Law and Society, he gave a much briefer presentation, based on this paper at the PAA meetings, and it was so interesting that I invited him to come and give the full-bore version today. With that, I will hand it over to John. Thank you. Thanks, Susan. Thank you. That was very nice. But full-bore, I guess, didn't want to talk like a New Yorker. I took two breaths, I think, during the presentation at PAA. Segregation through the lens of housing transition is the talk that I'm giving here. Most people know that I study neighborhoods, how neighborhoods change over time. A lot of my work focuses on crime as one outcome. That's just one way we can measure the quality of the neighborhood, what it's like, is it good or bad? If I live in a neighborhood with little crime, that's better than having a lot of crime. But my research, because I'm interested in how neighborhoods change, a fundamental process of how neighborhoods change, of course, is people living in them, and people who move in and move out of neighborhoods. So unnaturally, part of my research gets pulled in this direction of residential mobility decisions. Some of my work has looked at segregation because that ends up playing into, that's kind of an outcome, one more outcome of the process. Some of my work has looked at how mobility decisions are affected by crime as well. This one is, this particular paper working on here is focused on residential mobility decisions, mostly looking at moving into the neighborhood. So again, if you think of segregation, segregation can only happen basically when at the level of the housing unit, when we see a transition, it's the only way you're gonna get to a segregated outcome. It takes over time, it takes a process, but that's fundamentally what it takes to get there. So for my interest here, I'm interested in focusing on housing units. I'm gonna be following the data set. I'm gonna be using American Housing Survey, follows housing units over time, so it's a little different than other studies using following longitudinal samples of people who they're following where the people move, which is interesting, but it's a different question. So here it's a focus on people moving into the unit. So the question, how do people choose what unit to move into? What is the process? Do people care about the racial ethnic composition? I'm not gonna be focused here on trying to get at the perceptual sorts of things as a whole literature on that. I'm more just looking at some of the patterns in what we get from it. There's some interesting implications I think from some of those patterns that I'll talk about in a bit that some of the perceptual information out there focused on a very small unit of analysis. I'm actually gonna be using that small unit of analysis and showing how it captures part of the process, but not perhaps all of it. So when people make a decision where to move, what unit to move into, what are they looking at? If racial ethnic composition matters, that's a question we could even back up and ask, but if they're looking at that, what area are they looking at? Are they looking at some broader neighborhood? Of course that's a mushy concept, that's something I work with a lot and some of my work trying to get at what is a neighborhood? How do we define what it is? But if you set that aside for a moment, say well there's some sense of a broader area which is a neighborhood, is that what people look at? They look at the racial ethnic composition of that area and let that guide their decision. Or is it something much smaller? I refer to the micro neighborhood composition, this term is mushy itself as well, but nevermind. More and more this idea is kind of popping up. Sometimes you see it referred to as the street block where Granis has used that term a lot. The idea basically you can think of a street segment both sides of the street, where bounded by intersections at either end, kind of a small area in the suburbs, this is often what we think of as a block party, you see this real cohesiveness. Granis has done some work recently looking at the formation of what are referred to as neighborhood ties, neighborly ties, which is a vague concept in and of itself, but nevermind. But there you see this real strong geographic boundary where people are much more likely to form ties with people next door to them across the street and then it decays really quickly. So again that suggests that this local street really matters. And so maybe we would think when people make a decision on where to move to, that they're looking at the racial ethnic composition of the street. Or is it, do they look at the current residents, the racial ethnic composition of the household that they're moving into? This is something we're looking at here. I've not seen much in the literature looking at this, but it's something we're gonna consider as well in this paper here. How does segregation come about? This group here, I don't think I spent a lot of time I would imagine on this, but there's different theories out in the literature that have suggested how we get segregation coming about. Here's a few that I'm gonna talk, I'll just kind of go through briefly. And in particular I wanna say, well what implications would they have for these different units of analysis? Whether we're talking about whether it's the racial ethnic composition of the household or the micro neighborhood or the broader neighborhood that matter. There's the place stratification theory, the household preferences theory, which is this idea of people having a preference what the racial ethnic composition of the people that live near them are. Place stratification is the notion more that race matters even above and beyond the economic resources we have. Differential economic resources is more the classic assimilation model idea that as people gain economic resources you'd see less segregation and whatever you do see is just driven by this economic process. Discrimination and steering are the notion that you'd see access to certain units being denied or steered away from, if you will. Social networks, the idea that there's this networking process that goes on that somehow contacts are important for bringing about information about units. And then the last one that I'm gonna talk about a bit here that I'm gonna suggest at least throw out there as a possible part of the thing to think about is signaling, an idea from economics, I'll get to that in a bit. So again, talking about each of these, what do they mean for these processes? Place stratification theory, if it is indeed the case that this process works, what we really should see arguably is that the racial ethnic composition of the broader neighborhood is what you would see mattering. This is much more of a larger structural theory. It doesn't focus so much on micro areas, micro neighborhoods and that kind of thing. As much. Household preferences on the other hand is a theory that gets a little more micro as you might well imagine. Again, it's this idea of preferences. So preferences that are driving what the area looks like. So you might well think that the micro composition of both the local area and the broader neighborhood would matter for someone's preferences. They wouldn't just look at their local block and then ignore the broader area. According to this theory, it'd be less reason perhaps to think that the household itself composition or the characteristics of the previous household would matter to them. But that's what we'd expect from that. This notion of differential economic resources to classic assimilation model concepts. Well one, if arguably if we account for economic resources we shouldn't really see much other effect for race ethnicity. So it's of less interest to us here. Discrimination and steering a bit trickier to think about. What are the consequences? Discrimination, it depends how you model this. What do you think how the process works? If it works at the level of the housing unit then that's where we would see it. We would see this process where there'd be reduced likelihood that a housing unit would transition from a white household to a non-white household. So you wouldn't necessarily see it at the broader neighborhood or even the micro neighborhood. But it would happen right at the level of the housing unit. Steering, which is this notion of real estate agents playing this important role of guiding prospective residents to certain housing units, certain neighborhoods. What might matter there? Well you might think that the composition of the micro neighborhood or the broader neighborhood would matter. Although at the, originally I wrote this as the more I've thought about it, could you make an argument that steering might happen based on the race ethnicity of the previous, or the current occupants of the unit? Something that might occur, I don't know. It would require the real estate agent knowing the race ethnicity of the previous people would they use that as a cue of who to show the unit to. If that were the case, you could see that process occur as well. Social networks, social networking, the idea of who people talk to, how they get information about different units, different neighborhoods. How would we see this process play out? You could think about it in a couple different ways. One, we might see that the composition of the micro neighborhood might matter, or we might see that the housing unit matters. The housing unit, you can imagine this process if people find out the availability of a unit. Someone's moving out of a unit, they send information out through their networks, we see this differential likelihood of networks being members of the same race, but then you could see that information going to people of the same race ethnicity, and it could play out that way. John, are you talking about both turnover and rental units and owner occupied, or? Yes, I'm mushing them together, that's a great point. But we can talk about that. So it seems to be about the different processes. Exactly, yeah, that people raised that, posed that, yeah. What are you thinking of, in any particular? Well, the flow of information about finding out about units, and both the process by which the next occupant is determined, is it a real estate agent who's selling it, or a rental agent who's trying to fill it? So I think that there might be differences here. Yeah. For the analysis here, this initial analysis was mushing them together, if you will. I was pushing that direction of trying them. Some of the models I tried differently didn't show too many difference, not as many as some people expected to see, if you're not seeing, but it, there's definitely a different process that goes on there, and we'll get to that in just a moment when I talk about this idea of signaling. When we start thinking about that, how that plays out in a rental, or an owner situation might be different. So it's definitely worth, yeah, to the extent that that plays out differently, that's an important empirical distinction to make. And so the idea of the micro neighborhood is this idea of information you find out about others nearby, that could play out perhaps in a rental building. You know, you see a unit become available, you send out information to your network ties, and again, if they're more differentially, you're the same race ethnicity, you can see that process play out that way. And likewise, on the micro neighborhood, if you know a unit is available. The final idea that I'm kind of going through that I'm gonna kind of put out there is an idea to think about is this notion of signaling. It comes from economics, and at root, it's this idea of information asymmetry. It's been used, initially it was proposed for labor markets, those who are familiar with the idea, this, the classic case, the principal agent problem, where this person coming in wanting to get employment, knows how, I know how good a worker I am, but the person hiring me doesn't know that about me. They're trying to interview me, they're trying to figure out something about me. So they're looking for signals from me. What kind of a worker am I? And the early literature, the one idea was this idea of getting a degree, right?  Brody, you sit there. Can't I forbid? Can't I forbid? I have one, I'm happy. So you get this degree and it's a sign of certain quality that you have. And that sends a signal to the potential employer. So again, it's this information, a symmetry's popped up in other literature as well, having to do, basically any time you can see this process come up, they've done it in the investment literature, it's popped up a bit there. One implication of it that then was raised early on by economists, this notion that you can get this sort of statistical discrimination, they pointed out, if there's a tendency for one group to be poorer workers, well then if I see someone as a poorer worker, I can statistically infer that they're more likely to be a poorer worker given their characteristics. So that is a potential problem that can pop up with that. I'm suggesting the same situation in a sense can occur here, that the person living in the housing unit knows more about it than I do as a potential person moving in. I'm trying to figure that out, right? It's like buying a car, right? You're trying to figure out what kind of shape is new. And as well, they know more about the neighborhood than me as the perspective person moving in. And again, I'm kind of a detective when trying to figure that out. A lot of my work focuses on crime and there you can see the same potential thing becoming an issue. Someone who lives in the neighborhood knows, they may have seen things happening, it seems like the neighborhood's going downhill. Me as someone coming to consider the unit has less information about that. I'm trying to pick that up. I'm looking for signals, right, if you will. Maybe I'm looking for disorder or that sort of thing if I'm interested in being concerned about crime. If for some reason I have a particular preferences about race, ethnicity, would I use the race, ethnicity of the current household as a potential signal for something like that? What it would suggest to me, might suggest that, A, this is an indication of the race, ethnicity of the area, perhaps. It's a crude estimate, but other than me going door to door walking around and trying to see what the race, ethnicity is, that people might be one simple clue. Or another idea is that even if it's a racially, ethnically mixed neighborhood, this might be a sign to me that this is a welcome area for someone of my race, ethnicity, if that was something. For whatever reason I was concerned about. Because you just mentioned a minute that I was interested in some of the earlier versions where if I have a preference for living in a neighborhood that has people of this race and not people of that race, how do those theoretical approaches deal with that the information problem? How do I find out what the races of the people in the neighborhood are? I can't go to a door, they're not necessarily standing out on their porch steps. How are you supposed to, clearly if I lived in the neighborhood long enough I would eventually see people leave their houses unless they live in a suburb and they'll leave or see their cars. But how am I supposed to find out about this as a potential home buyer? I can't ask. I mean that's an excellent question. I don't know, are there people in here who know that have a sense of that? It's great I can. Years ago they did the National Survey of Black Americans and they were especially interested in trying to find Black families in largely Black neighborhoods. And it was an incredibly reliable process to ask any White resident. There were any Black residents in the neighborhood. Yeah. So that's the kind of search you're interested in. It's not that difficult once you start to just ask a few questions. Okay I guess that's the question is like as a potential home buyer is that something that people feel is politically okay to ask somebody or does that sound like a racist thing to ask? So are there any Black people in this neighborhood? I don't know. Anything you can imagine asking somebody that? Right. Yes. I'm sure. That's why you get a real estate agent, right? And then a real estate agent finds those things out. Well the real estate agent knows the neighborhoods, right? If they do, yeah. Well that's their business to assess. But it's illegal for them to tell you. Right, but they can show you certain houses and they can say, okay go. That it violates the Fair Housing Act because it's steering if you start talking about the racial composition or the crime level. But they can talk about the school district and the other amenities in the neighborhood. Okay. That's what I can only touch on. I don't know if you're a sociologist or you're not. I mean you touch, I mean that instrument, the crime is interesting because there's a little side note. I said crime in the neighborhood that I'm trying to collect data. And a lot of cities, some cities will provide it on the web, others won't and I think the concern is just that, that people will use that as a cue for inferring something else from it. But it's a tricky question at how you would determine that. Yeah, a real estate agent presumably would know that but their information would be imperfect I suppose. So then the question is, there might even be a question. Some have posed, I've said that, given this talk before and some of them immediately shot back, no way do people know the race ethnicity of previous residents, which I don't, I don't, I've heard it was such a sturdiness that it kind of, oh God, maybe I don't know something here. How could people know it or how could they infer it? One, you might meet them, it's very possible that you meet the previous residents. Two, they might be described by the real estate agent in some way. Three, I pose this sort of joking, new residents may be cultural anthropologists. I say half joking, but maybe not, right? We don't, we may be better than we realize and there's interesting evidence about this, but if you go walking through a house, can you tell the race ethnicity of the people living there? Susan mentioned it, what's this little museum up in San Francisco? Oh, it's called the Exploratorium. It's a kid's science museum essentially, but one of the exhibits there gives you pictures of a house and it says, can you guess who lives here? And they'll give you some of the Latina woman, they'll give you say an Asian couple or pictures of people who are very different and then they'll show you the house and you have to guess by the clues and one will have a picture of Milagros on it so let's see who might live there. Or another will have pictures on the refrigerator that are of an Asian family. Well, let's see who might live there. And you could very easily guess who lived in one kind of house. And so it's an exhibit in the museum. How common is staging, I mean for home sales? That's a key question, that's a key question. And on the Bay Area, you don't sell a house without having it staged. Yeah, and describe it, what is staging? So basically you have a professional come in, take all your stuff out and bring in stuff to make your house look appealing. Better for you. And it's appealing to sort of a certain kind of, I mean, so there again, it's a certain kind of buyer. It's still a cultural, yeah, yeah, yeah. But it's sending a certain kind of signal, right? And they say, you know, yeah, my understanding is they take all the pictures, all the family pictures out and yeah. I mean, they might, you know, if they're really good, they might bring in pictures of the prospective buyers' families and put them up. Right, right, right. How common is that up there? Do you know? It's pretty much universal. Yeah, I'm trying to get, this data set I'm using in his back would be the 80s into the very early 90s, do you suppose that was going on back then, you know? That's something that kind of need to get a sense of to what extent, if that is indeed prominent now, that would pose a bit of a problem for this, but. I know the rental market was tighter in the early 90s, but I don't know about the buying market. Yeah, okay. So again, how might we do this? Different ways, photos in the wall, unless it's been in a professional stage. Magazines line about, right? Magazines are an interesting cultural reference. And the type of magazines that people read can give you a clue. The art, music that's sitting around, decorations that are up and about. Empirical evidence, so this is a book back in the early 80s. So again, using late 1970s data found that 96% of respondents knew the race, ethnicity of the previous residents. So we're pretty strong empirical evidence. Now, does that still hold now? That's something, you know, now we're. That's after the fact, right? That's after the fact. Yeah, after the fact. Yeah, whether it holds now is another question as well. I'll just briefly talk about previous work that's focused on the same idea of housing unit transition. Marulo did a study back, again, using the same data set as what I'm gonna be using here, showing transitions in housing units, but didn't take into account the context at all. So he was just focusing this narrow question, do white people tend to replace other white people, Asians replace Asians, et cetera, and found really strong homophilia. But again, not taking into account the context. Rosenbaum and colleagues using New York City data done a number of studies, but there they've done the housing unit, but then they've also taken into account a context. But for them, there are neighborhoods, if you will, as they term them, are 100,000 people or more, which you can argue is a pretty big neighborhood. Regardless of how dense New York City is, it's still pretty darn big. Ellen used census tracts as the context and found this effect. Again, the racial ethnic composition of the tract, effect of who moved in, and at the same time, she still found the same household effect, even controlling for the composition of the tract, there was still this effect where people of the same race tended to replace one another. In there, she speculated that she wasn't sure if this was entirely a household thing, it could be the micro neighborhood as well as driving that. And with my data, that's when I'm gonna be able to tease out, we're gonna be able to take into account characteristics in the micro neighborhood. Sam Friedman has a forthcoming paper looking at micro neighborhoods and tracts, and then studies of racial ethnic preferences, it's interesting to point out that they've shown these cards to people and the cards are basically a micro neighborhood. And that's sort of, and it's interesting and then juxtaposed out with the segregation literature that uses tracts. So certainly the preferences have focused on a real small unit, so I'm gonna try to measure that here. The data, again, American Housing Survey, the neighborhood sub-sample, this was drawn in three years, 1985, 89, 93. They did this extra little sample, I didn't even put the numbers on there, did I? I have to do this, I've done this so many times, there's many others, over 670 micro neighborhoods, I think in 85, and then they supplemented that in 89 and 93 with new micro neighborhoods that came along. So I've got two move periods, I can study people moving from 85 to 89, do they move, 89 to 93. And movement being just does the head of the household change over that four year time period, so I don't know, I mean just at the beginning of the end, I don't know how many moved or anything like that. And so I'm gonna have three outcome measures of people that I'm looking at, basically looking at the race ethnicity, the new residents in the unit, are they white, are they Latino, are they African-American? Very clear for you, you said that the head of household changed, could the head of household only have moved out and the rest of the household stays the same? I don't know. I mean, they get divorced in a few weeks and the rest of the family's still there. That's not really a household unit change, but it would be a change in the head of household. Well that's a tricky one, yeah. If they were to a family person to point that out, you're right, that's an excellent point, but yeah, I don't know how that happened, I agree. Let's check if that gets caught or not in that case. I'm banking usage, I'm all moving. I got a check on that, that could be, not quite right. Most of the time. So again, focusing only on households who move in these over the two years, 5,700 moves we have. I don't know if I, I think I do mention, here we do, they do some models accounting for the non-movers and they don't change their results at all. Our independent variables, we're most interested at the household level, the race ethnicity of persons, white, black, Latino, and other. The other category is pretty small. Again, this is the mid-80s. This year there's just not enough Asians or other groups to look at them at all meaningfully. Micro-neighborhood and tract in each of those, we include the percent white, black, Latino, and other. In tracts we can split out Asians because there's enough variability to do they're not so in the micro-neighborhoods. We also include a measure of the racial ethnic mixing, the heterogeneity, based on herping dog index. How do you operationalize micro-neighborhood? Micro-neighborhood, yeah, good point. I ran through that. This, this American Housing Survey follows housing units over time and what they did in 1985, they came along, they randomly pulled about selected 670 of these units and then what they did is for each of those units they went and they interviewed the 10 closest units to them. That's what they have. So you have this center point and then the 10 closest. I've actually read through this documentation exactly how they do it. It's based, they don't go over a railroad track but it's whoever's closest, they go around the block sort of thing. If it's in an apartment structure or come back to there, they'll, there's a real complicated thing but they'll do all the people in the same floor. There's 20 on the same floor then you'll have 20 people in the micro-neighborhood. If it's less, if there's five, then they'll go down. I think they go downstairs and upstairs. I've been asked about your upstairs and downstairs neighbors because those are the ones you meet first, right? If you're here first. Or here first. Yeah, if you're there by the stairs then I'm gonna test it here. So that's pretty much exactly what you want. In a sense, yeah. It's pretty darn close, yeah. Amazing. And it's, the data's not been used very much. It's something, I stumbled along, I grabbed it for my dissertations when I started working on using. I did the analyses at, the US Census has these Census data centers. And I did the work there. Little bunker or no sunlight or anything like that. Other controls taking account income stability, crowded and perceived crime. Other neighborhood characteristics, school quality, bars and liquor stores. That kind of thing just to account for, maybe these are sort of spurious things that are driving it. Not many of them have much of it. Interesting fact that we did that. The models are just logit models with corrected standard errors for this clustering. I did do multi-level logit models but the results were similar. There's some estimation issues with the logit with SAS. It's a whole, it's ugly mess where you have to use starting values. Results can be different and the whole thing. And we're limited in the census data center. All you have is SAS there. So the results were the same. So I'm just gonna present those results. Multiple imputation for missing data. And as I kind of alluded, we did do a HECN selection model including the inverse mills ratio to taking into account nonmovers. The results were very similar, extremely, extremely similar. So it didn't have much of an effect. Let me show you a few of the results. What we found, first question again, asking is the new household black? It's moving into the unit. Talking about predicted probabilities. So here, again, the question if the black household replaces the white household, this previous unit had a white household. Now what is the probability that the new household will be black is what we're asking here. And for this, to look at the effects in these different micro-neighborhoods, we start picking the average micro-neighborhood racial composition for black residents in the sample entirely. So that's the, we start with that as the baseline, if you will. And there the predicted probability is 0.48 that a black household will replace a white household that was living in that micro-neighborhood. Now if you increase the standard, the percent white in that local micro-neighborhood, one standard deviation, that probability drops to 0.23. If you increase the percent Latino, a similar amount, it drops to 0.32 so it's not dropping quite as much. And conversely, yeah, go ahead, Greg. So this is, this can't be of all the white, original white households, what fraction switch? No. That's gonna be an incredibly small number, right? So. Yeah, of all the white, right. That would be a different thing. Yeah, do it like that, yeah. What is, what is this? Like, I don't understand that. What's the 0.48, for example? That would be, that's, that is gonna be the predicted probability. If we had a white household living in an average, a micro-neighborhood that has the racial composition of the average black, there's not, for one thing you imagine, there aren't a lot of white houses there, just that, yeah, off the top of your head, you say that's kind of surprising the big, somewhat of a big number. Why would it be almost a 50% chance that it would switch to black? That would be in a sense be a bit of an indicator of this sort of process. We see that white households living around more blacks are more likely to leave, and then more likely to be replaced by blacks. So that's what is, it's that white household living in that context. Then what is the probability of the new residents who are black? The average is about what, 12%? 13, 15%? Say that what? The average is 15%. What is that value? The average micro-neighborhood. Oh, what is the racial composition of that? Right. What's the, so what you're saying is like, if this is like 15% black, this neighborhood, and then they have one. No, it's much more than that because it's the average micro-neighborhood of a black resident in the sample. So that's, it's not the average micro-neighborhood, yeah. It's the average context of a black household. Oh, okay. So put that in context. Yeah. So it's a bit, yeah, you could write how to present the results. You could, it's. And then the point A that would look really high, right? Yeah. Right. And that. So you can, as you can well imagine, the numbers are gonna vary. It's particularly gonna vary when I get to tracks because we've got this, it turns out there is this heterogeneity effect, particularly for blacks. We don't see it as much for the other groups, but we do see it for them. And then that, so then it's gonna matter whether you're at a low percentage or a higher percentage is gonna make a difference. So it's not a straight linear effect, basically is what we get. And at the micro neighborhood level, again, if it's more a higher percentage black than the idea, then the probability of that transitioning from a white to a black household is even that much greater. And what would that, those numbers be if, or maybe I'm not just saying where you're going, but if that was the black household that was being replaced. Oh, a black replaced in another black household? Yeah, in the average black. I should just show you these. Don't show that or not. I don't think you can see this, maybe. Maybe so. Here's, yeah, here, the number is 0.87. Okay. Yeah. If it's, so it's 0.48 chance if it's white, 0.37 if it was Latino, 0.87 if it was black for that. And so I don't know if it's easy to follow this or the other one which you can see better, but so that's this micro neighborhood context we see this kind of straightforward effect. For tracks, we actually see a little effect for from in movement of a black household. And again, it's because of this hydrogenated effect that where you are, here we're starting with a track that's relatively high percentage black. So when you push it up higher, it doesn't have much of an effect at all. Probability is still 0.48 of course, but when you increase percent white, there's hardly a change, Latino hardly a change and percent black going up. It's even less of a likelihood. So blacks tend to be being pushed more into a heterogeneous. Are standard deviation changes comparable at those two levels? No, they're a little different. They're a little different. I went with, I chose to go with standard deviation change because the argument being that this represents really the amount of change because as you're intuiting, there's always gonna be more, I think I can say always, nearly always gonna be more variability at the micro neighborhood than at the track. This track's a larger agitation so it's not gonna move as much. So that makes a little bit hard to think about 0.46, right? Either way, yeah, I don't, it's a tough question to back up and say, well what number do we wanna get it? Do we want it? Because a 10% change in each are different things. So I don't know if that's comparable. So I went with this.  If we double that, it's gonna push it down even a little bit more. So it won't make that much of a change. Again, this is the only one where we found this effect. Now, controlling for that neighborhood, micro neighborhood, do we see the same race effect? Yes, and it's actually extremely strong, even controlling for these. Here, just presenting these as odds ratios. Compared to previous house will be in black, the odds are reduced. Of this new house will be in black, 86% of the previous were white and 91% of the previous household was Latino. So it's still a gigantic effect controlling for the track, controlling for the micro neighborhood. Still something going on about the race, ethnicity of the housing unit. And the pattern of results, very similar in general, for the other two racial ethnic compositions people will be in. Here, asking this new household white and here, micro neighborhood, a white household replacing the Latino. I just chose this one rather than going to that whole table I had before, although I've got that for people who want to come through that. And the average micro neighborhood of 0.31, chance that a white household replaced a Latino. If you increase the percent black or Latino, that probability goes down quite a bit. If you increase the percent white, it goes up. So again, a fairly substantial micro neighborhood effect. But here we also see a stronger effect for tracks, for white. So at the same time, controlling for them at the same time going on, the average is 0.31. Again, increasing the percent black or Latino goes down even more. And again, this is a little less of a percentage change. So it would be even more if we did an equal percent change. And then whites going up even more. So that's enormously more important, right? The track level than micro neighborhoods or whites and blacks? Yeah, or whites and blacks, absolutely. Blacks that had almost no effect, depends, yeah, where you're at. You could see a bit of an effect if it was a low percentage black. But for whites, yeah, it's a huge effect. So here would be interesting to look at home ownership, right, versus renting? Because if you're interested in house value, you might be interested in a larger neighborhood. Larger area. Yeah, it's important if you see blocks changing. That's an excellent point. That's an excellent point. Out to it. Looking at that one. Nonetheless, even controlling for it, there's huge effects for tracking micro neighborhoods. Still a huge effect for the housing unit, raceiveness. Again, it's 80%, odds are reduced 80% if the prior household was black or Latino. So finally, looking at it's new household Latino, similar pattern for blacks. Same story that it goes down if you increase the percent white or black and the micro neighborhood goes up, increase the percent Latino. So again, same race effect. Tracks were similar, similar kind of pattern going on there. So you can plot out this reinforcing effect to be increased to percent, one standard deviation increase in percent white in the micro neighborhood and the tract. This probability of 0.25 goes down to 0.06. So it's a big drop. Same way with percent black, drops quite a bit. So reinforcing, even though it's just a linear or an additive effect, but it's still strong when you combine the two. But again, this strong household level effect. Do you think a fraction of people moving in know the people they're replacing? Has anyone asked about that? I don't know. That's when people oppose that. If people know of literature, I've been scouring the literature trying to find this sort of a vast people about this. I've not found much. I've found that, I found a couple sites that talked about out to the fact that people know the race ethnicity of people, but whether they've met them or not, I don't know. Is that my account for some of the huge effects that are showing up at the individual unit? What do you mean? If you're recruiting the replacement or play a role and your own network is very singly, singly ethnicity. Right. Right. So as that was my disclaimer coming into this, I'm looking at patterns here. And since it leaves off in some ways a bigger question, why is this? And I've not seen literature looking in so to me it's a natural direction to go to try to figure out some of these things to what extent do people know who was in the unit, et cetera. Just a couple comments, quick comments on the control bureau's income. Higher income in the micro neighborhood affected, increased the probability that a white household movement moved in. Less likely to have a Latino household move in. The income in the tract had no effect. Residential stability in the micro neighborhood also increased the probability that a white household will move in. And lower the probability that a black household will move in. So these more stable, local areas of the tract had no effect. One final thing I tried doing a little bit is following up on this signaling idea. Like someone said, oh, people don't really know the race, ethnicity of people, how would they know? And then it becomes a question, well maybe there's certain contexts where it's more important to me to know. I mean you can imagine certain people care more than others. Some don't care at all. Some might be somewhat concerned about it. The people who are concerned might be particularly concerned in certain contexts is where they really, it becomes important for them to figure out this, use this signaling information. So I tried a couple things, interactions, kind of contextual things. Residential stability, thinking that there might be less signaling information in a case like this. Because there's a large amount of change going on anyway so you'd figure out all this change going on. The present household is less than an indicator of the household. They just haven't had a chance to move out. They might be getting ready to leave. So it's not as strong a signal. Racial ethnic composition, this may, again leaving aside George's question of how do you know what the race ethnic composition is. You trust your real estate agent. That might really increase for whatever reason the salient said this to you and you might use that signaling more. Or the economic environment might be important. There's less uncertainty perhaps. If I'm going into a high income neighborhood, I'm probably safe to assume it's a pretty quality neighborhood. A lower income one, it might be more dicey. Maybe it's a nice cohesive neighborhood that's just a little lower income or maybe it's a really problematic one. So there I might want to use the signaling much more. Test these out. For stability we do see somewhat of an effect that looking again at that micro neighborhood, there's no effect for the track but looking at these interactions, what effect do they have on this same race effect for the household. Neighborhoods with more stability, I'm sorry, micro neighborhoods with more stability, the white to black transition another 34% less likely. So even less likely to see that transition occur when you see a lot of stability in the micro neighborhood. And likewise Latino to white transition 20% less likely again in a very stable micro neighborhood. So again, somewhat consistent with that idea. Asking about the racial ethnic composition, if you increase the percent black in the micro neighborhood over the track, either one, black to white transition another 35% less likely. More Latinos in the micro neighborhood attract again, Latino to white another 34% less likely. So again, before that, whites seem to be more affected by the broader area. Here we're seeing it, it seems to affect this same race effect even more. Income had no effect, thought it would, but it didn't. One last thing we tried was looking at the broader context. Our viewers said, oh, look at central city areas. That turned out not to have an effect, but we thought, well, central city, really what that is a proxy for when people talk about what they mean, low income, high crime. We tried race as well, doesn't have an effect, but it's such a big context. But we do see a strong effect for violent crime and income. And it turns out, if you look at the county violent crime rate, that does in fact affect this same race transition.  The odds decrease 40% of seeing this transition or black to Latino. Again, that decreases quite a bit for a high violent crime county, so in that larger context. And, flip, you see the same thing if you look at the lower income counties.  So again, in these broader contexts, either high crime or lower income, that same race effect is the same. Almost out of time. So let me quickly summarize what I've been showing here. What does this mean? So we see this strong household effect that persists even controlling it from micro neighborhood and the broader track. That's kind of inconsistent with some of these models. Place stratification, the preferences, classic assimilation or not. There's something else going on here. Of course, the strong micro neighborhood effects also imply that stratification, assimilation, signaling. Signaling model doesn't account for that, but we still see this micro neighborhood effect as well. Of course, it's possible that there's more than one of these going on, quite likely. The micro neighborhood effects are consistent with some of these theoretical models, preferences, steering, networking. It could be that the case, but which one is at work? I can't say here is more. Again, I was looking at patterns. Again, it's possible that more than one is at work. So again, that might be something for future research to kind of look at. And again, this question of what is the important context which I started with, this idea trying to pick out what seems to be an empirical pattern, what reveals itself based on behavior. There's still this question of exactly how does it work? What do people look at? Both the micro neighborhood and the tracks appear important, especially for whites. But again, this issue of the race, ethnicity of the previous residence seems important, but I've seen there's not much literature out there talking about that. Or even these questions of how this might take place, how they know race, ethnicity, race, ethnicity of people. How do they know that? Even there, there's not a lot of literature on that. And different theories that might explain it. We touched on this notion of social networks might be in effect. Whether that differs between homeowners and renters, I think is a useful direction to kind of look at and say that if that is indeed how it plays out, the steering effect could be the case, but it's hard to say, do real estate agents. But it's tricky to find out because no one's going to admit or acknowledge that. So it's a real difficult thing to tease out. So just to conclude, the ratio of the composition of the track matters. So even though these little cards look at the local micro neighborhood, which does have an effect, and in fact, we found that for most groups, it was almost stronger, but the track did matter, especially for whites. The race, ethnicity of the previous household still has a strong effect. And why? It doesn't seem like it's discrimination because we kind of sat across the board. It's not just whites not transitioning to other groups. So it doesn't seem like it's that, but as it networks, it's the signaling. It's not clear, but either way, it's something is going on, something worth studying more. So I'll conclude there. Thanks. Did you just sample one micro neighborhood per track? Essentially. So you never get enough multiple micro neighborhood? At all. There's like about four or five doubles. There's just no variance on that. Yeah. Have you saw urban areas or I missed that? I didn't say it. I should have far-branded whistleback in Carolina would be jumping all over me, but it's urban and suburban basis. So it's non-rural is what they did. So they slopped off them and then they did a random sample from the urban and suburban persons. Again, they were sampling those housing units and then building the micro neighborhood around them. And that was the sampling device. So then that's why it ends up that there's almost none that are two or more in a track, which is nice for standard areas, but it's not great if you wanted to try it. Get this additional variability going. So you know whether it's on or, whether it's around the unit or on the unit, right? I do know that, yeah. And it seems like there are a lot of reasons to want to do this separately. Yeah. Because it might help you to distinguish between some of your theories. I agree. I'm kicking myself. The reason I'm kicking myself now, well, for many reasons, but one of which is now, this work I did back at Duke in their Census data center and now to do the analyses now, I go up to UCLA and I first have to beg and plead for the census and that to show me I have an R and R and I need you. So I need you basically. I'll send the paper to you, right? Critique it, give me an R and R and say I need to go back and with that, then I can go back. That's what I need is I need that and I can go back and say I need to redo these analyses. But it's something that's become startling clear to me that at the time, I thought, oh, it won't make that much of a difference, but that was a pretty hindsight, not a great decision. Because it makes sense that these processes would play out, at least potentially differently. I mean, I did some, I've got the public use data where I can't do the contextual effect, but I can look at same-raised transitions by renters versus owners there and there were some differences there, not huge. But again, that's not really getting that, what you really wanna be telling, you know, testing. Because it's more this idea, some of these contextual effects we might well think would play out differently for those two groups. I don't know, I'm trying to think if that causes problems for estimation, but I'll set this. Do you know how far people have moved? Do you know anything about whether it's a local, relatively local group or a distance? Well, I'm trying to think of the information that people would have available that most moves are relatively short distance. Do we know how they found the unit? Yeah. That's a great question. Almost certain, I don't think they ask where they're coming. Cause all I know is I don't know where the other people laugh, but I know the new people coming in, I mean the people coming in, that's the question. I don't know how far they've come. I don't think I have that. I'm not 100% sure I need to go look on that. They do ask questions about why you chose this unit. You know, what characteristics of the neighborhood, what characteristics of the unit. And I'm trying to remember now if they ask, was this... Like prior residents? Yeah. I guess the main thing we'd probably want to know, I think, where you're going with is, are they, were they in the same metropolitan area or not? I think you could probably split it based on that. If you're in the same metropolitan area, you have relatively decent information. If you're coming from outside. You might have a lot of things. You might have information, access to particular realtors. You might know the neighborhoods. You might also have the network connections. Yeah, right. Whereas if you're coming from outside the metropolitan area, those things... Right, and it might be a much grosser picture of what's going on. You might have heard about, oh, this area, but not that one, but not down to... A real flying grain? You know, Camille Charles has done some work on this, and what she discovered was that whites had more information than blacks. Interesting. Just in general, you mean... About the potential neighborhoods. Either, I mean for people living in the same metro area or even... You're living in the same metro area. Okay. So people coming from another metro area are kind of equally uncertain. They're something, yeah. Yeah, that's worth thinking about, too. I guess I'm biased coming from the Detroit area, but I'm trying to think about what would be a lot of the concerns about these white movers who are thinking about moving into this neighborhood. Why are they concerned about whether their minorities live in there or not? Yeah. And one of the issues is this neighborhood is churning. Yeah. It's going down. The property value's gonna go down. Right. And so that's one of the reasons you'd want to look at it. I would think that you'd see a really strong difference there in terms of like if you have a high SES neighborhood that's clearly being kept up and clearly very wealthy, that in a sense it might matter less what the races of the people are than if it's a neighborhood that's more urban or more sort of questionable in a sense. So you're not really sure where it's going up or down. Right. But you said that you didn't see an income difference. Yeah. That income in terms of the individual person's income or the SES of the neighborhood or... The neighborhood and micro neighborhood. Are you thinking? Yeah. So if this doesn't matter at all? Not for those two. The micro neighborhood, I mean measuring the average income in the micro neighborhood or the tract did not affect that. I thought the same thing. It seems pretty non-plausible to me, so I buy it. And that's controlling for race, ethnicity, and crime and other things? Yeah. Yeah. Right? Yeah. That's what we're testing on the system. Yeah. But I'm not clinging to it for the next 30 years and I give it up. So I just, Grace, I mean so one of the ideas is like, people, race is sort of socially salient, right? Sort of this idea like race is a master's status or something. Yeah, right, yeah. Do you have other thoughts about like, I mean so like the one that sort of jumps to mine is like language, right? Would be potentially really interesting to look at.  Yeah. But I just wondering what other kinds of information you might have that you could look at to potentially get information about. I mean, and I don't know if like the different sort of group identities would give you different ideas in terms of like networks, discrimination, signaling. Yeah. But it seemed like there might be some leverage there. So are you going, I suppose, are you not thinking for this particular study, is that what you're referring to? No, no, no. It's like the next group. Exactly, right, yeah, that's, no, right, thanks. I don't have enough to do. Yeah, I mean, absolutely.  And it used to be tremendously important and it's still somewhat important no matter what we might want to think. But I think, yeah, there's a lot of reason to think that some of these other groups would be important. And that signaling is getting fundamentally at that, right? I mean, that is, well, I mean, people in general, you move to a neighborhood, you want to get a sense of what's going on there. Just talking to someone there, saying there's someone who's, we're trying to do a paper looking at gentrification. And how do you measure gentrification? Someone came up with a proxy, the number of Starbucks. Yes, which I thought was interesting. That might be an easy way, you just drive on, oh, lots of Starbucks, I'll move here. It's tricky though, but yeah, for other groups, yeah, how do you, you know, for gays, who, I mean, that would be a fascinating group to look at because they have, I don't know what the word is, but they've moved into all sorts of neighborhoods in all sorts of different cities, a real process, like how does that go on? I think some of that is, I'm speaking really off the top of my head, but I think there's been some pretty clear signals that are given at points there. But that, yeah, you can imagine how that plays out. And in some of those instances there, you know, it's, there's reasons like that would be pretty important to know that, perhaps, right? Some neighborhoods might be downright inhospitable. That, you know, that's, that would be a concern as well here. And so in that case, again, that signaling is even more important than how it plays out. So then it raises all these, yeah, it raises these questions of how, you know, are you just, in that case, are you just looking at the, the characteristics of the household? Probably not, in that case, if, if we're talking about a case of transition, right, because presumably the people moving out are going to be different than those moving in. So then it doesn't hold up as well. Well, and you're looking at margin-free measures, right? So like, because I think like one of the things, like you have like more immigrants coming in or something like that, like that's essentially that's going to be taken into account. Cause I mean, the likelihood of a white to Latino transition is going to be increasing, but that's not going to show up in there, if I understood your models correctly. Yeah, I have to think about it. Yeah, I know, I know, and I need to think about that cause I don't want to, cause I know, yeah, that's a huge issue for like a lot of the segregation stuff, like, because yeah, certain movement in, you're going to see certain patterns are just a mathematical identity. I don't think that's a problem here, but I'm not going to commit to that, especially since it's on tape. I want to hear a look that other household members like children, I would imagine the people that are small, small-school-age children that are different than in certain ways, they would consider different options on moving in. Right. Like slaves? Yeah, that's a great point. I mean, other stuff I've done, I've looked at no mobility out in looking at crime matter, you know, some of my work has found that crime does matter, but yeah, you do see this strong pattern in here that those with children less than five years are more likely to move. Those with children six to 18 years are less likely to move. And you argue that that is the school factor, that's one simple story, is the school story going on. Yeah, but also when they move, they would sit in that place. Yeah, you're going, yeah, I know it. And it's funny, because I rattled that off and then, no, I have not thought about that for this process, but why would it not work? Of course it would, but certainly. And that's an excellent point. And I've not looked at that, but yeah. It just makes all the pictures, they're really different from people who don't have kids, I mean, they haven't. Yeah, those people with kids just mess everything up, I mean, the restaurants, it's noisy, I don't know how it's going to start. John, our time is up, it's been wonderful. Thank you very much. Thank you. That's all. Thank you.


What is up you guys, welcome back to another one. If you're new to the channel, I am Goldpony, I do new car truck SUV reviews on YouTube. And today, we are in the brand new 2023 Mercedes-Benz GLE 350 courtesy of Mercedes-Benz of Hagerstown in Hagerstown, Maryland for more information on their inventory. Please feel free to check out the link in the description box below. And so we are in this one today because this essentially is the E-Class SUV by Mercedes-Benz. This one is going to be competing with the BMW X5 and the Volvo XC90 for example. So, all to believe this video though, we will be testing out and going over everything about this one from acceleration to braking, steering feel, ride quality sounds to some exhaust with all that fun stuff. So having said all of that, what do you guys say? Let's just go ahead and jump right into it. And as always, let's start with pricing. And so there's essentially two different configurations for the GLE 350. First one being the rear wheel drive variant starting at $56,150, which is a very modest price bump from the 2022 model year by only $450. A lot of manufacturers are doing somewhere around 900 to 1,000 typically on average. So only 450, that's not that bad. All wheel drive version then is going to start at $58,650. But regardless of which configuration that you go with the power plant on the GLE 350 is going to be the same. Powering the beast is a two liter turbo charged inline four cylinder, putting out 255 horsepower at 5,800 RPM, 273 pound feet of torque coming in at 1,800 RPM. Power sent to rear wheels are all wheels through a nine speed automatic with paddle shifters, which you will be testing out here in a little bit zero to 60 time. It's going to differ slightly depending upon the configuration that you go with 7.1 seconds for the rear wheel drive seven seconds flat for the all wheel drive that with MPG numbers coming in at 19 city, 27 on the highway for the rear wheel drive, 19 city, 26 then on the highway for the all wheel drive taking premium unleaded fuel. And so before we do any kind of fun acceleration or paddle shifter test here in the GLE, I wanted to mention to you guys the drive modes. It is labeled dynamic for dynamic select. Located just to the left of that touch pad controller, it's going to give you different drive modes like eco, comfort, sport and individual allowing you to really tailor it to your own liking. But essentially this drive means we'll adjust things like the shift points of throttle response and the steering sensitivity. So now having got all of that out of the way, what do you guys say? Let's go ahead and find a straightaway. Let's put the paddle shifters and acceleration here to the test at the same time. And let's see how quickly the paddle shifters are going to react. And let's see how quickly we can get this one here up to speed. All right, user start. Go. Yikes. This thing is quick. Paddle shifters have a slight delay to them as expected in an SUV, but dang, this thing is quick. Definitely doesn't feel like zero to 16.7. It feels more like zero to 16.6 and a half for something like that. This thing is definitely, you're not going to have any issues emerging onto the highway. It is a very nice acceleration here in the GLE 350 without a doubt. But anyways, to go along with that acceleration as always braking is equally important. So as expected, you will find four wheel ventilated disc brakes coming standard. As far as this six easier stopping distance goes, it's going to come in at 118 feet. Mercedes-Benz always does a wonderful job with the braking system. It's definitely on the firmer side of things. Definitely not a softer, squishy braking feel. Like you sometimes do get with SUVs and typically with SUVs, that number actually comes in in the upper 120s if not 130s. So 118 feet, that's brilliant for the GLE 350. So I personally have no issues with the braking feel on this thing. But touching on suspension and handling, up front you're going to get an independent double wishbone tight front suspension, in the back independent multi-link rear suspension and an adaptive damping suspension as well. That's one you always look for, especially in luxury vehicles. Essentially what that is, is if monitors each shock absorber individually, not only adjusting to the road imperfections, but also tightening up that suspension during heavy cornering, really giving you the best of both worlds. So it's going to give you that smoother ride. It's also going to give you better handling. So that is why I always like to recommend that, because it is an instant noticeable difference, if you drive a vehicle without one versus with one. And I can tell you guys right off the bat, although Hagerstown and the Brutes are pretty darn good, but ride quality is 100% on point. So you're definitely not having any issues there. Steering feel is actually a little bit weighted on the heavier side of things as well. So a lot of times SUVs, they come in on the looser side when it comes to the steering feel. It's just less driver emotion, but Mercedes Benz typically does a pretty darn good job with driving dynamics, and that is included in the steering feel. So I like the weight to the steering. I'll put it that way. So where's cabin noise goes? I'm going 56 miles per hour. I'll let you guys be the judge of that. This is a very serene cabin, not a whole lot of exterior wind noise or road noise, really at all coming into the cabin. Definitely not the wind noise. It is very quiet in the stick. So I am loving that. Definitely catering to what this vehicle is, touching on visibility. I can see 100% perfectly fine out the back, so you're not going to have any issues there. But do also mention rain sensing windshield wipers do come standard on the GLE 350. So whenever this thing detects any kind of mist or rainfall, it's going to automatically turn on these windshield wipers for you. So it's kind of like automatic headlights. Just one less thing you got to worry about. So that is a big convenience feature really there as well. And I did want to also mention there's a head up display available that goes for $1,100 if you wanted that. Essentially that's just going to project your speed, speed limit and safety features up onto your windshield. Better helping you keep your eyes on the road. So that's going to assist with forward visibility then as well. But that pretty much rounds out the performance segment of this review you guys. Let's now go ahead and take a look at the exterior of our brand new 2023 Mercedes-Benz GLE 350. All right, so here she is you guys, the new 2023 Mercedes-Benz GLE 350 finished in Mojave Silver Metallic, which by the way is a $750 paint option if you wanted to go that route. It's kind of like a light brown. So it looks dang good in my opinion. Always like a different colors I guess you could say. But let me go ahead and show you guys real quick where this thing is made. The VIN actually starts with a four which means it is made here in the US. Now it doesn't mean that the parts are not going to come from Germany. I know the transmission is from Germany but for the most part this thing is built in the US. At least the GLE. But let's go ahead and start up front on this one. Bull horizontal aluminum bars will come standard unless you go with one of the AMG line packages, which we do have in which case you were going to get a single aluminum bar with a diamond block front grille. And that's gonna be kind of like those chrome accents kind of found within the front grille there. So it definitely looks good. Did what I also mentioned that there is an illuminated star available for an additional $500 if you wanted to go that route. That definitely looks very good at night, illuminated by LEDs of course. Chrome accenting found in the bottom portion of that front bumper with dual chrome accents on both sides with front air currents as well, helping direct the air around the wheel and tire combination though. To the sides though, LED headlights do come standard and they are full LED headlights to both low beam and high beam of course with LED daytime running lights get the automatic feature of course and automatic high beams which was a new feature for the 2022 GLE. But now again coming standard across the board for the 2023 as well. So if you have your high beams on at night sends the vehicle coming in the opposite direction it's gonna automatically dim them back to low beams then when that vehicle is gone it's gonna automatically bounce it back up to high beams. So very convenient feature there as well. And there is an adaptive front lighting system that will be optional on the GLE 350. Essentially when you're going around the bend at night the headlights are going to swivel based on the direction of your steering angle better help illuminating what is around that bend. So you're less likely to hit a deer or a bicyclist or a person or whatever the case. So definitely a safety feature and it's gonna help you see better at night as well around the corner. So that pretty much rounds out the front end of this one definitely looks good with our AMG line package that we have here today but let's now go ahead and make our way to the side of the GLE. And so now since we are around to the side of this one starting all the way up top there aluminum roof rails will come standard. Satin chrome windows surrounds also coming standard as well. Rear privacy glass, yet again, standard. Satin chrome accents on the door handles didn't want to leave that one out that is a pretty cool look. A lot of Mercedes Benz has that as well. Take a look at the side mirrors body colored power adjustable side mirrors will come standard that will be heated with LED integrated turd signals as well. But not only that power folding side mirrors also come standard.  So that is pretty cool. That doesn't always come standard even on luxury manufacturers actually. So I wanted to mention that. Take a look down at the wheel setup then 19 inch twin five spook alloys are going to come standard. However, there are several different optional wheel configurations for this thing including the AMG line wheels that we have today. We actually have AMG kind of embossed into the wheel. So definitely a very nice look and there are 20 and 21 inch wheel designs available on top of that. So overall, nice side profile here. Let's now go ahead and make our way to the back. All right, so now since we're all around to the back first thing I wanna mention is there is no shark fin antenna up top. So kind of interesting. Most vehicles I would say 90% of them out there have that shark fin antenna but a very clean look up top without it. I will say that but just below that rear spoiler with an integrated brake light of course. Rear render wiper affixiated to the rear glass. You get that formatic badging meaning the GLE that we have today has the all wheel drive system. That is what Mercedes calls their all wheel drive system cause every manufacturer names it of course. You do have LED tail lights coming standard. I absolutely love that look. Very bright back there. LED license plate lighting actually as well. So that is pretty cool. You do have a little bit of added chrome accenting found in the bottom portion of that rear bumper. And then to the sides, a very nice look here. Integrated dual exhaust outlets with chrome tips. So having said that I do believe you guys know what we have to do next. As always here is that exhaust clip. So but now since we are around to the back of the GLE when it comes to opening that rear tailgate it is a hands free power tailgate that does come standard on this thing. So if you have your hands full of groceries or kids or whatever the case it is automatically gonna open up for you. So that's definitely convenient. But once opened up, cargo capacity comes in at 33.3 cubic feet behind that second row. With the second row folded down that is going to bump that up to 74.9 cubic feet. But there is a ton going on in that cargo area including of course cargo lighting but grocery bag hooks coming standard, tie down anchors. There's a cargo cover back there that's gonna come standard. There is some netted storage on the driver's side in the back of that cargo area as well. That is pretty cool. And if you were to lift up underneath of that cargo floor that is where you're actually going to find a spare tire as opposed to the fixer flat which I personally prefer. I don't know, maybe I'm used to it but you can also probably fit in an ice scraper within that spare tire underneath the cargo floor as well. Basically everything you'd probably want in the cargo area then. But now making our way up to the rear legroom. First let me start by saying there is a third row available for the GLA. It's a $2,100 option. We don't have it but I had it last year when I reviewed the GLA. So not a whole lot of space going on back there. So we're just gonna go ahead and move up to the second row because that is the configuration that we have here today. 40.9 inches. That is quite a bit of space as far as rear legroom goes for that second row there. For reference I mean even six feet tall. This is how much space I had sitting behind my own driving position there. Rear ventilation does of course come standard. There's a rear center armrest with cupholders that will come standard as well. There's a couple phone charging ports back there. Little bit of storage around those phone charging ports as well. But if you wanted heated second row seats that is available for $580. If you wanted to go that route. Four-Zoon climate control is also available. That goes for $860. So both rear passengers can set their own temperatures. That is pretty dang cool. One thing I would have liked to have seen though especially in a vehicle like the GLE is rear window sunshades. Kind of surprised I didn't see them back there. But still very comfortable back seats. I will say that. But then make your way up to the front seats. Power adjustable front seats with four-way power lumbar coming standard. Memory settings for both driver and passenger. Yes, usually never get the passenger side. You always get the driver side and luxury vehicles. But passenger side can actually set three memory settings as well. I thought that was pretty cool. And Mercedes Benz typically always does that. But I always liked that. Heated front seats coming standard. Leather at seating coming standard. But leather seating is available for $1,620 if you wanted that. Benelated front seats go for $450. And there are also multi-contour front seats with the massage function. That goes for $1,100 if you wanted to go that route. But overall because of all the adjustment seating was 100% on point, plenty comfortable. No issues with taking this thing on a long road trip. Now let's make our way to one of my favorite parts, the steering wheel. And here's why. Tilt and telescoping of course. But it is power adjustable. It is leather wrapped that comes standard. But there is a wood leather combination available for $600. And that's the one you're looking at right now in between the wood on the steering wheel and the wood just above the passenger side glove box surrounding the air vets. When I first got in this thing, it smelled like a new home. It smelled like when I was building my home as opposed to a new car. So it's got that new home smell because of all of the wood that is included in this which I personally love.  But quite honestly, the new home smell is a little bit better. So that is what this thing smells like. If you wanted to heat your steering wheel though, that is an additional $250 as well. But now let's go ahead and make our way to the startup. Let me start by showing you guys the key here. Essentially, all of your buttons are located on one side of the key. Got lock, unlock, and of course that power liftgate button as well. But it is all keyless entry with a push button start. And then you got the remote start via the Mercedes Me Mobile app if you wanted to go that route as well. So all I'm going to do here simply put my front of the brake and press that black engine start button located just by the driver's right knee. So once started up, 12.3 inch digital gauge cluster will come standard on the GLE 350. And I love it. Here's why. There is a designs and display section. So if you go all the way over to the right here you're going to get designs and display and that is going to give you a couple options including classic, sport, progressive and understated that completely changed the look of the gauges and it looks absolutely amazing. Now of course you get everything else you would expect like there is a digital speedometer there's your outside temperature there's speed limit recognition technology as well as you're driving along the road. You check out how many miles you have left until you hit empty the list goes on but pretty much everything could possibly one up there and the best part being you can completely customize the look of the gauges. So loving that. But now making our way to overall interior quality there is a panoramic sunroof that goes for $1,000. We do have that option. So that is a massive sunroof. It goes all the way into the back seats as well. Autodimming rear view mirror with homely controls are up the three different garage doors. That's definitely a big fan of that. Dual-zone climate control coming standard but there is that optional four-zone climate control available. Wireless phone charger can be found just in front of the dual cup holders here. So that's always very nice. Still want to mention another option that we have with us here today though goes for $180 and that is going to be heated and cooled cup holders in the front here just in front of the touch pad controller. So if you have a coffee put it on the heat button or if you have a cold drink whatever that be you can put it on the cold cup holders button there's a little bit of ambient lighting within those cup holders as well. So we'll get to the ambient lighting in a little bit. You know what, let's just do it now. 64 colors of ambient lighting coming standard. Mercedes-Benz does ambient lighting better than anybody else including these massive grab handles for both the driver and passenger. You got ambient lighting surrounding that as well. So kind of of course adjust those colors through the infrutainment screen. So I absolutely love that but overall this thing is finished like a Mercedes-Benz. That's pretty much all you need to know. I like the little kind of diamond style lighting overhead lighting up top here as well. A lot of contrast stitching. I like this dark kind of cappuccino brown interior that we have with us here today. So overall 100% on point. And I almost forgot to mention all of these wood finishes they are matte wood finishes. Besides on the steering wheel that's smooth but everything else is a matte wood and it makes everything smell like a new car which is absolutely wonderful. But now let's go ahead and take a look at the infutainment screen 12.3 inch color touchscreen display. And of course like I said it is touchscreen but you can control it using the touchpad controller and buttons located just behind the cup holders. And you can also say things like, hey Mercedes. How may I help you? Turn on the radio. And there you go. I kept it simple there. I probably could have said a lot of other things and there's tons of commands for that but you could basically say, hey Mercedes whatever and it'll do it. So that's pretty cool. Anyways, Bluetooth and audio streaming coming standard Android Auto Apple CarPlay factory navigation system coming standard as well. Can adjust your drive modes up there and of course your ambient lighting but my very favorite part if you swipe up from underneath there you got themes, you got adventure trip experience efficiency, lounge and standard essentially adjusting everything from the ambient lighting colors to opening and closing the panoramic moon roof. It's just adjust so many different things. So that is definitely a cool little feature that Mercedes does. So I always like to mention that but of course you can check out your radio information up there and so when it comes to the sound systems there's your standard sound system but then you got the 13 speaker Bermester sound system with 590 Watts. That's actually the one we have today that comes with the premium package which gives for $1,375 and includes a bunch of other stuff besides just the sound system. But anyways, having said that, let's go ahead and turn on the radio see what we got playing today and let's test out the clarity of this one. All right, felt like the subwoofer was by my left foot because I was getting the rumbling down there but anyways, that was a very nice sound system kind of clarity with that thing. Again, ton of bass by my left foot like I was saying so Bermester did a wonderful job but yet again and not only that we got aluminum speaker covers built into the matte wood finishes and this thing so very high end look as well to go along with that. Anyways, last thing I wanna mention to you guys on the GLE is when you do put this thing in reverse you will find a rear view camera coming standard across the board. You actually do have the option to have that take up the entire screen and there is a surround view monitor that comes with the premium package like I was just mentioning to you guys with the sound system which is gonna let you know what is completely all around you which is always is going to lead us into safety. And so to start, IIHS top safety pick plus which is the very highest designation given by IIHS that pretty much says it all right there. Front side, side current airbags do come standard driver's knee airbag up front as well.  Active brake assist to driver attention monitoring system cross wind assist, blind spot assist, part tronic adaptive braking technology and a parking damage detector with the Mercedes Me Mobile app. So if anybody hits your car door in the Walmart parking lot, you're going to know. But not only that, there is also a driver assistance plus package that goes for $1,950 that gives you adaptive cruise control, active steering assist, evasive steering assist, rear cross traffic alert, emergency stop assist, speed limit assist, lane keep assist, lane change assist and root based speed adaptation as well. So overall I wanna come to my final thoughts that last package option should come standard. I'm just gonna start by saying that because 90% of what I just rambled off there comes standard on all other manufacturers like Mitsubishi, like Hyundai, like Kia, like Toyota, like Honda. They all get that stuff coming standard. So you would think Mercedes Benz would put it there as well. But anyways, great interior quality. It's really second to none when it comes to interior quality. The best ambient lighting out there and I say that because the color options are so vibrant and the ambient lighting setup, it's thicker. So a lot of times with other ambient lighting it'll be kind of a thinner strip with Mercedes Benz. It's more vibrant and it's a thicker strip. So it really lights everything up a good bit more. So I love the ambient lighting in this thing. Also of course, great driving dynamics, incredible acceleration, great handling, great braking with that 60-0 and 118 feet. So the driving dynamics, they're always on point with any Mercedes Benz really. So the only other constructive criticism I can think of really is this thing can get pricey quick. So from the MSRP, there is so many different options available like a price as tested in this thing is a little over $71,000 for example. Good, you can get a good bit in this thing. But anyways, let me know what you guys think of the GLE 350 in the comments section below and that is about it for this one. You guys, thank you so much for watching. Feel free to follow me on social media at the bottom of the screen if you want to see what's coming next on the channel before it gets to YouTube. Be sure to hit the subscribe and the bell notification button if you're in a new car reviews. That is what we do here on this channel after all. Do appreciate you guys watching more than you know and I will see you guys all in the next video. Stay Gold. I wish you guys could smell this new house smell.


All right, back to the floor, it's yours. Thank you so much and thank you everyone for joining the session today, it's been a fantastic week and yeah I'm really grateful to everyone that's been involved in OE Global this year. So as Willem said my name's Beck Pitt, I'm based at the Open University in the UK and I'm going to be talking today about co-creation at the distance, remixing the Creative Commons certificate for Myanmar. So what am I going to be talking about? First of all I wanted to give you a bit of an introduction to the Tide project and what we're trying to achieve. You may if you were around the conference earlier in the week of course Andy Lane and Bobo and the Wins presentation, colonising the curriculum which had loads of just fantastic kind of overview of the project and what we're trying to do and some of the issues kind of around that. I'm also going to talk a little bit about openness in Tide before I go on and talk about what we're actually doing for in terms of developing a Creative Commons course from the CC certificate for the Myanmar context and then finally I'll kind of go on and talk about where next really and next steps because as Willem has become clear this is very much a kind of ongoing process and something that we're currently still working on. So let's start off by project aims. So Tide stands for transformation by innovation in distance education. We're a UK aid funded project and we're part of the Sphere programme. So Sphere is strategic partnerships for higher education, innovation and reform and the project began in February 2018 with around three and a half four year long projects so we're currently due to finish in September 2021. We're very much focused on sustainable development goals particularly SDG4 around quality education and we also have a very specific focus around environmental science. This is a new discipline, an emerging discipline in Myanmar and of course Myanmar is very much a country which is affected by climate change. It's in the top three countries which are most vulnerable countries in terms of climate change. So the aim of the project which involves ourselves the open university but also universities in Manchester, universities of Oxford, Irrawaddy Policy Exchange in Yangon and then also Myanmar partners that's Yadavon, Yangon University of Distance Education, Yuud and Yangon will kind of bring obviously different strengths to the project but the overall aim of the project is to increase the quality of distance education and result in more employable graduates and we're working with around 40 universities and colleges across Myanmar in order to achieve this aim. As Andy mentioned in the presentation on Monday, distance education is really very much a large part of HE in Myanmar. It's about 60% and the activities of the project and the focus on distance learning will hopefully benefit more than half a million students. Just very briefly I wanted to give you the overview of the project just to show you where this work really fits in with what we're trying to do overall. So we have kind of three strands to project activity. One of them is kind of building staff capacity you can see on the green on the left hand side of the side. The second around enhancing programs to do with media production, student capabilities and so on and then finally also around strengthening distance education HE systems so focus around digital strategy and change management. So there's lots of different activity happening across the project and this is only what I'm talking about today is only a very small part of what's happening on Tide and the kind of remixing of the Creative Common Certificate which sits actually as part of our master training program which is kind of four courses that we're offering to Tide universities, people that people that are involved in the project kind of sits under the first strand around building capacity and building on the work that we've already done with colleagues in Myanmar. So when we talk about openness in Tide what do we mean and this is really just to give you a little bit of background and show you how central kind of open education and OER is to the project. We're very much, it's very much about kind of sharing and listening and learning from each other. It's not about us kind of coming in and saying you have to kind of do things this particular way. It's very much about listening and trying to better understand the context which if you're in Andy's presentation earlier in the week, Myanmar is obviously quite a unique and very different context than the one, for example, where I'm based in the UK or other places. Obviously Myanmar has been quite isolated for a number of decades and the way that education has been run, a very centralized approach that's gradually changing but obviously you know it's very different to the context that we're perhaps usually used to working in. So it's very much about listening and learning from our colleagues in Myanmar. We have a kind of aim in the project to produce around 400 hours worth of open educational resources as well so that's kind of built in as I'll show you in a minute to the project. We release all of our assets for the project on open licenses so that they can be reused and adapted and also used for people to cascade and share at their universities as well. So in Myanmar my HE, people talk in English as well so there's also that kind of angle to things. We're also working with private and public organizations within Myanmar as well to kind of as part of the project and some of the pilot activity that we're involved in and then there's also the co-creation aspect and I'll come on and talk a little bit about that in a moment. So just very briefly this slide I'm going to show you this slide really just to show you how central OER development and open education is to the project. This shows you is related to the capacity building element of the project and it shows basically a two-year cycle where pre-COVID we were working with a group of universities you can see on the left with 10 universities that we started working with in 2018 for a two-year period initially and that two-year program was based and structured around residential schools, kind of webinars, online courses between them both for academics and for ICT librarian and support staff and then you can see through the middle we have OER development so throughout the whole of this two-year kind of period as well as the kind of sessions around open licensing and kind of practical kind of things we're also kind of working with people and people are working with each other at their universities to develop OER. Okay so moving on to talk a bit more about the Creative Commons remix that that we're in the process of doing as part of the master training program. So besides this being part of what we're kind of offering to people, why would we want to remix it? I don't know how familiar folks are in the audience with the Creative Commons certificate but we obviously we wanted to kind of remix it for a number of different reasons the main one being of course context and fundamentally as well there is a big change in copyright law in Myanmar that is in the process of happening. So in May 2019 a new copyright law was enacted and this was replacing a copyright law that's over a hundred years old when that kind of came in during the British colonial period in 1914 obviously that's kind of very much out of date when you think of what's happened since then and in terms of it just not really being enforceable. So there's a new copyright law kind of working its way through the system and that has quite stiff penalties for people that violate the the law. There's a two-year transition period but obviously that has huge implications for HE and what's happening currently in higher education so we wanted to kind of include kind of information around that. There's also kind of obviously the opportunity to include Myanmar colleagues in co-creation of the course and I'll talk a little bit more about that in a moment. We also knew that people seemed to be very interested or quite interested in Creative Commons and the work that we've done previously with people and the kind of developing this course and offering it as a kind of one-stop shop kind of place for people to come and find out more seems kind of like a good way to consolidate what we've been doing as well as reflecting the kind of experience that we'd have of working with people running sessions around open licensing and Creative Commons as well. Obviously it's on an open license so I'm hoping you know if we move forward that people will obviously improve the course as well as the improvements we're going to make as well and then finally full disclosure but I did at the end of 2019 I also participated in the Creative Commons for Educators course so I was obviously familiar with the course material and so on. Okay so what did we do very briefly so far so the course currently is a six-part remix of the original Creative Commons course so if you're familiar with that I think it's five weeks if I remember correctly or five units and what we've kind of done is we've created a standalone version so I mentioned it's part of Master Training Programme that means it will be kind of run facilitated for around 25 of our participants but obviously we need standalone versions so that people can come and use the course subsequently so obviously there's quizzes and reflection points as part of that course. We've made it available obviously in Myanmar and English language versions and we're hosting it on Open and Create and essential to this is that we're hoping through the Master Training Programme and the activity within that we will develop the course further and I'll talk about that in a moment and also obviously we're making this available on a CC by license. Just very briefly to show you the course structure as I mentioned there's six kind of units or sections to the course very much we've kind of styled with copyright and this is just really partly for onboarding kind of reasons if you're familiar with the CC certificate you know you kind of join the program having at least some knowledge or understanding around CC this may not be true for people in the future so for this course so we've kind of started the onboarding around copyright instead and then kind of go on to introduce Creative Commons within that context. We've also included a lot more we've included some of the material we've developed as part of the project so things around finding and evaluating OER as well as remixing and a lot more kind of step by step and detailed kind of details around how to do particular things included in the course as part of this and that was participant feedback from the people we've been working with around kind of preferences for these step by step kind of guides to guides to activity and then finally we've kind of ended the course with kind of looking at ideas of the way in which people could practically take that forward and I'm hoping that will be something that we can improve on and critically reflect on as part of what we're going to do with the facilitated one of the course. Okay just very briefly I've kind of already covered this I think really but you know really the course is about you know the new Myanmar copyright law and the work with lawyers in Myanmar as well to better understand what that means as part of developing this you know the kind of role of CC and open licensed material and its benefits to universities and colleges and then also obviously your own kind of practice and supporting use of OER at your institution. So how did we develop the course? This is kind of an ongoing I mentioned we're kind of still working on this currently but we started working spring of this year and from the get go I wanted to kind of involve participants in that process so held a kind of call to let people know this is what we're thinking of doing you know do you think this is a good idea get some feedback around that kind of put the original material for the CC cert for librarians open for review obviously that was in English language so we didn't get I believe much feedback from that and really ideally we probably would have translated that all into Myanmar language which would have enabled more critique we're now doing that critique as part of this work so if we went slightly differently maybe then would have been ideal but as the course is still being developed we'll hopefully get a lot more feedback going forward but we did do a lot of work around seeing what people wanted included in this kind of course so we did a Facebook poll we did a review of the original material both by UK and Myanmar based project team members and other stakeholders so particularly thanks to Irina Kushner in Eiffel as well for working with us on this and then also we had a discussion with a small group of Myanmar participants to talk about their experiences with OER and Creative Commons and that also helped shape the course and some of these colleagues also worked with Brian Mather's visual thinkery to develop the picture so you can see some of these in the presentation as I move through that as well so we have got some custom images for the course and then finally as I've already mentioned we worked with lawyers in Myanmar around material and on copyright and reuse some of our own existing tied content so in terms of contextualization I've already mentioned translation and Myanmar examples that kind of onboarding as well is really I think important thinking beyond just the tied project and to have to you know how do we kind of I think one of the questions when you kind of start working with folks is how do you contextualize and present something like Creative Commons and OER to two people so that kind of onboarding is really crucial illustrations have already mentioned and also you know very much kind of having that dialogue with people around their preference for format and content I just want to pick up on the final two points really here around renewable assignments and critical engagement with the course so one of the things that I'm kind of working on at the moment is the kind of assessment piece really and kind of building assignments to kind of both support the cascading that people have said that they'll be doing so by participating in the master training program there's an expectation that they'll and people want to kind of go back and share that with colleagues so by producing kind of slides or other materials to share with people this company will hopefully support that as well as enabling and supporting people to develop OER I'm also hoping that from this will people will want to kind of share some of those things and that they will become part of a future iteration of the course so particularly around developing case studies about people's own practice as well and I'm hoping that we'll be able to include some of those with people obviously people are happy to as part of what we're doing and then finally really fundamentally this critical engagement with the course to improve it you know this is really important it's there's a lot more work to do and I'm hoping that we can continue to work with Myanmar colleagues to make the course even better than it is yeah currently so finally just to say about next steps really as you've gotten probably gathered by now this is very much an iterative kind of process we're kind of just really at the start of this we're about to kind of launch on Myanmar in English language versions in December which will be kind of be when we start the first facilitated run and you start wrapping up thanks the first facilitated run and then finally in kind of March time we'll be looking to reversion and update the course again then so thank you very much for your time and yeah any questions thank you very much we run out of time for questions so if you have any questions please post them in the connect platform I shared the link in the in the chat and I am certain that back will post your slides also on there so thank you very much back we can stop the recording


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