<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="en">
<Esri>
<CreaDate>20250215</CreaDate>
<CreaTime>15191700</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>TRUE</SyncOnce>
</Esri>
<dataIdInfo>
<idAbs>&lt;DIV STYLE="text-align:Left;"&gt;&lt;DIV&gt;&lt;DIV&gt;&lt;P&gt;&lt;SPAN&gt;Title VI of the Civil Rights Act and the Executive Order on Environmental Justice (#12898) do not provide specific guidance to evaluate EJ issues within a region's transportation planning process. Therefore, MPOs must devise their own methods for ensuring that EJ issues are investigated and evaluated in transportation decision-making. In 2001, DVRPC developed an EJ technical assessment to identify direct and disparate impacts of its plans, programs, and planning process on defined population groups in the Delaware Valley region. This assessment, called the Indicators of Potential Disadvantage Methodology, is utilized in a variety of DVRPC plans and programs. DVRPC currently assesses the following population groups, defined by the U.S. Census Bureau:&lt;/SPAN&gt;&lt;/P&gt;&lt;UL&gt;&lt;LI&gt;&lt;P&gt;&lt;SPAN&gt;Youth&lt;/SPAN&gt;&lt;/P&gt;&lt;/LI&gt;&lt;LI&gt;&lt;P&gt;&lt;SPAN&gt;Older Adults&lt;/SPAN&gt;&lt;/P&gt;&lt;/LI&gt;&lt;LI&gt;&lt;P&gt;&lt;SPAN&gt;Female&lt;/SPAN&gt;&lt;/P&gt;&lt;/LI&gt;&lt;LI&gt;&lt;P&gt;&lt;SPAN&gt;Racial Minority&lt;/SPAN&gt;&lt;/P&gt;&lt;/LI&gt;&lt;LI&gt;&lt;P&gt;&lt;SPAN&gt;Ethnic Minority&lt;/SPAN&gt;&lt;/P&gt;&lt;/LI&gt;&lt;LI&gt;&lt;P&gt;&lt;SPAN&gt;Foreign-Born&lt;/SPAN&gt;&lt;/P&gt;&lt;/LI&gt;&lt;LI&gt;&lt;P&gt;&lt;SPAN&gt;Disabled&lt;/SPAN&gt;&lt;/P&gt;&lt;/LI&gt;&lt;LI&gt;&lt;P&gt;&lt;SPAN&gt;Limited English Proficiency&lt;/SPAN&gt;&lt;/P&gt;&lt;/LI&gt;&lt;LI&gt;&lt;P&gt;&lt;SPAN&gt;Low-Income&lt;/SPAN&gt;&lt;/P&gt;&lt;/LI&gt;&lt;/UL&gt;&lt;P&gt;&lt;SPAN STYLE="font-weight:bold;"&gt;Census tables used to gather data from the 2018-2022 American Community Survey 5-Year Estimates&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;Using U.S. Census American Community Survey data, the population groups listed above are identified and located at the census tract level. Data is gathered at the regional level, combining populations from each of the nine counties, for either individuals or households, depending on the indicator. From there, the total number of persons in each demographic group is divided by the appropriate universe (either population or households) for the nine-county region, providing a regional average for that population group. Any census tract that meets or exceeds the regional average level, or threshold, is considered an EJ-sensitive tract for that group.&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;Census tables used to gather data from the 2018-2022 American Community Survey 5-Year Estimates.&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;For more information and for methodology, visit DVRPC's website:http://www.dvrpc.org/GetInvolved/TitleVI/&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;For technical documentation visit DVRPC's GitHub IPD repo: https://github.com/dvrpc/ipd&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;Source of tract boundaries: 2020 US Census Bureau, &lt;/SPAN&gt;&lt;A href="https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.html" STYLE="text-decoration:underline;"&gt;&lt;SPAN&gt;TIGER/Line Shapefiles&lt;/SPAN&gt;&lt;/A&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN STYLE="font-weight:bold;"&gt;Note: Tracts with null values should be symbolized as "Insufficient or No Data".&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;A href="https://docs.google.com/spreadsheets/d/1eVswJEEnDsLK3q6hqZN0L25tcwYKVzzvOmyQQsO0Db4/edit?usp=sharing" STYLE="text-decoration:underline;"&gt;&lt;SPAN STYLE="font-weight:bold;"&gt;Data Dictionary &lt;/SPAN&gt;&lt;/A&gt;&lt;SPAN STYLE="font-weight:bold;"&gt;for Attributes:&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN STYLE="font-style:italic;"&gt;(Source = DVRPC indicates a calculated field)&lt;/SPAN&gt;&lt;/P&gt;&lt;TABLE&gt;&lt;TBODY&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="font-weight:bold;margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Field&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="font-weight:bold;margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Alias&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="font-weight:bold;margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Description&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="font-weight:bold;margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Source&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;IPD analysis year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P /&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;DVRPC&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;geoid20&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;11-digit tract GEOID&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Census tract identifier&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;statefp&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;2-digit state GEOID&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;FIPS Code for State&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;countyfp&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;3-digit county GEOID&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;FIPS Code for County&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;tractce&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Tract number&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Tract Number&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;name&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Tract number&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Census tract identifier with decimal places&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;namelsad&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Tract name&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Census tract name with decimal places&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;d_class&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Disabled percentile class&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Classification of tract's disabled percentage as: well below average, below average, average, above average, or well above average&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;d_est&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Disabled count estimate&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Estimated count of disabled population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;d_est_moe&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Disabled count margin of error&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Margin of error for estimated count of disabled population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;d_pct&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Disabled percent estimate&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Estimated percentage of disabled population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;d_pct_moe&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Disabled percent margin of error&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Margin of error for percentage of disabled population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;d_pctile&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Disabled percentile&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Tract's regional percentile for percentage disabled&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;d_score&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Disabled percentile score&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Corresponding numeric score for tract's disabled classification: 0, 1, 2, 3, 4&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;em_class&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Ethnic minority percentile class&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Classification of tract's Hispanic/Latino percentage as: well below average, below average, average, above average, or well above average&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;em_est&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Ethnic minority count estimate&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Estimated count of Hispanic/Latino population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;em_est_moe&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Ethnic minority count margin of error&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Margin of error for estimated count of Hispanic/Latino population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;em_pct&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Ethnic minority percent estimate&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Estimated percentage of Hispanic/Latino population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;em_pct_moe&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Ethnic minority percent margin of error&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Margin of error for percentage of Hispanic/Latino population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;em_pctile&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Ethnic minority percentile&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Tract's regional percentile for percentage Hispanic/Latino&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;em_score&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Ethnic minority percentile score&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Corresponding numeric score for tract's Hispanic/Latino classification: 0, 1, 2, 3, 4&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;f_class&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Female percentile class&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Classification of tract's female percentage as: well below average, below average, average, above average, or well above average&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;f_est&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Female count estimate&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Estimated count of female population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;f_est_moe&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Female count margin of error&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Margin of error for estimated count of female population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;f_pct&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Female percent estimate&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Estimated percentage of female population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;f_pct_moe&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Female percent margin of error&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Margin of error for percentage of female population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;f_pctile&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Female percentile&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Tract's regional percentile for percentage female&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;f_score&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Female percentile score&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Corresponding numeric score for tract's female classification: 0, 1, 2, 3, 4&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;fb_class&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Foreign-born percentile class&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Classification of tract's foreign born percentage as: well below average, below average, average, above average, or well above average&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;fb_est&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Foreign-born count estimate&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Estimated count of foreign born population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;fb_est_moe&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Foreign-born count margin of error&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Margin of error for estimated count of foreign born population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;fb_pct&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Foreign-born percent estimate&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Estimated percentage of foreign born population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;fb_pct_moe&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Foreign-born percent margin of error&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Margin of error for percentage of foreign born population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;fb_pctile&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Foreign-born percentile&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Tract's regional percentile for percentage foreign born&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;fb_score&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Foreign-born percentile score&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Corresponding numeric score for tract's foreign born classification: 0, 1, 2, 3, 4&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;le_class&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Limited English proficiency percentile class&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Classification of tract's limited english proficiency percentage as: well below average, below average, average, above average, or well above average&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;le_est&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Limited English proficiency count estimate&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Estimated count of limited english proficiency population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;le_est_moe&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Limited English proficiency count margin of error&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Margin of error for estimated count of limited english proficiency population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;le_pct&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Limited English proficiency percent estimate&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Estimated percentage of limited english proficiency population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;le_pct_moe&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Limited English proficiency percent margin of error&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Margin of error for percentage of limited english proficiency population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;le_pctile&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Limited English proficiency percentile&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Tract's regional percentile for percentage limited english proficiency&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;le_score&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Limited English proficiency percentile score&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Corresponding numeric score for tract's limited english proficiency classification: 0, 1, 2, 3, 4&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;li_class&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Low-income percentile class&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Classification of tract's low income percentage as: well below average, below average, average, above average, or well above average&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;li_est&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Low-income count estimate&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Estimated count of low income (below 200% of poverty level) population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;li_est_moe&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Low-income count margin of error&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Margin of error for estimated count of low income population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;li_pct&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Low-income percent estimate&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Estimated percentage of low income (below 200% of poverty level) population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;li_pct_moe&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Low-income percent margin of error&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Margin of error for percentage of low income population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;li_pctile&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Low-income percentile&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Tract's regional percentile for percentage low income&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;li_score&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Low-income percentile score&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Corresponding numeric score for tract's low income classification: 0, 1, 2, 3, 4&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;oa_class&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Older adult percentile class&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Classification of tract's older adult percentage as: well below average, below average, average, above average, or well above average&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;oa_est&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Older adult count estimate&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Estimated count of older adult population (65 years or older)&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;oa_est_moe&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Older adult count margin of error&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Margin of error for estimated count of older adult population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;oa_pct&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Older adult percent estimate&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Estimated percentage of older adult population (65 years or older)&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;oa_pct_moe&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Older adult percent margin of error&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Margin of error for percentage of older adult population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;oa_pctile&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Older adult percentile&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Tract's regional percentile for percentage older adult&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;oa_score&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Older adult percentile score&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Corresponding numeric score for tract's older adult classification: 0, 1, 2, 3, 4&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;rm_class&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Racial minority percentile class&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Classification of tract's non-white percentage as: well below average, below average, average, above average, or well above average&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;rm_est&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Racial minority count estimate&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Estimated count of non-white population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;rm_est_moe&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Racial minority count margin of error&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Margin of error for estimated count of non-white population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;rm_pct&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Racial minority percent estimate&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Estimated percentage of non-white population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;rm_pct_moe&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Racial minority percent margin of error&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Margin of error for percentage of non-white population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;rm_pctile&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Racial minority percentile&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Tract's regional percentile for percentage non-white&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;rm_score&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Racial minority percentile score&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Corresponding numeric score for tract's non-white classification: 0, 1, 2, 3, 4&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;tot_pp&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Total population estimate&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Estimated total population of tract (universe [or denominator] for youth, older adult, female, racial minoriry, ethnic minority, &amp;amp; foreign born)&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;tot_pp_moe&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Total population margin of error&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Margin of error for estimated total population of tract&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;y_class&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Youth percentile class&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Classification of tract's youth percentage as: well below average, below average, average, above average, or well above average&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;y_est&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Youth count estimate&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Estimated count of youth population (under 18 years)&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;y_est_moe&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Youth count margin of error&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Margin of error for estimated count of youth population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;y_pct&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Youth population percentage estimate&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Estimated percentage of youth population (under 18 years)&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;y_pct_moe&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Youth population percentage margin of error&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Margin of error for percentage of youth population&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;y_pctile&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Youth population percentile&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Tract's regional percentile for percentage youth&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;y_score&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Youth percentile score&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Corresponding numeric score for tract's youth classification: 0, 1, 2, 3, 4&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ipd_score&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Indicator of potential disadvantage score&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Overall score adding the classification scores across all nine variables&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P /&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P /&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P /&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P /&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P /&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P /&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P /&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P /&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P /&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P /&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P /&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P /&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P /&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P /&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P /&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P /&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P /&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P /&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P /&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P /&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P /&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P /&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P /&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P /&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;mun1&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;First municipality name&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Municipality the census tract falls within&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated from crosswalk&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;mun2&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Second municipality name&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Second municipality the census tract falls within&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated from crosswalk&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;mun3&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Third municipality name&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Third municipality the census tract falls within&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated from crosswalk&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;mcdgeo1&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;First municipality unique identifier&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Municipality the census tract falls within&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated from crosswalk&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;mcdgeo2&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Second municipality unique identifier&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Second municipality the census tract falls within&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated from crosswalk&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;mcdgeo3&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Third municipality unique identifier&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;Third municipality the census tract falls within&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;calculated from crosswalk&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;co_name&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;County Name&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;County name&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;TR&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;state&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;State name&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;State name&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;TD&gt;&lt;P STYLE="margin:0 0 0 0;"&gt;&lt;SPAN&gt;&lt;SPAN&gt;ACS 5-year&lt;/SPAN&gt;&lt;/SPAN&gt;&lt;/P&gt;&lt;/TD&gt;&lt;/TR&gt;&lt;/TBODY&gt;&lt;/TABLE&gt;&lt;P&gt;&lt;SPAN /&gt;&lt;/P&gt;&lt;P /&gt;&lt;/DIV&gt;&lt;/DIV&gt;&lt;/DIV&gt;</idAbs>
<searchKeys>
<keyword>Environmental Justice</keyword>
<keyword>Census Tract</keyword>
<keyword>DVRPC Region</keyword>
<keyword>Degrees of Disadvantage</keyword>
<keyword>2022</keyword>
</searchKeys>
<idPurp>IPD analysis identifies populations of interest under Title VI and EJ using U.S. Census American Community Survey (ACS) 2018-2022 five-year estimates data in each of the Census Tracts in the DVRPC region.</idPurp>
<idCredit>Delaware Valley Regional Planning Commission (DVRPC)</idCredit>
<resConst>
<Consts>
<useLimit>&lt;DIV STYLE="text-align:Left;"&gt;&lt;DIV&gt;&lt;DIV&gt;&lt;P&gt;&lt;SPAN&gt;https://catalog.dvrpc.org/dvrpc_data_license.html&lt;/SPAN&gt;&lt;/P&gt;&lt;/DIV&gt;&lt;/DIV&gt;&lt;/DIV&gt;</useLimit>
</Consts>
</resConst>
<idCitation>
<resTitle>2022 Tract-level Indicators of Potential Disadvantage</resTitle>
</idCitation>
</dataIdInfo>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">iVBORw0KGgoAAAANSUhEUgAAASwAAADICAYAAABS39xVAAAAAXNSR0IB2cksfwAAAAlwSFlzAAAB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</Data>
</Thumbnail>
</Binary>
</metadata>
