Leah Hendey, MPP, Senior Research Associate at the Urban Institute, joined the podcast to reflect on her experiences co-directing the National Neighborhood Indicators Partnership (NNIP), a nationwide effort to advance the use of neighborhood-level data to drive local decision-making. NNIP is led by the Urban Institute and a network of 32 partners representing local data intermediaries across the country. Hendey discussed the role local data intermediaries play in their communities, explained how neighborhood-level data can be used to understand and address issues of health equity, and shared examples of communities that have successfully used neighborhood information systems in innovative ways to solve pressing public health challenges.
This podcast is also available on iTunes, Stitcher, and TuneIn.
- Find and connect with your local data intermediary at neighborhoodindicators.org
- Sign up for the NNIP newsletter and google group
- Follow @NNIPHQ and #NNIP on twitter
- Email questions to email@example.com
Takeaways from the Interview
In the words of Leah Hendey…
1. Neighborhood-level data illuminates disparities that are hidden at the city/state level
“We know it’s critical to look beyond a city or county average to figure out how the conditions are varying across neighborhoods and by race. Health conditions, for example, could be improving overall in the city, but getting worse in a neighborhood or for a specific group of people. Communities can’t make progress on issues of equity if we don’t understand these differences.”
2. Local data intermediaries empower community stakeholders to use data more effectively
“There is a ton of data out there, but communities really need someone to help curate that information someone to help them figure out, which are the important indicators that are going to help me structure and evaluate my initiative? That’s how we see an intermediary – as helping figure out the data and mediating that relationship between the data and the user. ”
3. Advancing equity requires a focus not just on data, but also on the people interpreting it
“An issue we really want to dig further into is how we make sure to use data and indicators in ways that advance racial equity. We often think of data as being neutral, but people are not. They will interpret information according to their own lenses and biases, whether those are conscious or unconscious.”