If journalism is in large part a tool of political education, and local politics are those that have the most explicit impact on readers (at least in the short term), then it makes sense for reporters to explore big-picture issues through a localized lens when possible.The proposition of self-serve local news, then, is thus: by creating technical infrastructures and reportorial processes that leverage national-scale resources toward local-scale stories, it’s possible to simultaneously engage with both the economic realities and the content needs of modern local journalism.Localizing the NewsAs a proof of concept of this theory, our team chose to work with a FiveThirtyEight article from 2017 by Maimuna Majumder titled “Higher Rates Of Hate Crimes Are Tied To Income Inequality.” Majumder’s article uses data analysis to explore — at the national scale — the connection between hate crimes per capita and economic inequality (as well as, to a lesser degree, education inequality).We chose to experiment with localizing this article for a number of reasons:The idea was interesting; especially in the context of Trump’s surprise electoral victory and the spike in hate crimes that followed, Majumder’s thesis piqued our interest.It had clearly defined claims — hate crimes and economic inequality are related; hate crimes and education levels are related — which could be tested quantitatively.Majumder made all her data available in a GitHub repository, eliminating many sourcing challenges.Data about hate crimes, economic inequality and education inequality is inherently geographic, such that our central task of localizing the article made sense given its content.To begin developing a system through which to localize Majumder’s article, we first created a neutral “template” version of the article off of which modified versions could be adapted..This involved removing any date-specific content from the template (as the article was over a year old) and cutting out most of the content explaining the methodology behind Majumder’s statistical analysis..This left us with what we referred to as the base layer.We then had to aggregate all the data necessary to take Majumder’s story and zoom in to the local level..This local data came from a variety of sources..We sourced demographic data for a given city or state, such as the Gini Index of economic inequality or high school graduation rates, from the annual American Community Survey by the United States Census Bureau..Meanwhile, data on hate crimes came from the FBI’s Unified Crime Reporting Program, which compiles crime data from local agencies..Lastly, we queried the Southern Poverty Law Center (SPLC) to find hate groups active in each state.With the exception of the SPLC data, we utilized precomputed summary statistics..For instance, for the graduation rates, the Census Bureau had already gathered details about the educational attainment of every resident in a given city and computed the percentage who attained at least a high school degree..As such, sourcing the data meant downloading these precomputed percentages rather than downloading the educational records of every single resident.We then created a dataframe in the programming language R that would allow us to test the correlation between hate crimes and both economic inequality and education rates..Joining together data from the FBI (hate crimes), SPLC (hate groups) and U.S..Census Bureau (Gini Index of economic inequality and high school graduation rates), we were left with a robust data set that could explore relationships between different factors over time — for instance, how closely correlated hate crime rates and economic inequality were over several years in any given city or state..We only looked at cities and states with data from at least six years in order to calculate the correlations.Moving from the particularities of regional data to the broad strokes of the stories a journalist might want to tell about that regional data, we settled on eight general types of articles that might be necessary to publish, depending on which city or state a reporter was writing for.. More details