Big Data, Data Analytics, and the Access to Justice “Card”


It is not uncommon for court leaders and justice stakeholders to raise the access to justice “card” to subvert the closing or consolidation of courts.  If you close this court -- the argument goes -- citizens will be denied access to justice.  This is a strong argument because it typically evokes an emotional response irrespective of the information’s truth value, especially if the counter-arguments are couched in bland terms like efficiency and cost-savings. Trouble is that such arguments are heavy on rhetoric and light on hard evidence; and they often produce factionalism and political stalemate (see Court Consolidation in Mahoning County).   

In a 2005 survey of the public and of attorneys in California, respondents who were asked about eleven reasons that might keep someone from “going to court,” cited “travel distance to court from home” less often than eight of the other reasons including fees, cost of hiring an attorney, the time it takes to reach a decision, lack of child care, and the hours the court is open. 

How far does a court have to be before it is too far -- before the distance constitutes a legitimate barrier to access to the courts?  It seems that the best that we’ve been able to say in response is what we said back in the horse-and-buggy days, i.e., that it should be no more than a hard day’s ride on horseback.  

Big data and data analytics may not remove dysfunctional politics but it could lead to data-driven decision-making and calculated boldness by leaders advocating reform efforts such as court consolidation. For example, court location data could be compared against a number of public databases with information from inside and outside the justice system including Zip codes, populations, demographics of the population (race, age, disability), travel times between locations, numbers and types of cases heard by different courts, levels of courts, and availability of public transportation.  By tapping into the every growing mobile data traffic, we may eventually be able to use real-time distance data from court users on their smart phones.  

Results may allow advocates and opponents to compare various court consolidation models and say, for example, that the consolidation of courts from ten locations to three would increase the average distance and driving time to the nearest court from 3.1 miles and a ten minute commute to 4.5 miles and a fourteen minutes, with the overall average can be disaggregated by age of citizens, income levels, case type and so forth.  

Who knows, this type of information might actually allow us to update the “a hard day’s ride” access to justice standard. 

© Copyright CourtMetrics and the National Center for State Courts 2012. All rights reserved.

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