Note: To use the Title VI Engine, you'll need to work with your Customer Success Manager to ensure it's calibrated for your agency. Click here to learn more.

How to run and interpret the Title VI Engine

Our Methodology 

Remix allows you to automatically generate a Title VI report (based on Census data) by comparing existing service to a set of proposed changes. This page outlines the methodology and data sources we use when generating this report.

Data sources

  • Census data is provided by the US American Community Survey, 2012-2016.
  • Population is coded by table B03002, field B03002001.
  • Low income status is set at 100%, 150% or 200% the US poverty level, depending on your individual agency. This is coded by the appropriate fields in table C17002.
  • Minority status is coded by table B03002, by subtracting the white, non-Hispanic population (B03002003) from the total population (B03002001).
  • Service area is a set of block groups determined by a shapefile your agency provides.
  • Map and routing data is provided OpenStreetMap, Mapbox, and Valhalla.

Methodology

1. Get the population near a route, including its low income and minority percentage.

  • For each route, build a shape that represents the area within quarter mile of any of its stops.
  • Intersect the catchment area with 2012-2016 ACS Census data. Get a list of block groups and the percentage overlap with each.
  • For each block group, take the percentage of overlap and multiply it by the block group’s statistics.
  • Get the population, minority population, and low income population for each group and sum them together. This is the total population a route could serve.

2. Compare the number of people-trips, before and after.

  • Multiply the population near a route times the number of trips it makes (per year) to get “people-trips”.
  • Repeat for low-income and minority populations to get “low income people-trips” and “minority people trips”.
  • Compare these numbers between the before and after versions of the route, to get a set of people-trip differences. We match before and after using routes that have the same name.

3. Get the total difference in people-trips across the transit system.

  • Repeat the process above for every route in the transit system.
  • Sum together the difference in people trips. This will return three numbers: total difference in people-trips, total difference in low-income people-trips, and total difference in minority people trips.

4. Calculate the change borne by low-income and minority populations.

  • Divide the total difference in low-income people trips by the total difference in people-trips to get the percentage of change borne by those with low incomes.
  • Repeat for minority people-trips.

5. Compare the percentage change to the average in the service area.

  • Calculate the average percentage of low-income and minority populations across the entire service area.
  • Subtract from the change borne by those populations.
  • Get two final numbers: the delta between the impact this set of transit changes had on low income and minority populations compared to any average change.

Additional Raw Data

In addition to the methodology outlined above, Remix also produces a set of raw data you can use in your own methodology. Specifically, we provide:

  • A list of Census block groups in the service area with population, low-income, minority information for each.
  • A before and after count of trips in each block group.
  • A service-area-wide average of minority and low-income populations

We’ve found that most US transit agencies can use the above data to run their existing Title VI methodology.

Did this answer your question?