[This transcript was generated automatically from audio using AI and hasn't been reviewed by a person -- it can contain mistakes, including plausible-sounding sentences that were never actually said. Treat it as a starting point, not a verbatim record.]

[0:00] I don't know if I'm going to be a zoo and it's looking, actually fairly, you've got all those people's part. I mean, you need to look at it like next. Yeah.
[0:12] Yeah, parents are walking, I thought it was a good old man.
[0:15] Well, man, yeah.
[0:17] I want to put parking along, it's definitely done to go to public heights.
[0:22] Yeah, a lot of people park on Westchester, the go-to Westchester.
[0:29] Yeah, who of us came through and got, I mean, we'll hold the chain.
[0:33] Oh, I see the safe route side.
[0:35] You won't be proud of that.
[0:37] I don't know.
[0:38] And they came out of the idea of working with more and more and walk on this trail to the back.
[0:45] to the hospital and to the hospital because I could have gone to the hospital.
[0:48] So as to the hospital.
[0:49] So that's a real kind of building.
[0:50] I feel like I got to do like single dance in the right here.
[0:57] It's a school in the park down the hill.
[0:59] It's full of dancing, but it's full of dance...
[1:00] The park is full of dance and the park is full of dance!
[1:01] You can't...
[1:03] Hello.
[1:04] Well I can't tell you.
[1:05] I can't tell, too.
[1:05] What?
[1:06] I can't tell.
[1:06] Yeah, the can't.
[1:07] The can't.
[1:07] The can't.
[1:08] I can't.
[1:09] You can't tell.
[1:10] I can't tell.
[1:14] We have to be like straw or excessive, so it's not like a height of the wood,
[1:33] but right, that's the density of the wood.
[1:38] In any case, we can do
[1:54] it.
[1:59] Are you all ready to start?
[2:02] Okay, I think we're ready.
[2:03] You know, the diversity is a big issue in the cater bin,
[2:06] been the continuing concern for really several decades and this year our public information
[2:15] officer at Casey Yoder decided to go a little fact-finding and recruited an intern, Christian
[2:24] Perry, who's a student at the Henry Young School at Georgia State to do some basic research
[2:30] about this and the catering.
[2:31] They have a product to their efforts efforts that they're going to share with us tonight.
[2:38] Good evening.
[2:39] I'm going to introduce kind of what the project was about that we got started with at the beginning of the summer.
[2:45] And then I'll hand it over to Chris Jen and he'll kind of go through the data that he pulled and talking about the qualitative that he talked to people.
[2:54] And then we'll kind of wrap it up and give you some time for some questions.
[2:59] So the reason why we decided that we needed to do some baseline research on the state of diversity
[3:06] indicator is because Decaturites have said over time that they value a diverse community
[3:12] and a diverse Decatur.
[3:14] And they've said that since the city has really started doing strategic planning, it was part
[3:19] of the 2000 strategic plan.
[3:21] It was goal number four to maintain an encourage various types of diversity.
[3:25] And it also came up again during the 2010 strategic planning process.
[3:30] There were quite a few roundtable discussions that happened during that planning process.
[3:36] And time and again people said that they valued a diverse community,
[3:40] but they were also concerned that economic forces in the city may diminish diversity.
[3:47] And so out of that came principle B, which is to encourage a diverse and engaged community.
[3:52] And we really started to realize that until we knew what the actual state of diversity was and looked at the actual data,
[3:59] we really couldn't figure out what the next steps were and how the city could continue to plan for this diversity in the future.
[4:07] So, Christian.
[4:12] So, Casey introduced the why to this project and I'm going to jump into the how the research is conductive.
[4:19] So, the foundation of this is in empirical quantitative data.
[4:23] that's what I received my training in, I studied economics as an undergraduate, and all the
[4:28] data that I pulled is maybe publicly available through the United States Census Bureau.
[4:34] I have a number of statistical products available, but I use the DCNL Census, which is
[4:39] conducted every 10 years since 1790, and the American Community Survey, which is conducted
[4:45] on a rolling basis since 2005.
[4:48] So
[4:51] the other aspect of it to complement the data is the qualitative research, took a
[4:56] convene sample of 21 community members and I asked them a series of questions to try to get
[5:03] their take on how the caters change over time. A convene sample is one that it's based off
[5:10] of volunteers so there is that bias, but the 21 people that I spoke with live both in and outside
[5:17] the city and the healthy mix of ages and tendors within the community.
[5:22] I also assured them that the information would be kept anonymous so that they would be
[5:27] comfortable with speaking candidly about the topic.
[5:34] So the scope of this project is of course the city of the cater which is conveniently
[5:40] split into four separate census tracks and a census track is the basic geographical unit
[5:48] that you do demographic research on, on average, to have about 4,000 people, and for the
[5:55] purposes of this research, I gave them neighborhood names to put it in the context.
[6:01] And so, clockwise from census track 2 to 5, I'm calling that Claremont neighborhood, and
[6:07] to the right of that, calling that Sikomore and Great Lakes in the southeast quadrant, calling
[6:14] that went on a park and Southwest is occurs.
[6:20] What I'm making mentioned to the county, of course,
[6:22] I'm talking about the cab county,
[6:24] and what I reference the region.
[6:25] I'm talking about the Atlanta metropolitan statistical area,
[6:29] which is the 28 or so counties around the city of Atlanta.
[6:39] So the research design use for this project
[6:41] is known as a cross section of research.
[6:44] And what that is, it looks at a set of variables
[6:47] for a case over a specified period of time.
[6:51] And it's not experimental, and it's actually used to observe trends and data over time.
[6:56] The variables you spend three different levels, the spend nominal level,
[7:01] coordinate, and interval level.
[7:04] An example of a nominal or a categorical variable that I use in this research is race.
[7:09] And for the purposes of this project, I use three race categories.
[7:14] Black or African American alone, white or Caucasian alone, and non-black minority,
[7:19] which is essentially everything else on a clue to Spatty and Latino designations include native American or Asian
[7:26] ethnicities, multi-racial, essentially everything up. That's not black or white alone.
[7:33] And it's a good point to mention that race, when you form a research perspective, is not a static concept.
[7:39] It's self-identified and the definitions have changed and evolved over time.
[7:43] And nowadays, there's more options that you can identify with than there have ever been.
[7:50] An example that is this 1970 census form here on the left, which is the last year that they listed Negro as a category later to be replaced by African-American dissetrics in example.
[8:01] And so that's a categorical or non-operatable.
[8:05] In Warner Variable is one that increases in a non-domarical degree.
[8:11] And an example that I use in this research is educational attainment.
[8:15] And so the census has seven education categories,
[8:19] starting from less than a ninth grade degree,
[8:21] all the way up to a graduate or professional degree.
[8:25] And lastly, an interval level measure is one with an absolute zero
[8:28] and so on this research, I use income levels
[8:31] and they've all been adjusted for inflation.
[8:38] So moving into what exactly the research found.
[8:48] So a quick search of the definition
[8:49] of a diversity comes with a lot of different things.
[8:52] So this is just a synthesis that I use to define diversity
[8:56] in a most technical form, the state of being
[8:58] diverse, the state of unlikeness, variety, or multi-formity.
[9:03] And as this quote here below, it's a good summary
[9:06] of the context of diversity is key. Historically, when you look at how the world was used, it
[9:13] was not used to identify people at all. So nowadays, when people think about diversity,
[9:18] they automatically think of characteristics of people, which is important, moving forward.
[9:27] And so what I asked, these 21 community members, what they thought of, what they personally defined
[9:33] diversity is, essentially had five different response types. The first of those being, I don't know,
[9:39] with that means which is fair because that diversity is an abstract and
[9:44] intangible concept that was about two or three of the cases the second
[9:49] level was a technical definition for example a resident said that diversity
[9:54] is having a lot of choices of variety of people white female age 72 building
[10:01] on that the next type of category was one that automatically implied race
[10:07] specifically black and white, for example, black female age 78 defined diversity simply as white and black coming together.
[10:20] So the fourth level,
[10:24] in a few years, acknowledged that race was the first implication, but expanded that definition to talk about more than just race as a variable.
[10:34] For example, race is the tip of the iceberg. Diversity is a mixture of income, talent,
[10:40] experiences, and nationalities. Blackmail age 53. And the last level, last type of definition,
[10:48] I got introduced the notion of embracing and valuing differences, kind of the above and beyond
[10:54] kind of definition. Diversity is more than being accepting a tolerant of people different than
[11:00] It's embracing that as a positive part of your life.
[11:03] Different experiences, backgrounds, interests.
[11:06] It's not racially based, age based, gender based,
[11:09] or even family status based, it's having all of that stuff.
[11:13] White female age 53.
[11:20] So the first variable that I looked at to define diversity
[11:23] is race, and that's for two major reasons.
[11:28] It's the most visible indicator of diversity.
[11:31] It's the color of your skin.
[11:32] You can't change it and you can't hide it.
[11:34] And in the Cater, particularly, there's a historically only bento races, which is not unique
[11:39] of the Cater, it's indicative of the Southern culture and the Southern legacy that we have.
[11:49] And so the next few slides, we're going to show you kind of like a heat map of the concentration
[11:55] of African-American in the city of the Cater, starting back in 1940,
[12:05] and the darker the area,
[12:06] the higher concentration of black or African Americans.
[12:28] So this is looking at the sheer of the ratio
[12:33] of the population for those three race categories, white, black,
[12:37] and non-black minority.
[12:39] And so the first thing you notice is that the share of the white
[12:42] population indicator has increased over the last 20 years,
[12:46] why that of the black population has decreased.
[12:49] But you do see the emergence of a non-black minority, which did not exist in 1990.
[13:02] So this is breaking out that racial composition of the population by neighborhood.
[13:07] And it's interesting because, by the way, at the back, you can see that
[13:12] South Dakota held the majority of the black population on North Dakota held the majority of the white population.
[13:18] And this is 1990.
[13:21] And to contrast, you see that the racial composition is a lot different.
[13:28] While it is more integrated, yes, the share of the black population,
[13:31] and the absolute number, that's the scale we're looking at here, has decreased tremendously.
[13:42] Oh, of course, just as an example, formally held the largest share of the black population.
[13:48] And from 1990 to 2010, it dropped from about 4,000 black residents to just 1,200 residents.
[14:08] So, trying to put the cater into context, this is comparing it to the amount of metropolitan region.
[14:14] And immediately, you can see that the opposite ratio trend is going on.
[14:19] regionally seated the white chair, the population is decreasing the black
[14:22] chairs increasing at a slower rate and that the non-black minority is
[14:28] increasing at a much faster rate than it is in decator.
[14:35] So comparing it to
[14:36] two of the the nine benchmark cities that the city uses to compare performance
[14:42] standards we have Carter'sville which is in industrial town of 75 in Bartow
[14:47] county and swan in Georgia, which is up 85 in Gwynette County and while they both have
[14:54] different racial compositions they do more or less mirror the regional trend and decayed or
[15:03] So
[15:10] when you break out the racial composition by age group, I would like this quote because it introduced the notion that decadence moving away from an old diversity, which is characterized by black and white alone and moving towards a new diversity where these different ethnic and racial groups have a much larger presence.
[15:32] And for example, in the chat population under five is where you see this presence taking the most form.
[15:38] And as the age groups get older, you see this become less and less prevalent.
[15:48] You can see that the non-black minorities are disproportionately in the 17 and below age group
[15:55] while the African-American population is disproportionately in the older age groups.
[16:04] And to put that in the more perspective, while one in five
[16:07] Decatur residents is black, about one in three of Decatur residents,
[16:11] 65 and over is black.
[16:20] So this is looking at the age breakdown alone.
[16:26] So regionally and countywide, we sway more towards the younger side.
[16:33] But Decatur is unique because it is a community that's
[16:37] ways towards the older side within a county and a region that
[16:41] primarily young. The top arrow here shows between 2000 and 2010 how the share
[16:49] the population 25 to 34 years old is quickly replaced by the share that it's 55 to 64 years old.
[16:59] And to the right of it, you see how that trend is not observed in the county,
[17:03] no national renewal regionally.
[17:10] So this is looking at an average household sizes
[17:15] and it's
[17:16] that researchers try to get a beat on the different types of families that are living in
[17:21] the community.
[17:22] And so to the right side of the chart, you can see that the K-D-R-N-Average has had smaller
[17:26] household sizes, but if you look at it spatially, by neighborly, then North Dakota has
[17:32] had much smaller household sizes, while South Dakota has had much larger household sizes.
[17:41] K-D-R-Z-O-S-O-S-Stork had a lower share of households with children than the other benchmarks.
[17:50] So the census acts a question, I'm going to ask, what's the sex of the householder, the
[17:56] head of the household, and the sex of their partner?
[17:58] And this is what research is used to get a beat on the gay and lesbian community within
[18:05] an area.
[18:06] And so the blue bar is looking at the share of same-sex households as a percentage of the total
[18:11] households in that area.
[18:13] So nationally, about 8% of the households are same-sex households split, almost evenly
[18:18] between same-sex male and same-sex female households. And just looking at the blue bar,
[18:23] you can see that Atlanta and the Cap County already have a much higher share of these types
[18:28] of households. And looking at the cater, it has about four times the national concentration,
[18:35] and it means having it towards the same-sex female households. In fact, between 2000 and 2010,
[18:41] there was actually a 5% net decrease in the number of same-sex male households.
[18:49] If I read that right, it's still less than three and a half percent of the same sex households.
[18:57] For the kid overall, yes.
[19:01] That seems like a small percentage for my home observations.
[19:13] But that's just self identified on the census.
[19:17] That's just self identified on the census data.
[19:21] Right, right. It's a proxy for the community. It's not a direct question at X, which is actually warrantational.
[19:29] So next we're going to add educational attainment from 1999 to 2010.
[19:35] Decatur is extremely well-educated.
[19:38] While in 1990 roughly 1 in 6 resident hat,
[19:43] a graduate of professional degree, fast-forward to 2010 and 1 in 3 resident hat,
[19:48] the highest level of education on this survey,
[19:52] which is about three times the concentration of the national.
[20:00] So looking at meeting household income,
[20:03] and you use meeting when you talk about income levels,
[20:05] because the averages are easily swayed by outliers.
[20:10] The cater,
[20:11] meeting household level of historically was lower than that of the benchmarks,
[20:16] but quickly caught up in the early 2000s.
[20:20] And if you look at that spatially, you see that the greatest growth has been in South
[20:25] Decatur households at about 1985,000 a year, respectively.
[20:34] And you also noticed that the green and the purple bars between 2000 and 2010 that all
[20:41] the other benchmarks saw a net loss and then meeting income level, which was of course the recession
[20:47] years. Yeah, Decatur's meeting income level still continued to increase.
[20:53] And if you look at this
[20:54] increase in that same time period by the race of the household, you see that while Decatur
[21:00] household overall increased and white households overall saw an increase in their income, that black
[21:07] households saw a decrease of about 50% of their meeting income. It dropped from about 34,000 a year
[21:14] to about 17,000 a year.
[21:28] And of course, if variables are presented or not comprehensive, I encourage you to read the report
[21:33] and I'd get into all the native-gritty details of all the data that have worked on this
[21:37] summer.
[21:38] And I'm going to hand it back over to Katie's here to talk about what's next.
[21:42] Well, before you do that, would you just back up one minute at those incomes?
[21:46] We went through that so quickly,
[21:50] and so
[21:54] the highest incomes in the 2010,
[21:56] and senses are on the south side, yes, and the very highest are in Oakhurst.
[22:08] Yep, and it's also interesting because North Decatur neighborhoods also saw a net loss
[22:12] in the immediate income in the recession years, but that's when South Decatur saw the greatest
[22:17] increases in their income levels.
[22:21] And of course it's not to say that everyone that lives in Oakhurst got a promotion or
[22:24] It's the only counts, the income level of the people that look there during the census year.
[22:33] And that was 2010, correct?
[22:37] When the actual counting of heads happens.
[22:43] Let me go back to the slide.
[22:45] They had like the arrows going.
[22:48] Each bird down.
[22:49] Yeah, that way.
[22:55] And tell us again what we're looking at.
[22:56] Okay, so this is just here.
[23:00] Come right outside.
[23:01] I don't know. Thanks Keesing.
[23:04] This is the share of the population as a percentage of that age group.
[23:11] And so the highest age group in 2004, the city indicator was the 25 to 34 year old age group.
[23:20] And that share of the population decreased about 5%.
[23:24] And at the same time, the share of the population that was 55 to 64-year-olds increased
[23:30] to 5% in just 10 years.
[23:32] And you don't see that replicated at any other levels.
[23:37] And what is the blue bar?
[23:38] That's an 18%.
[23:41] That's a 35-year-old.
[23:43] So what do you take that to me?
[23:48] It means that you've got to be in your higher earning years to live in the cater anymore.
[23:54] Well, looking at it alone, it's hard to make any concrete differences.
[24:00] But I will say that if you look at these populations as a share of the county population,
[24:10] overall, that the caterers have a disproportionately high amount of the cab counties older
[24:17] residents from 65 and older, and that's going back to 1980.
[24:25] we'll be interesting to see how this may change in the next census count because I think
[24:33] with the continued, I guess, influx of people with children we may see this shift a little bit
[24:43] of that 25 to 34 and the 35 to 44. Also with the multifamily young professionals.
[24:52] So we made a place that I think that's one thing that was hard.
[24:57] You don't get people out of college not having people with any opportunities to move to the care.
[25:02] Yeah, yeah.
[25:03] So the 18 to 24 may also, or that, yeah, go up considerably, because that's pretty low for the cater.
[25:18] Do you have a question on A's in particular?
[25:23] You can move on now.
[25:24] Thank you.
[25:26] I guess to tell them a little bit.
[25:35] So since this project that Christian worked on was only for eight weeks this summer there
[25:40] were some limits to what we could do in terms of our research and we do think that definitely
[25:46] we should consider doing more in-depth qualitative research meaning more interviews with residents
[25:51] and people who live maybe just outside to cater as well as possibly some actual like real focus groups.
[25:57] You know Christian was a one-man show so he was able to talk to 21 people which was great but
[26:03] I think there's more opportunity to have more conversations there.
[26:07] Quantitatively, it would be interesting to get more data and I know the city is in the process
[26:13] of this with some of the pedestrian counts and cyclists counts and other types of transportation
[26:18] patterns to see what people are doing in the city.
[26:22] It would also be interesting to get some new and updated demographic information on event
[26:28] attendance that something that can be difficult to capture unless you hire an outside
[26:33] firms to actually do some of those surveys on site the day of the event, because most of
[26:39] our events are open and are not ticketed. So it's very hard to capture exactly how many
[26:45] people are coming much less what their demographic makeup is. It would also be great if we could
[26:51] get some data on the demographics of city staff to see if the people who actually work for this
[26:56] city and sort of the community represent the community as well. Political affiliation I think would
[27:02] interesting but there are challenges pulling that type of data in the state of Georgia because
[27:07] we do not have party registration. There are ways to kind of extrapolate people's party registration,
[27:14] but it's a little bit more in depth than it's kind of complicated. Speaking of quantitative things
[27:20] that we really are really interesting to get, but are very difficult to capture would be migration patterns,
[27:25] meaning where people coming from when they move into the city and where are they going when they
[27:32] It's very difficult to capture.
[27:35] There's a question, there's not really anything that tracks that, right?
[27:39] What we came to our conclusion?
[27:41] You came to our conclusion.
[27:42] You came to our conclusion.
[27:45] You came to our conclusion, but when they come here, but when they leave here, we have no way
[27:49] of knowing we're on our thermoving too.
[27:52] Which actually would probably be the most useful piece of data.
[27:55] Also occupation.
[27:57] Christian started to look at occupation, but even more than race as a changing definition
[28:02] over time, occupations really change from census to census, just in 10 years.
[28:08] I mean, you think about some jobs that we have now in the tech industry, they didn't exist
[28:13] five years ago and much less 10 years ago. So it's very hard to capture occupational trends
[28:17] in the city over time and what people are doing.
[28:23] So that kind of brings us to our final point,
[28:25] which are, I'm sorry, Casey. No, they're at a hand. Unless you did it in some very general
[28:29] terms, this is a service industry, this is a manufacturing industry, this is a
[28:36] tech industry, something that just very general terms we might
[28:40] get some handles on it, because clearly, you know, it's more of a service
[28:45] than a work force today than it was 25 years ago, we know that, so you could
[28:51] see some trends like that if you did it in a very general process.
[28:55] I don't know about the migration patterns. Do you know if any of the real estate folks
[29:01] keep track of any of that data and we get a wholesale information? I wonder if we have
[29:09] to answer those sources to at least get a snapshot look at how many houses are being sold
[29:17] because an elderly past person passes away or they go to live with a family member.
[29:24] that doesn't live indicator or that might be one source that we could not get exact figures,
[29:32] but certainly trending data.
[29:34] Now, that's a really great idea. I just wrote it down. We'll look into that and see what our options
[29:38] are with that. So, you will actually start talking about some options that the city can do to
[29:46] encourage diversity already when you mentioned that 25 to 34-year-old age demographic and how
[29:52] There's not a lot of housing options in the city for them right now.
[29:55] And we're doing a couple of things to try and address that.
[29:58] One is the three.
[30:00] The apartment complex is that are currently in development around downtown. The other is the unified development ordinance that I know you're all very intimately acquainted with, that is actually going to have some new zoning options for housing, which means that there might be some options to build smaller cottage court still houses and different things like that that would encourage maybe smaller households which often tend to skew a little bit younger than people who are looking for the larger house where they can have several kinds.
[30:30] kids.
[30:32] In terms of economic incentives that the city could do, our size is kind of our challenge
[30:38] here. A lot of larger cities can actually do more economic incentives than would make sense
[30:44] for the city of Decayters since we're only 4.2 square miles. So what I'm talking about here
[30:49] are things like wages, you know, the city of Decayter passing a minimum wage or something like
[30:54] that doesn't really make a lot of sense since most of the people who live in the city of Decayter
[30:59] actually don't work in the city of Decatur. They work, you know, Emory, CDC, Downtown Atlanta,
[31:05] Midtown, Primeter, so anything along those lines really probably wouldn't impact the household
[31:14] income residents in the city. In terms of transit, we actually are very unique especially for the
[31:22] Atlanta area than that we have three transit stations in the city limits of Decatur and we are actually
[31:28] working with Marta to redevelop some of those empty parking lots, you know, the
[31:31] avondil station, which I think will also help with that multi-family housing we
[31:36] are talking about and I believe some of that is actually going to have some senior
[31:40] targeted housing as well.
[31:45] Oh senior and targeted income. So that's obviously not
[31:48] going to be built tomorrow but that's in our long-range plans already. Also with
[31:53] transit is when you're talking about that 25 to 34 year old age range, the
[31:57] shirt shows time and time again and with where people my age choose to live that we're
[32:04] looking for walkable communities which the cater has obviously invested highly into sidewalks
[32:10] which are great actually for every age anyone can use them and bike ability so we've been doing
[32:16] a lot with bike lanes and caros and I know that something that we're continuing to do and a lot of
[32:21] our long range transportation planning so that seems to be on the right track to help kind of encourage
[32:26] some younger residents to move into the city and then finally I know we're in the process
[32:32] of developing a annexation plan and that also will probably give us some options to further
[32:39] encourage diversity in the city and possibly annex in areas that have a different ethnic
[32:45] and racial groups than are already living the city and so that will be presents new opportunities
[32:50] as well.
[32:55] So questions, this is a fantastic graphic from the U.S. Census Bureau. And I don't
[33:03] think they use those machines anymore. Although it's the federal government, so I can't
[33:08] say for certain.
[33:11] There are two things that come to my mind. I certainly understand us why to get information
[33:17] of for those who actually attend our events on the square and so forth, but I've always wondered
[33:23] about those who do not. What is it that folks aren't coming to? What is it that residents
[33:31] who have ever are missing?
[33:35] And then another thought that came to mind is we were looking at those
[33:38] graphs and so forth. I wonder if there's any place where there's kind of a layering of
[33:44] of age and what's happening with real estate and tear downs and reconstructions and that type
[33:52] of thing.
[33:52] I think I have an idea of what has happened of course it is all assumptions and so forth.
[33:58] But I wonder if there are resources where those can be layered on top of each other to
[34:04] give us a sense of what's happening.
[34:06] I think that that would definitely be something for further research because it'd be something
[34:10] of a multi-step process.
[34:12] I know that having taught to our design environment
[34:16] and construction division before I'm this issue,
[34:19] we've only really been tracking tear downs
[34:20] for a couple of years now as distinct from renovations.
[34:25] So the data doesn't go back very far,
[34:27] but it would be interesting, I think, to layer that,
[34:30] even just for a couple of years,
[34:32] to kind of see where those intersections happen.
[34:35] So I'd be pulling that real estate data
[34:37] and the permitting data, and matching them up.
[34:46] I have a question for Kristen, that's OK.
[34:49] How are the 21 people selected?
[34:52] And can you tell us just, I mean, you highlighted some of the folks,
[34:56] can you tell us kind of the basic demographics that you looked at?
[35:01] Well, the most important qualification was that they'd
[35:04] be interested in the had time to do it this summer.
[35:07] But I did try to not have all people that lived in a certain neighborhood, I tried to have people that had moved out of the city and lived just on the city limits.
[35:17] I tried to be as diverse in any other variables that describe them as I could, but it's pretty limited with only 21 people.
[35:27] Were there any people in that say 18 to 24 age groups in that?
[35:32] Not in that young age group. No. I think the youngest was 32.
[35:44] Is that it?
[35:45] Oh, what's that? Thank you. Tell us now. Tell us for what's next for you.
[35:51] All right. Well, uh, we're working on another project. So I...
[35:57] I'm the biggest. I'm the biggest. Thank you.
[36:02] Cool. That's good.
[36:04] Did we kind of like a phase two of this?
[36:06] Okay, that's great. And you said that there was a report. Is there a full-on report that we're
[36:12] there is? We're wrapping it up. Now, we're doing some last minute editing and
[36:17] cross-reference in data. Okay. Well, will there be specific
[36:21] next steps if you would recommend or recommendations as to
[36:25] what you think might be the next? Yeah, absolutely. It's more developed than what's in the slide, for sure.
[36:33] Nice job. Really, really, seriously.
[36:36] Yeah, thank you very much for the presentation and thank you for all that. Good work.
[36:42] That's good. Thank you very much.
[36:45] And good luck with whatever it is you're going to do next.
[36:49] Alright, if that concludes the work session, we'll talk a few minutes break and be back here at 7.