1 00:00:01,840 --> 00:00:05,600 Speaker 1: Alsome Media. 2 00:00:06,280 --> 00:00:08,520 Speaker 2: Hello everyone, and welcome to the podcast. 3 00:00:08,560 --> 00:00:11,240 Speaker 1: It's me James today and I'm very lucky to be 4 00:00:11,360 --> 00:00:14,280 Speaker 1: joined by Bryce from No More Deaths And what we're 5 00:00:14,280 --> 00:00:17,040 Speaker 1: going to talk about today is this really excellent piece 6 00:00:17,320 --> 00:00:22,759 Speaker 1: of data visualization and research that depicts a very sad topic, 7 00:00:22,880 --> 00:00:26,160 Speaker 1: which is the deaths of migrant centering the United States. 8 00:00:26,560 --> 00:00:27,960 Speaker 1: And Bryce, I know he's done a lot of work 9 00:00:27,960 --> 00:00:30,880 Speaker 1: on this, so welcome to the show. Bryce, Thank you, Yeah, 10 00:00:30,920 --> 00:00:34,360 Speaker 1: you're welcome. I guess maybe we can start off. I'm 11 00:00:34,400 --> 00:00:37,159 Speaker 1: looking at this data visualization on a map right now, 12 00:00:37,200 --> 00:00:39,279 Speaker 1: and we'll have links in the show notes for other 13 00:00:39,360 --> 00:00:42,960 Speaker 1: people who want to look at it. Can you explain 14 00:00:43,560 --> 00:00:46,000 Speaker 1: what this data set is? 15 00:00:46,960 --> 00:00:51,280 Speaker 3: Yeah, So we collected through a bunch of different sources, 16 00:00:51,320 --> 00:00:56,160 Speaker 3: medical examiners, Justices of the Peace, SHERIFFISAL partner, CBPS owned data, 17 00:00:56,440 --> 00:01:00,600 Speaker 3: just a bunch of data on individual micro along the 18 00:01:00,680 --> 00:01:01,680 Speaker 3: US Mexican border. 19 00:01:02,400 --> 00:01:05,160 Speaker 4: And so this is different data through each. 20 00:01:05,040 --> 00:01:07,000 Speaker 3: Source, but generally we tried to get a lot of 21 00:01:07,160 --> 00:01:10,520 Speaker 3: demographic data, location data, positive death, and at least some 22 00:01:11,000 --> 00:01:13,440 Speaker 3: form of the instigram laertive to kind of get a 23 00:01:13,440 --> 00:01:14,959 Speaker 3: little bit of the context of. 24 00:01:15,000 --> 00:01:16,199 Speaker 4: How each of these people guide. 25 00:01:16,760 --> 00:01:18,920 Speaker 1: Yeah, if people are looking at the map, they can 26 00:01:19,000 --> 00:01:22,640 Speaker 1: see various colored dots, right, and they can click on 27 00:01:22,640 --> 00:01:25,280 Speaker 1: that dot and that will give them the fiscal year 28 00:01:25,440 --> 00:01:28,720 Speaker 1: the border trail sector. In some cases you'll see like 29 00:01:29,120 --> 00:01:32,000 Speaker 1: the type of death, maybe a gender and age, things 30 00:01:32,040 --> 00:01:35,960 Speaker 1: like that. Looking at it, like it's one of those 31 00:01:35,959 --> 00:01:38,680 Speaker 1: things that maybe is more emotionally difficult to view if 32 00:01:38,680 --> 00:01:41,640 Speaker 1: you're more familiar, Like I can look at these dots 33 00:01:41,680 --> 00:01:45,319 Speaker 1: and I can think of places I've been. I can 34 00:01:45,360 --> 00:01:47,880 Speaker 1: even think of that the day I was there, and 35 00:01:48,120 --> 00:01:52,120 Speaker 1: it's quite know, it's impactful to see that all these 36 00:01:52,120 --> 00:01:55,000 Speaker 1: people have died in places I know. So well, perhaps 37 00:01:55,520 --> 00:01:58,880 Speaker 1: we can explain, like the scale of this is huge, right, 38 00:01:58,920 --> 00:02:00,800 Speaker 1: do you know how many exactly how many data points 39 00:02:00,840 --> 00:02:01,640 Speaker 1: there are on here? 40 00:02:02,360 --> 00:02:04,480 Speaker 4: I think there's something like solve a thirteen thousand. 41 00:02:04,800 --> 00:02:08,280 Speaker 3: Yeah, it's fast, which overall is like not a great 42 00:02:08,720 --> 00:02:12,000 Speaker 3: sort of like indicator of how many people have actually 43 00:02:12,040 --> 00:02:14,920 Speaker 3: died or even know how many people could be reported 44 00:02:14,960 --> 00:02:17,560 Speaker 3: to have died, just because the Texas Day it all 45 00:02:17,600 --> 00:02:18,239 Speaker 3: is so walky. 46 00:02:19,400 --> 00:02:21,120 Speaker 2: Yeah, let's get into that. 47 00:02:21,120 --> 00:02:24,840 Speaker 1: Then let's talk about maybe the sources for this data, 48 00:02:25,000 --> 00:02:29,720 Speaker 1: and then maybe perhaps how your estimates are much high, 49 00:02:30,040 --> 00:02:33,400 Speaker 1: even with some of the emissions. Like the data that 50 00:02:33,440 --> 00:02:36,480 Speaker 1: you have tends to show under reporting, So like can 51 00:02:36,520 --> 00:02:39,200 Speaker 1: you explain first like where does this data come from 52 00:02:39,240 --> 00:02:41,120 Speaker 1: and how did you get it? You were saying the 53 00:02:41,120 --> 00:02:43,880 Speaker 1: Texas numbers are lower, but can you explain how like 54 00:02:43,919 --> 00:02:46,920 Speaker 1: there are these multiple jurisdictions and how you can't just 55 00:02:47,040 --> 00:02:48,760 Speaker 1: like ask someone for this information. 56 00:02:49,200 --> 00:02:52,200 Speaker 3: Yeah, there's a new people we're able to disask for it. Well, 57 00:02:52,240 --> 00:02:56,800 Speaker 3: generally it all comes from formal public records requests from 58 00:02:57,280 --> 00:03:00,120 Speaker 3: medical examiners. When we're lucky because medical examiners US we 59 00:03:00,240 --> 00:03:02,200 Speaker 3: have really good easily shaped double data. 60 00:03:03,040 --> 00:03:05,639 Speaker 4: So so we did for San Diego County, Yeah, that're 61 00:03:05,680 --> 00:03:06,359 Speaker 4: very good. 62 00:03:06,240 --> 00:03:09,880 Speaker 3: Pima County, the state of New Mexico, Al Passo, other 63 00:03:09,919 --> 00:03:13,440 Speaker 3: places have a corner that are associated with for sheriff department, 64 00:03:14,040 --> 00:03:17,239 Speaker 3: and that's usually a little dice year they're a little 65 00:03:17,280 --> 00:03:21,200 Speaker 3: more reluctant to give up records. The Imperial County, for 66 00:03:21,400 --> 00:03:25,560 Speaker 3: Yuma County and then Texas it's just like a medical 67 00:03:25,600 --> 00:03:31,440 Speaker 3: legal nightmare. So there's if smaller counties don't have medical examiners, 68 00:03:31,480 --> 00:03:33,440 Speaker 3: they just had justice into the peace culture. 69 00:03:33,720 --> 00:03:35,160 Speaker 4: Part of like the courts and. 70 00:03:35,280 --> 00:03:38,840 Speaker 3: They'll go out and investigate deaths and if an autopsy 71 00:03:38,880 --> 00:03:41,040 Speaker 3: is needed, they'll send it off to another county to 72 00:03:41,040 --> 00:03:43,560 Speaker 3: get an autopsy. There's a huge amount of counties in 73 00:03:43,600 --> 00:03:46,680 Speaker 3: Texas like this. So that data all came from this researcher, 74 00:03:46,800 --> 00:03:50,840 Speaker 3: Stephanie Luster from the University of Texas Austin, who is 75 00:03:50,880 --> 00:03:53,200 Speaker 3: working on a different project, but was gracious enough to 76 00:03:53,400 --> 00:03:56,960 Speaker 3: share everything that she had collected. But that was like 77 00:03:57,120 --> 00:03:59,680 Speaker 3: just a huge amount of work physically going to each 78 00:03:59,720 --> 00:04:03,600 Speaker 3: of these counties, looking at paper records from justices of 79 00:04:03,680 --> 00:04:07,520 Speaker 3: the peace, writing down all that data. There's some that 80 00:04:07,600 --> 00:04:11,480 Speaker 3: comes from like sheriff's department, some that comes from. 81 00:04:11,200 --> 00:04:14,880 Speaker 4: Various other sources. So the Texas data and some of it. 82 00:04:14,840 --> 00:04:18,600 Speaker 3: For example, Wegg County Medical Examiner, they don't give up 83 00:04:18,640 --> 00:04:22,279 Speaker 3: their data to anybody, and there's a lot of issues 84 00:04:22,320 --> 00:04:25,760 Speaker 3: with them potentially, like not having actually performed autopsy on 85 00:04:25,800 --> 00:04:28,159 Speaker 3: a lot of autopsies on a lot of migrants, and 86 00:04:28,240 --> 00:04:31,120 Speaker 3: there's some potential bookcases about that going on. 87 00:04:31,839 --> 00:04:32,360 Speaker 4: But yeah, so. 88 00:04:32,360 --> 00:04:35,719 Speaker 3: Texas is really messing and a lot of it you'll notice, 89 00:04:35,800 --> 00:04:36,719 Speaker 3: like Texas has a lot of. 90 00:04:36,680 --> 00:04:37,600 Speaker 4: The purple dots. 91 00:04:37,760 --> 00:04:42,560 Speaker 3: Yeah, the purple dots are their location data from Border 92 00:04:42,600 --> 00:04:46,600 Speaker 3: patrols database and so that ends in twenty eighteen. So 93 00:04:46,640 --> 00:04:50,719 Speaker 3: we have data possible needs border patrol over not location data. Yeah, 94 00:04:50,760 --> 00:04:52,920 Speaker 3: and so a lot of Texas on that being this 95 00:04:53,880 --> 00:04:57,680 Speaker 3: just the border patrol data unless we have loved specific 96 00:04:58,320 --> 00:05:02,760 Speaker 3: access to that places Justice of the Peace data. It's 97 00:05:02,800 --> 00:05:06,000 Speaker 3: so the Texas data is pretty limited for about reason. 98 00:05:06,520 --> 00:05:09,560 Speaker 1: Yeah, you can see a sort of very few red dots, 99 00:05:09,600 --> 00:05:14,000 Speaker 1: which which are your your other data sources like in 100 00:05:14,080 --> 00:05:16,560 Speaker 1: Texas aside from it. So maybe Brooks County you're able 101 00:05:16,640 --> 00:05:18,799 Speaker 1: to get Justice to the Peace data there because yeah, 102 00:05:18,920 --> 00:05:21,080 Speaker 1: the density is profound. 103 00:05:21,480 --> 00:05:24,600 Speaker 3: Yeah, it's just the So it's the Brooks County Chasta 104 00:05:24,680 --> 00:05:27,880 Speaker 3: Department that actually puts together that data, and they're really 105 00:05:28,040 --> 00:05:31,680 Speaker 3: keen on the whole thing. Okay, And partially it's because 106 00:05:31,720 --> 00:05:34,480 Speaker 3: the data exists, but partially it really wills just to 107 00:05:34,760 --> 00:05:38,120 Speaker 3: reach fluster death in that area because of a checkpoint 108 00:05:38,240 --> 00:05:41,040 Speaker 3: south of there where people will get dropped off south 109 00:05:41,040 --> 00:05:44,599 Speaker 3: of the checkpoint pipe around and it's just like massive, 110 00:05:45,720 --> 00:05:48,600 Speaker 3: massive open grade yard in Brooks County. 111 00:05:48,800 --> 00:05:49,240 Speaker 2: Jeez. 112 00:05:49,800 --> 00:05:51,599 Speaker 1: Yeah, I don't think I spent much time in that 113 00:05:51,720 --> 00:05:53,920 Speaker 1: part of Texas, but certainly like some of these other 114 00:05:53,960 --> 00:05:57,440 Speaker 1: ones that I'm much more familiar with. Let's talk about 115 00:05:57,680 --> 00:06:01,320 Speaker 1: the CBP data, right, you mentioned it there. One of 116 00:06:01,400 --> 00:06:05,440 Speaker 1: the things you found was that CBP has a systemic 117 00:06:05,520 --> 00:06:10,200 Speaker 1: issue with undercounting deaths, right yeah, So where does that 118 00:06:10,240 --> 00:06:10,640 Speaker 1: come from? 119 00:06:10,960 --> 00:06:14,960 Speaker 3: So I've heard from I guess for years Humane Borders 120 00:06:14,960 --> 00:06:18,479 Speaker 3: and Pema County Medical Examiner has been documenting this since 121 00:06:18,600 --> 00:06:22,440 Speaker 3: at least twenty fourteen. The major undercount on border patrols data. 122 00:06:22,760 --> 00:06:24,680 Speaker 3: But something I've here a lot is just that it's 123 00:06:24,760 --> 00:06:28,280 Speaker 3: cases where border thetow wasn't personally involved in the search 124 00:06:28,320 --> 00:06:30,440 Speaker 3: and that they had like changed their coounting system to 125 00:06:30,680 --> 00:06:33,240 Speaker 3: only be counting cases where they were involved. And I 126 00:06:33,279 --> 00:06:35,760 Speaker 3: think that may account for some of it. 127 00:06:36,160 --> 00:06:37,200 Speaker 4: But in order. 128 00:06:37,000 --> 00:06:41,599 Speaker 3: To compare these deaths, border patrols data is just really 129 00:06:41,640 --> 00:06:46,400 Speaker 3: gnarly and messy, and that there's typos, there's misspelling. States 130 00:06:46,440 --> 00:06:50,560 Speaker 3: are wrong, ages are wrong, genders are wrong. So you really, 131 00:06:50,600 --> 00:06:52,640 Speaker 3: in order to compare them, you really have to go 132 00:06:52,960 --> 00:06:54,240 Speaker 3: person by person. 133 00:06:54,200 --> 00:06:56,200 Speaker 4: Go down the list, find the death and in. 134 00:06:56,520 --> 00:06:59,760 Speaker 3: Order patrol database, look at Medical Examiner data on find 135 00:06:59,760 --> 00:07:03,120 Speaker 3: of them person by person. So because we have so 136 00:07:03,200 --> 00:07:06,400 Speaker 3: much of the incident narratives from the medical examiners, we 137 00:07:06,440 --> 00:07:09,080 Speaker 3: can actually tell when Border patrol was involved, and so 138 00:07:09,120 --> 00:07:12,360 Speaker 3: we mark when border patrols involved when they're not involved, 139 00:07:12,400 --> 00:07:14,720 Speaker 3: and then when that case doesn't actually get counted by 140 00:07:14,720 --> 00:07:15,360 Speaker 3: Border patrol. 141 00:07:15,720 --> 00:07:16,600 Speaker 4: Okay, and it. 142 00:07:16,560 --> 00:07:20,440 Speaker 3: Doesn't actually really line up. There's not a huge correlation there. 143 00:07:20,560 --> 00:07:23,600 Speaker 3: I mean there is some correlation, like older skeletal remains 144 00:07:23,640 --> 00:07:26,520 Speaker 3: things like that often won't get counted, but generally there 145 00:07:26,560 --> 00:07:28,679 Speaker 3: are a lot of cases where they directly involved where 146 00:07:28,800 --> 00:07:31,760 Speaker 3: even they were the first responders on the scene to 147 00:07:31,800 --> 00:07:35,760 Speaker 3: a distress call or any number of things, where that 148 00:07:35,880 --> 00:07:38,440 Speaker 3: person won't end up in Vorda patrols database. And then 149 00:07:38,480 --> 00:07:40,520 Speaker 3: other cases where it seems like they had no involvement, 150 00:07:41,040 --> 00:07:41,880 Speaker 3: that person ends. 151 00:07:41,760 --> 00:07:43,560 Speaker 4: Up being in Vortical Patrol's database. 152 00:07:43,640 --> 00:07:47,000 Speaker 3: So they've been in trouble with the GAO multiple times 153 00:07:47,120 --> 00:07:49,640 Speaker 3: for under counting or in prop of the accounting or 154 00:07:49,720 --> 00:07:53,640 Speaker 3: recording these debts, and so they have access to medical 155 00:07:53,640 --> 00:07:57,320 Speaker 3: examiner data. Medical examiners send them the data, they just 156 00:07:57,480 --> 00:08:00,960 Speaker 3: don't use it. We often also noticed that, uh, the 157 00:08:01,000 --> 00:08:03,560 Speaker 3: causes of death really don't match up in a lot 158 00:08:03,560 --> 00:08:07,520 Speaker 3: of like really specific cases like yeah, for Walfalls, for instance, 159 00:08:07,760 --> 00:08:10,720 Speaker 3: was the most notable one. There'll be a huge amount 160 00:08:10,760 --> 00:08:14,760 Speaker 3: of cases that medical examiner will say one force trauma, 161 00:08:15,320 --> 00:08:18,800 Speaker 3: and then Border Patrols data will say medical examiner and 162 00:08:18,880 --> 00:08:22,800 Speaker 3: detainment or exposure or any number of other things, which 163 00:08:22,920 --> 00:08:25,320 Speaker 3: like for the most part, causes the death seem to 164 00:08:25,320 --> 00:08:28,240 Speaker 3: line up. So the fact that these Waalfall deaths it 165 00:08:28,320 --> 00:08:31,280 Speaker 3: happens to not line up is like, you know, I 166 00:08:31,280 --> 00:08:34,720 Speaker 3: don't want to assume they have bad intent, although obviously 167 00:08:34,760 --> 00:08:38,640 Speaker 3: Bordemtrol is bad intent, but it seems like it happens 168 00:08:38,679 --> 00:08:40,960 Speaker 3: regularly enough that it's hard to feel like it's not 169 00:08:41,040 --> 00:08:44,120 Speaker 3: as somewhat intentional that the cases that they're kind of 170 00:08:44,160 --> 00:08:46,480 Speaker 3: choosing to change the causes of death. 171 00:08:46,320 --> 00:08:50,120 Speaker 1: For right, So let get obfuscates the lethality of the 172 00:08:50,160 --> 00:08:52,439 Speaker 1: border war, right length, it's the amount of people who 173 00:08:52,480 --> 00:08:52,960 Speaker 1: it kills. 174 00:08:53,240 --> 00:08:54,880 Speaker 4: Yeah, I mean to a huge degree too. 175 00:08:54,880 --> 00:08:57,240 Speaker 3: I mean the fact that Bordertrol's data is kind of 176 00:08:57,240 --> 00:09:00,200 Speaker 3: our only source of data for MCAN deaths and then 177 00:09:00,240 --> 00:09:03,560 Speaker 3: specifically for deaths caused by border patrol or like Walfall deaths, 178 00:09:03,960 --> 00:09:06,640 Speaker 3: means that the amount of death that we need the 179 00:09:06,640 --> 00:09:09,960 Speaker 3: public has access to, like Walhall death, for instance, is 180 00:09:10,040 --> 00:09:11,360 Speaker 3: just a drop in the bucket. 181 00:09:11,040 --> 00:09:12,400 Speaker 4: Compared to what's actually happening. 182 00:09:12,520 --> 00:09:14,760 Speaker 3: So all of the research and reporting and all the 183 00:09:14,760 --> 00:09:17,640 Speaker 3: stuff that happens around at these CC related deaths is 184 00:09:17,720 --> 00:09:20,640 Speaker 3: drawing off just like truly false numbers. 185 00:09:21,520 --> 00:09:26,120 Speaker 1: Yeah, yeah, and that leads to people growing bad conclusions, 186 00:09:26,200 --> 00:09:40,920 Speaker 1: right right. The other thing that you found is that 187 00:09:40,960 --> 00:09:43,360 Speaker 1: like that there seems to be an underreporting of in 188 00:09:43,400 --> 00:09:46,680 Speaker 1: custody deaths, right, or an undercounting of people who die 189 00:09:47,559 --> 00:09:49,679 Speaker 1: in custody. So can you explain how you're able to 190 00:09:49,720 --> 00:09:53,720 Speaker 1: ascertain that different between the in custody death recorded by 191 00:09:53,720 --> 00:09:55,640 Speaker 1: the Office of Professional Responsibility. 192 00:09:55,640 --> 00:09:57,760 Speaker 2: That's just the ones that you found, right, right. 193 00:09:57,800 --> 00:10:02,360 Speaker 3: So the opposite Professional Responsibility is part of CBP, and 194 00:10:02,960 --> 00:10:07,240 Speaker 3: they're supposed to be recording all the saw CBP related deaths, 195 00:10:07,280 --> 00:10:11,280 Speaker 3: including according to the Deats and Custody Reporting Act to 196 00:10:11,360 --> 00:10:14,120 Speaker 3: like twenty thirteen or whatever it was, army destin plustody. 197 00:10:14,120 --> 00:10:16,920 Speaker 3: There's a really specific definition of what in custody means, 198 00:10:17,280 --> 00:10:21,000 Speaker 3: and so we tried to follow pretty strictly what that 199 00:10:21,080 --> 00:10:25,000 Speaker 3: definition was to kind of make our own assessments using 200 00:10:25,120 --> 00:10:26,480 Speaker 3: the incident narratives. 201 00:10:26,720 --> 00:10:29,880 Speaker 1: Yeah, I'm curious what does it mean, Like I'm thinking 202 00:10:29,920 --> 00:10:33,240 Speaker 1: about door intention, right, Like does that count as in custody? 203 00:10:33,600 --> 00:10:33,840 Speaker 4: Yeah? 204 00:10:33,880 --> 00:10:36,080 Speaker 3: So any only time if the person is in the 205 00:10:36,120 --> 00:10:38,840 Speaker 3: process of being apprehended, if the person has been apprehended, 206 00:10:39,080 --> 00:10:41,680 Speaker 3: if a person has been detained, as a person is 207 00:10:41,800 --> 00:10:45,600 Speaker 3: physically in custody, bordertrol, in a bordertrol vehicle, in a 208 00:10:45,640 --> 00:10:49,360 Speaker 3: CP facility, all those things would count. Is inculsody okay, 209 00:10:49,520 --> 00:10:52,400 Speaker 3: which is important because and at least one of the cases, 210 00:10:52,400 --> 00:10:55,720 Speaker 3: the border patrol agent involved said the person wasn't in custody, 211 00:10:55,760 --> 00:10:59,040 Speaker 3: he was just detained, which for the purposes of reporting, 212 00:10:59,040 --> 00:11:00,320 Speaker 3: there's actually no difference. 213 00:11:00,400 --> 00:11:02,760 Speaker 4: Right, Yeah, but you said that clearly to. 214 00:11:02,960 --> 00:11:05,720 Speaker 3: Not have it be labeled as in custody death right, 215 00:11:05,920 --> 00:11:08,400 Speaker 3: and what it seems like that ended up not being 216 00:11:08,600 --> 00:11:11,880 Speaker 3: able toserve in custody death So it's definitely I think 217 00:11:11,880 --> 00:11:14,760 Speaker 3: they're they're aware the fact that these are being requoted 218 00:11:14,840 --> 00:11:16,240 Speaker 3: and kind of tron not to have. 219 00:11:16,240 --> 00:11:18,600 Speaker 1: That due to case they have too many of them, 220 00:11:18,720 --> 00:11:22,200 Speaker 1: like appear Another interesting data interesting is your own word, 221 00:11:22,240 --> 00:11:25,480 Speaker 1: but another data point here was the amount of death 222 00:11:25,600 --> 00:11:29,560 Speaker 1: caused by pursuit right or in pursuit I guess maybe 223 00:11:29,760 --> 00:11:33,240 Speaker 1: you should just explain what pursuit is to people if 224 00:11:33,240 --> 00:11:33,920 Speaker 1: they're not aware. 225 00:11:34,520 --> 00:11:37,840 Speaker 3: Yeah, so there's two kinds of pursuit. We listen at 226 00:11:37,880 --> 00:11:40,640 Speaker 3: the same gear on the database. You can see the 227 00:11:40,679 --> 00:11:45,120 Speaker 3: difference of there's chases on a motor vehicle and there's 228 00:11:45,200 --> 00:11:49,080 Speaker 3: chases on foot. So for example, a person's getting chase 229 00:11:49,520 --> 00:11:52,600 Speaker 3: through the desert and collapses and dies, they'll be considered 230 00:11:52,600 --> 00:11:55,839 Speaker 3: a death your pursuit. Or if a person is like 231 00:11:55,960 --> 00:11:59,480 Speaker 3: in al Paso or San Diego or Imperial County more 232 00:12:00,160 --> 00:12:03,560 Speaker 3: is chased ends up falling in a canal or jumping 233 00:12:03,559 --> 00:12:07,720 Speaker 3: into a canal escape and drowns. The idea chase on 234 00:12:07,760 --> 00:12:12,520 Speaker 3: foot and then motor vehicle pursuits are yeah, the person 235 00:12:12,640 --> 00:12:15,840 Speaker 3: is being chased by Border patrol and the glosing passions. 236 00:12:15,480 --> 00:12:16,640 Speaker 4: And people are chilled. Yeah. 237 00:12:17,040 --> 00:12:20,439 Speaker 3: Use of force cases also include some of these chases 238 00:12:20,840 --> 00:12:25,800 Speaker 3: through OPR standards and CVP standards. If spike strips are deployed, 239 00:12:26,040 --> 00:12:28,960 Speaker 3: or if a vehicle is ran by a Border Patrol vehicle, 240 00:12:29,040 --> 00:12:32,480 Speaker 3: that's considered use of force. So that's where a person 241 00:12:32,520 --> 00:12:34,959 Speaker 3: died due to that, we would call that a use 242 00:12:34,960 --> 00:12:37,439 Speaker 3: of force death. Yeah, So I guess those are the 243 00:12:37,720 --> 00:12:40,360 Speaker 3: two to three different times and perceived that's a. 244 00:12:40,360 --> 00:12:43,160 Speaker 1: Great do and so like the yeah, those are as 245 00:12:43,200 --> 00:12:45,320 Speaker 1: you say they're broken down the database, right, but in 246 00:12:45,400 --> 00:12:51,360 Speaker 1: the spreadsheet they are combined. What is this data show 247 00:12:51,480 --> 00:12:54,840 Speaker 1: us about? Like, I guess if we look at the 248 00:12:54,960 --> 00:12:58,360 Speaker 1: last half decade or so, let's go back to like 249 00:12:58,360 --> 00:13:02,280 Speaker 1: twenty sixteen, right, border police, Like, what does it show 250 00:13:02,400 --> 00:13:06,520 Speaker 1: us about like title eight, Title forty two, we're like 251 00:13:06,559 --> 00:13:10,200 Speaker 1: a little too close to the Biden asylum band to 252 00:13:10,280 --> 00:13:14,320 Speaker 1: have I guess, like good data on that yet. But 253 00:13:14,400 --> 00:13:18,400 Speaker 1: do you see a clear pattern in like the border 254 00:13:18,520 --> 00:13:23,040 Speaker 1: rhetoric and border quote unquote enforcement and the amount of 255 00:13:23,080 --> 00:13:24,240 Speaker 1: death or the type of death? 256 00:13:24,840 --> 00:13:30,000 Speaker 3: Well, definitely, yeah, it's it's immediately clear. I mean, even 257 00:13:30,160 --> 00:13:33,400 Speaker 3: Biden's asylum band, I think there's an immediate effect. I 258 00:13:33,400 --> 00:13:36,080 Speaker 3: mean even just with as a normal death volunteer, we 259 00:13:36,160 --> 00:13:39,920 Speaker 3: started seeing people crossing the border, crossing the desert that 260 00:13:40,080 --> 00:13:43,120 Speaker 3: just never would have yet made the attempt previously, you know, 261 00:13:43,160 --> 00:13:45,160 Speaker 3: and then started to see as people reported in death 262 00:13:45,240 --> 00:13:49,120 Speaker 3: data too. So I think all of that is pretty clear. 263 00:13:50,000 --> 00:13:55,240 Speaker 3: So with Trump's restrictions on asylum, I think the biggest thing, 264 00:13:55,280 --> 00:13:58,800 Speaker 3: honestly was all the metering policies rather than just Title 265 00:13:58,880 --> 00:14:01,640 Speaker 3: forty two or like Protection Book protocols or any of that. 266 00:14:02,080 --> 00:14:04,320 Speaker 3: It was just the fact that people weren't allowed to 267 00:14:04,320 --> 00:14:05,600 Speaker 3: access the border country. 268 00:14:05,720 --> 00:14:07,880 Speaker 4: Yeah, ended up kind of like going. 269 00:14:07,640 --> 00:14:11,080 Speaker 3: Around to enter like other places in the desert border 270 00:14:11,240 --> 00:14:14,000 Speaker 3: sort of pick them up. Then all this started happening, Yeah, 271 00:14:14,280 --> 00:14:17,440 Speaker 3: And so it's kind of like a trickle in twenty nineteen, 272 00:14:17,559 --> 00:14:20,040 Speaker 3: twenty twenty, a little bit more in twenty twenty one, 273 00:14:20,080 --> 00:14:22,800 Speaker 3: and then twenty twenty two you suddenly see just huge 274 00:14:22,840 --> 00:14:26,360 Speaker 3: amounts of people from countries other than Mexico and Central 275 00:14:26,400 --> 00:14:29,600 Speaker 3: America starting to show up in the data. And then 276 00:14:29,640 --> 00:14:33,880 Speaker 3: also like people who clearly were trying to seek asylum 277 00:14:34,120 --> 00:14:37,160 Speaker 3: showing up in this death data all the way up 278 00:14:37,240 --> 00:14:40,680 Speaker 3: until it slowed down after you know, the end of 279 00:14:40,840 --> 00:14:45,080 Speaker 3: three twenty three, and then but definitely continue. 280 00:14:44,680 --> 00:14:49,400 Speaker 1: Through through for Yeah, definitely, like I speaking from my 281 00:14:49,480 --> 00:14:52,800 Speaker 1: own experience on the border here, we saw the same thing, right, 282 00:14:52,840 --> 00:14:56,280 Speaker 1: like people crossing you wouldn't have seen making that crossing 283 00:14:56,920 --> 00:15:01,240 Speaker 1: in places at times that they wouldn't have crossed, you know, 284 00:15:01,360 --> 00:15:05,080 Speaker 1: before the Biden asylum ban, and like that definitely resulted 285 00:15:05,120 --> 00:15:08,280 Speaker 1: in I mean there was a weekend in September where 286 00:15:08,280 --> 00:15:12,480 Speaker 1: I think five people died September twenty twenty four, but 287 00:15:12,520 --> 00:15:15,400 Speaker 1: we had a heat wave and like it immediately resulted 288 00:15:15,400 --> 00:15:19,880 Speaker 1: in multiple fatalities that like wouldn't have been the case previously. 289 00:15:20,720 --> 00:15:25,120 Speaker 1: I wonder, like what is this data set in terms 290 00:15:25,200 --> 00:15:28,560 Speaker 1: of like recommendations, right in terms of like how we 291 00:15:28,640 --> 00:15:30,920 Speaker 1: can use this data set? Obviously, we're at a time 292 00:15:31,000 --> 00:15:33,320 Speaker 1: when I when I guess the Trump administration like had 293 00:15:33,320 --> 00:15:36,960 Speaker 1: its complete asylum band stayed, but we're back at like 294 00:15:37,600 --> 00:15:39,680 Speaker 1: people can't in good faith like turn up to a 295 00:15:39,760 --> 00:15:41,440 Speaker 1: port of entry anymore and just be like, Hey, I'd 296 00:15:41,480 --> 00:15:43,800 Speaker 1: like to claim asylum and really really hope for the best. 297 00:15:44,200 --> 00:15:46,280 Speaker 1: Like what does this data set tell us in terms 298 00:15:46,280 --> 00:15:49,640 Speaker 1: of like what policies kill more people? And like I guess, 299 00:15:49,680 --> 00:15:53,040 Speaker 1: like like what recommendations arise from the data in terms obviously, 300 00:15:53,640 --> 00:15:56,080 Speaker 1: I guess bit of the recommendation is to have laws 301 00:15:56,080 --> 00:15:58,640 Speaker 1: that allow people to fucking enter this country and claim 302 00:15:58,680 --> 00:16:01,840 Speaker 1: asylum without walking across a desert. But that seems like 303 00:16:01,840 --> 00:16:03,520 Speaker 1: it's too much to ask, So like what do we 304 00:16:03,640 --> 00:16:06,800 Speaker 1: learn in terms of like specific policies that are particularly 305 00:16:06,840 --> 00:16:11,600 Speaker 1: fatal and like the ways that those that could be 306 00:16:11,760 --> 00:16:15,920 Speaker 1: mitigated and if it's not already by like water drops 307 00:16:15,920 --> 00:16:16,280 Speaker 1: and search. 308 00:16:17,080 --> 00:16:21,320 Speaker 3: Yeah, that's a hard question, just because talking to you know, 309 00:16:21,360 --> 00:16:24,000 Speaker 3: the older people and the more death's been around since 310 00:16:24,080 --> 00:16:27,560 Speaker 3: like kind of the early years of prevention to the terrence. Yeah, 311 00:16:27,760 --> 00:16:30,080 Speaker 3: they thought about sort of feeling like you know, when 312 00:16:30,120 --> 00:16:32,000 Speaker 3: they were first out there, being like, man, this is 313 00:16:32,040 --> 00:16:35,120 Speaker 3: really unsustainable. We can't out here all the time like this. 314 00:16:35,680 --> 00:16:37,840 Speaker 3: Maybe like a few more years we could probably handle 315 00:16:37,880 --> 00:16:40,760 Speaker 3: and then hopefully this prevention to the terrence thing will 316 00:16:40,800 --> 00:16:43,480 Speaker 3: have like kind of stopped. They'll see like this is unsustainable, 317 00:16:43,760 --> 00:16:45,800 Speaker 3: and then here we are all these years later and 318 00:16:45,840 --> 00:16:49,120 Speaker 3: it's worse than it's et in. Yeah, And the original 319 00:16:49,120 --> 00:16:52,080 Speaker 3: prevention to the terance policy is like this strategy of 320 00:16:52,640 --> 00:16:54,800 Speaker 3: essentially killing people and the hopes, you know, people will 321 00:16:54,840 --> 00:16:58,240 Speaker 3: stop trying to cross the border or something, and kind 322 00:16:58,240 --> 00:17:00,000 Speaker 3: of just is the original thing that it's really hard 323 00:17:00,120 --> 00:17:03,520 Speaker 3: to get away from. Yeah, the fact that we're now 324 00:17:03,600 --> 00:17:08,440 Speaker 3: applying the same strategy of death and suffering to asylum 325 00:17:08,440 --> 00:17:10,439 Speaker 3: seekers is really horrifying. 326 00:17:10,720 --> 00:17:14,200 Speaker 4: So I think, yeah, Number one, open up courts. 327 00:17:14,000 --> 00:17:16,880 Speaker 3: Eventually to allow asylum secret to seek asylum, bring back 328 00:17:17,000 --> 00:17:19,720 Speaker 3: like even the sort of minimum asylum projections that we 329 00:17:19,800 --> 00:17:23,240 Speaker 3: had back then. Other things like how people are dying 330 00:17:23,280 --> 00:17:27,359 Speaker 3: really matters. Yeah, So for example, in the Lapasto sector, 331 00:17:27,720 --> 00:17:30,720 Speaker 3: there was very very few deaths in twenty fourteen. The 332 00:17:30,800 --> 00:17:33,960 Speaker 3: last couple of years it's been the deadliest single small 333 00:17:34,040 --> 00:17:36,960 Speaker 3: area in the entire border, and a lot of that 334 00:17:37,119 --> 00:17:39,800 Speaker 3: was just because the order has just become so militarized 335 00:17:39,800 --> 00:17:42,880 Speaker 3: that even this like urban area where you know, people 336 00:17:42,960 --> 00:17:46,560 Speaker 3: are dying a mile from town, people are dying in town. 337 00:17:46,680 --> 00:17:49,159 Speaker 3: We I was part of the recovery where we this 338 00:17:49,240 --> 00:17:51,879 Speaker 3: person was on a road, had been there for about 339 00:17:51,880 --> 00:17:55,800 Speaker 3: three days dead. It was about forty feet from the 340 00:17:55,840 --> 00:17:59,879 Speaker 3: busiest the busiest road in the entire town. Yeah, and 341 00:18:00,560 --> 00:18:03,119 Speaker 3: that's just not something that really fits in with the 342 00:18:03,280 --> 00:18:06,960 Speaker 3: ordinary narrative like prevenual Tuiterians people getting pushed out to 343 00:18:06,960 --> 00:18:10,359 Speaker 3: these more remote areas, and I think just a level 344 00:18:10,359 --> 00:18:12,840 Speaker 3: of militarization is just up to the level that it 345 00:18:13,000 --> 00:18:15,480 Speaker 3: really is just deadly kind of. I mean even yeah, 346 00:18:15,520 --> 00:18:19,080 Speaker 3: all these deaths in San Diego, as you know, also 347 00:18:19,200 --> 00:18:21,760 Speaker 3: do so like all these Walfall deaths are pretty much 348 00:18:21,760 --> 00:18:24,800 Speaker 3: all since like twenty seventeen or even more recently, so 349 00:18:24,840 --> 00:18:27,200 Speaker 3: the construction of all this new border wall, you can 350 00:18:27,200 --> 00:18:29,960 Speaker 3: point very directly to a huge amount of deaths. 351 00:18:29,560 --> 00:18:31,000 Speaker 4: Just caused by walfalls. 352 00:18:31,160 --> 00:18:37,040 Speaker 3: There's the canals in Imperial County and al Paso that 353 00:18:37,320 --> 00:18:40,080 Speaker 3: there a huge amount of people. There's Alpaso right now 354 00:18:40,160 --> 00:18:42,359 Speaker 3: is in the process of revamping their whole canal system. 355 00:18:42,680 --> 00:18:44,680 Speaker 4: Would be a great opportunity. 356 00:18:44,119 --> 00:18:46,880 Speaker 3: To add some sort of like safety systems in place 357 00:18:46,920 --> 00:18:50,440 Speaker 3: so that people don't die. Yeah, there is all the 358 00:18:50,480 --> 00:18:52,399 Speaker 3: pursue deaths which now are not just being caused the 359 00:18:52,400 --> 00:18:55,840 Speaker 3: border patrol, but also like the Texas Department of Public 360 00:18:55,840 --> 00:18:59,280 Speaker 3: Public Safety now that Operation Lone Star has helped up 361 00:18:59,880 --> 00:19:03,040 Speaker 3: all these things where the kinds of death and the 362 00:19:03,119 --> 00:19:06,880 Speaker 3: kinds of people dying and all that stuff has changed 363 00:19:07,040 --> 00:19:10,280 Speaker 3: and increased really drastically in the last few years. 364 00:19:10,320 --> 00:19:12,240 Speaker 4: And you can kind of point to a lot of them. 365 00:19:12,359 --> 00:19:15,080 Speaker 3: But also it's like, yeah, I don't know, it's hard 366 00:19:15,200 --> 00:19:18,520 Speaker 3: to really have any smart thoughts on it. Besides, just 367 00:19:18,800 --> 00:19:22,639 Speaker 3: like bore control is underformable and just needs to be disbanded. 368 00:19:22,240 --> 00:19:26,119 Speaker 1: Entire Yeah, and like this whole border regime, right, the 369 00:19:26,160 --> 00:19:29,280 Speaker 1: whole idea of like an iron border that we enforce 370 00:19:29,720 --> 00:19:32,920 Speaker 1: in a physical space. The point of it is to 371 00:19:33,040 --> 00:19:35,800 Speaker 1: kill people, Like the point of it is to hurt 372 00:19:35,840 --> 00:19:40,879 Speaker 1: people by having perfectly innocent people who you'd be happy 373 00:19:40,920 --> 00:19:42,840 Speaker 1: to have with your neighbor die in the desert. 374 00:19:43,040 --> 00:19:45,520 Speaker 2: Like that's that is, that is the policy goal. 375 00:19:45,840 --> 00:19:48,200 Speaker 1: Like I'm just looking at like I'm looking at Pinto Canyon, 376 00:19:48,240 --> 00:19:51,040 Speaker 1: which San Diego people will know. It's like it's pretty 377 00:19:51,040 --> 00:19:52,440 Speaker 1: Like don't if you're listening to this, don't go to 378 00:19:52,480 --> 00:19:53,159 Speaker 1: Pinto Canyon. 379 00:19:53,520 --> 00:19:54,160 Speaker 2: You might die. 380 00:19:54,280 --> 00:19:56,959 Speaker 1: It's not a place to just go looking around if 381 00:19:57,000 --> 00:19:59,560 Speaker 1: you're not experienced traveling out in the desert. But like 382 00:19:59,640 --> 00:20:03,640 Speaker 1: even Pinter Canyon is Nali, But looking along the wall, 383 00:20:03,680 --> 00:20:06,440 Speaker 1: the wall kills way more people than this rugged and 384 00:20:07,440 --> 00:20:09,840 Speaker 1: difficult piece of terrain in the middle of nowhere. Like 385 00:20:10,000 --> 00:20:13,040 Speaker 1: it's it's things that we have paid a lot of 386 00:20:13,080 --> 00:20:15,680 Speaker 1: money for that kill the most people. And that's pretty 387 00:20:15,680 --> 00:20:31,000 Speaker 1: brutal to confront. One of the other things that you 388 00:20:31,040 --> 00:20:34,119 Speaker 1: guys were able to determine was that like a number 389 00:20:34,160 --> 00:20:38,960 Speaker 1: of United States residents had died right in this data sect. 390 00:20:39,119 --> 00:20:42,200 Speaker 2: Yeah, can you explain that for people totally? 391 00:20:42,240 --> 00:20:42,320 Speaker 4: So? 392 00:20:42,440 --> 00:20:44,840 Speaker 3: Yeah, Like you said, there's people you'd love to have 393 00:20:44,880 --> 00:20:47,960 Speaker 3: as your neighbor dying in all these places, and not 394 00:20:48,040 --> 00:20:50,679 Speaker 3: just that, but your actual neighbor. The amount of people 395 00:20:51,600 --> 00:20:55,119 Speaker 3: whose main residence listed was just in San Diego County, 396 00:20:55,240 --> 00:21:01,120 Speaker 3: in Oceanside, in Bakersfield and Indianapolis, places that we've all 397 00:21:01,119 --> 00:21:04,680 Speaker 3: been to. We were able to record for San Diego 398 00:21:04,720 --> 00:21:08,080 Speaker 3: County and a few other counties a lot of where 399 00:21:08,119 --> 00:21:12,720 Speaker 3: people actually lived in some of the circumstances for why 400 00:21:12,720 --> 00:21:14,560 Speaker 3: they were crossing through the desert in the first place. 401 00:21:15,119 --> 00:21:17,800 Speaker 3: A lot of it is people who are very recently deported, 402 00:21:18,119 --> 00:21:20,919 Speaker 3: or who just traveled to Mexico because they had to 403 00:21:20,920 --> 00:21:24,200 Speaker 3: get some paperwork done or wanted to visit family or 404 00:21:24,240 --> 00:21:27,080 Speaker 3: things like this. Just had entire lives in the United 405 00:21:27,080 --> 00:21:29,920 Speaker 3: States and then and then passed away on the way 406 00:21:29,920 --> 00:21:31,640 Speaker 3: back ends of the country. 407 00:21:31,960 --> 00:21:32,920 Speaker 4: Yeah, including them. 408 00:21:33,320 --> 00:21:35,680 Speaker 3: I mean, it's really heartbreaking to you can see, there's 409 00:21:35,720 --> 00:21:38,600 Speaker 3: there's a lot of cases where the person who actually 410 00:21:39,080 --> 00:21:41,679 Speaker 3: finds the body or recovers the body is not there 411 00:21:41,760 --> 00:21:45,800 Speaker 3: some family members or their spouse or their children, even 412 00:21:46,480 --> 00:21:49,760 Speaker 3: which only happens because you know, bord of Trol is 413 00:21:49,800 --> 00:21:54,119 Speaker 3: generally not that interested in recovering bodies or in looking 414 00:21:54,160 --> 00:21:57,640 Speaker 3: for people who are lost. So often often it'll be 415 00:21:58,400 --> 00:22:01,199 Speaker 3: somebody's spouse who comes. I mean, when it's actually the 416 00:22:01,200 --> 00:22:02,160 Speaker 3: first person on the stea. 417 00:22:02,840 --> 00:22:07,720 Speaker 1: Yeah, it's it's very common right for volunteers to be 418 00:22:07,760 --> 00:22:10,679 Speaker 1: alerted via like you know, I know some of the 419 00:22:10,720 --> 00:22:13,680 Speaker 1: certain rescue groups are alerted by like Instagram for instance, 420 00:22:13,760 --> 00:22:17,160 Speaker 1: that like someone is missing, right, It's not like there 421 00:22:17,240 --> 00:22:22,520 Speaker 1: is like despite this being massively overfunded, you can't just 422 00:22:22,560 --> 00:22:24,680 Speaker 1: call and they won't just send out an ambulance like 423 00:22:24,880 --> 00:22:27,080 Speaker 1: a lot a lot of a lot of times it 424 00:22:27,160 --> 00:22:30,240 Speaker 1: is either the family members or like a bunch of 425 00:22:30,320 --> 00:22:32,760 Speaker 1: volunteers just driving out there in the trucks at last night. 426 00:22:32,800 --> 00:22:35,720 Speaker 1: Like I can remember in running into some migrants in 427 00:22:35,720 --> 00:22:37,600 Speaker 1: like twenty twenty three and then being like, hey, there 428 00:22:37,600 --> 00:22:40,639 Speaker 1: are some other people down there, and I was like where, 429 00:22:40,680 --> 00:22:42,000 Speaker 1: how do you know? And they found them on a 430 00:22:42,040 --> 00:22:45,600 Speaker 1: snapchat mat wow, and like that that was you know, 431 00:22:45,640 --> 00:22:48,879 Speaker 1: the only thing that maybe said those people's life. And 432 00:22:48,960 --> 00:22:51,160 Speaker 1: yet it it's pretty brutal to think that like there's 433 00:22:51,200 --> 00:22:53,920 Speaker 1: still really there's no one where there are people you 434 00:22:53,920 --> 00:22:55,320 Speaker 1: can call, I'm help you, But it's not the people 435 00:22:55,320 --> 00:22:58,760 Speaker 1: who are getting billions of dollars. Let's talk very briefly 436 00:22:59,200 --> 00:23:01,919 Speaker 1: before we finish up about deaths outside of the United States. 437 00:23:01,960 --> 00:23:03,280 Speaker 2: I see you have some data. 438 00:23:03,880 --> 00:23:07,560 Speaker 1: Like obviously my familiarity is with the Daddy and GAP, 439 00:23:07,680 --> 00:23:11,040 Speaker 1: which good luck getting. I don't think that data exists. 440 00:23:11,800 --> 00:23:13,680 Speaker 1: But like, I see you have a number of data 441 00:23:13,720 --> 00:23:16,560 Speaker 1: points within Mexico. Can you explain like how you came 442 00:23:16,600 --> 00:23:20,760 Speaker 1: across thovis and to what extent that data is if 443 00:23:20,800 --> 00:23:22,959 Speaker 1: at all like representative or complete. 444 00:23:23,520 --> 00:23:26,359 Speaker 3: Yeah, so it's not at all representative or complete. It 445 00:23:26,400 --> 00:23:29,640 Speaker 3: all comes from the National Institute of Integration, the. 446 00:23:29,840 --> 00:23:35,000 Speaker 4: I and M in Mexico. Yeah, I guess. 447 00:23:35,000 --> 00:23:38,400 Speaker 3: Actually the water working People's VETA are they're like sort 448 00:23:38,400 --> 00:23:43,359 Speaker 3: of like quot n flot entity and it were migrants 449 00:23:43,520 --> 00:23:48,280 Speaker 3: instituted by the government of Mexico in Mexico, and so 450 00:23:48,320 --> 00:23:53,680 Speaker 3: we through the Mexican Golooya, you're able to get data 451 00:23:53,720 --> 00:23:57,240 Speaker 3: from the group of veta, which throughout the years there's 452 00:23:57,280 --> 00:24:01,119 Speaker 3: been kind of like changing locations of offices, so the 453 00:24:01,960 --> 00:24:05,400 Speaker 3: data we had was just from where their offices are. 454 00:24:05,600 --> 00:24:07,600 Speaker 3: So it's usually just sort of like a number of 455 00:24:07,680 --> 00:24:11,800 Speaker 3: deaths for that particular office for that particular year. It's 456 00:24:11,960 --> 00:24:16,880 Speaker 3: very very limited, and there's many, many, many deaths that 457 00:24:17,480 --> 00:24:22,560 Speaker 3: we then have other data to show that doesn't exist here. 458 00:24:22,680 --> 00:24:25,840 Speaker 3: So it's really just planet right, Yeah, shouldn't be taken 459 00:24:25,880 --> 00:24:28,359 Speaker 3: as any kind of like representative sample, or it's just 460 00:24:29,040 --> 00:24:32,080 Speaker 3: the one piece of Mexican data that we were able to. 461 00:24:32,320 --> 00:24:33,320 Speaker 4: Quickly put on the map. 462 00:24:33,520 --> 00:24:38,080 Speaker 3: Yeah, we did get other data from like specific states 463 00:24:38,119 --> 00:24:42,560 Speaker 3: in Mexico, but we through because of time and capacity 464 00:24:42,680 --> 00:24:45,440 Speaker 3: and just the data itself we were unable to turn 465 00:24:45,520 --> 00:24:46,800 Speaker 3: back into. 466 00:24:47,359 --> 00:24:50,199 Speaker 4: Yet we wouldn't do something with that. 467 00:24:51,160 --> 00:24:53,720 Speaker 1: Yeah, And I think it still remains true that like 468 00:24:53,760 --> 00:24:56,720 Speaker 1: the single deadliest mind of this journey is the United 469 00:24:56,720 --> 00:25:02,120 Speaker 1: States border, at least from this data that you're seeing. 470 00:25:02,359 --> 00:25:04,040 Speaker 1: Would you say this data still supports that. 471 00:25:05,320 --> 00:25:06,760 Speaker 4: Probably I don't know. 472 00:25:06,920 --> 00:25:11,320 Speaker 3: Yeah, yeah, probably, I just don't want to say, because 473 00:25:11,320 --> 00:25:12,920 Speaker 3: the data is just so bad in so many places, 474 00:25:13,000 --> 00:25:14,119 Speaker 3: especially in Mexico abought. 475 00:25:14,440 --> 00:25:17,240 Speaker 1: Yeah, I'm thinking of like the Daddy in right, Like 476 00:25:17,359 --> 00:25:22,480 Speaker 1: it's it's very deadly. I've seen people die there, Like 477 00:25:23,640 --> 00:25:26,359 Speaker 1: it's obviously a very very difficult and rugged place. But 478 00:25:26,440 --> 00:25:29,480 Speaker 1: I think comparatively, probably more people die in the US border, 479 00:25:29,600 --> 00:25:33,920 Speaker 1: just because there were more of them and because people 480 00:25:33,960 --> 00:25:36,560 Speaker 1: come like people are ye, not everyone has to cross 481 00:25:36,600 --> 00:25:39,439 Speaker 1: a dairy end, like people can fly to Mexico or 482 00:25:39,520 --> 00:25:42,400 Speaker 1: somewhere further south, right and then come up that way 483 00:25:43,280 --> 00:25:45,879 Speaker 1: where if people want to find this data, or perhaps 484 00:25:45,920 --> 00:25:49,359 Speaker 1: as someone who's like a ninja with with data and 485 00:25:49,480 --> 00:25:52,160 Speaker 1: data visualization, they want to offer to help, like where 486 00:25:52,160 --> 00:25:54,200 Speaker 1: can people find this and how can they reach out 487 00:25:54,240 --> 00:25:55,840 Speaker 1: to no more desks if they'd like to help in 488 00:25:55,840 --> 00:25:56,240 Speaker 1: some way. 489 00:25:56,800 --> 00:25:58,960 Speaker 3: Yeah, So just on the normal DOES website, we can 490 00:25:59,000 --> 00:26:01,440 Speaker 3: see the report on the map and all that stuff. 491 00:26:01,600 --> 00:26:07,120 Speaker 3: And in there there's a link to the media outreach email, 492 00:26:07,240 --> 00:26:09,800 Speaker 3: which in the next couple of months is my email, 493 00:26:10,200 --> 00:26:13,040 Speaker 3: and just feel free to send send an email there. 494 00:26:13,280 --> 00:26:15,560 Speaker 3: And yeah, happy to. 495 00:26:15,359 --> 00:26:17,120 Speaker 4: Give greater accent right now. 496 00:26:17,440 --> 00:26:22,080 Speaker 3: The data is pretty anonymized for privacy and safety. Yeah, 497 00:26:22,359 --> 00:26:25,280 Speaker 3: and there's a lot of the fields that we've kind 498 00:26:25,280 --> 00:26:28,240 Speaker 3: of talked about that don't look here in the public database, 499 00:26:28,760 --> 00:26:33,440 Speaker 3: so happy to share that with researchers, activists, advocacy. 500 00:26:33,000 --> 00:26:35,040 Speaker 4: People, chain us, things like that. 501 00:26:35,200 --> 00:26:38,359 Speaker 3: And also we desperately would have a lot to help, so 502 00:26:39,040 --> 00:26:41,120 Speaker 3: you're interested in looking at some spreadsheets? 503 00:26:41,400 --> 00:26:44,240 Speaker 1: Yeah, yeah, cool, great, Thank you so much your time 504 00:26:44,280 --> 00:26:45,639 Speaker 1: and for all the work on this. I know this 505 00:26:45,760 --> 00:26:47,560 Speaker 1: was a lot of work getting those records and I 506 00:26:47,560 --> 00:26:50,280 Speaker 1: think it. I know it gives us something to point 507 00:26:50,320 --> 00:26:53,200 Speaker 1: to to show how many people this this border shit 508 00:26:53,320 --> 00:26:54,600 Speaker 1: is killing totally. 509 00:26:57,960 --> 00:27:00,560 Speaker 4: It Could Happen Here is a production of Coolson Media. 510 00:27:00,600 --> 00:27:03,680 Speaker 4: For more podcasts from cool Zone Media, visit our website 511 00:27:03,720 --> 00:27:07,320 Speaker 4: Coolzonmedia dot com, or check us out on the iHeartRadio app, 512 00:27:07,400 --> 00:27:10,960 Speaker 4: Apple Podcasts, or wherever you listen to podcasts. You can 513 00:27:11,000 --> 00:27:13,320 Speaker 4: now find sources for it Could Happen Here, listed directly 514 00:27:13,359 --> 00:27:15,640 Speaker 4: in episode descriptions. Thanks for listening.