General transportation equity for disadvantaged groups is often required by law in the United States. This means that transit agencies have a responsibility to provide service to underserved groups.
But “general transportation” doesn’t always mean high-quality transit service. It could mean as little as a bus that comes once an hour.
A new study from Oregon State University found that existing methods of measuring transit equity – the results of which often inform transit planning – might be too simplistic. The desire to quantify analysis of transit equity make acting on results difficult because there isn’t enough information, researchers Philip Carleton and J. David Porter argue.
Researchers performing transit equity analyses define “disadvantaged” (the term used in this study) as either socioeconomic factors, such as race, ethnicity, income, and employment status, or ability factors (which might overlap with socioeconomic factors) such as age, income, and immigrant status. Carleton and Porter did not include disability in the latter category.
A refresher: equity is not the same as equality. Equity is acknowledging that people have unequal access to opportunities and services, so they must receive different provisions to right this.
There are two main methods of quantifying transit equity: gap analysis and Lorenz curves. Both of these are based on measuring transit supply.
Gap analysis is performed by calculating the “needs gap” of a certain neighborhood and its corresponding transit supply. This method often finds that the areas of the least need are the most urbanized, meaning that people in downtowns have theoretically the best transit access.
However, gap analysis doesn’t account for the quality of that transit service. The results often “conflate all disadvantaged groups into a single aggregate metric,” according to Carleton and Porter.
Lorenz curves look instead at entire cities rather than neighborhoods by comparing the proportion of transit supply to the proportion of disadvantaged people. While the results can be useful for assessing the reach of public transportation (researchers in Perth used Lorenz curves to find that 70 percent of the city’s population received only 33 percent of the entire transit supply), they cannot help planners determine what neighborhoods need more transit service.
What’s key: the researchers warn that these “aggregate measures of disadvantage” alone might not produce helpful, actionable results. Together these two methods can paint a full picture of transit equality in a city, but not equity.
Photo of a bus stop in Helsinki from Flickr’s Creative Commons