Speaker 3 (00:17)
once people understand that we are trying to get to the root cause of a problem as opposed to trying to put them down, right, or place them in a particular bracket, I think they appreciate, as she said, the work we're doing. We're trying to

get to the root cause of a problem, present solutions, like we see through this project, Working across the different themes.

TxTC Staff (00:43)
In this episode, we dive into the collaborative efforts of Dr. Michelle Meyer from Texas A University and Dr. Noelle Estwick from Prairie View A University. They discuss their roles in addressing social vulnerability and disaster resilience in southeast Texas. I'm Jamie Masterson.

TxTC Staff (01:01)
And I'm Cedric Shye, and this is Lessons from the Field Lab.

Speaker 1 (01:07)
So we're here with the social science team of the project. And we've got Dr. Michelle Meyer here from Texas A University and Dr. Noelle Estwick from Prairie View A University. Would you each introduce yourself and kind of describe your role on the project?

Speaker 2 (01:24)
Yeah, I'm Michelle Meyer. I'm director of the Hazard Reduction and Recovery Center here at Texas A and an associate professor of urban planning. And I'm co-PI on the project, and I lead this theme we're going to talk about today with our social science team.

Speaker 3 (01:40)
Thank you, Michelle and Jamie. Cedric,

good morning and thanks for the opportunity to be here on the podcast. I am an assistant professor in the College of Agriculture and Food and Natural Resources at Prairie View A &M University. I teach in the agribusiness concentration and I'm an urban planner by training. I'm the institutional lead for Prairie View and also a member of the equity team on the project.

Speaker 1 (02:09)
Great. So what drew y'all to social science?

Speaker 2 (02:14)
Yeah, so I didn't start off in social science. I started off as a biology major and was really interested in environmental issues. then I took one sociology course, like a social problems course, that was going to go with my wildlife biology degree. And I was hooked because it talked about so much more stuff than just how polluted the lakes were or something like that. yeah, it made.

Speaker 4 (02:21)
Yeah.

Speaker 2 (02:42)
It made sense that studying people would help us address how people interact with the environment and how they're affected by environmental issues like disasters or they cause environmental issues. So from there, I got interested in hazard and disaster risks in graduate school when I went to grad school for environmental sociology because it became a very applied, clear focus of environment and people. This is environment at its most extreme.

and how people are interacting with that and reducing it, making their communities safer, or making it worse.

Speaker 3 (03:18)
So I first got introduced into this through actually civil engineering. As a teenager, did the City and Guilds of London Ordinary Technicians Diploma in civil engineering. as a boy growing up in the island of Barbados in the Caribbean, know, hurricanes is a natural part of what we experience.

As a youngster, the government had something called a mobile cinema where they'll come out to the community and show these movies. I won the playgrounds and I recall one particularly, they had a movie called Lady Called Camille. Knowing nothing about it, I decided to go check it out.

It turned out to be a film about Hurricane Camille. And that is what piqued my interest in this work and got me started. And as I said, I went on to ⁓ do the civil engineering diploma and then went on to urban planning.

Speaker 1 (04:19)
Wow, that's great. tell us then about what you're doing on this project as it relates to social science, disasters, Beaumont and Port Arthur.

Speaker 4 (04:28)
Yeah, like who's on the team and why is it important?

Speaker 2 (04:31)
Yeah, so our team, social scientists, it's mostly us here at A ⁓ and then Prairie View and a few partners in UT and public policy. we're really aiming at this question of who's most at risk and who's going to need the most support to recover. And once we know who's most at risk, how can that feed into what the other teams and teams are doing?

to say, OK, well, we need to put this infrastructure here, or we need to adapt the environment or co-design something here to protect these people in particular. So I think everybody would kind of agree, we want to worry about folks who are elderly or persons with disabilities who would have more trouble in an immediate emergency response.

From social science, we know it's actually a much broader group of people that have different abilities to respond to the disasters that affect us on a regular basis. And in ways, the way we build our environments too can make them more or less able to respond and recover from those events when they happen. But one of our challenges scientifically is that

Most of this work is done through secondary data, like from the US Census, that only happens every 10 years or is big estimates. And it's not always applicable to the specific community and the demographics and processes happening in that community. So we don't currently have a really good method for doing what we are calling like a place-based

social vulnerability indicator to help local communities decide on their own that these are our populations that are most at risk and this is why we know them to be most at risk and why we're going to put infrastructure investments to support these populations, which might be in Beaumont, Port Arthur is going to be completely different than the populations in Los Angeles or the populations in northern Minnesota.

Right, and we need to understand that by working with the community and reviewing the indicators that we have to see what works.

Speaker 1 (06:46)
You said social vulnerability. Could you ⁓ describe that a little bit more? And what are you looking at in terms of what does that mean? And what do you look at in terms of demographics?

Speaker 2 (06:56)
Yeah, so social vulnerability is this big catch-all term as a way to take a variety of demographic factors and put it into one number that makes it kind of easy to put into assessments or to map. But as I mentioned earlier, we have elderly and persons with disabilities would be more at risk or have more trouble during a disaster. But we also know things like households with a lot of children, right? They need probably more support evacuating.

They're going to need more support post-disaster. Their schools are going to need to be open. Playgrounds are going to need available. Child care is going to need to be available for them to be able to recover. We also know that households that say don't speak English or have few native speakers here in the US, they might not hear warning communication, might not be able to apply for aid that's available to them. They'll have more difficulty getting over those barriers.

⁓ Single parents are often lower income. They're often busy with their children. So they're also not able to participate as much in some of our programming. And then especially low income populations. Preparing for a disaster is expensive. Recovering from a disaster is expensive. so those are different populations that we often consider, but it can be very unique depending on what community you're in, where you draw those lines. If you're in a community that's

has a lot of people living in poverty just saying, we're going where people live in poverty, well then you're going to have to work everywhere. So how do you define that? Versus if you go to a high income community, yeah, you might be able to find a pocket of poverty and then you can really focus your attention. So each community needs to adapt the metrics a little bit.

Speaker 4 (08:35)
you guys being on this project, y'all are specifically looking in Southeast Texas and looking for, what is the kind of, what is the vulnerability scale here? Where should we be looking when it's flooding or when the air quality? So can you even start to open up or Noel a little bit about some of the things y'all saw, some of the vulnerabilities that y'all saw in Southeast Texas?

Speaker 3 (08:58)
Yes, and before I go to that, to comment there, I'd also want to mention, you know, Michelle spoke about the secondary data, and one of the things I'm working with with our students is ⁓ collecting some of that primary data, working with the team here, the Hazard Reduction Recovery Center, to collect that primary data that goes along with the secondary data to help inform our decisions better.

you asked about some of the findings. We're still doing the analysis, but a lot of the respondents are talking about the important relationships, the community relationships, right? And the importance of framing flooding, not only to deal with the physical hazards, but also

relationships are on the community. And so ⁓ I recall from one of the responses, they describe how the church is typically used as a food pantry, but also as a resource outlet when disasters occur. So these ⁓ faith-based institutions play a critical role in these particular communities in the Boa Moa area in response to disaster.

in response to disasters because they're trusted and the parishioners can know that this is a place where they can get resources during disasters.

Speaker 1 (10:22)
Is that something you've been doing through surveys or interviews? What is...

Speaker 3 (10:27)
So this primary collection is through interviews. The tech cinema preview team travel there, schedule interviews. The majority face-to-face interviews with local nonprofits, ⁓ local government, as I mentioned, faith-based organizations, educational institutions.

and neighborhood associations.

Speaker 4 (10:49)
Yeah, so guess another part of this is what's happening on the ground already? And that's probably also a big part of else research.

Speaker 2 (10:58)
Yeah, so these interviews were asking folks, know, folks who kind of understand their community, interact with different population groups pretty regularly, you know, where are you seeing flooding? And then we can take that information back to the water team to say, does this match? Are your models matching what people are experiencing? Where are you experiencing poor air quality? And we can take that back to the air team, and they could drive their sniffer around and really try to get the,

more objective data on exactly what is going on in the air for those areas. And then we're also asking them, like, what populations do you know that have trouble recovering from disaster? Where are the neighborhoods that seem like they're having the hardest time rebounding? Where are we losing population at? Where do people want to live? Where do they not want to live? And how are people connecting then to resources, to...

address these challenges. So from these perspectives, we get at a broader view of the vulnerability going on in the community, as well as the different capacities that they see as making it possible, and how we might leverage those capacities or build upon them to increase resilience, rather than trying to do something completely different.

Speaker 3 (12:15)
And you mentioned, you know, getting that community input. So one of the areas, of part of our approach is to use something called Participatory GIS or PGIS. And we are using the information from the interviews to map the cross streets where flooding ⁓ is occurring. And it's interesting, you know, we talk about interacting with community. They use terms that ⁓

They explain things based on their understanding and the best way possible, not necessarily using scientific terms, but then we can use that information and apply the science to it. So one example is one of the descriptions in terms of flooding. They said that this area acts like a bowl. Well, we know already that this means that this is an area of lower elevation. And obviously, we would expect flooding to occur there.

That local knowledge, that local information really helps to verify some of what we know scientifically and from our maps and so on.

Speaker 4 (13:21)
That's what I love about social science just personally is that you can, once you listen to the community, you actually would find that they know what's going on. Probably better than the map knows what's going on.

Speaker 2 (13:33)
100

% they

Speaker 4 (13:35)
I

exactly where it floats, know exactly how it floats, and they can tell you.

Speaker 2 (13:39)
I think I can tell you when I go to work on a rainy day, I'm not taking the street. I'm going to go that way, right?

Speaker 4 (13:46)
Incredible data which is incredible data that could be used for resilience. So I know you guys have started to kind of Calculate this vulnerability you're trying to come up with like how do I how do we calculate and quantify it? So can you explain us a little bit of that like what that looks like?

Speaker 2 (14:03)
Yeah, so that's the hard part. And that's where we're at right now. So it's not fully completed yet. But we're in the process of going from secondary indicators that have laid out different demographic groups, and then from the interview data, looking at, which indicators have come up as the most important for them? And then so how can we then take those indicators and use that?

And then once we put them together, how does that compare to what our standard indicators are?

Speaker 4 (14:31)
Can you let me know, can you give me some examples of some of those indicators?

Speaker 3 (14:34)
So poverty, educational attainment, housing type, transportation, i.e. the availability of transportation when you think about things like evacuation and so on.

Speaker 2 (14:36)
Poverty is a

Yeah, think, so for Beaumont, Port Arthur, one of the unique things about that area that makes this a little difficult is that it's a little bit more homogenous, right? So when we think about comparing demographics, we're often thinking about like, ⁓ this community has all these different types of people. But like, Port Arthur is a majority black city. So if we're using race to be an indicator,

then it's going to say, well, there's not that much difference amongst different neighborhoods. So one of the things that we've heard people talk about is older neighborhoods. And so then looking at those older neighborhoods, who lives there, which is often more minority and low-income populations are living in these older neighborhoods that also haven't had any infrastructure redevelopment.

or improvement in a while. And so those would be indicators that we would be able to look at in terms of the age of the community or the age of the neighborhood to say these particular areas might be a need of reinvestment or a need of some sort of new co-designed kind of process that can help them adapt to different types of flooding or ⁓ air pollution.

Speaker 1 (16:04)
And so just to think about this a little bit more, because there's been some criticism of social vulnerability, the term. so what would you say to those that think that calling someone vulnerable feels like you're victimizing them or that maybe they're not capable of, you know, recovering or handling a disaster situation? Has that been something that you've encountered?

Speaker 2 (16:30)
Yes, so that's been a difficult, it's been an interesting discussion because it's a discussion that I've actually heard more from non-vulnerable academics. Not to say social vulnerability, whereas on the ground, one of the most interesting things going into this community is that we often don't say social vulnerability because it's an academic term. We might talk about inequality, or differences in capacity or disparity, right? And that is something that

It does exist, And inequality doesn't mean that somebody's unable, right? It just means something in our power structure, right? Something in our economic system has led to different people having different access to resources. So it's not the individual's response. But when we went in and we had meetings in Beaumont-PourArthur, they knew the term social vulnerability. And they were ready to debate it. ⁓

Speaker 1 (17:20)
Okay.

Speaker 2 (17:21)
And not because they disliked it in any way, not because of those reasons, but because they felt that, no, we are vulnerable. We are a very vulnerable community. Look at our income level, right? Look at our educational attainment. Look at all these different indicators. We should be prioritized. But in a different process that happened, they were not, right? And it was said that the social vulnerability indicators led

sent money to other communities for a certain reason.

Speaker 1 (17:51)
then describe that. So what are the current social vulnerability indicators and how then, how is the funding being pushed to certain areas and what is y'all's research trying to do to kind of alleviate that or change that?

Speaker 2 (18:05)
Yeah, until recently, under the previous federal administration is really when social vulnerability started to be used as a funding indicator. they had these resilient zones that were created. then, depending on how vulnerable a community was labeled socially under this indicator that's been mostly promoted through the Center for Disease Control, their indicator,

then those communities would be prioritized for federal investment related to disaster resilience.

Speaker 1 (18:36)
So was it by the whole municipality? Was it by a county? Was it by a zip code? What was the

Speaker 2 (18:44)
Yeah, so the Center for Disease Control indicators are at a pretty high level. So they were doing counties, zip codes. at that level, yeah, you're going to blur a lot of differences. When I talk to students, I'm often saying, like, yeah, if you...

If you have like a sample of people and you want an average income and then you throw Jeff Bezos in there, right? Your average income is ridiculous, but he might be one person in your county, right? And now you're no longer vulnerable even if everybody else is living in poverty, right? Because it throws it. Excuse it, right? That's a good way to describe So coming down ⁓ at a very local level, which is what we've been doing on this project, that you can come down to a census block group level, which is the

Speaker 3 (19:17)
Excuse me.

Speaker 2 (19:30)
Smallest for aggregate data from the census which in a city is like a few blocks. That's why it's called a block But then ⁓ our colleague Nathaniel Rosenheim has a has an estimation method to even bring it down to the household level So that then we can re-aggregate it back up and get a nice estimate at a very fine scale to say these are the areas right and

This is stuff that the community already knows. They know who lives in what neighborhoods, and they know where those pockets of need are.

Speaker 4 (20:00)
It's like you guys are trying to validate with science what's on the ground. ⁓

Speaker 3 (20:05)
And Michelle made an important point there when you asked about how people view when we use that term. And I think in agreement with what she was saying, once people understand that we are trying to get to the root cause of a problem as opposed to trying to put them down, right, or place them in a particular bracket, I think they appreciate, as she said, the work we're doing. We're trying to

get to the root cause of a problem, present solutions, like we see through this project, right? Working across the different themes.

Speaker 4 (20:39)
Yeah, I remember hearing this from someone in the HRRC. I don't remember who said this, but it really spoke to me. They're like, if you watch the news after a disaster, you see all of the neighborhoods that are flooded, but what you don't see is the neighborhoods that have bounced back really quickly and are just fine. they're always, and they're always, sometimes they're sometimes very close to those neighborhoods that have been wiped out. And we don't hear that, but the communities know that.

communities now. know that. And scientists and social scientists try to bring that up. So we go, hey, how do we make sure all of these communities, these pockets, especially in our case in Port Arthur, can bounce back and can mitigate these crazy hazards that happen?

Speaker 2 (21:17)
Yeah, and it could be really small differences. So the thing unique about Beaumont Port Arthur is that in terms of elevation, there's not a lot of difference.

The holes are like six inches. Like this is what we're talking in, know, centimeters and inches of difference that can make massive differences. And they're thinking of, well, I want to live in that neighborhood because it's higher. And I look at it like, this isn't higher. What are you talking about? But it's a few inches higher. And those few inches matter a lot for those communities.

Speaker 3 (21:53)
And then the index allows us to then rank the communities based on these factors that we're looking at. And that's how we can present solutions to the problem.

Speaker 1 (22:06)
So do you have ideas then about what the local government, I mean, or any level of government can do to then support these? If we're re-ranking or we're looking at what are the pockets that need help the most, what are things that different levels of government can do to support them?

Speaker 3 (22:24)
So when I think about, when you talk about what local government can do, the results that we're disseminating to the community, they can use this. This is not authoritative, right? It is based, what we're presenting is based on science. And they can use this to apply for funding, to support their arguments to apply for funding.

And also as they think about the future in their development plans and other planning, they can use this information to make projections and decisions as they create plans moving forward.

Speaker 2 (23:00)
Yeah, I think that that's what we would love to happen, right? That like the government has a set amount of money, right, that they can use in any given year. And where are you going to use that and how, right? But if you don't have the data to really understand where could say something simple create a lot of change, right? Then you might invest in that more if you can make that argument of

these few little changes will then protect this many households, right? Or will keep this much property tax still in the community, or will prevent this much out migration, right? Then they could have that data to make more informed choices. But also the data can be used by a variety of organizations that as we, it's not just local government that's investing, right? We might have

private funders who are investing in some sort of you know adaptation response or redoing a park or You know something like that that communities can go for and apply for funding to do we have nonprofits that are you know rebuilding houses in communities post-disaster and You know my dream is that they would rebuild those houses in more resilient ways when they go back into the community right and then Knowing more about their neighborhoods where they're rebuilding they might be able to adapt

how they do that and how they're supporting those populations to make them help them be more resilient to the next disaster so they're not pushed out and forced to migrate when they don't really need to be.

Speaker 3 (24:35)
And I also know that in an earlier podcast, you mentioned the other ⁓ IFLs. So they would also have communities that are experiencing the same things as Beaumont and even other states, other Gulf Coast states. So they can also use this data to inform what they do in their community. So it's not even only about helping our study area, but

really across the country.

Speaker 4 (25:03)
Yeah, so you guys, so you mentioned other IFOs and we also have other teams, other, we have our team on climate, team on air, team on water. So as you guys, like you said, you guys were on the ground, you guys conducted interviews. How did those interviews start to inform the other teams? So I there's a lot of cross back and forth between social sciences and the hard data, the air quality, the water quality, the climate. So can you talk a little bit about that relationship?

Speaker 3 (25:33)
Yeah, so in a lot of responses we got, some of the participants actually talk about some of the smells and certain times of day that they would get these smells. they have their own theories about what happens at different times of the day. And so this is information that we share with the AIR team. And so that's how we can get this collaboration.

and also with the co-design team as they map this information.

Speaker 2 (26:03)
Yeah, the air team, have a thing that you can wear that like when you breathe things in, It like you're smelling something, like we smell, but it's actually like, you know, collecting what are the particles, like what is the chemicals that are in what you're smelling, right? And how can that, because not all smells, not all bad smells are bad health-wise, right?

Speaker 1 (26:27)
And

some of the things we can't smell.

Speaker 2 (26:29)
Or might be bad right and so one of the things that struck me in the interviews would be asked him about flooding We asked him about air quality flooding was really easy to talk about like they they were ready You know with this place floods that place floods. This is why this is what's going on drainage needs to be done here and blah blah blah blah But the air quality was a little more of a challenge for them to talk about and and really put their finger on You know Where is it better and why?

you know, what's the smell? Are they just used to it? know, is it just pervasive across the whole community that, you know, they're just used to everywhere having a particular smell? So they weren't, it wasn't as easy for them to really kind of pinpoint those types of things.

Speaker 3 (27:18)
And you know, in some cases they said you may not be able to smell, but you can see the evidence because they said sometimes in the morning when you wake up you see some type of residue on your car. Really? Yeah, that's outside. So even though they know that something is there even if they can't smell it.

Speaker 2 (27:38)
Mm.

Speaker 4 (27:39)
So there's lots of overlap in your connection with the Air Team. We've already got the Air Team on, but did you see that begin to change their perspective or the Air Team's data perspective?

Speaker 2 (27:52)
Yeah, I think we were trying to inform where the sniffer should go. And one of the interesting things from this project that we found is that, as social scientists, we want to know data about the whole population in the area. So we want to know where is there low-income populations, but also where is there high-income populations? We need those comparisons. Whereas for air and flooding,

They just want to know where it's bad. Right? Like, where's the flooding at? we don't need any data for these other places because they don't flood. We're like, but they might flood. But also, and we need that data to say this population is worse off than that population. And for air quality, if you just measure it next to the plant, we don't have the comparison farther away from the facility or plant to say, well, the air is better or worse here. And here's how that

relates to populations and who has better access to cleaner air or are less likely to flood. So we kind of had to encourage them, like, you're going to go drive a sniffer around in an area, you think you're not going to find anything. But we need that evidence that you didn't find anything to be able to show that there's an inequality. Because if we don't have the data, you can't show that there's an inequality.

Speaker 1 (29:07)
So

have you found any disparities across the population?

Speaker 2 (29:11)
We're still working on that. Coming soon.

Speaker 3 (29:17)
And one thing I add to that though, when you talk about if we've found anything, so part of the kind of wonderful interaction between the ERR team and our team is the elderly population, Pinpoint of where the elderly population is, obviously they're more vulnerable, and then the younger population, some health issues like asthma and so on.

The interaction between our team and their team with the data that we have is critical to helping these more vulnerable populations in the community.

Speaker 2 (29:57)
Yeah, and we've been able to look at some of those. Our colleague Dongying has looked at some of the state-level data on different health indicators and where do we see populations most affected by different cancers and things like that, and how can that relate to our different data that we're finding and our different population groups, right? And so we've been working on

on those correlations as well.

I think maybe just to give an example from water that came out kind of interesting is that we, flood sensors are mostly along rivers, which makes sense, that's where water is. But then when we have these massive floods of a thousand year flood, you don't have any sensors then that are like miles from the river.

this area of Beaumont-Port Arthur, they got a lot of investment after Harvey to add a lot more sensors. And so one of the things we wanted to make sure was that there was sensors covering the whole population. all different population groups had a sensor that could accurately measure how much flooding they might experience. And we actually found that, they do. That there are sensors that cover...

the whole population, so there's not a scientific disparity in our knowledge for different population groups so that we can say, now we know if it's going to flood and who it's going to affect. you won't have community groups going, it flooded here. And the scientists are going, we don't have any data on that, so we don't know. We know that by putting in all these extra sensors that they've done a really good job of covering the whole population so we can really know where the flooding is happening and who it's happening to.

Speaker 1 (31:46)
I think that's what's been very powerful about y'all's work is the way, because if the data's not there, it seems you can't say anything. so kind of drilling down a little bit more allows us to understand the full picture a little bit better, I think.

Speaker 2 (32:04)
Yeah, and it gives that authoritative view that Noel was talking about that when if you have just a you know a neighborhood that doesn't have a lot of power Going we flood a lot and then you have scientists on the other side going well, we don't know Then there you don't have that authoritative voice to say well, actually we do know and there should be investment here

Speaker 4 (32:24)
Yeah, and here's how we can use our money wiser. Yeah. With a better man of our community. Yeah. Like better stewards.

Speaker 1 (32:32)
I think something as we think about as you live in your community and if you own a home, you're usually concerned about your property value in some way because that then impacts your how you're taxed and and your ability to then generate or create wealth and sell your home in the future. What did how do you reconcile this type of data with property values and then

Would members not want their property labeled in a certain way or not? Does this impact that?

Speaker 2 (33:06)
Yes. This is the challenge. And there's been some stories been popping up lately across the country of different communities wanting to be removed from the FEMA flood maps. those have the FEMA flood map is the one that has a regulatory control of that you have to buy flood insurance if you're.

Speaker 1 (33:07)
You

Speaker 2 (33:30)
property is in a FEMA flood map unless it's been mitigated in terms of like elevated or you know the property is not going to be damaged in some way and you can prove that but structure is not going to be damaged right but we know that flooding is happening in places much outside the FEMA flood maps and that without this mapping information

Speaker 1 (33:39)
structures.

Speaker 2 (33:53)
individuals can't make choices about how to mitigate their property. But it also does, rationally, people might think, well, then it's going to lower my property value or I'm going to be harder to sell because it is risky for a flood. There's not a great argument against that, except the fact that right now we have not really seen that. We're in property values are still increasing.

Places are still, properties are still being bought, even if they're being bought and then the structure is demolished and something more resilient is being built in its place. So I would think from the scientific perspective, we've often seen this happen in a way that is not a loss of property value, but it might be a loss of community that we might see gentrification enter that space. whoever has been there for generations might be pushed out and

than it's bought by different owners or corporations or firms and redeveloped in some way that might be more resilient, but either way is a way to kind of break up neighborhoods.

Speaker 3 (34:58)
Yeah, and some of the discussion was around just what you said, the companies in the area purchasing some of the ⁓ properties. And when we think about the property, I think there was one discussion where someone said that they're staying where they are because they their benefit from the security that the company provide because of their proximity to the plants.

Speaker 1 (35:21)
From crime, not floods or... interesting. Do you have a story personally or with this project or others that really illuminates this work?

Speaker 2 (35:32)
Yeah, one of the things we're seeing in research, and I'll connect it to my personal story, is that insurances, we're more underinsured or uninsured for homes. And that's becoming a bigger challenge for communities. So often, like, if you haven't had a disaster in your community for a long time, you might assume everybody's got insurance, and they'll be fine, and they'll just get their money, and they'll rebuild.

But we're actually pretty dramatically uninsured or underinsured. People are making hard choices about what to pay for, and they're going to choose groceries over insurance if they're down to those are their choices. And this affected my family growing up. My dad was, I'm a first generation college student. My dad was a factory worker. My mom was a receptionist or secretary of some sort most of the time.

Factories kept closing. grew up in Illinois in the Rust Belt. you know, factories started closing and he would have to start over at the bottom at minimum wage jobs and then work his way back up. And so was during some of these periods when I was in high school that we were hit by a tornado and we had not, we were living in a house built in the 1800s. Like this house had stood, this house stood for 120 years, right? And then we get hit by a tornado.

And we didn't have homeowners insurance. My parents were making the choice at that time that we need to put gas in the car to get to work. We need to pay for groceries. Michelle needs clothes to wear to high school. We were making really hard choices, and home insurance wasn't one of them. And the house wasn't destroyed. Our neighbor's house was completely destroyed. They did have insurance. It was rebuilt bigger.

And nicer, know, shortly after that. But our house had, it had roof damage that wasn't really noticeable. Like, and we didn't have insurance, so nobody came and checked the house. We didn't get up on the roof. We didn't do any structural things to it. yeah, over a few years, those small holes just kept leaking and leaking and leaking.

And over time, it had leaked into all the walls and kind of rotted out a lot of the wall space to the point that within five or six years, the house wasn't, it wasn't livable and it was not feasible financially to fix it. And so then we ended up selling it the property for only what the land was worth. And so in the U.S., we often, our houses are usually our biggest source of wealth.

for so many middle class and lower class families. And that is what you need to sell or you need to pass on to your kids to sell. having a property value that then, like after 20 years, we sold it for less than what we bought it for, that generational wealth isn't there. And it wasn't something that could be passed down to me. I mean, I've done fine. But if we think about that as happening to

communities today in an environment where housing values are ridiculous, right? That if their house is damaged and it just gets, you know, it's not going to be sellable because they don't have insurance and they're going to have to sell it for next to nothing and not increase the wealth of their families.

Speaker 1 (38:47)
in

an environment that's impacted regularly from different types of disasters, know, flooding, hurricanes constantly. So I can only imagine, you know, some of the conditions of the homes. Yeah. And along the Gulf Coast and throughout the United States.

Speaker 2 (39:03)
Yeah, in an environment that's much more hot, much more humid than where I grew up. A more mold. A lot more mold going on in those houses. So there could be a lot more health effects coming from living in a house that has a little bit of damage on it. And that little bit of damage really mattered for my family and for other families. It really matters.

Speaker 3 (39:20)
So I have not personally experienced a disaster in these issues, ⁓ thankfully. But as I think about the interviews we've been having and other stories I've heard and so on, one of the things that came out in the interviews we spoke here a minute ago about insurance and the flood and so on, was one of the things that came was that higher elevation.

In these times that we're living in and with the frequency and intensity of disasters, a higher elevation does not necessarily mean that you're safe. One of the interviewers mentioned that one of the areas that traditionally does not flood, in one recent event, they were this deep in water, right? And so that's why things like insurance. ⁓

is critical in order to help to give us some cushion against these events. One of the other things that stood out to me so far in our discussions and our interviews, and that's not necessarily surprising, is that the aid provided by churches and other nonprofits and volunteers, actually they're swifter about providing aid than

down government agencies. And so that speaks to the importance of these organizations within the community and the role they play in disaster response and recovery.

Speaker 1 (40:48)
Well.

Speaker 2 (40:48)
Yeah, think people, when I talk to folks about some of the recovery research I do, folks are incredibly surprised by how many nonprofits are building houses in post-disaster communities in America. And they're building houses for free for the residents to live in. And that this is kind of the state of our current economy at this moment, that folks who are not fully covered by insurance are supported not by FEMA, not by government programs, but...

by nonprofit builders.

Speaker 4 (41:17)
So, we can look ahead. You know, you guys are, we're on year four, the last year, kinda got cut short on our project. But from what you know now, and I you guys are wrapping up the data, but if you had a wish, how this data would be used locally, and you probably already touched on it a little bit with the funding piece, but if you can kinda get specific for some of our listeners, what would you hope this kind of data to be used for? And maybe even touch on,

Speaker 1 (41:17)
Yeah.

Speaker 4 (41:45)
some of what kind of data is out there for people to look at.

Speaker 3 (41:48)
So like you said, to me, personal decisions, making personal decisions and improving at the whole soul level, the preparation, taking disasters seriously, right? Taking the warning seriously and actually ⁓

sharing the information more, using the information to share it with family members. And as Michelle was saying, it's time that we, people look out for one another more than they did in the past.

Speaker 2 (42:22)
Noel brings up this great point of like, the goal is survivor agency, right? Disaster survivor agency, that they aren't compelled to do something because they just don't have enough money to do it, right? That they have choice of where they live and in what community, as much flexible choice as we could.

And then thinking about how the community will address that. So with this data, could we think more about mitigation and preparedness, right? Could we think about how those local churches or local organizations that are so great in response, could we turn their attention to mitigation and give them specific areas and processes that might help with that? So we know for...

say low-income households, there's an issue with deferred maintenance to houses. So houses that have some sort of damage to them before a storm, when the storm happens, the government and nonprofits aren't going to fund that if it was already damaged. How can our community step in and fill that void to do some housing repairs ahead of time that ensures that houses are more safe before the disaster, but then also are more ready to receive funding if a disaster happens?

right? Can we think about unique and new ways to do more mitigation and adaptation rather than just response and recovery every time? I think those are important processes and keeping the data updated and alive is always a hard part to be able to make those decisions. So our colleagues have been working on building dashboards that are

we say dashboard, it's like an online platform where you can play with the data. So you can decide what indicators are most important to you, and you can adjust some of those indicators. it changes the map. So you have a map that has different data on it. It has social data. It will have flooding data and some of the air quality data. And you could say, well, I only want to look at the 100-year floodplain.

And then I want to look at like low income homeowners or something like that. And you could adjust the data to kind of say, well then that highlights these neighborhoods. let me move it. Because each organization has a different kind of service goal and mission. So I want to look at persons with disabilities. Where is that going to impact? And how can I move these variables? And where does that show me need is? That then we can target our programming.

The community can target its programming, the government can target its programming in those ways.

Speaker 4 (45:05)
Yeah, so it's kind of like the decision makers and the and those that are helping could actually get ahead of some of these disasters By using the dashboard and single hey these these areas might be the areas that are affected more Let's do some some pre work. Let's let's get into these communities early instead of after disaster, right? That'd be great

Speaker 2 (45:25)
Right, and on variables that are really important to them. If they really care about having children have safe spaces in their community, they could really highlight that and give it more weight in their models. And so that they can do their variables in that way that really focuses on children's health. And then that means these kind of adaptations might be most useful.

And I think that makes a good point in terms of speaking to our current kind of federal role in this, right? So the previous administration really emphasized social vulnerability. It's been de-emphasized currently. But what I would love to see is that we have this more place-based adapted approach to this. So the local community is really deciding.

Right? And then they're able to justify that. And then if the federal government then can invest in that to support them financially to make different options happen. But it's better than just a blanket approach that says indicator. Right? And every community needs to measure this on the indicator. But that might not be a fit for that community. It might not. not a one size fits Yeah. The one size fits all is terrible, especially for social demographic data.

Speaker 1 (46:28)
Here's your.

Speaker 2 (46:42)
across our wide swath of a country, right? And so I think that by putting it in the hands of locals gives them more, the community also has more agency to argue for what they want and the vision that they see of their community going forward.

Speaker 4 (46:57)
It's a voice for those who feel like their voice isn't heard as much.

Speaker 2 (47:01)
Yeah, we're gonna keep...

Speaker 1 (47:02)
Re-routing for another hour. So how can other scientists, planners, communities build on this work that you've done?

Speaker 2 (47:12)
So doing place-based work, there's always a scientific question of like, well, is it generalizable? Can it apply other places? the outcomes might not apply other places, but the method should apply other places. And that's what I would like to see other places test of like, can they also build?

place-based indicators, right? And how does that work and in what ways will it not work, right? What communities will have trouble making this happen or what factors will affect them being able to identify or can it? Or is it just too much work and let's just use some indicator that already exists. So I think I would like to see more academics try it and then we see what is the variability in these place-based indicators across our country.

And how can they be used? What do they tell us about hazard risk, about social vulnerability, these different topics.

Speaker 3 (48:06)
So I don't know if this is a diversion, but I think I'm approaching your question, Jimmy, from another angle. And because of what I have got out of this project and in working with students, so you asked how can other scientists use it. So one of the things we're doing is we're training.

The next set of scientists, when I look at the Summer Institute, I see how many students have worked on this project. And even for the students I've worked with, I think of one of my students who was, as an agriculture student, was only interested in animals. No, it's finding this work to be very interesting. And so I think we helping to create that next set of scientists and these students who working with us.

master's students, doctoral students, there isn't going to need to be a need for being much convincing about the value of this work and in taking it further. can see them being part of this next set of scientists that we want to carry on this work. And definitely based on this work that I've seen, I know other projects will come out of this.

Speaker 4 (49:12)
That's amazing. So what are some things that are going to come out? I you guys are probably going to write papers. We have a dashboard. Anything else that people can look for?

Speaker 2 (49:22)
Yeah, so for the social vulnerability indicators, we're working up to trying to align them with each of the other themes. So there'll be a water and social vulnerability. There'll be an air and social vulnerability. There'll be a climate heat and social vulnerability kind of.

Geo placement, right? So where are the social vulnerable populations and how does that fit with the hazard risk? As well as then the participatory GIS piece that we're taking in if Noel wants to.

Speaker 3 (49:52)
Talk about that. Yeah, so one of my students is actually taking on the participatory GIS as her thesis work. so she's learning a whole lot. And we're going to pair that with the thematic analysis from the interviews. And again, that's a new area. In fact, she's the one I was speaking about who is no.

really interested in this work and hopefully can be one of the next researchers as we move forward.

Speaker 4 (50:28)
Well, thank you all. thank you all for coming. This was great. ⁓

Speaker 3 (50:30)
Thank you for having me. Fantastic.

Speaker 2 (50:31)
Yeah, this was one, this is a lot of fun.