A New Podcast: Elizabeth Linos on Public Sector Employees
On the Evidence is one of our favorite podcasts, featuring ace-interviewer J.B. Wogan. It is sponsored by Mathematica and can be found here beginning on Wednesday, November 8. It features Elizabeth Linos, a public management scholar and behavioral scientist who studies, designs, and tests innovations in how government operates. She is currently an Associate Professor of Public Policy and Management at the Harvard Kennedy School; and she’s the Faculty Director of the People Lab at Harvard. She wrote a guest column for this website that you can find here.
Here are some highlights from Linos’s podcast comments about her research on public sector employees, including ways they can be attracted and then supported when they’ve taken a job working for a governmental entity.
I think the narrative about who public sector workers are and what they do really changes over time. So, I think there’s been periods in U.S. history where it was certainly the case that people thought the best and the brightest were working in government. Then there’s periods in U.S. history – more recently, I would say – where even our politicians who depend on that career civil service spread a narrative of disdain for the people who work in government. I think that does seep into the general kind of popular belief that either we don’t need innovators and smart thinkers in government or that the people who currently work in government don’t have those skills – both of which I think are false.
We need to do a lot more research to better understand . . . the causal link between what it means to invest in the workforce and how that translates into better service delivery. But at least in some of my research, we do see that connection popping up. So, during COVID, we did quite a few projects related to burnout for frontline workers which, as you can imagine, was a significant problem and continues to be a significant challenge for a lot of government agencies.
If you invest in the mental health of the workforce, that might change how they then view their role vis-à-vis the people that they’re serving. Just to give you an example, we’ve done some work with . . . the Bangor Sheriff’s Department that focuses on the burnout challenges and mental health challenges of correctional officers. What we find is that if we invest in improving that through peer support programs (they don’t) only have benefits for the employees themselves but that also changes how they view the incarcerated population.
There’s a lot of research in public management that suggests that if the people who are delivering those services look like the communities they’re called to serve, whether that’s demographically or in terms of experience, that outcomes are better. We’re still trying to figure out exactly why that is, whose behavior is changing for those outcomes to be better. But you can imagine a world where, if we brought in more of the people into the government bureaucracy that have the same lived experience as the people that they’re called to serve, that might improve those kind of mini interactions that happen when a low-income household is showing up for an interview to get access to benefits or when you have to call a household to say, “okay, you missed your appointment.”
[In the What Works Cities Initiative] the part that I was involved with through the Behavioral Insights Team was related to evaluations. So, we were working with mid-sized cities who were interested in doing rigorous randomized controlled trials to test some sort of change in a program or a service in their city. So, in some ways, this is kind of the dream scenario for an academic policy/practitioner partnership where you work together to codesign a potential intervention and you test if it works in that context . . . We just went back five years later and said, “Did you actually use the treatments that we tested in those interventions. . . It turns out, much to my heartbreak, that it is not the case. . . we found significant evidence that . . . the evidence is not a predictor of whether or not something gets adopted.