1 00:00:00,360 --> 00:00:06,640 Speaker 1: Content warning. This podcast discusses violence, murder, suicide, civil unrest, 2 00:00:06,680 --> 00:00:11,520 Speaker 1: aggressive policing, racism, and lynching. If you or anyone you 3 00:00:11,600 --> 00:00:15,319 Speaker 1: know is considering suicide or self harm, or just need 4 00:00:15,400 --> 00:00:20,200 Speaker 1: to talk about problems, please call the National Suicide Prevention 5 00:00:20,280 --> 00:00:25,520 Speaker 1: Lifeline at two seven three eight two five five, or 6 00:00:25,600 --> 00:00:29,200 Speaker 1: text the Crisis text line at seven four one seven 7 00:00:29,200 --> 00:00:35,360 Speaker 1: four one. Previously and after the uprising, I call now 8 00:00:35,440 --> 00:00:39,880 Speaker 1: one one and all I remember screaming, is my baby? 9 00:00:40,280 --> 00:00:42,320 Speaker 1: All signs right on the bad point that this was 10 00:00:42,360 --> 00:00:47,120 Speaker 1: a suicide. They feel like we don't appreciate law enforcement here. Therefore, 11 00:00:47,120 --> 00:00:49,879 Speaker 1: it has in the first effect of certain cops not 12 00:00:49,960 --> 00:00:51,600 Speaker 1: being as ill as you when it comes to straight 13 00:00:51,680 --> 00:00:54,760 Speaker 1: up and down police work. I just know that the 14 00:00:54,880 --> 00:00:58,000 Speaker 1: one detective Debt, the one with the black eye, did 15 00:00:58,040 --> 00:01:01,480 Speaker 1: not give us his business card, gave us a card 16 00:01:01,640 --> 00:01:05,720 Speaker 1: for h the airport police. But at the same time 17 00:01:05,800 --> 00:01:10,280 Speaker 1: investigation of speaking with the police anyone else who's also 18 00:01:10,400 --> 00:01:12,480 Speaker 1: been to the scene. I guess it's just it can 19 00:01:12,560 --> 00:01:15,679 Speaker 1: kind of become sort of a self reinforcing circle. And 20 00:01:15,760 --> 00:01:18,000 Speaker 1: I will say this, do you know how many suicides 21 00:01:18,040 --> 00:01:19,840 Speaker 1: do we have a year? I'm sure it's a lot, 22 00:01:20,120 --> 00:01:22,640 Speaker 1: and when we have them, there is a certain amount 23 00:01:22,680 --> 00:01:26,679 Speaker 1: of investigation, but it is not much more than this. 24 00:01:39,319 --> 00:01:43,360 Speaker 1: What you're looking at is the aftermath of the grand 25 00:01:43,440 --> 00:01:56,120 Speaker 1: jury deciding not to indict Officer Wilson. A young man 26 00:01:56,240 --> 00:01:59,120 Speaker 1: found hanging from a tree in October. His mom believes 27 00:01:59,160 --> 00:02:05,280 Speaker 1: someone murdered son targeting him. Don Ye became an activist 28 00:02:05,320 --> 00:02:07,560 Speaker 1: in the wake of the shooting death of Michael Brown 29 00:02:07,720 --> 00:02:11,720 Speaker 1: by a white police officer. But that's why Melissa mckinnis 30 00:02:11,720 --> 00:02:14,760 Speaker 1: wants St. Louis County police to dig deeper to her 31 00:02:14,760 --> 00:02:22,120 Speaker 1: son's death. He was not suicidal. This is after the uprising, 32 00:02:22,480 --> 00:02:32,440 Speaker 1: the death of Donye Dion Jones. People are asking, like, 33 00:02:32,680 --> 00:02:38,400 Speaker 1: if you were promotionally, we wouldn't hear it because we 34 00:02:38,560 --> 00:02:40,840 Speaker 1: live on track, Like it's who as you jumped the 35 00:02:40,880 --> 00:02:45,120 Speaker 1: bank mark, you're you're standing on train track. During our 36 00:02:45,160 --> 00:02:48,560 Speaker 1: first long phone call with Melissa, we asked how a 37 00:02:48,680 --> 00:02:51,920 Speaker 1: struggle could have happened in her backyard without anyone in 38 00:02:51,960 --> 00:02:55,040 Speaker 1: the house having heard it. Her answer was that there 39 00:02:55,040 --> 00:02:58,000 Speaker 1: are freight train tracks right behind their home, and when 40 00:02:58,000 --> 00:03:00,639 Speaker 1: a train passed, it would be so loud that it 41 00:03:00,639 --> 00:03:04,280 Speaker 1: would shake the house. When we visited for the first time. 42 00:03:04,600 --> 00:03:07,320 Speaker 1: Her husband, Derek, said the same thing as he walked 43 00:03:07,400 --> 00:03:16,440 Speaker 1: us into the backyard, where it took a minute and 44 00:03:16,520 --> 00:03:18,639 Speaker 1: a bit of work to track down which line ran 45 00:03:18,720 --> 00:03:21,840 Speaker 1: past their home, but we eventually found that it is 46 00:03:21,880 --> 00:03:29,919 Speaker 1: the Hannibal subline operated by b NSF. Hello, Mr Williams. Yes, 47 00:03:31,120 --> 00:03:33,760 Speaker 1: this is Andy Williams. He works as a media rep 48 00:03:33,840 --> 00:03:37,480 Speaker 1: for b NSF. And let's just say he was certainly 49 00:03:37,520 --> 00:03:40,960 Speaker 1: curious as to why I was so curious. I talked 50 00:03:40,960 --> 00:03:42,400 Speaker 1: to you a couple of months ago and sent you 51 00:03:42,440 --> 00:03:46,840 Speaker 1: some emails about trying to find whether or not you kids. Yeah, yeah, yeah, yeah, yeah, 52 00:03:46,880 --> 00:03:49,000 Speaker 1: But I do have a question. What differences when a 53 00:03:49,040 --> 00:03:53,040 Speaker 1: train went by. Basically, this person died in the backyard, correct, 54 00:03:53,400 --> 00:03:59,440 Speaker 1: and the train tracks are he died by heus? Sure, No, 55 00:03:59,480 --> 00:04:01,200 Speaker 1: I don't. I don't mind telling you at all. He 56 00:04:01,480 --> 00:04:05,200 Speaker 1: died by hanging, and the family is suspicious that he 57 00:04:05,280 --> 00:04:08,560 Speaker 1: was murdered. And since these trains run behind the house, 58 00:04:09,240 --> 00:04:12,440 Speaker 1: it makes a lot of noise. So if there was 59 00:04:12,520 --> 00:04:16,240 Speaker 1: a period where there was a struggle, a train going 60 00:04:16,279 --> 00:04:21,560 Speaker 1: by could have covered up the sound of the hung him. Well, 61 00:04:21,600 --> 00:04:23,440 Speaker 1: the train was going by, and they didn't hear it. 62 00:04:23,640 --> 00:04:27,440 Speaker 1: Here's the struggle that that is a possibility. Correct. Have 63 00:04:27,560 --> 00:04:29,960 Speaker 1: you been back there when a train goes by. I 64 00:04:30,000 --> 00:04:31,680 Speaker 1: have been to the house, but not when a train 65 00:04:31,760 --> 00:04:34,279 Speaker 1: goes by. They said they allot them go by in 66 00:04:34,279 --> 00:04:37,360 Speaker 1: the night, and they said that it it basically shakes 67 00:04:37,400 --> 00:04:40,400 Speaker 1: the house, and that it's very, very loud within the house. 68 00:04:41,480 --> 00:04:44,400 Speaker 1: And what did the police saying? The police have ruled 69 00:04:44,520 --> 00:04:47,960 Speaker 1: a suicide. And you know, we're digging into all the 70 00:04:48,040 --> 00:04:50,960 Speaker 1: details there. Now there's some back and forth stuff like 71 00:04:51,000 --> 00:04:54,400 Speaker 1: there's d n A that's on the bedsheet of a 72 00:04:54,600 --> 00:04:57,880 Speaker 1: second individual that never got tested. There's a lot of 73 00:04:58,279 --> 00:05:01,320 Speaker 1: you know, little caveats to the pace, which makes it interesting. 74 00:05:01,680 --> 00:05:05,280 Speaker 1: And so they're they're basically saying, not only could this 75 00:05:05,400 --> 00:05:07,919 Speaker 1: train have covered it up the sound, but these people 76 00:05:08,320 --> 00:05:11,240 Speaker 1: who are involved may have known sort of a rough 77 00:05:11,320 --> 00:05:15,159 Speaker 1: time frame when these trains went by. Well, the trains 78 00:05:15,160 --> 00:05:18,240 Speaker 1: don't operate on a set schedule, so there's no way 79 00:05:18,279 --> 00:05:22,120 Speaker 1: to predict when a train is gonna come through. Okay, 80 00:05:22,600 --> 00:05:26,000 Speaker 1: and so what's your I mean, why are you investigating it? 81 00:05:26,440 --> 00:05:29,359 Speaker 1: The mask is nobody has time to be looking into this, 82 00:05:29,400 --> 00:05:31,320 Speaker 1: so I've got to have some good reason other than 83 00:05:31,720 --> 00:05:35,719 Speaker 1: some guys interested in You know, I'm trying to figure 84 00:05:35,720 --> 00:05:38,560 Speaker 1: out what why you're so persistent in what it is that. 85 00:05:38,640 --> 00:05:42,600 Speaker 1: I mean, you're ultimate, we know why you're doing it. 86 00:05:42,880 --> 00:05:44,520 Speaker 1: I mean I can't give you a better answer than 87 00:05:44,920 --> 00:05:48,440 Speaker 1: there is a family that is hurting because their son 88 00:05:48,560 --> 00:05:53,000 Speaker 1: is dead and I want my brother committed suicide. Trying 89 00:05:53,000 --> 00:05:55,719 Speaker 1: to get the pain issue. I understand all that we've 90 00:05:55,720 --> 00:05:58,040 Speaker 1: got thirty two thousand miles of track in twenty gates 91 00:05:58,120 --> 00:06:00,480 Speaker 1: dates and three Canadian provinces, and trying to fight somebody 92 00:06:00,480 --> 00:06:02,000 Speaker 1: to go through some sort of records and see if 93 00:06:02,000 --> 00:06:05,360 Speaker 1: there was a train that came through to specific time. Uh, 94 00:06:05,520 --> 00:06:08,880 Speaker 1: you know, it's is a task. You know. I'll keep 95 00:06:08,920 --> 00:06:11,279 Speaker 1: trying to get the information for you, so I'm not 96 00:06:11,360 --> 00:06:13,839 Speaker 1: in like a huge rush. And this doesn't have to 97 00:06:13,880 --> 00:06:16,320 Speaker 1: be like on the top of the Inboxmail me in 98 00:06:16,360 --> 00:06:18,800 Speaker 1: a couple of weeks. Then we'll see where we're at. 99 00:06:18,839 --> 00:06:28,800 Speaker 1: Dead Right now, We're just it's can't do you guys 100 00:06:29,200 --> 00:06:33,680 Speaker 1: try to establish time of death? You know, unlike television, 101 00:06:33,800 --> 00:06:36,680 Speaker 1: we do not do that because it's not very scientific. 102 00:06:37,320 --> 00:06:40,920 Speaker 1: The chief Medical Examiner for St. Louis County, Dr Mary Case, 103 00:06:41,360 --> 00:06:43,400 Speaker 1: had told us that they don't try to find a 104 00:06:43,480 --> 00:06:46,760 Speaker 1: time of death. She said that it wasn't scientific enough, 105 00:06:46,839 --> 00:06:49,360 Speaker 1: and that when a body is outside on a cold night, 106 00:06:49,880 --> 00:06:54,640 Speaker 1: all bets are off. Now we we try to look 107 00:06:54,640 --> 00:06:59,440 Speaker 1: at a parameter that that might be helpful. The body 108 00:06:59,480 --> 00:07:02,880 Speaker 1: temperature of tells is that he's been out there a 109 00:07:02,960 --> 00:07:06,120 Speaker 1: long time, a number of hours. If he was Lansing 110 00:07:06,160 --> 00:07:09,000 Speaker 1: at nine o'clock and he's found whatever time in the morning, 111 00:07:09,560 --> 00:07:12,400 Speaker 1: you know, the temperature will drop a degree, a degree 112 00:07:12,440 --> 00:07:16,040 Speaker 1: and a half. If you're in in temperate conditions like 113 00:07:16,160 --> 00:07:19,480 Speaker 1: in the house after you die, it don't drop that 114 00:07:19,920 --> 00:07:23,440 Speaker 1: when you're outside then twenty three degrees. All vents are off. 115 00:07:24,280 --> 00:07:26,160 Speaker 1: Most of his clothing, you know, he didn't. He was 116 00:07:26,240 --> 00:07:29,640 Speaker 1: not like clothes. So all we can say is he's 117 00:07:29,680 --> 00:07:32,200 Speaker 1: been dead a number of hours. It's not a recent death. 118 00:07:33,200 --> 00:07:35,920 Speaker 1: We figured someone had to know how to determine at 119 00:07:35,960 --> 00:07:39,640 Speaker 1: least an approximate time of death using the ambient temperature 120 00:07:39,680 --> 00:07:43,640 Speaker 1: as a variable, so we started researching. We found that 121 00:07:43,720 --> 00:07:47,760 Speaker 1: starting in the mid nineteenth century, investigators began using ambient 122 00:07:47,800 --> 00:07:50,600 Speaker 1: temperature at the time of discovery as well as the 123 00:07:50,640 --> 00:07:53,720 Speaker 1: temperature of a body to estimate a deceased person's time 124 00:07:53,760 --> 00:07:57,280 Speaker 1: of death. Eventually, two methods were devised that one could 125 00:07:57,280 --> 00:08:00,480 Speaker 1: plug variables into the first one is called the Glaser 126 00:08:00,600 --> 00:08:04,560 Speaker 1: equation and the other is henzis aenomogram. While these methods 127 00:08:04,600 --> 00:08:07,840 Speaker 1: can be helpful in generating estimates, they can fail and 128 00:08:07,960 --> 00:08:13,160 Speaker 1: especially cold or hot conditions. My name is Cardie Burton 129 00:08:13,320 --> 00:08:17,480 Speaker 1: and I'm a medical legal test investigator. Carly works in Newark, 130 00:08:17,560 --> 00:08:20,239 Speaker 1: New Jersey, and is sent out to investigate the scenes 131 00:08:20,280 --> 00:08:23,080 Speaker 1: of people's deaths. We reached out to her because in 132 00:08:24,320 --> 00:08:28,200 Speaker 1: she published a research paper titled Improving Methods to Estimate 133 00:08:28,240 --> 00:08:32,080 Speaker 1: time of Death from body temperature. Come of death is 134 00:08:32,400 --> 00:08:36,760 Speaker 1: something that's crucial, especially in homicide cases, and it's an 135 00:08:36,760 --> 00:08:42,000 Speaker 1: important factor when I'm when solving any unnatural deaths. Um 136 00:08:42,160 --> 00:08:46,199 Speaker 1: body temperature, ambient centaures play a huge part. Nothing has 137 00:08:46,200 --> 00:08:51,280 Speaker 1: been reliably used consistently because there's so many outside factors, 138 00:08:51,320 --> 00:08:54,880 Speaker 1: including body weight, closing objects, that's the de seed that 139 00:08:54,960 --> 00:08:59,520 Speaker 1: may be touching. There's so many different methods and everyone 140 00:08:59,559 --> 00:09:03,080 Speaker 1: says that there's no single method that can reliably to us. 141 00:09:03,200 --> 00:09:05,160 Speaker 1: So I want to see if I could come up 142 00:09:05,160 --> 00:09:08,840 Speaker 1: with something that could become the best new method. Carly 143 00:09:08,960 --> 00:09:11,960 Speaker 1: went on to explain just how she created an improved 144 00:09:12,000 --> 00:09:15,920 Speaker 1: equation for figuring out time of death. So what I 145 00:09:15,960 --> 00:09:18,120 Speaker 1: did was I collect the data by a penny c. 146 00:09:19,200 --> 00:09:23,600 Speaker 1: So on the scene I would set over nine seven 147 00:09:23,880 --> 00:09:25,880 Speaker 1: going to equal wide, and that was going to get 148 00:09:25,880 --> 00:09:29,440 Speaker 1: me the temperature of the conject proportional to the difference 149 00:09:29,480 --> 00:09:34,160 Speaker 1: between the initial temperature and anti adcempture. There's a in 150 00:09:34,240 --> 00:09:37,559 Speaker 1: there where she seen volume in the third power and 151 00:09:37,640 --> 00:09:41,120 Speaker 1: third area affect equal in the second power. I used 152 00:09:41,520 --> 00:09:47,480 Speaker 1: the power of third. I want to use, as she did, 153 00:09:47,559 --> 00:09:51,920 Speaker 1: math a lot of math. The gist of her work 154 00:09:51,960 --> 00:09:54,959 Speaker 1: is this, using a large data set of body and 155 00:09:55,000 --> 00:09:58,000 Speaker 1: ambient temperatures in which the time of death was known. 156 00:09:58,679 --> 00:10:01,640 Speaker 1: She first modified the glade to equation to include ambient 157 00:10:01,640 --> 00:10:05,920 Speaker 1: temperature more effectively, and then used an artificial intelligence system 158 00:10:05,960 --> 00:10:10,959 Speaker 1: called Eureka to generate a new superior equation. Since she 159 00:10:11,000 --> 00:10:13,480 Speaker 1: could run the equation and compare the answers given to 160 00:10:13,520 --> 00:10:16,080 Speaker 1: the known times of death, she was able to check 161 00:10:16,080 --> 00:10:22,400 Speaker 1: her rate of error. Eureka sam closest to the actual 162 00:10:22,440 --> 00:10:24,280 Speaker 1: time of desk. It didn't matter even if the body 163 00:10:24,320 --> 00:10:28,440 Speaker 1: temperature was ken degrees. Sara night, the error was very low. 164 00:10:28,880 --> 00:10:31,720 Speaker 1: We asked Carly if after publishing her paper she knew 165 00:10:31,720 --> 00:10:34,480 Speaker 1: of any other investigators who were using her adjusted glaser 166 00:10:34,559 --> 00:10:37,960 Speaker 1: equation and their work, and she said yes. My name 167 00:10:38,080 --> 00:10:43,240 Speaker 1: is Christian Torres. I am currently the chief investigator for 168 00:10:43,360 --> 00:10:48,200 Speaker 1: Bergen County, New Jersey. I pretty much investigate vests for 169 00:10:48,320 --> 00:10:51,760 Speaker 1: the Medical Examiner's Office over the years, you know, I 170 00:10:51,880 --> 00:10:57,720 Speaker 1: have investigated about sevent cases. So I'm of forensic scientists. 171 00:10:57,800 --> 00:11:02,120 Speaker 1: I'm always looking for the scientific aspect of the investigations. 172 00:11:02,480 --> 00:11:05,280 Speaker 1: I always try to estimate a time of death to 173 00:11:05,480 --> 00:11:09,600 Speaker 1: help the doctors. But body temperatures are pretty funny, you know, 174 00:11:09,760 --> 00:11:14,559 Speaker 1: Like there it's really hard to get like an exact 175 00:11:14,640 --> 00:11:19,160 Speaker 1: time of death with body temperatures. But after the equation 176 00:11:19,280 --> 00:11:23,280 Speaker 1: it we were pretty much able to get a closer time, 177 00:11:24,120 --> 00:11:28,120 Speaker 1: you know, and they were pretty close. Aside from just 178 00:11:28,240 --> 00:11:31,600 Speaker 1: body temperature, another factor to look at an assessing time 179 00:11:31,640 --> 00:11:34,600 Speaker 1: of death is rigor mortis, which is a contracting of 180 00:11:34,640 --> 00:11:37,000 Speaker 1: the muscles and the body for a period of time 181 00:11:37,040 --> 00:11:40,160 Speaker 1: after death, starting in the head and face and moving 182 00:11:40,160 --> 00:11:43,200 Speaker 1: steadily downward towards the feet and then back up again 183 00:11:43,360 --> 00:11:47,480 Speaker 1: as the condition subsides. So rigor mortis um normally appears 184 00:11:47,520 --> 00:11:51,880 Speaker 1: after two hours, and the fully rigid state happens in 185 00:11:51,960 --> 00:11:54,640 Speaker 1: between eight to twelve hours. If you did both like 186 00:11:54,679 --> 00:11:57,000 Speaker 1: the temperature equation and kind of compared that to the 187 00:11:57,040 --> 00:11:59,560 Speaker 1: rigor mortist, you could be pretty confident you knew a 188 00:11:59,640 --> 00:12:03,880 Speaker 1: rough time of death. Yeah, um, I personally would. I 189 00:12:03,880 --> 00:12:06,320 Speaker 1: don't know how other investigators doctors steel, but I could 190 00:12:06,320 --> 00:12:09,160 Speaker 1: say out of mind, I would be. So if I 191 00:12:09,160 --> 00:12:12,080 Speaker 1: could throw you a few data points, is it possible 192 00:12:12,120 --> 00:12:15,920 Speaker 1: for you to try to, like come up with how 193 00:12:15,920 --> 00:12:18,520 Speaker 1: many hours this person was dead? For me, I used 194 00:12:18,520 --> 00:12:23,640 Speaker 1: your I used your adjusted equation, but I'm also stupid. Um, 195 00:12:23,720 --> 00:12:25,520 Speaker 1: So I was wondering if I could throw you a 196 00:12:25,559 --> 00:12:27,560 Speaker 1: couple of numbers and maybe you could punch him in 197 00:12:27,720 --> 00:12:32,600 Speaker 1: and see what you think. Carly was interested in Dania's case, 198 00:12:32,960 --> 00:12:34,920 Speaker 1: and in the end we sent her the full medical 199 00:12:34,960 --> 00:12:37,880 Speaker 1: examiners report to look over. We're going to talk again 200 00:12:37,880 --> 00:12:40,240 Speaker 1: in a week after she crunched the numbers and assess 201 00:12:40,280 --> 00:12:42,680 Speaker 1: the relevant facts of the case to give us her opinion. 202 00:12:43,360 --> 00:12:47,079 Speaker 1: An Episode three, the pathologist and the chief medical examiner, 203 00:12:47,160 --> 00:12:50,360 Speaker 1: who together came to the conclusion that Danie died by suicide. 204 00:12:50,679 --> 00:12:52,960 Speaker 1: Both told us that the work St. Louis County detectives 205 00:12:53,000 --> 00:12:55,920 Speaker 1: did investigating the scene was very important for their findings. 206 00:12:56,559 --> 00:12:58,640 Speaker 1: But Melissa and her family members who had been present, 207 00:12:58,720 --> 00:13:02,599 Speaker 1: told us that the lead detective of Timothy Anderer was disrespectful. 208 00:13:03,280 --> 00:13:06,600 Speaker 1: They asserted he was seen laughing by multiple people. They 209 00:13:06,600 --> 00:13:08,600 Speaker 1: showed us the business card that they all say he 210 00:13:08,640 --> 00:13:12,680 Speaker 1: gave them another person's card, they believed on purpose, and 211 00:13:12,720 --> 00:13:15,720 Speaker 1: despite allegedly telling them that morning that he believed Danye 212 00:13:15,880 --> 00:13:20,040 Speaker 1: died by suicide, in May of a full seven months 213 00:13:20,080 --> 00:13:23,120 Speaker 1: after Danye's death, he still hadn't closed the case and 214 00:13:23,160 --> 00:13:26,720 Speaker 1: made available his final report, which would detail his investigation, 215 00:13:27,120 --> 00:13:30,000 Speaker 1: showing specifically what work he did, who he spoke with, 216 00:13:30,559 --> 00:13:32,840 Speaker 1: and outlining the results of the DNA testing on the 217 00:13:32,920 --> 00:13:35,440 Speaker 1: sheet done by the crime lab. All of this made 218 00:13:35,480 --> 00:13:39,400 Speaker 1: melissen or family skeptical that Detective Anderer ever did much 219 00:13:39,400 --> 00:13:42,840 Speaker 1: investigating into Danie's death, and frankly, they thought he just 220 00:13:42,880 --> 00:13:49,319 Speaker 1: didn't care. Police bias, whether politically motivated or racially motivated, 221 00:13:49,520 --> 00:13:52,880 Speaker 1: is obviously a huge topic in America right now. What 222 00:13:53,040 --> 00:13:56,080 Speaker 1: you may not know is that in a group of 223 00:13:56,120 --> 00:13:59,280 Speaker 1: interested attorneys started what they called the Plane View Project, 224 00:14:00,000 --> 00:14:01,559 Speaker 1: there was an effort to look at eight u S 225 00:14:01,640 --> 00:14:05,319 Speaker 1: jurisdictions and to document the public Internet postings of police 226 00:14:05,360 --> 00:14:08,760 Speaker 1: officers that would tend to make the public feel, let's say, 227 00:14:08,880 --> 00:14:12,040 Speaker 1: less than confident that those particular officers would do their 228 00:14:12,160 --> 00:14:15,800 Speaker 1: job with much integrity. We spoke with project lead Emily 229 00:14:15,840 --> 00:14:19,800 Speaker 1: Baker White about what she found. I went to Harvard 230 00:14:19,840 --> 00:14:23,320 Speaker 1: for law school, and after graduation, I got a year 231 00:14:23,320 --> 00:14:25,560 Speaker 1: long fellowship to work at the Capital HADIAS units at 232 00:14:25,560 --> 00:14:28,800 Speaker 1: the Federal Defender in Philadelphia, and so I was assigned 233 00:14:29,000 --> 00:14:32,120 Speaker 1: to a slate of capital cases death penalty cases where 234 00:14:32,120 --> 00:14:34,480 Speaker 1: our client had received a death sentence and we were 235 00:14:34,560 --> 00:14:37,400 Speaker 1: challenging the validity of the conviction for one reason or 236 00:14:37,440 --> 00:14:40,400 Speaker 1: another in needs of these cases. In one of the cases, 237 00:14:40,880 --> 00:14:43,480 Speaker 1: I found that several of the police officers who may 238 00:14:43,480 --> 00:14:46,640 Speaker 1: have had contact with our client had public Facebook pages 239 00:14:46,840 --> 00:14:50,880 Speaker 1: and we're posting troubling material that could impact the case. 240 00:14:51,320 --> 00:14:53,440 Speaker 1: One of them, the one that sort of really stuck 241 00:14:53,480 --> 00:14:57,680 Speaker 1: out to me, was a picture of a police dog 242 00:14:58,600 --> 00:15:01,840 Speaker 1: who was bearing his teeth um easier to run after something. 243 00:15:02,120 --> 00:15:04,280 Speaker 1: He was being restrained by an officer and swass here 244 00:15:04,840 --> 00:15:07,160 Speaker 1: and there was a caption over that image that said, 245 00:15:07,160 --> 00:15:11,600 Speaker 1: I hope you run. He likes fast food, And that 246 00:15:11,680 --> 00:15:15,760 Speaker 1: image was troubling to me also because it was a meme. 247 00:15:16,200 --> 00:15:18,280 Speaker 1: It made me wonder where the officer had gotten it 248 00:15:18,400 --> 00:15:21,000 Speaker 1: and whether there might be more content like that out there. 249 00:15:21,200 --> 00:15:24,640 Speaker 1: And after that, I began the plane View Project, which 250 00:15:24,840 --> 00:15:28,080 Speaker 1: aimed to answer the question that that I had sort 251 00:15:28,080 --> 00:15:31,280 Speaker 1: of asked after my work at the Federal Defender, how 252 00:15:31,360 --> 00:15:33,320 Speaker 1: much more of this is they're out there? And how 253 00:15:33,360 --> 00:15:36,360 Speaker 1: many officers are engaged in this kind of conduct online. 254 00:15:38,480 --> 00:15:40,760 Speaker 1: Though a lot of reporting on the plane View Project 255 00:15:40,840 --> 00:15:45,240 Speaker 1: focused on racist content posted by police officers online, Emily 256 00:15:45,280 --> 00:15:47,800 Speaker 1: wanted to make it clear that the criteria for inclusion 257 00:15:47,840 --> 00:15:52,200 Speaker 1: in her work went well beyond racism. Up front, as 258 00:15:52,240 --> 00:15:55,520 Speaker 1: a sort of reminder, the standards we used to decide 259 00:15:55,560 --> 00:15:57,760 Speaker 1: whether opposed should be included in the database is the 260 00:15:57,800 --> 00:16:02,240 Speaker 1: same across jurisdiction. Yes, is one question, is it possible 261 00:16:02,280 --> 00:16:07,840 Speaker 1: that this post, this meme, comment, etcetera. Could affect civilian 262 00:16:07,960 --> 00:16:11,600 Speaker 1: trust in potic thing. One of the jurisdictions the Plane 263 00:16:11,680 --> 00:16:14,800 Speaker 1: View Project decided to look at was the city of St. Louis. 264 00:16:15,320 --> 00:16:18,120 Speaker 1: This is not St. Louis County which is where Melissa 265 00:16:18,120 --> 00:16:21,480 Speaker 1: and Donye were living and where Detective Andrew works. But 266 00:16:21,600 --> 00:16:24,000 Speaker 1: it should be understood that both the St. Louis City 267 00:16:24,040 --> 00:16:27,480 Speaker 1: Police Department and the St. Louis County Police Department basically 268 00:16:27,520 --> 00:16:30,400 Speaker 1: pull officers from the same pool of people. Just like 269 00:16:30,440 --> 00:16:33,680 Speaker 1: how Officer Darren Wilson, the white police officer who shot 270 00:16:33,720 --> 00:16:37,280 Speaker 1: Mike Brown Jr. Did not live in Ferguson, many officers 271 00:16:37,280 --> 00:16:39,360 Speaker 1: who work for St. Louis City p D Do not 272 00:16:39,520 --> 00:16:42,400 Speaker 1: live within the St. Louis City itself, So there is 273 00:16:42,440 --> 00:16:44,640 Speaker 1: no reason to believe that the findings of the Plane 274 00:16:44,680 --> 00:16:47,480 Speaker 1: View project are any more confined to the borders of St. 275 00:16:47,560 --> 00:16:51,840 Speaker 1: Louis City than the officers themselves. How did St. Louis 276 00:16:51,880 --> 00:16:55,640 Speaker 1: seem to compare to the other seven jurisdictions of the 277 00:16:55,720 --> 00:16:58,440 Speaker 1: officers that we found and verified? In St. Louis, a 278 00:16:58,560 --> 00:17:02,280 Speaker 1: slightly lower incident of officers were included in the database 279 00:17:02,320 --> 00:17:07,520 Speaker 1: than in other large cities. However, I don't want to 280 00:17:07,560 --> 00:17:12,040 Speaker 1: say that because Saint Willis officers posted less of this content. Overall, 281 00:17:13,359 --> 00:17:17,320 Speaker 1: this is not the scientific fact, but in my anecdotal experience, 282 00:17:17,359 --> 00:17:21,159 Speaker 1: I tended to find more St. Louis officers posting only 283 00:17:21,200 --> 00:17:27,000 Speaker 1: behind privacy settings only to their friends than in other jurisdictions. 284 00:17:27,040 --> 00:17:29,560 Speaker 1: And I don't know why that is, but it may 285 00:17:29,600 --> 00:17:33,359 Speaker 1: be because they received more training or were used to 286 00:17:33,480 --> 00:17:36,639 Speaker 1: more oversight. Given how St. Louis has been in the 287 00:17:36,680 --> 00:17:41,160 Speaker 1: national spotlight for so long about these issues, we asked 288 00:17:41,160 --> 00:17:44,440 Speaker 1: Emily if there were any themes that jumped out for St. Louis. 289 00:17:44,480 --> 00:17:47,560 Speaker 1: So most of the content in the database, with with 290 00:17:47,640 --> 00:17:49,840 Speaker 1: my caveat from before that not all of it does, 291 00:17:50,480 --> 00:17:54,240 Speaker 1: falls into into one of three sort of buckets of content. 292 00:17:54,920 --> 00:17:58,760 Speaker 1: And the first bucket is his statements, means, etcetera that 293 00:17:58,880 --> 00:18:03,840 Speaker 1: appear to endorsed or glorify violence. One type of violence 294 00:18:03,880 --> 00:18:09,080 Speaker 1: that we see encouraged or were supported is putty successive force. 295 00:18:09,520 --> 00:18:12,399 Speaker 1: The second big bucket of material is material that appears 296 00:18:12,480 --> 00:18:15,679 Speaker 1: to discriminating against a certain group of people, see that 297 00:18:16,200 --> 00:18:20,080 Speaker 1: people of color or people of minority face. We saw 298 00:18:20,080 --> 00:18:23,160 Speaker 1: a lot of very abominable material in the database, and 299 00:18:23,240 --> 00:18:26,560 Speaker 1: we saw that across jurisdictions. The third trend, which often 300 00:18:26,600 --> 00:18:29,320 Speaker 1: overlaps as a second trend but not always, was the 301 00:18:29,440 --> 00:18:31,960 Speaker 1: use of what I would refer to as do humanizing 302 00:18:32,040 --> 00:18:36,480 Speaker 1: language about other people, whether those people are protesters, people 303 00:18:36,520 --> 00:18:39,679 Speaker 1: of color, people affiliated with Black Lives Matter, etcetera. And 304 00:18:39,720 --> 00:18:44,560 Speaker 1: we saw a lot of officers referring to groups of 305 00:18:44,560 --> 00:18:48,919 Speaker 1: people as animals, savages, sub human, etcetera. UM, and we 306 00:18:49,000 --> 00:18:53,240 Speaker 1: flagged back too. Anecdotally, I remember a few officers in 307 00:18:53,240 --> 00:18:56,760 Speaker 1: smilists whose profiles I personally looked at and and really 308 00:18:56,800 --> 00:19:01,520 Speaker 1: saw a sort of concentrated effort to to do positive 309 00:19:01,560 --> 00:19:04,840 Speaker 1: community relations work and positive community relationship within the black 310 00:19:04,840 --> 00:19:08,480 Speaker 1: community specifically. I think after the beginning of Black Lives 311 00:19:08,480 --> 00:19:12,320 Speaker 1: Matter and fergus inter Reality real relationships between the police 312 00:19:12,320 --> 00:19:14,880 Speaker 1: and the community, and I definitely think that that work 313 00:19:14,960 --> 00:19:17,800 Speaker 1: is happening within the police department. I just also think, unfortunately, 314 00:19:18,200 --> 00:19:21,240 Speaker 1: there are comment being being made by other officers that 315 00:19:21,240 --> 00:19:24,479 Speaker 1: are getting in a way of that. We told Emily 316 00:19:24,480 --> 00:19:26,360 Speaker 1: that we were working on a story about the son 317 00:19:26,440 --> 00:19:29,280 Speaker 1: of a prominent Ferguson activist who had died and whose 318 00:19:29,280 --> 00:19:32,320 Speaker 1: family didn't believe the police did a very thorough investigation 319 00:19:32,359 --> 00:19:34,800 Speaker 1: of his death. She told us about some of the 320 00:19:34,840 --> 00:19:37,560 Speaker 1: content her projected log that might be relevant to our work. 321 00:19:39,320 --> 00:19:45,000 Speaker 1: There are a number of popular police means that suggests 322 00:19:45,119 --> 00:19:48,800 Speaker 1: that police will not or do not want to respond 323 00:19:48,920 --> 00:19:51,760 Speaker 1: to the emergencies of people who have been critical of 324 00:19:51,840 --> 00:19:55,280 Speaker 1: the police. There are means that show a person responding 325 00:19:55,280 --> 00:19:58,320 Speaker 1: to a nine one one call who says, oh, I 326 00:19:58,400 --> 00:20:01,159 Speaker 1: see three weeks ago you said suck the police, so 327 00:20:01,320 --> 00:20:04,560 Speaker 1: we'll be unable to respond to your emergency today. There's 328 00:20:04,560 --> 00:20:08,160 Speaker 1: another meme that shows a cup laughing having a good 329 00:20:08,200 --> 00:20:12,560 Speaker 1: time with a buddy, and the caption over that is, yeah, 330 00:20:12,720 --> 00:20:15,280 Speaker 1: you said the police, so I'm going to finish my 331 00:20:15,320 --> 00:20:19,920 Speaker 1: coffee before I come rescue You're dying homeboy or something 332 00:20:19,960 --> 00:20:24,240 Speaker 1: like that. And that set of images and and that 333 00:20:24,560 --> 00:20:27,800 Speaker 1: theme within some of the memes and the comments that 334 00:20:27,840 --> 00:20:31,800 Speaker 1: we saw very very much troubled me as a as 335 00:20:31,800 --> 00:20:35,880 Speaker 1: a former Avias attorney, but I imagine is very troubling 336 00:20:35,960 --> 00:20:41,119 Speaker 1: to you and this mother, because some officers seem to 337 00:20:41,160 --> 00:20:43,760 Speaker 1: suggest that they will do their work less well or 338 00:20:43,760 --> 00:20:48,280 Speaker 1: not at all if and when their work requires them 339 00:20:48,840 --> 00:20:52,480 Speaker 1: to protect people who have been critical of them, and 340 00:20:52,560 --> 00:20:55,800 Speaker 1: that's obviously unacceptable. I would look deeper if I were you, 341 00:20:55,960 --> 00:21:00,520 Speaker 1: into those into that set of memes and that thread 342 00:21:00,520 --> 00:21:02,920 Speaker 1: of conversation because of how relevant it could be to 343 00:21:02,960 --> 00:21:07,479 Speaker 1: the case you're working on. Detective Andrewer did not have 344 00:21:07,560 --> 00:21:10,920 Speaker 1: a Facebook page that we could find. However, we found 345 00:21:10,920 --> 00:21:14,679 Speaker 1: that his wife, Amy Ander, had a Pinterest page. She 346 00:21:14,800 --> 00:21:17,480 Speaker 1: was also a St. Louis County Police officer who works 347 00:21:17,480 --> 00:21:21,360 Speaker 1: as an instructor training cadets at the Police Academy. Officer 348 00:21:21,400 --> 00:21:24,280 Speaker 1: Amy Andrewer's page has many boards for posts on things 349 00:21:24,320 --> 00:21:28,200 Speaker 1: like recipes, fitness, and gift ideas. One of the boards 350 00:21:28,200 --> 00:21:31,120 Speaker 1: she created was called work stuff, and this contained a 351 00:21:31,119 --> 00:21:33,440 Speaker 1: lot of the type of material that Emily talked about 352 00:21:33,440 --> 00:21:36,399 Speaker 1: documenting for the plane View project. Some of the stuff 353 00:21:36,400 --> 00:21:39,560 Speaker 1: she posted was sort of obvious, like mug shots of say, 354 00:21:40,040 --> 00:21:43,720 Speaker 1: unique looking individuals. Other things were harmless memes that even 355 00:21:43,760 --> 00:21:46,560 Speaker 1: poked fun at police themselves, like one of a police 356 00:21:46,600 --> 00:21:51,359 Speaker 1: helicopter that was captioned holy shit pigs can fly. Ironically enough, 357 00:21:51,760 --> 00:21:55,119 Speaker 1: she even has the exact memes that Emily found troubling, 358 00:21:55,480 --> 00:21:58,160 Speaker 1: the one she described with the SWAT member holding back 359 00:21:58,200 --> 00:22:01,199 Speaker 1: the police dog with the caption about past food, and 360 00:22:01,240 --> 00:22:04,400 Speaker 1: the one with the laughing cops captioned they said fuck 361 00:22:04,480 --> 00:22:06,960 Speaker 1: the police, So I said, fuck your nine one one call. 362 00:22:07,200 --> 00:22:09,840 Speaker 1: I'll get to your dying homeboy. When I finished my coffee, 363 00:22:10,680 --> 00:22:14,760 Speaker 1: we brought Amy Ander's Pinterest page to Melissa's attention. After 364 00:22:14,840 --> 00:22:17,399 Speaker 1: looking it over and scanning through the list of her followers, 365 00:22:17,520 --> 00:22:19,600 Speaker 1: Melissa got back to us with an email and said 366 00:22:19,600 --> 00:22:22,360 Speaker 1: that she had actually found the Detective Andrewer, the lead 367 00:22:22,400 --> 00:22:25,879 Speaker 1: investigator and her son's death, also had a Pinterest page. 368 00:22:26,320 --> 00:22:30,919 Speaker 1: An examination of Detective Andrewer's posts reveals several racial jokes, 369 00:22:30,960 --> 00:22:33,560 Speaker 1: including a meme that shows a variety of Asian people 370 00:22:33,800 --> 00:22:37,400 Speaker 1: enlist their actual nationalities, but then jokes that every non 371 00:22:37,440 --> 00:22:40,959 Speaker 1: Asian person just sees them as Chinese, as well as 372 00:22:40,960 --> 00:22:44,159 Speaker 1: a screen grab from a soccer match in which Nigeria 373 00:22:44,320 --> 00:22:47,520 Speaker 1: is playing Germany and the three letter abbreviations for each 374 00:22:47,560 --> 00:22:52,159 Speaker 1: country spell out the N word. Taken in context with 375 00:22:52,240 --> 00:22:54,439 Speaker 1: the fact that Andrewer was caught on his own body 376 00:22:54,480 --> 00:22:59,840 Speaker 1: camera admitting to brutalizing black protesters and seemingly bragging about it. Again, 377 00:23:00,320 --> 00:23:03,320 Speaker 1: what is Melissa and the rest of Danye's family supposed 378 00:23:03,359 --> 00:23:09,400 Speaker 1: to think it was? It was screenshot this document, right, 379 00:23:09,880 --> 00:23:16,040 Speaker 1: m hm, So if he takes it down, it doesn't matter. Um, 380 00:23:16,160 --> 00:23:20,920 Speaker 1: that's how he really feels. So my thought, why would 381 00:23:20,960 --> 00:23:27,040 Speaker 1: he even care about how a young black man ends 382 00:23:27,160 --> 00:23:33,080 Speaker 1: up dead? Like? Why put forth any effort and finding 383 00:23:33,080 --> 00:23:36,680 Speaker 1: out what will be happen. I'm seeing that he wouldn't 384 00:23:36,680 --> 00:23:41,320 Speaker 1: give a damn because he looks at us as diggers, 385 00:23:41,680 --> 00:23:46,639 Speaker 1: you know. Um, and I'm just being black. But he 386 00:23:46,800 --> 00:23:52,440 Speaker 1: showed he showed his character when he said what he 387 00:23:52,560 --> 00:23:56,800 Speaker 1: said about the protesters when we were out there in Berkeley. 388 00:23:57,440 --> 00:24:01,280 Speaker 1: I know I'm going proe and or and I'm just saying, 389 00:24:01,320 --> 00:24:07,199 Speaker 1: what do't it? Thank you? Look, we get it. Police 390 00:24:07,280 --> 00:24:09,480 Speaker 1: or people. They like to crack jokes, and they like 391 00:24:09,560 --> 00:24:12,199 Speaker 1: to have a laugh about their work day. Who doesn't. 392 00:24:12,640 --> 00:24:15,280 Speaker 1: It's a stress reliever. But to be in the role 393 00:24:15,320 --> 00:24:18,080 Speaker 1: the police are, in their salaries, paid for by a 394 00:24:18,119 --> 00:24:22,520 Speaker 1: trusting public, granted special privileges and powers to use violence, 395 00:24:22,560 --> 00:24:25,600 Speaker 1: and tasked with respecting the rights of individuals as they 396 00:24:25,600 --> 00:24:28,800 Speaker 1: go about their job and forcing the law. It is, 397 00:24:29,000 --> 00:24:32,240 Speaker 1: if nothing else, disheartening to know that what they find 398 00:24:32,280 --> 00:24:35,280 Speaker 1: funny is the notion of violating all of that public trust, 399 00:24:35,720 --> 00:24:39,479 Speaker 1: of having a thirst for harming civilians or intentionally not 400 00:24:39,600 --> 00:24:42,840 Speaker 1: doing their jobs. Would you go to a dentist who 401 00:24:42,840 --> 00:24:45,280 Speaker 1: thought it was funny to pull healthy teeth from your head, 402 00:24:45,880 --> 00:24:48,080 Speaker 1: or to a doctor who laughed about doing as little 403 00:24:48,119 --> 00:24:53,240 Speaker 1: for you as possible. Probably not, And sure memes people 404 00:24:53,280 --> 00:24:56,240 Speaker 1: post on their social media pages aren't exactly a complete 405 00:24:56,240 --> 00:24:59,640 Speaker 1: description of their attitudes and opinions. But what we find 406 00:24:59,680 --> 00:25:03,239 Speaker 1: humor is a window into our thinking. It shows what 407 00:25:03,280 --> 00:25:07,440 Speaker 1: we think is at least kind of true. I spent 408 00:25:07,520 --> 00:25:09,720 Speaker 1: all my time tracking hate groups, right, not so much 409 00:25:09,720 --> 00:25:13,199 Speaker 1: speaking with activists. We also talked about this issue with 410 00:25:13,280 --> 00:25:16,320 Speaker 1: Heidi Barrick, who was then tracking hate groups for the 411 00:25:16,359 --> 00:25:20,480 Speaker 1: Southern Poverty Law Center. Today she is chief strategist for 412 00:25:20,520 --> 00:25:24,040 Speaker 1: the Global Project Against Hate and Extremism, which she co founded. 413 00:25:25,080 --> 00:25:27,680 Speaker 1: In the summer of she told us that she had 414 00:25:27,720 --> 00:25:31,520 Speaker 1: followed closely the story about police officers posting racist content 415 00:25:31,600 --> 00:25:36,440 Speaker 1: on their Facebook profiles. I can't tell you that every 416 00:25:36,480 --> 00:25:40,600 Speaker 1: time there's a lynching, there is usually an outcry from 417 00:25:40,600 --> 00:25:43,720 Speaker 1: people in the black community that weird things are being 418 00:25:43,760 --> 00:25:46,840 Speaker 1: done to them. And I don't believe that that many 419 00:25:46,960 --> 00:25:50,840 Speaker 1: folks feeling that way about like lack of police investigation, 420 00:25:51,440 --> 00:25:54,439 Speaker 1: lack of taking the crimes seriously. I don't think that 421 00:25:54,480 --> 00:25:58,359 Speaker 1: can all be a mistake. And the amounts of times 422 00:25:58,400 --> 00:26:00,960 Speaker 1: that we've seen law enforcement office or sort of decried 423 00:26:01,040 --> 00:26:05,280 Speaker 1: Black lives matter makes me wonder too about BIOSes there, 424 00:26:05,920 --> 00:26:08,960 Speaker 1: and you layer on top of it, you know, all 425 00:26:09,000 --> 00:26:11,679 Speaker 1: this craft that we're finding on social media, and I 426 00:26:11,680 --> 00:26:15,520 Speaker 1: don't think it's crazy to think then an activist wouldn't 427 00:26:15,520 --> 00:26:18,160 Speaker 1: get the same service from law enforcement and someone else. 428 00:26:18,600 --> 00:26:20,560 Speaker 1: I mean, the history of law enforcement in this country 429 00:26:20,680 --> 00:26:22,399 Speaker 1: is just not really good when it comes to people 430 00:26:22,400 --> 00:26:25,719 Speaker 1: of color or people who challenge the police. We also 431 00:26:25,800 --> 00:26:31,400 Speaker 1: know from the Department of Justice's investigation into Ferguson that 432 00:26:31,400 --> 00:26:34,960 Speaker 1: that police department also was filled with a bunch of racists. 433 00:26:35,680 --> 00:26:37,720 Speaker 1: And there have been some other investigations coming out of 434 00:26:37,760 --> 00:26:40,760 Speaker 1: the d J, you know, obviously prior to Trump, that 435 00:26:40,960 --> 00:26:44,760 Speaker 1: show sort of systematic racial problems. In terms of the 436 00:26:44,840 --> 00:26:49,560 Speaker 1: sentiments of police officers. Reading the Department of Justice report 437 00:26:49,600 --> 00:26:52,880 Speaker 1: on the Ferguson Police Department, we were more than disheartened, 438 00:26:53,240 --> 00:26:57,200 Speaker 1: were horrified. Yes, it's a look at one municipality, one 439 00:26:57,240 --> 00:27:01,360 Speaker 1: department and doesn't necessarily speak to all lease everywhere, agreed, 440 00:27:02,200 --> 00:27:05,520 Speaker 1: but it shows what's possible, what's been documented, what's been 441 00:27:05,560 --> 00:27:09,680 Speaker 1: proven to have occurred. The report is full of statements 442 00:27:09,720 --> 00:27:13,960 Speaker 1: like officers expected and demanded compliance even when they lacked 443 00:27:14,040 --> 00:27:19,600 Speaker 1: legal authority. One of the report's primary conclusions reads Ferguson's 444 00:27:19,640 --> 00:27:23,119 Speaker 1: law enforcement practices are shaped by the city's focus on 445 00:27:23,200 --> 00:27:27,840 Speaker 1: revenue rather than by public safety needs. This emphasis on 446 00:27:27,960 --> 00:27:32,560 Speaker 1: revenue has compromised the institutional character of Ferguson's police department, 447 00:27:32,800 --> 00:27:36,920 Speaker 1: contributing to a pattern of unconstitutional policing, and has also 448 00:27:37,040 --> 00:27:40,440 Speaker 1: shaped its municipal court, leading to procedures that raise do 449 00:27:40,640 --> 00:27:44,520 Speaker 1: process concerns and inflict unnecessary harm on members of the 450 00:27:44,520 --> 00:27:48,160 Speaker 1: Ferguson community. It then goes on to list a host 451 00:27:48,200 --> 00:27:51,439 Speaker 1: of specific examples, So if you're skeptical, I'd say just 452 00:27:51,560 --> 00:27:56,600 Speaker 1: read it. The idea of that was often late at 453 00:27:56,600 --> 00:27:59,680 Speaker 1: the feat. For example of Black Lives Matter activists, see 454 00:27:59,760 --> 00:28:04,040 Speaker 1: your exaggerating problems with the police and biases and police forces. 455 00:28:04,119 --> 00:28:06,119 Speaker 1: I think it's pretty much big pitt to West. Now, 456 00:28:06,240 --> 00:28:09,160 Speaker 1: maybe not by the cops themselves, but the evidence shows 457 00:28:09,200 --> 00:28:13,080 Speaker 1: that these things are happening all over the country. Officers 458 00:28:13,119 --> 00:28:17,080 Speaker 1: in North County police departments like Ferguson frequently don't live there. 459 00:28:17,640 --> 00:28:20,359 Speaker 1: These various departments are pulling from the same basic crop 460 00:28:20,400 --> 00:28:22,760 Speaker 1: of people. So just as we cannot say that the 461 00:28:22,840 --> 00:28:27,040 Speaker 1: specific misdeeds of Ferguson's police department are being repeated across 462 00:28:27,080 --> 00:28:29,720 Speaker 1: the greater St. Louis area. We also have to be 463 00:28:29,760 --> 00:28:33,800 Speaker 1: careful about suggesting that attitudes and behaviors in one department 464 00:28:34,040 --> 00:28:40,240 Speaker 1: are necessarily confined to it. For example, when protesters took 465 00:28:40,240 --> 00:28:42,959 Speaker 1: to the streets of St. Louis to demand former officer 466 00:28:43,080 --> 00:28:46,880 Speaker 1: Jason Stockley beheld accountable for the killing of Anthony Lamar Smith, 467 00:28:47,720 --> 00:28:50,240 Speaker 1: several police officers ended up beating the crap out of 468 00:28:50,840 --> 00:28:55,320 Speaker 1: wait for it, a black undercover cop named Luther Hall. 469 00:28:56,640 --> 00:28:59,120 Speaker 1: They took an oath to serve and protect the people 470 00:28:59,240 --> 00:29:01,840 Speaker 1: of St. Louis, but to night for city police officers 471 00:29:01,880 --> 00:29:04,840 Speaker 1: are off the job after they were indicted on federal 472 00:29:04,880 --> 00:29:09,640 Speaker 1: felony charges September seventeen, two thousand seventeen. For a third 473 00:29:09,760 --> 00:29:13,280 Speaker 1: night protests erupted in St. Louis after the acquittal of 474 00:29:13,320 --> 00:29:16,480 Speaker 1: former police officer Jason Stockley and the shooting depth of 475 00:29:16,520 --> 00:29:20,120 Speaker 1: Anthony Lamar Smith. Four city officers have been charged with 476 00:29:20,200 --> 00:29:24,280 Speaker 1: using excessive force and beating up an undercover city police 477 00:29:24,280 --> 00:29:27,480 Speaker 1: officer who's also a twenty two year veteran of the 478 00:29:27,520 --> 00:29:31,120 Speaker 1: force that was assigned that same night to cover the protests. 479 00:29:31,640 --> 00:29:35,000 Speaker 1: A federal investigation was able to find that these officers 480 00:29:35,080 --> 00:29:38,400 Speaker 1: had been sending each other text messages about how excited 481 00:29:38,440 --> 00:29:41,760 Speaker 1: they were to get to beat up protesters. According to 482 00:29:41,800 --> 00:29:45,520 Speaker 1: the indictment, text messages show that Boone, Hayes, and Myers 483 00:29:45,760 --> 00:29:50,440 Speaker 1: expressed disdain for the Stockley protesters and excitement about using 484 00:29:50,640 --> 00:29:55,640 Speaker 1: unjustified force against them. In one exchange, Boone wrote quote, 485 00:29:55,760 --> 00:29:58,800 Speaker 1: it's gonna get ignorant tonight, but it's gonna be a 486 00:29:58,840 --> 00:30:02,680 Speaker 1: lot of fun beating the expletive out of these expletives 487 00:30:02,760 --> 00:30:05,920 Speaker 1: once the sun goes down and nobody can tell us apart. 488 00:30:06,600 --> 00:30:09,720 Speaker 1: The case against the officers who beat Luther Hall ended 489 00:30:09,760 --> 00:30:14,400 Speaker 1: in early with two mistrial counts and not guilty verdicts 490 00:30:14,400 --> 00:30:18,160 Speaker 1: on the remaining counts, and just like Anderer being promoted 491 00:30:18,200 --> 00:30:22,240 Speaker 1: to detective immediately after the excessive fource incident involving State 492 00:30:22,280 --> 00:30:25,880 Speaker 1: Representative Bruce Franks Jr. One of the officers named in 493 00:30:25,920 --> 00:30:29,080 Speaker 1: the indictment for the beating of Luther Hall, was promoted 494 00:30:29,120 --> 00:30:33,720 Speaker 1: to sergeant three months after the event. The plain View 495 00:30:33,760 --> 00:30:38,320 Speaker 1: Project database contained over four hundred Facebook posts from current 496 00:30:38,520 --> 00:30:41,600 Speaker 1: and former officers in the St. Louis City Police Department. 497 00:30:42,040 --> 00:30:45,400 Speaker 1: In the end, two of those officers whose posts were 498 00:30:45,440 --> 00:30:49,840 Speaker 1: flagged by the Project. Ronald Hasty and Thomas Mobrey would 499 00:30:49,840 --> 00:30:52,960 Speaker 1: find themselves fired for what we're determined to be their 500 00:30:53,000 --> 00:30:58,440 Speaker 1: anti Muslim, anti Black Lives Matter, and pro Confederacy posts. 501 00:30:59,440 --> 00:31:02,680 Speaker 1: We tried contacting Detective Andrew for comment at his office 502 00:31:02,920 --> 00:31:05,800 Speaker 1: and via his cell phone. One week when we were 503 00:31:05,800 --> 00:31:08,720 Speaker 1: in St. Louis, we decided to just stop by his house. 504 00:31:09,320 --> 00:31:12,120 Speaker 1: We figured we could knock on his door, introduce ourselves, 505 00:31:12,480 --> 00:31:14,840 Speaker 1: and with a smile on our faces, ask if he 506 00:31:14,920 --> 00:31:17,560 Speaker 1: was willing to talk to us. After all, it's not 507 00:31:17,600 --> 00:31:20,480 Speaker 1: a crime to knock on doors. Jehovah's witnesses do it 508 00:31:20,520 --> 00:31:23,400 Speaker 1: all the time. Heck, detectives do it all the time. 509 00:31:26,560 --> 00:31:29,240 Speaker 1: It's gonna be on the left and there's a cop car. 510 00:31:29,280 --> 00:31:31,600 Speaker 1: There's a cop car, all right, So what do we 511 00:31:31,640 --> 00:31:35,480 Speaker 1: say here? It's uh, listen, I hope we're not bothering you. 512 00:31:35,520 --> 00:31:40,280 Speaker 1: Were journalists. We're working on a story about the death 513 00:31:40,280 --> 00:31:44,800 Speaker 1: of Donye Jones and doing a story in Dania Jones. Um. 514 00:31:45,000 --> 00:31:47,000 Speaker 1: We tried getting in touch with you to the office, 515 00:31:47,000 --> 00:31:49,360 Speaker 1: couldn't And then we were in town this weekend and 516 00:31:50,400 --> 00:31:52,360 Speaker 1: we're just hoping we could catch you in person to 517 00:31:52,480 --> 00:31:55,560 Speaker 1: just you know, sit down for a few minutes and 518 00:31:55,680 --> 00:31:59,640 Speaker 1: get your side of uh the investigation, and you know, 519 00:32:00,080 --> 00:32:03,400 Speaker 1: things he saw and what led you to your determinations. 520 00:32:06,160 --> 00:32:08,320 Speaker 1: We didn't want to walk up with a tape recorder 521 00:32:08,360 --> 00:32:11,120 Speaker 1: in our hands. So the gist of what happened is 522 00:32:11,480 --> 00:32:14,560 Speaker 1: that we knocked on Detective Andrewer's door. When he answered, 523 00:32:14,880 --> 00:32:16,840 Speaker 1: we told him who we were and that we were 524 00:32:16,840 --> 00:32:21,280 Speaker 1: working on a story about Donya Jones. Andrewer was immediately 525 00:32:21,360 --> 00:32:24,080 Speaker 1: upset that we were there. We tried to explain that 526 00:32:24,360 --> 00:32:26,880 Speaker 1: we wanted to give him an opportunity to schedule a 527 00:32:26,920 --> 00:32:29,600 Speaker 1: time to talk, even on background, if he wanted to, 528 00:32:30,440 --> 00:32:32,880 Speaker 1: and then we gave him our contact information and he 529 00:32:32,920 --> 00:32:39,440 Speaker 1: then asked us to get off his property, so we left. First. 530 00:32:39,480 --> 00:32:41,480 Speaker 1: What I took from what you gave me, which was 531 00:32:41,560 --> 00:32:45,160 Speaker 1: most important, was the body temperature was seventy six degrees 532 00:32:45,200 --> 00:32:48,880 Speaker 1: sarrenheight at seven fifty seven am, and the ambient temperature 533 00:32:48,920 --> 00:32:53,000 Speaker 1: was forty five point five degrees farrenheight at seven three am. 534 00:32:53,040 --> 00:32:56,520 Speaker 1: And I also noted that the rhythm mortis was fixed 535 00:32:56,520 --> 00:33:00,320 Speaker 1: in the jaw but breakable in the extremities. So just 536 00:33:00,400 --> 00:33:03,320 Speaker 1: looking at the time frame, someone who was last known 537 00:33:03,360 --> 00:33:05,640 Speaker 1: to be alive and found was an eight hour and 538 00:33:05,800 --> 00:33:11,080 Speaker 1: thirty minutes range. So looking at the again mortist first 539 00:33:11,880 --> 00:33:14,000 Speaker 1: where the mortist begins in the muffles of the face 540 00:33:14,080 --> 00:33:17,200 Speaker 1: on the neck, and it appears after two hours, and 541 00:33:17,240 --> 00:33:20,280 Speaker 1: it's in a fully fixed form in an eight to 542 00:33:20,360 --> 00:33:23,640 Speaker 1: twelve hour mark. So right there, knowing that it's fixed 543 00:33:23,680 --> 00:33:26,160 Speaker 1: only in the jaw but not in the rest of 544 00:33:26,160 --> 00:33:28,360 Speaker 1: the extremities, we know that we're in a two to 545 00:33:28,480 --> 00:33:32,160 Speaker 1: eight hour time trains. Then I'd chugged in the numbers 546 00:33:32,160 --> 00:33:35,800 Speaker 1: to be adjusted Glacier equation and I got two point 547 00:33:35,920 --> 00:33:39,280 Speaker 1: ninety six hours. When I plugged it into Eureka, I 548 00:33:39,360 --> 00:33:43,280 Speaker 1: got three point forty two hours. So with Eureka, that 549 00:33:43,280 --> 00:33:46,320 Speaker 1: would show that it's three hours and twenty five minutes 550 00:33:46,320 --> 00:33:49,720 Speaker 1: ago from money. The temperature was taken, so that approximated 551 00:33:49,800 --> 00:33:53,320 Speaker 1: to be around four thirty in the morning. And this 552 00:33:53,440 --> 00:33:56,120 Speaker 1: could be a little bit tricky well, because the body 553 00:33:56,200 --> 00:33:59,719 Speaker 1: did drop twenty two point five degrees there and night. However, 554 00:34:00,280 --> 00:34:03,000 Speaker 1: it was cold outside he was outside, and the cold 555 00:34:03,080 --> 00:34:05,720 Speaker 1: anti appempature I can speed up the temperature rate of dropping. 556 00:34:06,240 --> 00:34:10,080 Speaker 1: So I found using the equasions and the rigor Mortis. 557 00:34:10,080 --> 00:34:12,920 Speaker 1: That's that it probably was about was three and a 558 00:34:12,920 --> 00:34:17,680 Speaker 1: half that our time things when he was found. Okay, awesome. 559 00:34:17,719 --> 00:34:22,600 Speaker 1: So so you're putting out roughly about four yes, And 560 00:34:24,080 --> 00:34:26,279 Speaker 1: like I said, it's hard because it was thy five 561 00:34:26,760 --> 00:34:30,440 Speaker 1: five degrees out, so the cold temperature really messes with 562 00:34:30,520 --> 00:34:34,400 Speaker 1: the rate. But going off of my whole entire thesism, 563 00:34:34,400 --> 00:34:36,160 Speaker 1: what I found to be true and things like that, 564 00:34:36,160 --> 00:34:39,880 Speaker 1: that would be my best estiment. We thought it was 565 00:34:39,960 --> 00:34:43,240 Speaker 1: only fair to present this information to the chief Medical 566 00:34:43,239 --> 00:34:48,319 Speaker 1: Examiner for comment. Your investigator noted that Rigor Mortis and 567 00:34:48,400 --> 00:34:52,160 Speaker 1: his extremities was had begun but was breakable. And then 568 00:34:52,280 --> 00:34:56,440 Speaker 1: I actually spoke to an out of state medical investigator 569 00:34:56,640 --> 00:35:00,480 Speaker 1: who wrote their master's thesis on determining time of death 570 00:35:00,480 --> 00:35:04,480 Speaker 1: based on ambient temperature, body mass, and temperature of body 571 00:35:04,600 --> 00:35:09,600 Speaker 1: at time of discovery, and she generated an equation that 572 00:35:09,880 --> 00:35:12,600 Speaker 1: through a computer system called Eureka that plugs in the 573 00:35:12,640 --> 00:35:15,960 Speaker 1: important variables and comes up with what she has found 574 00:35:16,000 --> 00:35:20,279 Speaker 1: through testing to be a fairly reliable method, and that 575 00:35:20,440 --> 00:35:22,799 Speaker 1: puts his time of death roughly at four thirty in 576 00:35:22,800 --> 00:35:25,080 Speaker 1: the morning. If you're saying that that it goes back 577 00:35:25,080 --> 00:35:27,919 Speaker 1: in two hours, I would very much doubt that even 578 00:35:27,920 --> 00:35:30,839 Speaker 1: based on even based on the riga mortis. The rigor 579 00:35:30,840 --> 00:35:32,960 Speaker 1: mortis at the time that he was examined at ten 580 00:35:33,000 --> 00:35:37,960 Speaker 1: amim has described as moderately developed technically. According to the 581 00:35:38,000 --> 00:35:41,920 Speaker 1: report at about seven thirty am, the on site investigator said, 582 00:35:41,960 --> 00:35:44,560 Speaker 1: the rigor mortis was in the jaw and breakable in 583 00:35:44,600 --> 00:35:49,440 Speaker 1: the limbs. But anyway, these are not rigid parameters that 584 00:35:49,480 --> 00:35:51,960 Speaker 1: we can use to establish a time of death. You 585 00:35:52,000 --> 00:35:54,759 Speaker 1: can certainly do that if you like, but we're not 586 00:35:54,800 --> 00:35:57,239 Speaker 1: going to be doing that. If I if I say, well, 587 00:35:57,280 --> 00:35:59,880 Speaker 1: this is the time of death, I need to be 588 00:36:00,040 --> 00:36:02,359 Speaker 1: will to support that, to go into court and say 589 00:36:02,360 --> 00:36:05,440 Speaker 1: that if I am called upon to do that. This 590 00:36:05,520 --> 00:36:09,440 Speaker 1: person that you're talking to about the songs trying to 591 00:36:09,480 --> 00:36:13,239 Speaker 1: come up with this methodology that she uses. You know, 592 00:36:14,120 --> 00:36:17,120 Speaker 1: that is not something that is established in the scientific 593 00:36:17,840 --> 00:36:20,719 Speaker 1: literature that we can say, well, here, based upon this 594 00:36:20,800 --> 00:36:23,719 Speaker 1: is how long this person has been dead. Do you 595 00:36:23,840 --> 00:36:27,120 Speaker 1: use this now in your work? Um? I cannot. Some 596 00:36:27,280 --> 00:36:30,360 Speaker 1: cases where I'm working, our case load is so heavy 597 00:36:30,600 --> 00:36:34,040 Speaker 1: that it's not something I can use on a daily basis. 598 00:36:34,040 --> 00:36:37,440 Speaker 1: But if I ever meet you, right doctor, doctor asks 599 00:36:37,520 --> 00:36:40,080 Speaker 1: me to I would be willing to and I believe 600 00:36:40,080 --> 00:36:44,000 Speaker 1: it would show accurately. So could you say that now 601 00:36:44,320 --> 00:36:48,640 Speaker 1: after she developed that new adjusted Glacier equation, that it's 602 00:36:48,680 --> 00:36:51,440 Speaker 1: something you use in your work. I do use it 603 00:36:51,520 --> 00:36:55,120 Speaker 1: to estimate some time of death. It is pretty accurate. 604 00:36:57,200 --> 00:37:00,600 Speaker 1: We're not trying to suggest that doctor cases wrong not 605 00:37:00,640 --> 00:37:03,120 Speaker 1: to seek an estimated time of death in her cases. 606 00:37:04,160 --> 00:37:06,560 Speaker 1: For our own purposes, though, we wanted to have a 607 00:37:06,600 --> 00:37:11,120 Speaker 1: reliable estimate of when Danye died, and we think Carly's 608 00:37:11,200 --> 00:37:14,560 Speaker 1: estimate is worth taking seriously, especially as it lines up 609 00:37:14,560 --> 00:37:17,640 Speaker 1: with the rigor mortis and Donye's limbs. And that means 610 00:37:17,680 --> 00:37:22,040 Speaker 1: considering the possibility that he didn't die until roughly four 611 00:37:22,200 --> 00:37:26,080 Speaker 1: thirty in the morning. Remember, he was last seen by 612 00:37:26,120 --> 00:37:30,120 Speaker 1: his uncle walking out the back door around nine PM. 613 00:37:30,160 --> 00:37:33,560 Speaker 1: And something we haven't pointed out yet is this Donye's 614 00:37:33,600 --> 00:37:37,240 Speaker 1: phone did not have cell service at this time. In fact, 615 00:37:37,600 --> 00:37:40,920 Speaker 1: he had two cell phones, one in Android and the 616 00:37:41,000 --> 00:37:44,960 Speaker 1: other an iPhone. Apparently the Android was newer it was 617 00:37:45,000 --> 00:37:48,400 Speaker 1: the device he primarily used, but at the time of 618 00:37:48,440 --> 00:37:52,319 Speaker 1: his death, neither device had service. He used them on 619 00:37:52,440 --> 00:37:55,880 Speaker 1: WiFi only and relied on apps to send out texts 620 00:37:55,880 --> 00:37:59,840 Speaker 1: and to talk, so that nine p m. Text message 621 00:37:59,880 --> 00:38:03,399 Speaker 1: to his sister Militia that said sorry Sis. It had 622 00:38:03,440 --> 00:38:05,600 Speaker 1: to have been sent before he left the range of 623 00:38:05,640 --> 00:38:09,400 Speaker 1: the WiFi router in his house. Taking all of this together, 624 00:38:09,719 --> 00:38:12,560 Speaker 1: we know that Donna left with his overnight bag a 625 00:38:12,600 --> 00:38:16,680 Speaker 1: little after nine pm, but maybe didn't take his last 626 00:38:16,719 --> 00:38:20,440 Speaker 1: breath for what looks like another seven hours. And based 627 00:38:20,440 --> 00:38:23,239 Speaker 1: on the fact that Melissa thinks Donya was going out 628 00:38:23,280 --> 00:38:26,320 Speaker 1: to meet a girl and Derek was the last person 629 00:38:26,360 --> 00:38:28,840 Speaker 1: to really hang out with Danyae in the house and 630 00:38:28,920 --> 00:38:31,960 Speaker 1: he claims that while they watched basketball, danye was in 631 00:38:32,000 --> 00:38:35,800 Speaker 1: good spirits. We cannot help but wonder if the mystery 632 00:38:35,880 --> 00:38:38,920 Speaker 1: person or people that Dania went out with that night 633 00:38:39,480 --> 00:38:42,120 Speaker 1: might be able to shed light and how he ended 634 00:38:42,200 --> 00:38:45,719 Speaker 1: up dead by morning. But who is this person or 635 00:38:45,840 --> 00:38:50,480 Speaker 1: people and why haven't they come forward? Even if Danyae 636 00:38:50,600 --> 00:38:54,360 Speaker 1: did die by suicide, why wouldn't this person or people 637 00:38:54,920 --> 00:38:57,600 Speaker 1: reach out to Melissa and tell her what they know 638 00:38:57,680 --> 00:39:02,080 Speaker 1: of Dnya's last hours alive? Well, what's a hazard? Suspicions? 639 00:39:03,600 --> 00:39:12,320 Speaker 1: That's next time and after the uprising, After the uprising 640 00:39:12,400 --> 00:39:16,360 Speaker 1: is directed, produced, investigated, written, and reported by myself, Rainovschelski, 641 00:39:16,480 --> 00:39:19,080 Speaker 1: and John Duffy. John Duffy was also the editor. Dave 642 00:39:19,160 --> 00:39:22,960 Speaker 1: Cassidy was producer, sound engineering, design and mixed by Josh Condon. 643 00:39:23,160 --> 00:39:26,160 Speaker 1: Executive producers were Matt McDonough and Tina x Eros for 644 00:39:26,239 --> 00:39:29,000 Speaker 1: Now This, Brett Kushner for Group nine Media, and Jess 645 00:39:29,000 --> 00:39:31,920 Speaker 1: Borov was executive in charge of production. Jonathan Hartwig and 646 00:39:31,920 --> 00:39:35,520 Speaker 1: Bradley Rayford were consulting producers. Eliza Craig was assistant producer 647 00:39:35,560 --> 00:39:38,880 Speaker 1: and did additional reporting. Malory Keenoy was a writer's assistant. 648 00:39:38,960 --> 00:39:42,320 Speaker 1: Kristin McVicker and Taya Wilson were production assistants, and Haley 649 00:39:42,400 --> 00:39:45,840 Speaker 1: Klesmer was a post production assistant. Fact checking by Alison Humes. 650 00:39:46,080 --> 00:39:48,880 Speaker 1: Theme song and other music by Zachary Walter, legal by 651 00:39:48,960 --> 00:39:52,040 Speaker 1: Keith Sclar and Peter Yazy. Special thanks to Ann Frado, 652 00:39:52,120 --> 00:39:57,000 Speaker 1: Danny Gonzalez, Barbara Copple, Alex Lester, Bethan Mcalouzo, Emily Maronoff, 653 00:39:57,080 --> 00:39:59,840 Speaker 1: Ruth Vaka, and the Reporters Committee for Freedom of the Press. 654 00:40:00,120 --> 00:40:02,360 Speaker 1: After the Uprising is a production of Double asterisk I, 655 00:40:02,440 --> 00:40:05,320 Speaker 1: Heart Media and Now This in association with True Stories. 656 00:40:05,480 --> 00:40:07,680 Speaker 1: You can find us on Twitter and Facebook. If you 657 00:40:07,760 --> 00:40:10,279 Speaker 1: have useful information about the death of Danye Jones or 658 00:40:10,320 --> 00:40:12,680 Speaker 1: anything we've covered, please leave a message on our tip 659 00:40:12,719 --> 00:40:15,799 Speaker 1: line at three four seven six seven four seven four 660 00:40:15,960 --> 00:40:16,520 Speaker 1: zero one.