The U.S. Census Bureau's latest big data release - long-form questionnaire results reported down to the tract or block group - is keeping journalists busy as they report the latest economic, social and demographic trends. (See article on page 3) Many of the journalists have been using geographic information system (GIS) programs to uncover patterns and changes. Here are some recent examples from newsrooms across the country:
Language barriers
Ron Campbell at The Orange County Register used ArcView 3.2 and Census long-form data to find areas with the highest concentrations of residents over 14 who did not speak English fluently. The map he generated (Map 1) displayed the tracts with the highest non-English speaking rates using darker shades.
One Santa Ana neighborhood - with 57 percent of its population over age 14 not speaking English - had the highest rate. Another reporter visited the neighborhood and found residents who routinely spoke Spanish at home, church and inside stores.
A demographer quoted in the story noted that the neighborhood, like some others, is the point of arrival for new immigrants who find it easier to adapt by living among people who speak the same tongue.
Some residents described the tension between generations: Parents wanted their children to speak Spanish, while their children wanted to learn English.
Rich and poor
Mapping helped Garry Lenton, the CAR coordinator at The (Harrisburg, Pa.) Patriot-News, find pockets of poverty in Cumberland County. The county has one of the highest median incomes in the Harrisburg region, yet it had the third-highest poverty rate increase among Pennsylvania's 67 counties.
Lenton wanted to learn the extent of poverty in the county's municipalities. After posting a request for advice to the NICAR-L listserv, Lenton settled on mapping the percentage of people meeting federal poverty guidelines by community and running the numbers of families in poverty by municipality within the newspaper's graphic. (Map 2)
Mapping by percent revealed that some of the sparsely populated communities, mainly in the rural western portion of the county, suffered the highest poverty rates. Reporters for the paper later found that a boom in the number of low-income housing units had helped fuel the increase.
Commuting patterns
Journalists have written plenty of stories showing how affluent commuters are willing to spend more time on the road so they can have big houses in the suburbs. Using GIS, journalists at the Fort Worth Star-Telegram discovered another pattern.
CAR specialist Jeff Claassen analyzed long-form commuting pattern data by tract with ArcView 3.2 to identify areas where a higher percentage of commuters left before 7 a.m. for work. The newspaper found that people living in low-income inner city neighborhoods had some of the longest and earliest commutes (Map 3).
The Star-Telegram used its findings for a "Your Commute" page report dedicated to Census 2000 commuting statistics for the newspaper's area.
Would you be willing to share a mapping example with fellow journalists? Send an electronic copy of the map along with details to David Herzog at dherzog@nicar.org.