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Public beta - This website will be continuously updated

Limited data sources — This tool currently includes 16 datasets. Over time, datasets could be added, updated, or removed. The datasets come from a variety of sources based on availability, quality, and relevance to environmental, energy, and climate issues. Each dataset has limitations, such as how recently the data was updated.

Methodology

The Just Progress tool combines demographic, environmental, and socio-economic data to generate a cumulative index score, referred to as the Just Progress Index. The tool currently utilizes national, publically-available data from the United States Census Bureau’s American Community Survey (ACS) and the EPA’s EJScreen tool.

The various inputs into the Just Progress Index are averaged into 2 categories: Pollution Burden and Demographics.

Pollution Burden: health risks arising from proximity and potential exposures to pollution and other adverse environmental conditions

Demographics: sensitive populations and socioeconomic factors that make a community more vulnerable

Pollution Burden average x Demographics average = Just Progress Index

Limited data sources — Datasets may be added, updated, or removed.

Datasets used in cumulative score

The datasets come from a variety of sources and were selected after considering relevance, availability, recency and quality.

Poverty

What is it?
Percent of a block group's population in households where the household income is less than or equal to twice the federal "poverty level"
  • Data resolution: Census block group
  • Data source: U.S. Census Bureau
  • Data date range: 5-year estimates, 2015-2019

Education (less than high school)

What is it?
Percent of people age 25 or older in a block group whose education is short of a high school diploma
  • Data resolution: Census block group
  • Data source: U.S. Census Bureau
  • Data date range: 5-year estimates, 2015-2019

Linguistic isolation

What is it?
Percent of people in a block group living in linguistically isolated households — a linguistically isolated household is a household in which all members aged 14 years and over speak a non-English language and also speak English less than "very well" (i.e., have difficulty with English)
  • Data resolution: Census block group
  • Data source: U.S. Census Bureau
  • Data date range: 5-year estimates, 2015-2019

Unemployment rate

What is it?
Unemployment rate (people who are unemployed divided by the total population of people in the labor force over 16 years old)
  • Data resolution: Census block group
  • Data source: U.S. Census Bureau
  • Data date range: 5-year estimates, 2015-2019

Housing burden

What is it?
Percent of households in a census tract that are both low income (making less than 80% of the HUD Area Median Family Income) and severely burdened by housing costs (paying greater than 30% of their income to housing costs)
  • Data resolution: Census block group
  • Data source: U.S. Census Bureau
  • Data date range: 5-year estimates, 2015-2019

  • Gather datasets

    Data inputs

    The cumulative index score includes the following equally weighted inputs.
    • Poverty
    • Less than high school education
    • Linguistic isolation
    • Unemployment rate
    • Housing burden

    Combining data from different geographic units

    Some data is not available at the census block group level and is instead only available for larger units such as census tracts or counties. In these cases, all census block groups will get an even contribution from the larger unit. For example, if a census tract scores 90th percentile on an indicator, then all census block groups within that tract will receive a value of 90th percentile.

    Normalizing data

    The range of the data that makes up the score varies, so the data must be normalized so that each data indicator can be more equally weighted. Min-max normalization is utilized, where the minimum value in the range of values for each dataset is set at 0, the maximum value is set at 1, and every other value is transformed into a decimal between 0 and 1. For example, if the minimum value for unemployment was 10 and the maximum value was 30, a value of 20 would be transformed to 0.5 since it is halfway between 10 and 30.

  • Calculate cumulative index score

    To combine all variables into a single cumulative index score, we average the normalized values across indicators.

    Dataset 1 + Dataset 2 + ... + Dataset N
    # of datasets
    =
    Cumulative index score

  • Assign priority

    Census block groups are sorted by their cumulative index score from highest to lowest. Census block groups that are in the top 25 percentile (i.e. have a cumulative index score in the 75 - 100th percentile) will be considered the prioritized communities.