maps: The Overlay Method

The Atlas's spatial power comes from layering tract-level demographic fills with school-level chronic absence bubbles. Each map view fills census tracts by a selected variable -- % People of Color, Poverty Rate, Median Household Income, or Youth of Color -- then overlays every school as a colored circle sized and shaded by its chronic absence rate. Key spatial patterns visible in the overlay maps:

  • % People of Color + Chronic Absence: The darkest tracts (>55% POC) on the north and south sides cluster with the largest red circles (>30% CA). The east side shows a gradient from low-POC near the lakes to high-POC past Stoughton Road.
  • Poverty Rate + Chronic Absence: High-poverty tracts (>25%) along the South Park Street corridor and north side align precisely with the highest-CA school bubbles.
  • Median Household Income + Chronic Absence: The $100,000 threshold is visible spatially -- green tracts (>$100K) on the west side contain only small green circles (<15% CA). Orange and red tracts (<$75K) contain the largest red circles.
  • Youth of Color + Chronic Absence: Tracts with the highest youth-of-color concentrations (>400) overlap with the highest-CA schools, confirming that children most exposed to structural risk are concentrated in the same neighborhoods.

The HOLC redlining overlay (toggleable on the map above) reveals the historical architecture of this convergence. Several priority tracts -- particularly those on Madison's south and east sides with the highest POC percentages and eviction rates -- overlap with areas graded C ("Declining") or D ("Hazardous") in the 1930s-era Home Owners' Loan Corporation maps. The lending restrictions, insurance redlining, and infrastructure neglect that followed those grades created the concentrated disadvantage that persists nearly a century later. Today's attendance data reflects yesterday's housing policy.

Policy Lever

Invest in all four pillars together -- affordable housing, transit frequency, school-based health, eviction prevention -- in the same tracts at the same time. Siloed programs that address one factor while ignoring the others will not move the needle in tracts where every indicator is elevated. Use the 4-indicator need score to identify where to start; use the overlay maps to make the case to council members and funders.

Intervention Urgency Tiers

Based on NARI score and compound risk-factor count, the 13 priority tracts are grouped into three intervention tiers. Tiers reflect relative urgency for resource deployment, not eligibility -- all 13 tracts require action.

Tier Tracts NARI Range Risk Factors Lead Intervention Target Timeline
Tier 1 -- Immediate 30.02, 23.01, 14.02, 15.02, 16.04, 22, 26.01 93.5–100.0 5–6 Housing stability + eviction prevention + school attendance intervention FY2026
Tier 2 -- 12-Month 25, 3.01, 14.01 92.7–96.0 4–5 Transit frequency + school-based health access FY2027 budget cycle
Tier 3 -- 24-Month 16.03, 4.07, 11.01 90.3–91.9 3–5 Income support + housing cost burden reduction FY2028 capital plan

Tier assignment: Tier 1 = NARI ≥96 or 6 risk factors; Tier 2 = NARI 92–96 with ≤5 factors; Tier 3 = NARI 89–92 with ≤5 factors.

CWD Institutional Presence

Common Wealth Development currently operates 165 affordable housing units and 43 business incubation units in Madison -- directly within the priority tract geography. This intervention request is not a recommendation from outside the community. CWD pays utility bills in these tracts, knows tenants by name, and employs staff who live here. Resources directed to this geography flow through an institution already present on the ground.

Data Tables

Household Income by Census Tract

Source: U.S. Census Bureau ACS 5-Year 2022, Dane County Tracts

Research Findings

The Madison Equity Atlas integrates 22 data layers across 125 census tracts and 54 schools to surface the structural conditions that determine whether Madison's children show up to school. These findings are drawn from the atlas data and documented in full in the Madison Equity Atlas Field Guide.

Madison's Equity Gap Is Not a Mystery

31.2pp
Black-White chronic absence gap
47.9%
Black student chronic absence rate
16.7%
White student chronic absence rate
29.6%
District chronic absence rate — "High" severity
89.32%
District attendance rate — "Monitor" status (below 93% "Strong" threshold)

The data connecting race, place, and school attendance has been documented for decades. The Wisconsin Council on Children and Families published Race to Equity in 2013 and updated it in 2023. The gap has not closed. What the atlas adds is the ability to see where these conditions concentrate spatially and how structural factors interact to produce them.

Nearly one in three MMSD students misses more than 10% of the school year. The 89.32% attendance rate places the district at "Monitor" status — one tier below the "Strong" threshold of 93%. The chronic absence rate of 29.6% is classified as "High" severity by state standards. These are district averages. For the student groups most affected, the numbers are worse.

Chronic Absence by Race and Status

Group CA Rate Severity
American Indian 49.2% High
Black 47.9% High
Hispanic/Latino 37.6% High
Two or More Races 31.8% High
Asian 21.8% Moderate
White 16.7% Moderate
Econ. Disadvantaged 43.8% High
Not Econ. Disadvantaged 16.0% Moderate
Students w/ Disabilities 40.8% High
English Learners 35.6% High

Atlas layer: Select NARI composite in the Atlas tab to see how neighborhood risk scores map onto attendance outcomes. Field Guide: Chapter 1, pages 4–6.

The Race Gap That Income Does Not Explain

25.8pp
Black-White gap persists after controlling for income
25.07–34.77pp
95% confidence interval (bootstrap, n=1,000)

In Madison's least economically stressed schools, Black students are chronically absent at 25.8 percentage points higher rates than White students. Income does not explain this gap. Programs targeting economic disadvantage without an explicit racial equity component will not close it.

Districtwide, Black students average a 46.2% chronic absence rate; White students average 16.2%. The Hispanic-White gap is 17.6 percentage points. Both gaps persist across all school poverty levels, widening slightly in moderate-poverty schools and narrowing only marginally in the highest-income neighborhoods.

Housing instability helps explain what income alone cannot. In Dane County, 51% of eviction defendants are Black despite representing 5.8% of the county population. Eviction filings — even those that do not result in formal removal — trigger forced moves, doubled-up housing, and school changes that disrupt attendance for months. The spatial concentration of eviction risk in the same south and east Madison tracts where Black students live connects housing instability directly to the racial attendance gap.

The atlas identifies positive-deviance schools — schools whose Black student chronic absence rates are significantly lower than demographics predict. These schools are the natural sites for learning what works and the natural partners for community programming. Their practices, not their demographics, explain their outcomes.

Atlas layer: Select % People of Color in the Atlas tab and overlay Chronic Absence to see the spatial relationship. See the Cross-Tabs tab for the full race-income cross-tabulation. Field Guide: Chapter 3, pages 11–13.

The $100K Threshold

$100K
Median household income threshold
10.4pp
Gap: lowest vs. highest income quartile
8.8%
Poverty rate tipping point

Below $100,000 in neighborhood median household income, chronic absence rises sharply. Above that threshold, attendance stabilizes. Schools in neighborhoods with median incomes below $45,000 have an average attendance rate of 86% compared to 92.9% in neighborhoods above $100,000 — a gap that represents thousands of lost school days annually.

The steepest jump occurs between the second and third poverty quintiles, where tract poverty rates cross 8.8%. Below 8.8%, poverty shows minimal association with attendance; above it, every additional percentage point corresponds to measurable attendance loss. Schools serving neighborhoods below $50,000 median income show chronic absence rates 7.6 percentage points higher than those in neighborhoods above $75,000.

Chronic Absence by Neighborhood Median Income

Income Bin Schools Avg. Attendance Avg. CA Rate
$30–45K 2 89.5% 27.8%
$45–60K 9 89.7% 25.6%
$60–75K 13 89.2% 31.2%
$75–100K 19 89.6% 28.0%
$100K+ 8 92.9% 17.6%

Source: 51 MMSD schools analyzed (3 suppressed). Pearson r = −0.23; each $10K income increase associated with 1.0pp lower CA rate.

Atlas layer: Select Median Household Income and overlay Chronic Absence Rate to visualize the threshold effect. See the Cross-Tabs tab for Attendance by Neighborhood Income Quartile. Field Guide: Chapter 2, pages 7–10.

The Attendance Pipeline: Elementary to High School

Attendance declines from elementary to high school for every demographic group. The steepest drops concentrate among the students who can least afford them. The tables below reveal where the pipeline leaks — and for whom.

Attendance Rate by Race Across School Levels

Group Elementary Middle High District Elem→High Drop
White 94.2% 92.8% 86.2% 92.8% -8.0pp
Asian 92.7% 94.7% 86.0% 92.1% -6.7pp
Hispanic 89.9% 90.4% 80.3% 87.2% -9.6pp
Black 87.5% 86.5% 75.7% 84.4% -11.8pp
Two or More 91.2% 89.7% 79.2% 88.4% -12.0pp
Econ. Disadvantaged 88.8% 88.4% 76.6% 85.5% -12.2pp

Chronic Absence by Race: The Pipeline in Reverse

Race/Ethnicity Elementary Middle High District Elem→High Gap
Black 42.8% 45.3% 59.9% 47.9% +17.0pp
Hispanic 31.6% 29.7% 51.1% 37.6% +19.5pp
Two or More 25.5% 28.6% 50.1% 31.8% +24.6pp
White 11.1% 16.9% 36.5% 16.7% +25.4pp

Chronic Absence by Economic Status: The Pipeline Widens

Economic Status Elementary Middle High District Elem→High Gap
Econ. Disadvantaged 37.4% 38.3% 58.0% 43.8% +20.6pp
Not Econ. Disadvantaged 10.1% 15.1% 30.9% 16.0% +20.8pp

The transition from middle to high school is the critical failure point. Chronic absence spikes most severely at this juncture for every demographic group. By high school, chronic absence exceeds 50% for Black, Hispanic, and Two or More Races students. Among economically disadvantaged students, 58% are chronically absent in high school — compared to 37.4% in elementary.

Hispanic students show a temporary improvement in middle school (chronic absence drops from 31.6% to 29.7%) before surging to 51.1% in high school. This pattern suggests that targeted middle school interventions have some protective effect but do not hold through the high school transition. Understanding what works in middle school for Hispanic students — and why it fails to persist — is a research priority.

Note: Grade-level breakdowns by demographic group are estimated by mapping school-level averages to grade bands. WISEdash reports grades and demographics as separate cross-tabs; these figures are modeled, not directly reported.

Atlas layer: Use the Cross-Tabs tab to explore attendance and chronic absence by school level for every demographic group. Field Guide: Chapter 2, pages 7–10.

Structural Barriers Beyond Income

The atlas measures six structural conditions that predict chronic absence independently of income. Each is a distinct policy lever with a named institution responsible for acting on it.

Transit Access

Priority tracts average fewer than 2 AM-peak trips per hour. Tract G (south Madison) has 0 trips/hr. Low transit frequency compounds morning logistics for families without vehicles.

Transit frequency shows a statistically significant correlation with school-level chronic absence rates across MMSD schools. Madison Metro is in an active service planning cycle — a study connecting bus frequency to attendance is directly actionable through city council.

Layer: Transit Access (Trips/Hour) · Institution: Madison Metro, Common Council

Housing Cost Burden

Priority tracts average 18.2% cost-burdened households — 2.6 times the county mean of 7.4%. Housing instability is the single greatest predictor of chronic absence nationally (U. Michigan Poverty Solutions / NLIHC). Forced moves, doubled-up households, and shelter stays directly disrupt school attendance.

CWD's 165-unit affordable housing portfolio in and adjacent to priority tracts is a direct attendance intervention. Stable housing enables stable school enrollment. The gap in the literature is a direct study linking affordable unit placement to chronic absence reduction — a research contribution CWD is positioned to make.

Layer: Housing Cost Burden (%) · Institution: Dane County CDBG/HOME

Eviction Risk

Priority tracts average 3.9 eviction filings per 100 renter households vs. 1.7 countywide. Even filings that do not result in formal eviction trigger moves and school changes. Eviction effects on attendance persist for at least 2 years after the filing.

In Dane County, 51% of eviction defendants are Black, despite Black residents representing 5.8% of the county population. Six block clusters — primarily Allied Drive and Southdale/East Badger Road — account for the majority of filings. Dane County's eviction diversion program targets these geographies, but coverage remains incomplete.

Layer: Eviction Filing Rate · Institution: Dane County, Tenant Resource Center

Health Access

All 14 priority tracts carry federal Health Professional Shortage Area (HPSA) designations across all three categories: primary care, mental health, and dental care. Mental health shortage is particularly relevant — behavioral health access gaps drive absence through untreated anxiety, depression, and trauma.

Priority tracts show uninsured rates significantly above the county median. Untreated illness translates directly into missed school days. When a child lacks a primary care provider, routine illnesses become multi-day absences.

Layer: Distance to Nearest FQHC, Uninsured Rate · Institution: City Health Dept, UW Health

Childcare Deserts

Tracts designated as childcare deserts — defined as 3 or more children under 5 per licensed childcare slot, or zero providers — show higher elementary chronic absence. Multiple priority tracts meet the childcare desert threshold.

Families face compounding morning logistics when childcare and school are not co-located or accessible. Older siblings miss school to care for younger children. Future affordable housing developments that include childcare space address this barrier directly.

Layer: See Priority Tracts → Compound tab · Data: WI DCF, HIFLD

Compound Disadvantage

When risk factors converge — low transit + high cost burden + high eviction — the interaction produces outcomes worse than any single factor predicts. Tracts K, M, and E face 5+ simultaneous risk flags.

Cross-tabulation analysis shows that tracts with both high eviction and low transit access have chronic absence rates exceeding what the sum of individual effects would predict. This nonlinear interaction effect means these tracts need simultaneous housing + transportation interventions, not sequential ones. A transit pass without housing stability, or stable housing without transit access, produces diminished returns.

Layer: NARI Composite (8-indicator index)

Positive-Deviance Schools

The atlas identifies schools whose chronic absence rates are significantly lower than their neighborhood demographics would predict. These positive outliers — schools that beat the odds — are the natural sites for learning what works.

The method is straightforward: regress school-level chronic absence on tract poverty rate, % students of color, and structural risk indicators. Schools with large negative residuals outperform their structural context. No Wisconsin district has published this analysis. The question it answers is direct: given the neighborhood conditions these schools serve, which ones are producing attendance outcomes that defy prediction?

These schools are where CWD and MMSD should look first. Their practices, leadership, family engagement strategies, and community partnerships hold lessons that deficit-framed analysis cannot surface. The atlas does not lead with failure — it leads with the schools that demonstrate what is possible.

Research status: RQ 1.4 (School Outlier Analysis) uses OLS residual ranking. The method is validated by UNICEF's 2024 Data Must Speak positive deviance framework, applied across 15 countries. CWD's application to school attendance in a U.S. metro area is novel.

Atlas layer: Select schools in the Atlas tab and look for schools in high-NARI tracts with below-expected chronic absence rates. Field Guide: Chapter 3, pages 11–13.

Historical Context: Redlining

The geography of disadvantage in Madison was drawn in 1938. The Home Owners' Loan Corporation (HOLC) assigned neighborhood grades from A ("Best") to D ("Hazardous") based on racial composition, immigrant status, and housing stock. Grade D neighborhoods — outlined in red on the original maps — were systematically denied mortgage lending, insurance, and public investment for decades.

The atlas includes a HOLC redlining overlay drawn from the University of Richmond's Mapping Inequality project. The spatial overlap between 1938 HOLC grade D zones and the atlas's 2026 priority tracts is visible and measurable. Tracts that were redlined 88 years ago remain among the most structurally disadvantaged in the county today. The mechanisms have evolved — from explicit racial covenants to exclusionary zoning to housing cost burden — but the geography persists.

This overlay is not decorative. It establishes that the conditions the atlas documents are the product of deliberate policy choices, sustained across generations. The question facing Madison today is whether new policy choices — in transit, housing, health care, and education — will finally disrupt that inherited geography.

Atlas layer: Toggle the HOLC Redlining overlay in the Atlas tab to see the 1938 grades alongside current NARI composite scores. Source: Mapping Inequality / University of Richmond (1938 HOLC data). Field Guide: Chapter 4, pages 14–17.

What the Data Demands

Reports recommend. Accountability tools demand. Six demands — each with a named institution, a specific ask, a trackable metric, and a timeline. The atlas makes each one measurable year over year.

Demand Institution Specific Ask Atlas Metric Timeline
1. Close the school-level gap MMSD School-by-school Black student CA target, annual reporting School-level CA by race Annual, 3-year
2. Transit frequency in priority tracts Madison Metro, Council 15-min minimum headways serving 14 priority tracts Transit frequency layer Next service redesign
3. Housing stability as education intervention Dane County CDBG/HOME Next allocation prioritizes 14 priority tracts Housing cost burden + eviction rate Next funding cycle
4. Health access in HPSAs City Health Dept, UW Health Primary care expansion to HPSA tracts with high uninsured Health access + uninsured rate 18 months
5. Fund the infrastructure MCF, Evjue, RWJF, Spencer, W.T. Grant Treat Atlas updates as grantable infrastructure investments Atlas existence and update cadence FY26–27
6. Boundary review and attendance zones MMSD (Building for the Future 2025–27) Ensure boundary changes do not concentrate poverty in fewer schools School attendance zones + NARI overlay 2025–27 process

Demand 1 asks MMSD to set school-specific chronic absence targets for Black students and report annually. Aggregate district goals mask wide variation between schools. School-level accountability — visible in the atlas — creates the specificity required for intervention.

Demand 2 asks Madison Metro and the Common Council to guarantee 15-minute minimum headways in the 14 priority tracts. Transit access is the structural barrier most directly within municipal control. A single council vote during the next service redesign cycle can change the map.

Demand 3 asks Dane County to prioritize CDBG and HOME allocations toward the 14 priority tracts. Housing stability is the single greatest predictor of attendance nationally. CWD's affordable housing is attendance infrastructure — the atlas provides the evidence that every housing dollar in these tracts yields education outcomes.

Demand 4 asks the City Health Department and UW Health to expand primary care access in HPSA-designated tracts with high uninsured rates. Untreated illness is a direct cause of absence, and the priority tracts carry triple HPSA designations.

Demand 5 asks funders to treat the atlas itself as grantable infrastructure. An accountability tool that is not maintained becomes an artifact. Annual updates, additional data layers, and longitudinal tracking require sustained investment.

Demand 6 asks MMSD's Building for the Future 2025–27 boundary review to ensure that redrawn attendance zones do not concentrate poverty in fewer schools. The atlas's school attendance zone overlays, paired with NARI scores, provide the data to evaluate every proposed boundary change before it takes effect.

This is the first edition of the Madison Equity Atlas. It will not be the last. The gap documented here is not fixed — it is measured. Measurement is the beginning of accountability.

Methodology

NARI Composite Construction

The Neighborhood Attendance Risk Index (NARI) is an 8-indicator composite that ranks each of Dane County's 125 census tracts on structural risk to school attendance. The construction follows the established methodology of peer composite indices (CDC Social Vulnerability Index, Child Opportunity Index 3.0, Area Deprivation Index).

Indicators and Weights

Indicator Source Weighting
Poverty RateACS 5-YearEmpirical (Pearson r with CA)
% People of ColorACS 5-YearEmpirical
Youth Population (<18)ACS 5-YearEmpirical
Transit Frequency (AM peak trips/hr)Madison Metro GTFSEmpirical (inverse)
Housing Cost Burden (%)ACS B25106Empirical
Uninsured Rate (%)ACS S2701Empirical
Eviction Filing RatePrinceton Eviction LabEmpirical
HPSA Designation (3-category)HRSAEmpirical

Normalization

Each indicator is percentile-normalized to a 0–100 scale before weighting. This prevents indicators measured on different scales from dominating the composite — a critical methodological requirement identified in the ADI literature (Health Affairs, 2024). Weights are derived from each indicator's empirical Pearson correlation with chronic absence rates across MMSD schools. The equal-weight version and the outcome-weighted version produce highly correlated tract rankings (r > 0.85), and the simpler equal-weight version is used in the primary display.

Tier Definitions

Tier NARI Score Classification
Critical80–100Highest structural risk; priority investment geography
Severe60–79High structural risk; active monitoring
Elevated40–59Moderate structural risk; emerging concern
Moderate20–39Below-average risk; standard monitoring
On-Track0–19Low structural risk; protective conditions present

The 14 priority tracts are those scoring in the top two tiers (Critical or Severe) of the NARI composite. They are lettered A–N by descending NARI score for identification in maps and tables.

Data Limitations

All analyses are correlational. The atlas does not have experimental variation or a natural experiment. Outputs are framed as associations and model predictions, not causal claims. Grade-level breakdowns by demographic group are modeled from school-level averages mapped to grade bands; WISEdash reports grades and demographics as separate cross-tabs. Eviction data vintage (2015–2017) predates the pandemic and current filing patterns. The NARI composite is a relative ranking within Dane County and should not be compared numerically to indices from other geographies.

Update Commitment

CWD commits to annual atlas updates as new WISEdash and ACS data become available. Each update will re-rank tracts, update school-level statistics, and track year-over-year change in the 14 priority tracts. The atlas is designed to be a living accountability tool, not a one-time report.

Data sources: WI DPI WISEdash Certified Data (2024–25), U.S. Census ACS 5-Year (2022, 2023), Princeton Eviction Lab (2015–2017), HRSA HPSA designations (2026-Q1), Madison Metro GTFS (March 2026), Mapping Inequality / Univ. of Richmond (1938 HOLC), MMSD ArcGIS FeatureServer (2025–26 attendance boundaries).

Cross Tabulations

Source: WI DPI WISEdash Certified Data, 2024-25 · ACS 5-Year 2022

About the Madison Equity Atlas

Madison Equity Atlas

The Madison Equity Atlas integrates public datasets spanning school attendance, household income, racial composition, youth population, transit access, housing cost burden, health insurance coverage, eviction filing rates, and health care access across 125 census tracts and 54 schools in the Madison Metropolitan School District. It was developed by Common Wealth Development (CWD) to support data-driven decisions about affordable housing, youth programming, and community investment.

The atlas is designed around an emotional arc — a sequence of understanding that moves the reader from recognition through action:

Stage Experience
Recognition"I recognize this city in the data."
Unsettlement"I knew the gap existed. I did not know income doesn't explain it."
Specificity"This is about real children at real addresses."
Agency"I know what is being asked of me."
Resolve"This is the beginning of a new accountability infrastructure."

The atlas serves three audiences: policy makers who allocate public resources, funders who evaluate place-based investments, and community advocates who organize for change in specific neighborhoods. Each tab is designed to support these audiences with the data they need in the format they use.

Twenty-two data layers are organized across five categories: Demographics (income, race, youth, poverty), Education (attendance, chronic absence, homeless students), Housing (cost burden, eviction rates), Health (HPSA designation, uninsured rate, FQHC distance), and Transportation (transit frequency). The NARI composite synthesizes eight of these indicators into a single 0–100 risk score per tract — the layer that integrates them all.

Data Sources

DatasetSourceVintageCoverage
School Attendance & Chronic AbsenceWI DPI WISEdash Certified Data2024-2554 MMSD schools
Household Income & PovertyU.S. Census Bureau ACS 5-Year2022125 Dane County tracts
Racial/Ethnic CompositionU.S. Census Bureau ACS 5-Year2022125 Dane County tracts
Youth Population by RaceU.S. Census Bureau ACS 5-Year2022125 Dane County tracts
Transit Frequency (AM Peak)Madison Metro Transit GTFSMarch 20261,681 stops / 125 tracts
Housing Cost BurdenU.S. Census Bureau ACS 5-Year (B25106)2023125 Dane County tracts
Uninsured RateU.S. Census Bureau ACS 5-Year (S2701)2023125 Dane County tracts
Census Tract BoundariesU.S. Census Bureau TIGER/Line2022125 Dane County tracts
MMSD School LocationsWI DPI GIS Open Data2024-2554 schools
Eviction Filing RatesPrinceton Eviction Lab2015-2017142 Dane County tracts
Health Professional Shortage Areas (HPSA)HRSA HPSA2026-Q1125 Dane County tracts
Federally Qualified Health Centers (FQHC)HRSA FQHC Sites2026-Q1125 Dane County tracts
Homeless Student CountsWI DPI WISEdash2024-25District-level (MMSD)
NARI Composite IndexCWD Research2026125 Dane County tracts (8 indicators)
HOLC Redlining GradesMapping Inequality / Univ. of Richmond1938Madison, WI HOLC zones
School Attendance ZonesMMSD ArcGIS FeatureServer2025-26Elementary (30), middle (12), high school (6) attendance boundaries. Note: MMSD 2025-27 boundary review in progress.

How to Use the Atlas

The atlas is designed for five use cases. Each represents a real decision point where the data changes what happens next.

Council member before a budget vote

Open the Atlas tab and select the NARI composite layer. Identify which of the 14 priority tracts fall within your district. Click any tract to see all 22 data layers for that neighborhood. Use the transit frequency and housing cost burden layers to evaluate whether proposed budget allocations reach the tracts with the highest structural risk. The Research tab provides the evidence narrative for floor statements.

Funder evaluating a place-based grant

Use the atlas to verify that a proposed investment geography aligns with documented need. The NARI composite score provides a single defensible metric for tract-level targeting. The Cross-Tabs tab shows how school-level outcomes vary by neighborhood context. Compare the applicant's target area against the 14 priority tracts to assess geographic precision.

Community organizer at a neighborhood meeting

Open the atlas on a shared screen. Select your neighborhood's census tract and walk through the layers: income, race, transit, eviction, health access. Each layer tells one part of the story. The NARI composite tells the whole story in a single number. Export the tract view as a PDF to distribute at the meeting. The data belongs to the community — the atlas makes it accessible.

Researcher building on findings

The Research tab documents completed analyses (RQ 1.2, RQ 1.5) and identifies open research questions (RQ 1.4, RQ 2.1–2.4). The Cross-Tabs tab provides the sortable cross-tabulations underlying the headline findings. All data sources are public and documented in the table above. Contact CWD for data partnership opportunities, particularly regarding the positive-deviance school analysis and the housing-to-attendance pathway study.

Anyone tracking year-over-year progress

Return to the atlas each year as updated data becomes available. The NARI composite will re-rank tracts annually. School-level chronic absence rates will update with each WISEdash release. The question to ask each year: are the 14 priority tracts improving, stable, or declining? Are the demands being met? The atlas is designed to answer these questions without requiring a new report.

Research Analyses

AnalysisMethodStatusFinding
RQ 1.2: Income Threshold Income-bin analysis + linear regression (51 schools) Complete $100K median income threshold; steepest CA decline below threshold; 8.8% poverty tipping point
RQ 1.4: School Outlier Analysis OLS residual ranking (school CA vs. tract demographics) In Progress Identifies positive-deviance schools beating neighborhood predictions on Black student CA
RQ 1.5: Race/Income Proxy Partial correlation + segmented analysis (44 schools) Complete 25.8pp Black-White gap persists after controlling for income (95% CI: 25.07–34.77pp)
RQ 2.1: Transit Access Correlation of tract-level transit frequency with school CA rates Data Acquired Transit frequency layer integrated; formal analysis write-up needed for policy brief
RQ 2.2: Childcare Deserts Childcare desert designation vs. elementary CA rates Data Acquired Childcare provider data acquired (HIFLD + DCF); analysis integrated into viewer
RQ 2.3: Housing Instability Housing cost burden + eviction rates vs. school CA Data Acquired Housing and eviction data integrated; CWD portfolio proximity analysis still needed
RQ 2.4: Health Access HPSA designation + uninsured rate vs. CA beyond economic status Data Acquired All three HPSA categories integrated; uninsured rates mapped; formal write-up needed

Note: RQ 1.5 uses a school-level proxy, not a true race x income cross-tab. See Analysis tab for full methodology and caveats. All analyses are correlational.

NARI Composite Construction

The Neighborhood Attendance Risk Index (NARI) synthesizes eight structural indicators into a single 0–100 score per census tract, following the established methodology of peer composite indices.

Eight Indicators

1. Poverty Rate (ACS)
2. % People of Color (ACS)
3. Youth Population <18 (ACS)
4. Transit Frequency (GTFS, inverse)
5. Housing Cost Burden (ACS B25106)
6. Uninsured Rate (ACS S2701)
7. Eviction Filing Rate (Eviction Lab)
8. HPSA Designation (HRSA, 3-category)

Normalization

Each indicator is percentile-normalized to 0–100 before weighting. Weights are derived from each indicator's Pearson correlation with chronic absence rates across MMSD schools.

Tier Definitions

Critical 80–100
Severe 60–79
Elevated 40–59
Moderate 20–39
On-Track 0–19

Validation

The NARI composite is validated against school-level chronic absence rates. The equal-weight and outcome-weighted versions produce highly correlated tract rankings (r > 0.85). The 14 priority tracts (Critical and Severe tiers) concentrate the highest structural risk and the highest chronic absence rates in the district. Peer indices (CDC SVI, COI 3.0, ADI) use the same percentile-normalization approach.

Release History

v2.0 (March 2026): Public launch as Madison Equity Atlas. Added HOLC redlining overlay (1938 grades from Mapping Inequality), NARI composite as default map layer, editorial landing panel with research narrative, expanded Research tab with pipeline analysis and positive-deviance framing, per-map PNG export, school attendance zone overlays (elementary, middle, high), and MMSD Building for the Future boundary review context.

v1.0 (March 2026): Initial MMSD Community & Youth Equity Data Viewer (YABIR) with 6 tabs, 13 data layers, 7 research analyses, income threshold and race-income proxy findings as headline cards, sortable cross-tabulations across 10 demographic dimensions, and interactive choropleth mapping with school overlays.

Acknowledgments

The Madison Equity Atlas was developed by Common Wealth Development (CWD). The atlas draws on public data from the Wisconsin Department of Public Instruction, the U.S. Census Bureau, HRSA, Madison Metro Transit, the Princeton Eviction Lab, and the University of Richmond's Mapping Inequality project. CWD acknowledges the families and communities in south and east Madison whose lived experience these data represent. The atlas exists to make their conditions visible, measurable, and actionable.

Contact

Common Wealth Development (CWD)
Madison, Wisconsin
Building community equity through housing, data, and advocacy.