1 00:00:01,120 --> 00:00:04,160 Speaker 1: You're listening to the Mind Over Murder podcast. 2 00:00:06,000 --> 00:00:09,679 Speaker 2: My name is Bill Thomas. I'm a writer, consulting, producer, 3 00:00:09,720 --> 00:00:12,839 and now podcaster. I am now trying to use my 4 00:00:12,919 --> 00:00:15,800 experience as the brother of a murder victim to help 5 00:00:15,880 --> 00:00:18,600 other victims of violent crime. I'm working on a book 6 00:00:18,679 --> 00:00:21,440 on the unsolved Colonial Parkway murders and I'm the co 7 00:00:21,519 --> 00:00:24,760 administrator of the Colonial Parkway Murders Facebook group together with 8 00:00:24,839 --> 00:00:25,519 Kristin Dilly. 9 00:00:26,079 --> 00:00:29,120 Speaker 3: My name is Kristin Dilly. I'm a writer, a researcher, 10 00:00:29,320 --> 00:00:32,079 a teacher, and a victim's advocate, as well as the 11 00:00:32,119 --> 00:00:35,840 social media manager and co administrator for the Colonial Parkway 12 00:00:35,880 --> 00:00:39,079 Murders Facebook page with my partner in crime, Bill Thomas. 13 00:00:42,119 --> 00:00:43,600 Welcome to Mind Ever Murderer. 14 00:00:43,719 --> 00:00:46,320 Speaker 2: I'm Kristin Dilly and I'm Bill Thomas, and. 15 00:00:46,399 --> 00:00:50,640 Speaker 3: We're joined today by doctor Mike Amott of the Bradford University, 16 00:00:50,719 --> 00:00:55,039 Florida Gulf Coast University Serial Killer Research Database here to 17 00:00:55,079 --> 00:00:59,000 talk to us all about serial killers. Mike, thank you 18 00:00:59,079 --> 00:00:59,880 so much for joining us. 19 00:01:00,520 --> 00:01:02,520 Speaker 2: So happy to be here, christ and you make it 20 00:01:02,560 --> 00:01:03,439 sound so upbeat. 21 00:01:04,480 --> 00:01:05,120 Speaker 4: I do. 22 00:01:05,359 --> 00:01:07,599 Speaker 3: That's just a function of me being excited to be 23 00:01:07,680 --> 00:01:11,879 here and really geeking out over this amazing data analysis 24 00:01:11,920 --> 00:01:14,040 that I have at my fingertips as a result of 25 00:01:14,079 --> 00:01:16,719 this serial killer study. So, yeah, I'm a little amped 26 00:01:16,760 --> 00:01:19,239 about serial killers. Maybe I need to tone it down 27 00:01:19,319 --> 00:01:20,840 just a bit. I'll try to dial it back. 28 00:01:21,519 --> 00:01:24,120 Speaker 2: Let's let you jump right into it, since you're so 29 00:01:24,280 --> 00:01:26,319 incredibly enthusiastic. 30 00:01:26,760 --> 00:01:28,840 Speaker 3: Mike, go ahead and start by talking to us about 31 00:01:28,920 --> 00:01:32,599 how this database originated. I know you said that it 32 00:01:32,640 --> 00:01:36,159 started as a classroom project. Tell us more as an educator. 33 00:01:36,239 --> 00:01:39,200 I love that. I'm fascinated, So tell us all about 34 00:01:39,200 --> 00:01:40,599 the database and how it got started. 35 00:01:40,879 --> 00:01:43,480 Speaker 4: Sure, so, there was no intention of creating the database 36 00:01:43,519 --> 00:01:46,040 when it when it first started, but I was teaching 37 00:01:46,079 --> 00:01:50,239 a course in forensic psychology at Radford University, and the 38 00:01:50,239 --> 00:01:52,640 students were really interested, even back then, this is the 39 00:01:52,840 --> 00:01:56,000 early nineties, even in serial murder. But what I found 40 00:01:56,079 --> 00:01:59,840 was that there really weren't very many good sources of information. 41 00:02:00,040 --> 00:02:01,640 There were a lot of true crime books, but there 42 00:02:01,680 --> 00:02:06,000 really weren't any good academic sources. There was a profile 43 00:02:06,079 --> 00:02:08,759 that the FBI had put out about serial killers. You 44 00:02:08,800 --> 00:02:10,800 had a lot of people speculating, but there really wasn't 45 00:02:10,840 --> 00:02:13,520 good data. So what I did was. I had my 46 00:02:13,599 --> 00:02:16,280 students do a serial killer timeline. So put them into 47 00:02:16,280 --> 00:02:18,840 groups of about three or four students, gave them a 48 00:02:18,879 --> 00:02:21,479 true crime book on a serial killer, and told them 49 00:02:21,520 --> 00:02:24,759 basically to create a timeline from when that serial killer 50 00:02:24,800 --> 00:02:26,879 was born all the way through until they died or 51 00:02:27,280 --> 00:02:30,919 were convicted, and then to compare with their timeline and 52 00:02:30,960 --> 00:02:34,039 what their research is showing how it compares to what 53 00:02:34,080 --> 00:02:36,719 we talked about in terms of aggression in the classroom. 54 00:02:37,280 --> 00:02:38,759 And so we started off with a few of those. 55 00:02:38,879 --> 00:02:40,680 I took them and throw in the firing cabinet, and 56 00:02:40,719 --> 00:02:43,080 then I started looking through my filing cabinet realized I've 57 00:02:43,120 --> 00:02:45,159 got a lot of timelines. So I just stuck them 58 00:02:45,159 --> 00:02:47,840 into an Excel sheet and it might not even been 59 00:02:47,919 --> 00:02:50,000 Excel back then. I can't remember what the order was, 60 00:02:50,039 --> 00:02:52,319 but I think maybe Excel wasn't even ready. Then just 61 00:02:52,360 --> 00:02:54,599 started putting them in there. And then students wanted to 62 00:02:54,680 --> 00:02:57,319 know if they could do independent studies, to start doing 63 00:02:57,360 --> 00:03:00,800 more research, and it just kept building and building, and 64 00:03:00,840 --> 00:03:03,680 then it got out to our local news media that 65 00:03:03,719 --> 00:03:06,319 we had this database, and they were so interested in it. 66 00:03:06,319 --> 00:03:08,120 We thought, let's make it a little more formal and 67 00:03:08,439 --> 00:03:09,680 it's just kept growing. 68 00:03:11,319 --> 00:03:16,080 Speaker 2: So did it change format over time as that data 69 00:03:16,199 --> 00:03:18,479 was entered by you and the students? How did it 70 00:03:18,520 --> 00:03:19,319 all come together? 71 00:03:20,240 --> 00:03:23,280 Speaker 4: It changed and that we removed some fields and we 72 00:03:23,319 --> 00:03:26,159 added quite a few fields. And then when the FBI 73 00:03:26,560 --> 00:03:30,319 changed the definition from three murders to two, we had 74 00:03:30,360 --> 00:03:32,479 to go back and collect the people that we had 75 00:03:32,520 --> 00:03:35,560 thrown out because they had only the two murders. But 76 00:03:35,599 --> 00:03:37,479 we keep adding the fields, and we add a field, 77 00:03:37,560 --> 00:03:39,360 we have to go back and start filling in the 78 00:03:39,759 --> 00:03:42,800 thousands that we hadn't looked for that piece of information for. 79 00:03:43,599 --> 00:03:46,120 Speaker 3: I'll ask the question that I think a lot of 80 00:03:46,199 --> 00:03:49,520 lay people who are not interested in true criming serial 81 00:03:49,599 --> 00:03:53,000 killers might ask, what is the end goal of having 82 00:03:53,159 --> 00:03:54,560 a serial killer database? 83 00:03:54,960 --> 00:03:56,680 Speaker 4: That goal has changed a little bit. So when I 84 00:03:56,719 --> 00:03:59,159 first started, it was really more to just give me 85 00:03:59,759 --> 00:04:02,520 good statistics to use while I teach my class. And 86 00:04:02,560 --> 00:04:05,000 then it became let's go ahead and try to see 87 00:04:05,000 --> 00:04:07,919 if we can get great statistics for everybody to use 88 00:04:08,039 --> 00:04:11,439 on serial murder. And then the goal became, in addition 89 00:04:11,520 --> 00:04:13,599 to that, let's see if we can find some ways 90 00:04:13,639 --> 00:04:16,240 to maybe help law enforcement be able to find or 91 00:04:16,279 --> 00:04:19,279 profile serial killers. And then we got rid of that 92 00:04:19,360 --> 00:04:21,519 goal because it didn't look like that was going to 93 00:04:21,519 --> 00:04:23,759 be very successful for a number of reasons. I think 94 00:04:23,759 --> 00:04:26,759 the goal right now is just compiling the most accurate 95 00:04:26,839 --> 00:04:29,240 data that's available, So we don't really have some of 96 00:04:29,279 --> 00:04:32,040 these misunderstandings about about serial killers. 97 00:04:32,560 --> 00:04:36,079 Speaker 2: So how many subjects are currently in the database, Mike, 98 00:04:36,439 --> 00:04:39,959 what's the universe of people were looking at? 99 00:04:40,160 --> 00:04:43,319 Speaker 4: So overall we have just short of fifty eight hundred 100 00:04:43,600 --> 00:04:46,720 serial killers in there. Most of them thirty seven hundred 101 00:04:46,759 --> 00:04:50,560 are from the US and about twenty one hundred are international. 102 00:04:51,199 --> 00:04:52,680 Speaker 3: That's a scary number. 103 00:04:52,759 --> 00:04:56,160 Speaker 4: It is. And we've created a kind of a second 104 00:04:56,199 --> 00:04:58,519 database where we're looking at instead of just a serial 105 00:04:58,600 --> 00:05:01,519 killers were looking at their victim and so that's limited 106 00:05:01,519 --> 00:05:04,399 for the most part to the US and Canadian victims. 107 00:05:04,839 --> 00:05:07,120 But I'll tell you that was a huge change in 108 00:05:08,079 --> 00:05:12,480 our database because what we realized is breaking really basically 109 00:05:12,519 --> 00:05:15,920 saying we need to see each victim name for each 110 00:05:15,920 --> 00:05:19,680 serial killer really made the database more accurate because we 111 00:05:19,759 --> 00:05:22,839 had people listed as, for example, having killed six. You 112 00:05:22,879 --> 00:05:24,720 go through and try to find out who those six are, 113 00:05:24,800 --> 00:05:27,439 and you realize there were only two. But somewhere along 114 00:05:27,480 --> 00:05:30,279 the way somebody in law enforcement said, it wouldn't surprise 115 00:05:30,360 --> 00:05:33,360 me if they've killed six, and you realize that's not proof. 116 00:05:35,000 --> 00:05:36,360 Speaker 3: It's not the same thing at all. 117 00:05:36,639 --> 00:05:36,879 Speaker 4: Though. 118 00:05:37,879 --> 00:05:41,079 Speaker 2: One thing before we move past these numbers. Is it 119 00:05:41,120 --> 00:05:44,480 significant to you that there are thirty seven hundred serial 120 00:05:44,560 --> 00:05:47,959 killers in the database for the United States and twenty 121 00:05:48,000 --> 00:05:52,480 one hundred internationally. Is that a matter of data access 122 00:05:52,680 --> 00:05:55,279 or does the US have more serial killers on a 123 00:05:55,279 --> 00:05:58,600 per capita basis than every other country on the planet. 124 00:05:59,519 --> 00:06:02,360 Speaker 4: My take on this, and not everybody agrees with this take, 125 00:06:02,560 --> 00:06:05,040 but my take on it, it's a matter of access, 126 00:06:05,279 --> 00:06:08,199 because if you look at murder rates by country, the 127 00:06:08,319 --> 00:06:10,560 US falls about in the middle, and so it doesn't 128 00:06:10,600 --> 00:06:13,000 make any sense that we would be about in the 129 00:06:13,040 --> 00:06:16,079 middle in terms of murder rates but number one by 130 00:06:16,279 --> 00:06:19,560 so much in terms of serial killers. It doesn't make 131 00:06:19,560 --> 00:06:21,519 a lot of sense. But then, if you think about 132 00:06:22,000 --> 00:06:25,000 how people get into the database, they had somebody had 133 00:06:25,040 --> 00:06:26,959 to have killed two or more people on two or 134 00:06:26,959 --> 00:06:31,120 more occasions. That had to be discovered, It had to 135 00:06:31,120 --> 00:06:34,759 be reported someplace, had to be reported someplace in English, 136 00:06:34,759 --> 00:06:37,879 because that's pretty much the only language I speak, and 137 00:06:37,920 --> 00:06:40,439 I barely speak that, and so I think the thing 138 00:06:40,519 --> 00:06:43,600 is it's just so much easier to get information about 139 00:06:43,800 --> 00:06:47,040 US serial killers than it is others. To give you 140 00:06:47,040 --> 00:06:49,360 a good example of that, years ago, there was a 141 00:06:49,399 --> 00:06:52,480 master student out in California, and I can't remember the 142 00:06:52,600 --> 00:06:54,959 name of the university, but she was from Japan. So 143 00:06:55,000 --> 00:06:58,399 she spoke fluent Japanese and she did her thesis on 144 00:06:58,480 --> 00:07:02,680 Japanese serial killers, and her thesis found so many serial 145 00:07:02,720 --> 00:07:05,680 killers that nobody had ever reported before. But the difference 146 00:07:05,839 --> 00:07:07,680 was she spoke the language. She could look at the 147 00:07:07,759 --> 00:07:11,920 Japanese newspapers and media sources and find things nobody else could. So, 148 00:07:12,040 --> 00:07:14,079 even though it's a boring answer, it's a matter of 149 00:07:14,319 --> 00:07:16,399 it's more a matter of access than it is something 150 00:07:16,879 --> 00:07:21,399 about the US. I think that's really the explanation for it. 151 00:07:21,480 --> 00:07:23,600 And that's why I think when you interpret serial killer 152 00:07:23,680 --> 00:07:26,360 data in general, you just really have to be careful 153 00:07:26,839 --> 00:07:29,720 about how you interpret things because so much of it 154 00:07:29,800 --> 00:07:30,480 is access. 155 00:07:31,519 --> 00:07:35,120 Speaker 3: What is your methodology for this in terms of data collection, 156 00:07:36,000 --> 00:07:38,240 what are the metrics that you're looking at, How do 157 00:07:38,319 --> 00:07:40,720 you get all your data, and who is doing the 158 00:07:41,360 --> 00:07:43,800 data entry? Hopefully this doesn't all fall to you. 159 00:07:44,920 --> 00:07:48,399 Speaker 4: It does for the most part, these days. But over 160 00:07:48,639 --> 00:07:51,920 the years, it was mostly my students creating the the 161 00:07:52,000 --> 00:07:54,319 data I started to put in the database. But again, 162 00:07:54,360 --> 00:07:57,199 as students wanted to do independent studies, they would start 163 00:07:57,240 --> 00:08:00,639 to enter the the data. I retired from I'm teaching 164 00:08:00,720 --> 00:08:03,720 about fifteen years ago. I'm a full time consultant with 165 00:08:04,040 --> 00:08:06,920 a consulting FIRMAUNT at DC, and so I don't have 166 00:08:06,959 --> 00:08:10,040 the access to the students that I used to. When 167 00:08:10,079 --> 00:08:12,920 we first started the database, the Internet really didn't exist, 168 00:08:13,199 --> 00:08:16,279 and so pretty much it was a matter of looking 169 00:08:16,319 --> 00:08:19,279 at true crime books, and there's such a difference in 170 00:08:19,360 --> 00:08:21,839 terms of accuracy of those books. There are some really 171 00:08:21,879 --> 00:08:25,199 good true crime writers and there are some horrible ones. 172 00:08:25,439 --> 00:08:27,519 One of my students got confused because the book she 173 00:08:27,639 --> 00:08:30,000 had they listed three different birth dates for the killer 174 00:08:30,040 --> 00:08:33,080 in the same book. And that's not really a good that. 175 00:08:33,080 --> 00:08:35,960 It doesn't give you much confidence in the inaccuracy of 176 00:08:36,039 --> 00:08:38,440 the book. But then the students would go into the 177 00:08:38,480 --> 00:08:42,559 library and look at microfiche and microfilm, of looking at 178 00:08:42,600 --> 00:08:45,759 major newspapers like the New York Times. But then as 179 00:08:45,919 --> 00:08:50,240 the Internet came about, it started changing everything. And if 180 00:08:50,279 --> 00:08:52,639 you think about today, we go through and we still 181 00:08:52,679 --> 00:08:55,480 look at true crime books. We look at different media sources, 182 00:08:55,799 --> 00:08:59,440 but for example, ancestry dot com has been a phenomenal 183 00:08:59,480 --> 00:09:02,360 source in terms of getting birth dates and death dates, 184 00:09:02,360 --> 00:09:05,519 and race information and family information whether they served in 185 00:09:05,559 --> 00:09:08,919 the military. Newspapers dot com is again one of those. 186 00:09:08,960 --> 00:09:11,679 We get these from these small towns. We get access 187 00:09:11,679 --> 00:09:15,440 to all these different newspapers. So the methods has changed 188 00:09:15,480 --> 00:09:17,120 in a little bit. But what we try to do 189 00:09:17,679 --> 00:09:19,200 is make sure we have at least a couple of 190 00:09:19,279 --> 00:09:21,879 sources that are going to say the same thing. For example, 191 00:09:21,879 --> 00:09:24,559 if we have the date of a particular murder, we 192 00:09:24,600 --> 00:09:26,799 want to find out a couple of sources more for 193 00:09:26,879 --> 00:09:30,240 the birth dates, same type of situation. Everything we have 194 00:09:30,320 --> 00:09:33,399 in the database is from public information, so we don't 195 00:09:33,399 --> 00:09:36,120 have any secret access, let's say, to the FBI files. 196 00:09:36,159 --> 00:09:39,159 We don't have psychiatrist reports that weren't part of the 197 00:09:39,200 --> 00:09:42,639 court proceeding, and we have done that on purpose because 198 00:09:42,720 --> 00:09:46,639 we want to share our database with other researchers, and 199 00:09:46,679 --> 00:09:49,960 if we had access to data that was private, it 200 00:09:50,000 --> 00:09:52,120 would limit our ability to share that. So everything we 201 00:09:52,159 --> 00:09:55,200 have now is something that anybody could get if you 202 00:09:55,240 --> 00:10:00,480 want to spend thousands and thousands of hours getting it. 203 00:10:00,480 --> 00:10:02,840 Speaker 2: It sounds like you miss your students in that regard. 204 00:10:03,519 --> 00:10:05,759 Speaker 4: Oh I do. I miss teaching quite a bit, But 205 00:10:05,799 --> 00:10:08,440 I just had they were offering a early retirement option, 206 00:10:08,519 --> 00:10:11,960 the state was and this consulting firm had wanted me 207 00:10:12,000 --> 00:10:14,600 to come on board full time. It was a tough decision, 208 00:10:14,840 --> 00:10:17,919 but I'm glad I made it. But I really missed teaching, 209 00:10:17,960 --> 00:10:19,480 being with my students. 210 00:10:20,120 --> 00:10:23,399 Speaker 3: How often do you add new information to the database. 211 00:10:23,519 --> 00:10:26,759 Is this a weekly thing, a daily thing, monthly? 212 00:10:27,639 --> 00:10:29,759 Speaker 4: It's at least a weekly thing, So at least once 213 00:10:29,799 --> 00:10:32,200 a week I'll go in and search to see if 214 00:10:32,240 --> 00:10:35,879 there are new serial killers that have been identified, or if, 215 00:10:35,919 --> 00:10:38,879 for example, from an old case, there's new information that 216 00:10:38,919 --> 00:10:42,440 came out, for example that with the DNA technology now 217 00:10:42,720 --> 00:10:44,960 to beginning to identify victims that we had to be 218 00:10:45,039 --> 00:10:47,639 listed as unknown in the past. And so those are 219 00:10:47,679 --> 00:10:49,840 the kinds of things we update. But it's really it's 220 00:10:49,840 --> 00:10:50,960 a weekly process. 221 00:10:52,039 --> 00:10:55,000 Speaker 3: When I had called you, I think it was last week, 222 00:10:55,159 --> 00:10:57,399 to ask if you wanted to appear in my mind 223 00:10:57,399 --> 00:11:01,039 ever murder, and I had mentioned the Wade Wilmer Senior. 224 00:11:01,399 --> 00:11:02,879 You had said, oh, yeah, we already have him in 225 00:11:02,879 --> 00:11:07,080 the database. So Oh my gosh, that's fast work. That's 226 00:11:07,120 --> 00:11:11,080 great because it's really only been since January eighth that 227 00:11:11,159 --> 00:11:14,600 they made that announcement that he is good for the 228 00:11:14,679 --> 00:11:17,679 murders of Robin Edwards, David Noveline, and Teresa Howell, which 229 00:11:17,679 --> 00:11:20,039 does make him a serial killer absolutely. 230 00:11:20,799 --> 00:11:23,919 Speaker 2: How does Wilmer move on to your database so quickly? 231 00:11:23,960 --> 00:11:28,039 Speaker 4: In this example, again just going through media sources, it 232 00:11:28,080 --> 00:11:30,639 popped up in the headlines, and so I had his 233 00:11:30,759 --> 00:11:33,519 name go through and verify that, in fact, the three 234 00:11:33,519 --> 00:11:37,000 people he was suspected of killing there's a reasonable suspicion 235 00:11:37,039 --> 00:11:39,159 for that. You get a lot of ones of people 236 00:11:39,159 --> 00:11:42,039 that you can't really put in because they suspect but 237 00:11:42,080 --> 00:11:45,759 there's not really enough evidence to suggest that they did it. 238 00:11:45,879 --> 00:11:48,720 But right away the name goes in. I spend some 239 00:11:48,799 --> 00:11:51,639 time trying to find whatever information I can find at him, 240 00:11:51,840 --> 00:11:54,399 and then mark him down as a follow up because 241 00:11:54,399 --> 00:11:57,039 there'll be other information that comes out. But he's one 242 00:11:57,039 --> 00:11:59,159 of those, for example, that could go to ancestry dot 243 00:11:59,159 --> 00:12:01,559 com get the birth date information, get the death information. 244 00:12:01,559 --> 00:12:03,399 You get all that stuff that wouldn't be in a 245 00:12:03,399 --> 00:12:07,360 newspaper article for example, or a media source, but is available. 246 00:12:07,200 --> 00:12:08,960 Speaker 2: As soon as we knew about him, which is a 247 00:12:08,960 --> 00:12:12,000 few months ago before the announcement, we had done all 248 00:12:12,039 --> 00:12:16,639 that basic research with using ancestry in newspapers, dot com 249 00:12:16,679 --> 00:12:21,000 and other sources, so we had a pretty decent address history, 250 00:12:21,120 --> 00:12:25,039 day of birth, marriage, divorce, when his kids were born. 251 00:12:25,120 --> 00:12:27,440 But that's sort of thing, so we had a sense 252 00:12:27,480 --> 00:12:30,799 of that. We're just pleasantly surprised that as a newly 253 00:12:30,919 --> 00:12:34,360 minted serial killer, which by the way, is an expression 254 00:12:34,480 --> 00:12:38,799 we're comfortable using because according to as you said, according 255 00:12:38,799 --> 00:12:45,240 to the FBI's criteria, Alan Wade Wilmer Senior meets their criteria. Interestingly, 256 00:12:45,600 --> 00:12:48,039 the FBI, so far and it's only been a month, 257 00:12:48,240 --> 00:12:51,120 they never call him a serial killer. They seem to 258 00:12:51,159 --> 00:12:55,240 avoid terms like that quite often they. 259 00:12:55,080 --> 00:12:58,440 Speaker 4: Do, and I think that the fbis boxed themselves into 260 00:12:58,480 --> 00:13:01,080 a corner with their definition, because if you think about 261 00:13:01,279 --> 00:13:04,759 two or more murders on separate occasions, think about somebody 262 00:13:04,759 --> 00:13:08,279 who's a contract killer, they certainly fit the definition of 263 00:13:08,279 --> 00:13:10,519 a serial killer. So as we find them, we'll put 264 00:13:10,519 --> 00:13:12,399 them in our database. We don't go searching for the 265 00:13:12,440 --> 00:13:14,639 contract killers, but they would be in there. But those 266 00:13:14,679 --> 00:13:18,000 are certainly different types of people than somebody that is 267 00:13:18,080 --> 00:13:21,279 killing homeless folks on the street. The kind of the 268 00:13:21,360 --> 00:13:24,000 term I like to use instead of serial killer is 269 00:13:24,320 --> 00:13:29,320 multiple event killer, and then I think a serial killer 270 00:13:29,440 --> 00:13:31,480 is going to be a subdivision of that, because when 271 00:13:31,480 --> 00:13:34,480 that term first came out, it was coined to describe 272 00:13:34,559 --> 00:13:38,360 people who killed in the series. And most of these 273 00:13:38,440 --> 00:13:41,679 multiple event killers, again, they fit the definition of the 274 00:13:41,720 --> 00:13:44,919 FBI serial killer, but they're not killing in the series. 275 00:13:45,159 --> 00:13:47,480 They might kill three people over a thirty year period 276 00:13:47,519 --> 00:13:49,840 because they're angry, or they kill people over a period 277 00:13:49,840 --> 00:13:52,519 of time because they're robbing banks, but they're different. They're 278 00:13:52,559 --> 00:13:55,080 not that serial killer. And that's one of the things 279 00:13:55,080 --> 00:13:56,360 that I think that we're going to try to do 280 00:13:56,399 --> 00:13:59,399 at some point is see if we can subdivide serial 281 00:13:59,480 --> 00:14:01,879 killers into different types. We already have started that, but 282 00:14:01,919 --> 00:14:04,320 we haven't done any analysis on that, and I think 283 00:14:04,519 --> 00:14:07,159 we're going to see some real differences in these kind 284 00:14:07,200 --> 00:14:10,720 of these subtypes. For example, a person who is killing 285 00:14:10,720 --> 00:14:13,440 women and sexually assaulting women is going to be very 286 00:14:13,440 --> 00:14:15,519 different from the person who is killing people at seven 287 00:14:15,519 --> 00:14:18,000 to eleven. They're still they're going to be serial killers, 288 00:14:18,200 --> 00:14:20,320 but they're not the same type of serial killer. And 289 00:14:20,360 --> 00:14:23,679 I think once that research really starts again, we're already 290 00:14:23,679 --> 00:14:26,200 doing the categorization of those I think we're going to 291 00:14:26,240 --> 00:14:29,200 see some really different results, different patterns. 292 00:14:29,960 --> 00:14:32,720 Speaker 2: So are you thinking going to end up with several 293 00:14:32,759 --> 00:14:34,240 different subcategories? 294 00:14:35,120 --> 00:14:37,360 Speaker 4: Yes, however many that is, I'm not sure whether it's 295 00:14:37,399 --> 00:14:39,840 going to be something like ten or twenty. I'm not sure. 296 00:14:40,000 --> 00:14:43,039 But I think one of the reasons that profiling has 297 00:14:43,080 --> 00:14:46,679 not been very successful is because all serial killers aren't 298 00:14:46,720 --> 00:14:48,840 the same. What it could be that if you look 299 00:14:48,840 --> 00:14:52,320 at a certain type or subtype, that maybe they share 300 00:14:52,360 --> 00:14:54,360 a lot more in common and that profile can be 301 00:14:54,480 --> 00:14:57,080 much more accurate, because the current profile is certainly not 302 00:14:57,080 --> 00:14:58,000 not very accurate. 303 00:14:58,840 --> 00:15:01,000 Speaker 3: I was taking a look at the landing page for 304 00:15:01,039 --> 00:15:04,159 this study and it states that you utilize over one 305 00:15:04,240 --> 00:15:08,200 hundred and eighty five data points multiple murderer methodology, victimology, 306 00:15:08,240 --> 00:15:12,000 and statistical analysis. Can you talk about those one hundred 307 00:15:12,000 --> 00:15:13,720 and eighty five data points that you look at? 308 00:15:14,440 --> 00:15:17,799 Speaker 4: Sure, but to save your audience a lot of listening, 309 00:15:18,879 --> 00:15:20,240 let me put it into categories. 310 00:15:20,399 --> 00:15:21,240 Speaker 3: Perfect. That'd be great. 311 00:15:21,320 --> 00:15:25,120 Speaker 4: Yes, So we start off with the actual murders themselves, 312 00:15:25,159 --> 00:15:27,879 in terms of when they began and when they ended. 313 00:15:28,399 --> 00:15:31,639 What cities they occurred in, what counties what countries. We 314 00:15:31,720 --> 00:15:35,279 then go to a series of columns that describe childhood, 315 00:15:35,600 --> 00:15:38,000 So when they were born, where they were born, who 316 00:15:38,000 --> 00:15:40,799 were they raised by, Did they have problems in school? 317 00:15:41,159 --> 00:15:43,240 What type of education did they have at the time 318 00:15:43,279 --> 00:15:46,559 of the first murder. Then going to the information about 319 00:15:46,559 --> 00:15:49,960 the person themselves in terms of where they abused as 320 00:15:50,000 --> 00:15:52,919 a child, Did they have the try, did they abuse 321 00:15:53,200 --> 00:15:54,080 drugs or alcohol? 322 00:15:54,279 --> 00:15:57,000 Speaker 2: Can you explain the triad? I'm sorry for those of 323 00:15:57,000 --> 00:15:59,080 our listeners who are not criminologists. 324 00:16:00,039 --> 00:16:02,759 Speaker 4: The McDonald's try. It basically postulates that people who were 325 00:16:02,799 --> 00:16:07,799 aggressive had three common experiences. They were having bed wedding 326 00:16:08,279 --> 00:16:11,039 past the age at which you would expect bed wedding. 327 00:16:11,440 --> 00:16:14,960 They were they were setting fires, and there was animal abuse, 328 00:16:15,720 --> 00:16:18,120 and so that was pretty exciting when when it first 329 00:16:18,200 --> 00:16:21,360 came out, But like anything, people thought that meant everybody 330 00:16:21,399 --> 00:16:23,919 that's a killer has those characteristics, and if you have 331 00:16:23,960 --> 00:16:26,519 those characteristics, you're going to be a killer. And what 332 00:16:26,559 --> 00:16:29,279 it turns out is that most of your killers and 333 00:16:29,360 --> 00:16:33,120 most murders don't have those characteristics. They might have one, 334 00:16:33,279 --> 00:16:35,399 but they're not going to have all three. And there 335 00:16:35,480 --> 00:16:38,200 are plenty of people who have those that don't become murders. 336 00:16:38,559 --> 00:16:41,120 But if you look at the kind of the probability, 337 00:16:41,559 --> 00:16:44,440 those that have all three characteristics are probably more likely 338 00:16:44,559 --> 00:16:47,440 to become violent than those that don't. But it's not 339 00:16:47,600 --> 00:16:51,200 strong enough that you can predict with those. But if 340 00:16:51,240 --> 00:16:53,519 they have those three characteristics, regardless of whether they're going 341 00:16:53,559 --> 00:16:56,480 to be violent in the future, it's problematic in terms 342 00:16:56,480 --> 00:16:58,879 that they're going through psychological trauma. So it's not one 343 00:16:58,879 --> 00:17:01,440 of those things that you ignore, but you don't instantly 344 00:17:01,960 --> 00:17:03,360 assume that they're going to become a killer. 345 00:17:04,519 --> 00:17:09,599 Speaker 3: Very interesting, So murder's childhood, emotional factors. Any So those 346 00:17:09,599 --> 00:17:11,680 are the three main categories. Were there any others that 347 00:17:11,720 --> 00:17:12,480 you take a look at. 348 00:17:12,839 --> 00:17:15,079 Speaker 4: Sure, And then we go ahead and look at the 349 00:17:15,440 --> 00:17:19,079 murders themselves in terms of how they were committed, whether, 350 00:17:19,119 --> 00:17:22,319 for example, there was something such as necrophilia that occurred, 351 00:17:23,079 --> 00:17:25,839 what type of weapon was used, who were their victims, 352 00:17:26,319 --> 00:17:29,000 And then it goes into the outcome of when they 353 00:17:29,000 --> 00:17:31,920 were arrested, how many murders were they charged for, did 354 00:17:31,920 --> 00:17:35,279 they confess, did they plead insanity? So it goes to 355 00:17:35,359 --> 00:17:38,359 pretty much every part of their life, in every part 356 00:17:38,440 --> 00:17:42,480 of kind of the murder series. Now, I would love 357 00:17:42,519 --> 00:17:44,240 to say we have every bit of that information for 358 00:17:44,279 --> 00:17:48,039 every killer, but we don't. There are some things, for example, 359 00:17:48,039 --> 00:17:50,839 like race and gender that we have information on for everybody, 360 00:17:51,319 --> 00:17:54,319 but then things like were there abused as children we 361 00:17:54,400 --> 00:17:58,319 might have information on let's say twenty percent with that. 362 00:17:58,519 --> 00:18:00,720 And that's a good example, by the way, with the 363 00:18:00,799 --> 00:18:04,519 child abuse of a difficult variable because if you're reading 364 00:18:04,920 --> 00:18:09,160 the trial transcripts, if the person was abused as a child, 365 00:18:09,440 --> 00:18:11,680 it's going to show up, most likely in the sentencing 366 00:18:11,839 --> 00:18:15,880 part of the trial. But if they weren't abused, it's 367 00:18:15,920 --> 00:18:17,960 not really going to be mentioned. So when you see 368 00:18:18,000 --> 00:18:19,799 that lack of it being mentioned, you don't know if 369 00:18:19,799 --> 00:18:23,799 that's a no or just we don't know, And so 370 00:18:23,960 --> 00:18:26,119 you have to just be and so we limit our 371 00:18:26,279 --> 00:18:28,839 entries to ones that we know, and most of the 372 00:18:28,839 --> 00:18:31,559 ones it just isn't mentioned anywhere. And then you have 373 00:18:31,640 --> 00:18:34,880 to be careful too. For example, like with Arthur Shawcross, 374 00:18:34,920 --> 00:18:38,119 who was the Genesee River killer, he told all these 375 00:18:38,160 --> 00:18:41,319 stories about being abused as a child. When they interviewed 376 00:18:41,319 --> 00:18:44,160 his parents. Of course, his parents said didn't happen when 377 00:18:44,160 --> 00:18:46,359 they interviewed some relatives they said some of it happened 378 00:18:46,400 --> 00:18:48,480 and some of it didn't. And that's what you deal 379 00:18:48,519 --> 00:18:50,119 with a lot, and so you have to make some 380 00:18:50,200 --> 00:18:54,079 judgment calls on who are we believing here, And we've 381 00:18:54,160 --> 00:18:56,880 changed several of those codes or ratings over the years 382 00:18:56,920 --> 00:18:59,559 where we realize what we thought twenty years ago, there's 383 00:18:59,599 --> 00:19:02,160 evidence to suggests either it did or didn't happen. 384 00:19:02,799 --> 00:19:06,720 Speaker 2: This is pretty data intensive. How long is each entry 385 00:19:06,839 --> 00:19:10,200 if it's complete, Does it go on for page after page? 386 00:19:10,640 --> 00:19:13,880 Speaker 4: Oh? No, it's an Excel spreadsheet. So every serial killer 387 00:19:13,920 --> 00:19:17,160 will have one row in the database, and then they'll 388 00:19:17,200 --> 00:19:19,960 have hopefully entries in most of the columns. 389 00:19:20,480 --> 00:19:23,720 Speaker 2: And you can add more data as it becomes available. 390 00:19:23,759 --> 00:19:27,240 So if you learn new things from an interview or 391 00:19:27,279 --> 00:19:30,799 a court transcript or a well researched book, you may 392 00:19:31,039 --> 00:19:33,400 add additional data points as you go along. 393 00:19:33,880 --> 00:19:36,519 Speaker 4: Oh absolutely, yep. And then we have and this is 394 00:19:36,519 --> 00:19:39,079 where it's probably going to get start sounding boring, but 395 00:19:39,960 --> 00:19:41,839 in the same file as the rest of the database, 396 00:19:41,920 --> 00:19:46,960 we have separate tabs that will automatically calculate all the 397 00:19:47,039 --> 00:19:49,559 data Kristen that you were looking at in the board. 398 00:19:50,039 --> 00:19:52,559 It's going to automatically update those every time we add 399 00:19:52,799 --> 00:19:55,400 some new data, so it makes it makes it easier 400 00:19:55,440 --> 00:19:57,480 to summarize. 401 00:19:57,480 --> 00:20:00,680 Speaker 3: And it is fascinating. What we'll do. We'll put a 402 00:20:00,720 --> 00:20:03,720 link to your most recent annual report into the show 403 00:20:03,759 --> 00:20:05,640 notes so that people can take a look at it, 404 00:20:05,720 --> 00:20:08,000 or that the most recent one that people have access to. 405 00:20:08,160 --> 00:20:11,160 I know it's not all publicly available. It was just 406 00:20:11,279 --> 00:20:15,039 fascinating sitting there and combing through that because it is 407 00:20:15,359 --> 00:20:17,839 it is just so much interesting data to take a 408 00:20:17,880 --> 00:20:21,200 look at. So how did the partnership with Florida Gulf 409 00:20:21,240 --> 00:20:24,599 Coast University come about? Because this was originally it started 410 00:20:24,640 --> 00:20:27,400 at Radford. How did that partnership come about? 411 00:20:27,599 --> 00:20:30,880 Speaker 4: It was really interesting. There was a grad student at 412 00:20:30,880 --> 00:20:35,799 Florida Golf Coast University, Kristin eLink Sherman, Laura so a 413 00:20:35,839 --> 00:20:39,240 long name, but she was requested to access to the 414 00:20:39,319 --> 00:20:41,640 deity base to work on her thesis. She was looking 415 00:20:41,640 --> 00:20:44,559 at from a remembering rite. It was the relationship between 416 00:20:44,599 --> 00:20:49,480 military service and serial murder. And she got the idea 417 00:20:49,559 --> 00:20:51,799 that it would be great to put this thing online 418 00:20:51,960 --> 00:20:54,200 where people could go in and have access to it. 419 00:20:54,640 --> 00:20:57,599 And I thought maybe, and so they brought me down 420 00:20:57,599 --> 00:21:00,440 to Florida Gulf Coast and did a to meet all 421 00:21:00,480 --> 00:21:03,839 their students and they were really charged up about doing this, 422 00:21:03,880 --> 00:21:07,000 so let's do it. Dween Daubert was the faculty advisor 423 00:21:07,039 --> 00:21:10,640 at the at the time, and so they took the database, 424 00:21:10,720 --> 00:21:13,079 they went through and they try to confirm every entry 425 00:21:13,079 --> 00:21:15,359 in it, and so we went back and forth about 426 00:21:15,480 --> 00:21:17,799 whether they found something wrong, whether I thought it was 427 00:21:17,839 --> 00:21:20,279 actually wrong or not, or whether the their source was wrong. 428 00:21:20,319 --> 00:21:22,640 So that went back and forth, and then they put 429 00:21:22,640 --> 00:21:25,519 that online and people can try to get access it. 430 00:21:25,720 --> 00:21:29,319 Now the online version is way behind. That's not hasn't 431 00:21:29,319 --> 00:21:31,839 been updated, and we're working right now with Florida Golf 432 00:21:31,880 --> 00:21:34,839 Coast to try to update something. And we're actually starting 433 00:21:34,880 --> 00:21:38,400 a new partnership with Norwich University in Vermont, and they've 434 00:21:38,400 --> 00:21:41,599 got some just really smart faculty and smart people there 435 00:21:41,680 --> 00:21:44,279 that Elizabeth Gurri and Rachel Sickler that are going to 436 00:21:44,319 --> 00:21:46,799 take it to the next level. So right now we're 437 00:21:46,839 --> 00:21:49,480 going to be working with them and in Florida Golf 438 00:21:49,519 --> 00:21:51,720 Coast to try to bring this to the kind of 439 00:21:51,720 --> 00:21:54,319 the modern times as opposed to my spreadsheet. 440 00:21:56,200 --> 00:21:58,880 Speaker 2: Is there such a thing as a typical user, like 441 00:21:58,920 --> 00:22:02,359 what are some of the examples of things that people 442 00:22:02,440 --> 00:22:05,079 might do with the information and the database. 443 00:22:05,519 --> 00:22:08,319 Speaker 4: So the typical user is either going to be a 444 00:22:08,359 --> 00:22:11,279 college professor or a grad student working on, for example, 445 00:22:11,279 --> 00:22:14,240 a thesis or a dissertation that has a particular question 446 00:22:14,359 --> 00:22:16,720 in mind that they're trying to answer. So we'll provide 447 00:22:16,720 --> 00:22:20,039 the database to them and they will use what we 448 00:22:20,119 --> 00:22:23,599 have but also add new information. For example, if they're 449 00:22:23,599 --> 00:22:26,519 going to only be concentrated on one thing, for example, 450 00:22:26,880 --> 00:22:29,119 that they can maybe find things that we didn't because 451 00:22:29,160 --> 00:22:31,839 we're concentrated on so many different variables, and then we 452 00:22:31,880 --> 00:22:34,920 can add that to the database as well. We've had 453 00:22:35,039 --> 00:22:38,160 a few folks in law enforcement that have asked for it. 454 00:22:38,599 --> 00:22:41,039 We thought it would actually we'd get many more requests 455 00:22:41,039 --> 00:22:42,960 from law enforcement, but we haven't. 456 00:22:43,319 --> 00:22:45,599 Speaker 3: Is that because people don't know about it, or because 457 00:22:45,640 --> 00:22:48,319 they don't see how they can immediately relate that to 458 00:22:48,359 --> 00:22:49,359 the work that they're doing. 459 00:22:49,880 --> 00:22:51,960 Speaker 4: That's a good question. I think it's probably a mixture 460 00:22:51,960 --> 00:22:52,400 of both. 461 00:22:54,440 --> 00:22:57,160 Speaker 2: You're listening to Mind over Murder. We'll be right back 462 00:22:57,359 --> 00:23:15,279 after this word from our sponsors. We're back here at 463 00:23:15,319 --> 00:23:16,240 mindover Murder. 464 00:23:18,559 --> 00:23:21,720 Speaker 3: So when you hear about a new serial killer, like 465 00:23:21,920 --> 00:23:24,920 Allen Wade Wilmer Senior. We talked a little bit about 466 00:23:25,119 --> 00:23:27,920 some of the basic data that you can put into 467 00:23:27,960 --> 00:23:30,400 the database for them, so date of birth, so on 468 00:23:30,440 --> 00:23:33,119 and so forth. What other sort of information are you 469 00:23:33,200 --> 00:23:35,519 looking for when you add a new killer to the database. 470 00:23:35,960 --> 00:23:38,319 Would it benefit you, for example, to talk to an 471 00:23:38,319 --> 00:23:40,200 investigator that's worked on the case. 472 00:23:40,720 --> 00:23:44,720 Speaker 4: Would as long as it was data that we can publish. Again, 473 00:23:44,920 --> 00:23:47,519 so if we talked to an investigator said, now this 474 00:23:47,599 --> 00:23:49,400 is off the record, but that's not going to help 475 00:23:49,480 --> 00:23:53,720 us because we have to have things that are publicly available. 476 00:23:54,000 --> 00:23:57,039 Where I think it comes in handy or where information 477 00:23:57,119 --> 00:23:59,920 is to be helpful is when we added the victims section. 478 00:24:00,480 --> 00:24:04,039 We've added a lot of columns involving what went on 479 00:24:04,160 --> 00:24:07,279 at the actual murder site. For example, was a person bound, 480 00:24:07,519 --> 00:24:10,160 was their torture, was their overkill? And that can be 481 00:24:10,279 --> 00:24:12,920 really difficult information to get. But that some of that 482 00:24:12,960 --> 00:24:15,599 information is still very public. It's just maybe something we 483 00:24:15,640 --> 00:24:18,319 haven't come across, and so that's the type of information 484 00:24:18,440 --> 00:24:20,680 that would be helpful. A lot of that's just not 485 00:24:20,720 --> 00:24:23,279 available because they hold it back, or if there's not 486 00:24:23,480 --> 00:24:25,720 enough for a trial. For a trial, if there's not 487 00:24:25,759 --> 00:24:28,640 really an appeals. It doesn't show up very easily. To 488 00:24:28,960 --> 00:24:30,720 be able to read that, you'd have to be able 489 00:24:30,759 --> 00:24:33,359 to go get the original documents, and that's more work 490 00:24:33,400 --> 00:24:34,440 than eveninem willing to spend. 491 00:24:35,640 --> 00:24:38,400 Speaker 2: Is there a difference in what you feel you can 492 00:24:38,480 --> 00:24:41,440 put into the public record depending on whether or not 493 00:24:41,599 --> 00:24:45,400 a serial killer is alive or dead. For example, Alan 494 00:24:45,480 --> 00:24:50,279 Wade Wilmer Senior died in twenty seventeen. The FBI and 495 00:24:50,319 --> 00:24:53,880 the Hampton, Virginia Police Department have confirmed through DNA that 496 00:24:53,920 --> 00:24:56,960 he's responsible for the murder of at least three people, 497 00:24:57,000 --> 00:25:00,000 and they're looking into more. Kristin and I aren't terribly 498 00:25:00,160 --> 00:25:05,200 shy about using his name publicly and saying he's involved 499 00:25:05,359 --> 00:25:09,720 in these murders, whereas if someone's alive, maybe they're incarcerated. 500 00:25:09,759 --> 00:25:13,559 But are you as comfortable sharing data about their crimes? 501 00:25:13,960 --> 00:25:16,839 Speaker 4: I am? But the reason I am is because we 502 00:25:16,880 --> 00:25:19,920 have a column where we will label the person as, 503 00:25:19,920 --> 00:25:25,480 for example, serial suspected, serial accused, And so various researchers, 504 00:25:25,480 --> 00:25:27,400 for example, have made the decision they're only going to 505 00:25:27,480 --> 00:25:30,119 use those that have been convicted in their study that 506 00:25:30,839 --> 00:25:33,079 being accused of being suspected is not going to be enough. 507 00:25:33,400 --> 00:25:35,880 With that kind of hedge. We feel a little bit 508 00:25:35,920 --> 00:25:39,519 more comfortable where we're very careful and don't release to 509 00:25:39,759 --> 00:25:44,039 very many researchers is our victim data, because it might be, 510 00:25:44,119 --> 00:25:47,880 for example, that a particular victim was a prostitute, at 511 00:25:47,960 --> 00:25:50,079 least that's what the police labeled that person or the 512 00:25:50,079 --> 00:25:54,839 media labeled that person. And we've had instances where people said, 513 00:25:54,960 --> 00:25:57,039 I see in their database that so and so would 514 00:25:57,119 --> 00:25:59,640 kill prostitutes. Well, he killed my daughter and she wasn't 515 00:25:59,640 --> 00:26:03,119 a pute, and go back and look at the individual victims, 516 00:26:03,200 --> 00:26:05,440 and that's exactly right. Let's say eight of the nine 517 00:26:05,519 --> 00:26:09,119 were prostitutes that the one person actually wasn't. But when 518 00:26:09,119 --> 00:26:11,960 you're trying to define what's that person's basic motive or 519 00:26:12,000 --> 00:26:14,680 who are they killing, it was prostitutes. So I'm really 520 00:26:14,720 --> 00:26:17,799 gun shy about sharing victim data. For example, that would 521 00:26:17,799 --> 00:26:19,920 never go to a grad student. That would have to 522 00:26:19,920 --> 00:26:23,160 be to an academic that we trusted in that agreed 523 00:26:23,200 --> 00:26:24,440 to be very careful. 524 00:26:24,799 --> 00:26:27,400 Speaker 3: And if you have we have several people that we 525 00:26:27,440 --> 00:26:31,079 are close with in the community who have survived serial killers. 526 00:26:31,359 --> 00:26:33,759 If someone has survived an attacked by a serial killer, 527 00:26:33,839 --> 00:26:36,119 do they go into the victim database or is there 528 00:26:36,160 --> 00:26:38,640 like a whole separate set of data to go with that. 529 00:26:39,480 --> 00:26:42,359 Speaker 4: That's a great question. Right now, the only victims we 530 00:26:42,400 --> 00:26:45,079 have are ones that were killed first a serial killer. 531 00:26:45,079 --> 00:26:48,960 We might list them as, for example, two murders plus attempts, 532 00:26:49,279 --> 00:26:52,599 So it may be that they had three unsuccessful attempts. 533 00:26:53,079 --> 00:26:56,319 And we think that's important because again we find researchers 534 00:26:56,319 --> 00:26:58,720 don't feel comfortable with the FBI two or more. They 535 00:26:58,759 --> 00:27:00,960 want to maybe go three or four, and so they 536 00:27:01,000 --> 00:27:04,279 can then decide is two murders and two attempts enough 537 00:27:04,319 --> 00:27:05,240 for them to do that. 538 00:27:05,839 --> 00:27:07,640 Speaker 3: I want to get into some of the nitty gritty 539 00:27:07,720 --> 00:27:09,839 questions that I came up with as I was doing 540 00:27:09,920 --> 00:27:13,559 my deep dive into the data analysis here. So I'll 541 00:27:13,559 --> 00:27:15,680 start with something kind of general, and then we'll move 542 00:27:15,720 --> 00:27:18,680 into more specifics. What were some of the most interesting 543 00:27:18,759 --> 00:27:22,240 or surprising pieces of data that really stood out to 544 00:27:22,359 --> 00:27:26,240 you as you went and started combing over the database. 545 00:27:26,640 --> 00:27:29,720 Speaker 4: I think the biggest surprise, this is one I've mentioned previously, 546 00:27:29,960 --> 00:27:32,599 is that there's so many types of serial killers. We 547 00:27:32,640 --> 00:27:35,440 got just that one term that wasn't expecting to see 548 00:27:35,440 --> 00:27:38,119 that because when we started the database. That term was 549 00:27:38,880 --> 00:27:40,839 you conjure up like a Ted Bundy, that all of 550 00:27:40,839 --> 00:27:42,880 these serial killers we find are going to be Ted Bundy. 551 00:27:43,079 --> 00:27:46,079 They're not. And so that was the biggest surprise, and 552 00:27:46,079 --> 00:27:48,599 the thing I think that's complicated again some of the 553 00:27:48,680 --> 00:27:52,039 data analysis the most is until we really get these 554 00:27:52,119 --> 00:27:55,559 types figured out, these subtypes, we're not going to make 555 00:27:55,559 --> 00:27:58,319 as much progress as we wanted. Another thing I found 556 00:27:58,400 --> 00:28:02,519 that was surprising was how inaccurate that kind of common 557 00:28:02,559 --> 00:28:05,160 profile was. So the common profile is that it's a 558 00:28:05,200 --> 00:28:07,480 serial killer, was it's a white male in their mid 559 00:28:07,519 --> 00:28:10,480 to late twenties. So that profile, if you look to 560 00:28:10,480 --> 00:28:13,680 say it's nineteen ninety, it's seven percent fit that profile. 561 00:28:14,000 --> 00:28:16,160 That's not a much of a profile when it's seven 562 00:28:16,240 --> 00:28:17,079 years old. 563 00:28:16,880 --> 00:28:21,480 Speaker 2: And far from a general category that would fit most 564 00:28:21,480 --> 00:28:22,680 of the crimes committed. 565 00:28:23,079 --> 00:28:25,680 Speaker 4: Yeah, so that's one And one of the reasons I 566 00:28:25,720 --> 00:28:29,000 think that's particularly important is that you get somebody who 567 00:28:29,079 --> 00:28:32,440 might be, for example, fifty five years old and is black, 568 00:28:32,640 --> 00:28:34,119 and people would say that can't be one of our 569 00:28:34,160 --> 00:28:37,400 suspects because they don't fit the profile. Nobody fits your profile, 570 00:28:37,720 --> 00:28:40,440 so you have to be careful about about that. Another 571 00:28:40,480 --> 00:28:42,880 thing that I found really interesting was that there's a 572 00:28:42,960 --> 00:28:45,640 thought that a stereotype that serial killers are going to 573 00:28:45,680 --> 00:28:48,079 have a certain type of victim, So I'm only going 574 00:28:48,119 --> 00:28:49,559 to kill women, I'm only going to kill somebody with 575 00:28:49,599 --> 00:28:52,480 a certain race or age. Turns out that only thirty 576 00:28:52,519 --> 00:28:55,559 seven percent of serial killers kill people that are the 577 00:28:55,640 --> 00:28:58,640 same sex, the same race, the same age. And so again, 578 00:28:58,680 --> 00:29:02,079 if you're law enforcement and you're trying to determine, trying 579 00:29:02,079 --> 00:29:04,960 to link different murders, and he said, couldn't be this 580 00:29:05,359 --> 00:29:07,880 person couldn't be linked because they were shot as opposed 581 00:29:07,920 --> 00:29:10,359 to stab or this was a male and most of 582 00:29:10,400 --> 00:29:13,480 the victims are women. It turns out that linkage is 583 00:29:13,519 --> 00:29:15,440 just not there. And I think when you talked to 584 00:29:15,640 --> 00:29:18,079 Thomas Hargraved, he probably found this. He probably told you 585 00:29:18,160 --> 00:29:20,279 some of the same things. The linkage is a very 586 00:29:20,319 --> 00:29:21,839 difficult thing to do. 587 00:29:22,359 --> 00:29:26,920 Speaker 2: I was pushing back on this issue today regarding discussions 588 00:29:26,960 --> 00:29:30,200 in our social media pages on the Colonial Parkway murders. 589 00:29:31,000 --> 00:29:34,839 People are looking for patterns which may or may not 590 00:29:34,960 --> 00:29:37,880 be there. But for example, I've got several people and 591 00:29:37,920 --> 00:29:41,079 these are well meaning folks, are supporters of ours and 592 00:29:41,119 --> 00:29:43,880 are interested in these cases. But for instance, I've got 593 00:29:44,160 --> 00:29:47,599 several people insisting, Oh, it's very clear that Wilmer likes 594 00:29:47,880 --> 00:29:52,319 dark haired women. Yes, there are some victims with dark hair, 595 00:29:52,440 --> 00:29:55,839 but in the mix there's some blondes and redheads too. 596 00:29:56,200 --> 00:29:59,400 And he has killed both women and men, and he's 597 00:29:59,440 --> 00:30:03,880 killed there's one single woman and at least one straight couple. 598 00:30:04,240 --> 00:30:07,319 And he's suspected of killing a lesbian couple my sister 599 00:30:07,359 --> 00:30:10,119 and her girlfriend. Now that hasn't been proving yet, but 600 00:30:10,160 --> 00:30:13,920 my point is, boy, everybody wants to say this particular 601 00:30:14,079 --> 00:30:18,200 killer kills this particular kind of person in this way, 602 00:30:18,400 --> 00:30:21,759 and both Kristin and I are trying to respectfully push 603 00:30:21,839 --> 00:30:24,559 back on that because the profilers that we've met with 604 00:30:24,640 --> 00:30:27,400 and we've learned a lot and they're fascinating people. 605 00:30:27,440 --> 00:30:27,920 Speaker 3: Oh my gosh. 606 00:30:28,000 --> 00:30:32,400 Speaker 2: Yeah, it's been so interesting for us to have opportunities 607 00:30:32,400 --> 00:30:35,200 to sit down with these folks, both on and off 608 00:30:35,240 --> 00:30:38,079 the air. They're saying the same thing that you are, Mike, 609 00:30:38,160 --> 00:30:41,799 which is that we can't keep insisting that serial killers 610 00:30:41,920 --> 00:30:44,359 kill the same type of victim in the same type 611 00:30:44,359 --> 00:30:48,279 of way under the same circumstances. That just doesn't seem 612 00:30:48,319 --> 00:30:51,839 to be anything close to the way profilers in twenty 613 00:30:51,960 --> 00:30:53,759 twenty four are seeing things. 614 00:30:54,160 --> 00:30:56,680 Speaker 4: I agree completely, and that's the problem though, when you 615 00:30:56,720 --> 00:30:59,559 have something that was published at say, thirty forty years ago, 616 00:31:00,160 --> 00:31:03,720 it doesn't go away, It just keeps it hangs on, 617 00:31:03,839 --> 00:31:05,960 regardless of what the kind of the current facts are. 618 00:31:06,640 --> 00:31:09,480 Speaker 3: It makes something else that I found very interesting, And 619 00:31:09,680 --> 00:31:14,279 I'm wondering if some of this question can be answered 620 00:31:14,359 --> 00:31:17,920 by the idea that maybe there just wasn't enough reporting 621 00:31:18,000 --> 00:31:21,519 going on during these decades. There is a massive jump 622 00:31:21,559 --> 00:31:25,240 in the number of serial killers between nineteen fifty and 623 00:31:25,559 --> 00:31:29,400 nineteen eighty. You went from ninety active serial killers in 624 00:31:29,480 --> 00:31:32,119 nineteen fifty to sixty to two hundred and fifty one 625 00:31:32,319 --> 00:31:34,920 to six hundred seventy to eight hundred and twenty three 626 00:31:35,160 --> 00:31:38,400 in nineteen eighty. Is that a reporting issue or were 627 00:31:38,400 --> 00:31:40,920 there really just a massive jump in the number of 628 00:31:40,920 --> 00:31:43,319 serial killers in this country in those decades. 629 00:31:44,000 --> 00:31:46,839 Speaker 4: I think a big part of it a reporting issue. 630 00:31:47,119 --> 00:31:49,920 So the term serial killer was coined depends on who 631 00:31:50,000 --> 00:31:52,000 you believe, but was coined in for the most part 632 00:31:52,000 --> 00:31:54,720 in the nineteen seventies. So if you're doing a search 633 00:31:54,759 --> 00:31:57,359 for serial kill like using the term serial killer, you're 634 00:31:57,359 --> 00:31:59,200 not going to pop up with something in the nineteen 635 00:31:59,200 --> 00:32:02,319 fifties or sixty So you have to look for headlines 636 00:32:02,359 --> 00:32:05,839 that might be killed two, killed three, and so we 637 00:32:06,400 --> 00:32:08,279 meticulously go through when you use all those kind of 638 00:32:08,319 --> 00:32:11,440 combinations to try to find those. Now, it makes sense 639 00:32:11,480 --> 00:32:15,680 that serial killers means would rise in the fifties, sixties, 640 00:32:15,680 --> 00:32:18,720 and seventies because the interstate system, there's more access to 641 00:32:18,759 --> 00:32:21,640 the country, and if they're killing in different states, it's 642 00:32:21,640 --> 00:32:24,519 more difficult to perhaps to be to be identified and caught. 643 00:32:24,599 --> 00:32:28,200 But I think so much of it is a reporting issue. 644 00:32:27,880 --> 00:32:31,119 Speaker 3: That definitely makes sense. I'm writing that down about the 645 00:32:31,119 --> 00:32:34,039 interstate system because that is not something that I had 646 00:32:34,319 --> 00:32:37,559 previously thought of. It was interesting to think about the 647 00:32:37,559 --> 00:32:40,640 ways that the country was changing during those time periods 648 00:32:40,799 --> 00:32:43,880 that might lead to those numbers changing. I'm making sure 649 00:32:43,920 --> 00:32:46,440 i'm putting that down. I guess in the same sort 650 00:32:46,440 --> 00:32:49,079 of vein why is it that the numbers of serial 651 00:32:49,160 --> 00:32:52,839 killers have trended steadily downwards since nineteen eighty Is that 652 00:32:52,920 --> 00:32:56,440 because law enforcement is getting better at tracking them in 653 00:32:56,480 --> 00:33:00,400 solving cases. Is it just that maybe serial killers are 654 00:33:00,400 --> 00:33:02,359 getting a little tired and taking a break and going 655 00:33:02,359 --> 00:33:03,160 into retirement. 656 00:33:04,599 --> 00:33:07,680 Speaker 4: I think there's several things that are going on there. 657 00:33:07,839 --> 00:33:10,359 One is certainly the law enforcement's gotten better in terms 658 00:33:10,400 --> 00:33:12,640 of things like DNA being able to link murder, so 659 00:33:12,720 --> 00:33:15,279 that's certainly part of it. Technology, though, I think, is 660 00:33:15,319 --> 00:33:18,200 another one of those things that has changed. For example, 661 00:33:18,440 --> 00:33:21,599 if you think about serial killers that are black widows, 662 00:33:21,720 --> 00:33:25,240 so those are predominantly women who kill spouses for usually 663 00:33:25,240 --> 00:33:27,359 for money, but there are other reasons as well. If 664 00:33:27,400 --> 00:33:29,759 you go back to for example, nineteen twenty or nineteen thirty, 665 00:33:29,880 --> 00:33:32,240 somebody could kill a spouse, move to another state, kill 666 00:33:32,240 --> 00:33:35,319 a spouse, still get the insurance money. Where today all 667 00:33:35,480 --> 00:33:38,680 these computers are, the databases are linked, it would be 668 00:33:38,799 --> 00:33:41,440 very difficult to try to get insurance on a third 669 00:33:41,440 --> 00:33:45,599 spouse that was mysteriously killed. So I think the technology 670 00:33:45,680 --> 00:33:48,359 is there. When you think about hospitals, serial killers who 671 00:33:48,440 --> 00:33:50,960 kill their patients, the software is out there now that 672 00:33:51,440 --> 00:33:54,440 you have expected death rates for every type of illness, 673 00:33:54,720 --> 00:33:58,279 and when those death rates exceed a certain level, it's flagged. 674 00:33:58,440 --> 00:34:00,440 So those are some of the reasons. But I think 675 00:34:00,440 --> 00:34:05,119 there's really two main reasons that are responsible for this decline. 676 00:34:05,559 --> 00:34:08,519 One is change in parole. If you look at the 677 00:34:08,559 --> 00:34:11,039 seventies and eighties, for example, where the serial killer rates 678 00:34:11,039 --> 00:34:14,000 were highest, there was a lot of pressure to parole people. 679 00:34:14,119 --> 00:34:16,639 The prisons were overcrowded, there was kind of a movement 680 00:34:16,679 --> 00:34:19,760 toward prison reform, So we're releasing people then that would 681 00:34:19,840 --> 00:34:23,119 maybe become serial killers. An interesting fact is that in 682 00:34:23,159 --> 00:34:26,840 our database, eighteen percent of the serial killers in our 683 00:34:26,920 --> 00:34:31,280 database had killed, gone to prison and been released. And 684 00:34:31,360 --> 00:34:35,480 so if you are more strict on parole, I think 685 00:34:35,519 --> 00:34:38,440 that's one of the reasons people which we are these days. 686 00:34:38,960 --> 00:34:42,639 I think that is one of the explanations. And the 687 00:34:42,719 --> 00:34:46,920 other one is there are just fewer high risk behaviors 688 00:34:46,920 --> 00:34:49,559 that people engage in today. So when I think about 689 00:34:49,599 --> 00:34:52,440 when I was growing up, I rode my bike everywhere, 690 00:34:52,920 --> 00:34:58,000 I hitchhiked, I picked up hitchhikers, I walked to elementary school. Today, 691 00:34:58,360 --> 00:34:59,719 there are no parents that are going to let you 692 00:34:59,760 --> 00:35:02,199 do that. There are very few people who would hitchhikers 693 00:35:02,360 --> 00:35:05,719 hitch hikers. And so we did an analysis of comparing 694 00:35:05,760 --> 00:35:08,960 in the seventies and eighties the percentage of murders that 695 00:35:09,000 --> 00:35:12,880 were serial killers, serial murders that were of high risk 696 00:35:12,920 --> 00:35:15,760 behaviors such as hitch hiking, and helping people who with 697 00:35:15,840 --> 00:35:19,320 stranded motorists with the ones from the last two decades, 698 00:35:19,639 --> 00:35:22,519 and there's such a drop. It's a huge drop. And 699 00:35:22,599 --> 00:35:25,559 when you think about cell phones, thirty years ago, if 700 00:35:25,599 --> 00:35:27,519 your car broke down, you'd either have to get in 701 00:35:27,519 --> 00:35:29,360 a car with somebody or have them go to the 702 00:35:29,400 --> 00:35:32,119 gas station to use a payphone. Now you're not going 703 00:35:32,159 --> 00:35:33,880 to let anybody in your car. You're not going to 704 00:35:33,920 --> 00:35:35,360 get in their car. You're going to use your cell 705 00:35:35,360 --> 00:35:37,159 phone call for help. And so I think a lot 706 00:35:37,199 --> 00:35:39,639 of those high risk behaviors have changed. 707 00:35:40,159 --> 00:35:42,599 Speaker 2: A few days ago, my partner Pamela and I were 708 00:35:42,639 --> 00:35:45,079 driving along the country road and there was a pickup 709 00:35:45,119 --> 00:35:47,960 truck parked next to the road on this kind of straight, 710 00:35:48,039 --> 00:35:51,039 quiet stretch. The hazard drawn on and we didn't see 711 00:35:51,039 --> 00:35:54,079 anybody in the vehicle. But then a couple one hundred 712 00:35:54,159 --> 00:35:58,000 yards down the road, and this is wintertime, snowy and cold, 713 00:35:58,360 --> 00:36:01,880 there's a woman walking along on the road. We stopped. 714 00:36:02,000 --> 00:36:05,679 I tried to let Haamla be visible, so she leaned forward. 715 00:36:05,719 --> 00:36:08,920 But we just stopped briefly to ask if the woman 716 00:36:09,079 --> 00:36:12,400 was all right, and she smiled and said she was, 717 00:36:12,480 --> 00:36:14,400 and it looked like she was actually out for a 718 00:36:14,440 --> 00:36:17,880 walk and I'm not even sure that was her truck. Necessarily, 719 00:36:18,039 --> 00:36:19,679 she told us she was fine and she was just 720 00:36:19,760 --> 00:36:23,000 out for a walk on a beautiful winter day. We 721 00:36:23,039 --> 00:36:25,239 just wanted to make certain that she wasn't out there 722 00:36:25,239 --> 00:36:28,800 in the boonies without a cell phone or whatever. So 723 00:36:28,880 --> 00:36:32,000 she smiled, and she seemed accepting of the fact that 724 00:36:32,159 --> 00:36:35,840 we'd made this offer of assistance. In listening to you 725 00:36:36,000 --> 00:36:39,400 just now, Mike, I'm thinking maybe that's increasingly rare. 726 00:36:40,039 --> 00:36:40,679 Speaker 4: I think it is. 727 00:36:41,280 --> 00:36:45,800 Speaker 3: Yeah. Absolutely. Do you have enough information yet to draw 728 00:36:45,920 --> 00:36:50,199 any conclusions on how the pandemic affected the number and 729 00:36:50,320 --> 00:36:53,360 type of serial killers? I realized we're really barely out 730 00:36:53,360 --> 00:36:56,119 of the pandemic. Has there been any information that you 731 00:36:56,159 --> 00:36:59,800 can lean about how that affected serial killers? And there 732 00:36:59,800 --> 00:37:01,360 are activities. 733 00:37:01,239 --> 00:37:03,800 Speaker 4: Not at this point. One reason would be is that 734 00:37:03,840 --> 00:37:06,719 there have not really been a lot of serial murders 735 00:37:06,760 --> 00:37:08,920 over the last few years, which is a good thing, 736 00:37:09,480 --> 00:37:11,760 but it's a bad thing for data, so it would 737 00:37:11,840 --> 00:37:14,800 be difficult to do that. There's a lag period really 738 00:37:14,840 --> 00:37:19,119 between oftentimes the serial killings and then when they're arrested 739 00:37:19,159 --> 00:37:21,840 and whether it gets announced. So I would say it'll 740 00:37:21,840 --> 00:37:23,719 be at least a decade before we could start to 741 00:37:23,760 --> 00:37:24,679 address that question. 742 00:37:25,000 --> 00:37:28,599 Speaker 3: Oh wow, Okay, that does make sense though. Absolutely. 743 00:37:29,239 --> 00:37:33,960 Speaker 2: Do you feel like the advances in forensic technology and 744 00:37:34,400 --> 00:37:36,920 manly the things we've talked about over the last few 745 00:37:36,960 --> 00:37:41,760 minutes have discouraged people who might have exhibited these behaviors 746 00:37:41,840 --> 00:37:42,480 in the past. 747 00:37:42,840 --> 00:37:46,519 Speaker 4: That's a great question, and I've had those conversations with colleagues, 748 00:37:46,880 --> 00:37:49,800 and my initial response to you is, I don't know, 749 00:37:50,239 --> 00:37:52,719 because it can go both ways, right. It can be 750 00:37:53,000 --> 00:37:55,440 now that I know what these advances and forensics are, 751 00:37:55,880 --> 00:37:58,719 I'm going to avoid leaving fingerprints. I'm going to avoid 752 00:37:59,159 --> 00:38:01,800 leaving DnaB and so it could be to encourage some 753 00:38:02,039 --> 00:38:04,519 that think that they can avoid it, or for some 754 00:38:04,599 --> 00:38:06,519 of them, it may be They're going to catch me, 755 00:38:06,679 --> 00:38:09,199 so I'm not going to do it. And that would depend, 756 00:38:09,199 --> 00:38:11,559 I think on the again, like the subtype of serial killer, 757 00:38:11,599 --> 00:38:13,159 because there are going to be some killers that they 758 00:38:13,159 --> 00:38:15,119 haven't need to kill, and they're going to probably kill 759 00:38:15,239 --> 00:38:17,320 no matter what. But I think some of these ones 760 00:38:17,360 --> 00:38:20,480 that maybe kill for financial gain that may have slown 761 00:38:20,519 --> 00:38:21,599 that pace down a little bit. 762 00:38:22,159 --> 00:38:24,599 Speaker 3: Just occurred to me when you were talking earlier about 763 00:38:24,639 --> 00:38:28,400 subdividing different types of killers. Are you eventually going to 764 00:38:28,440 --> 00:38:32,599 have a different database for mass shooters and spree shooters. 765 00:38:32,679 --> 00:38:34,559 Is that going to become a whole separate database or 766 00:38:34,559 --> 00:38:36,880 are they just going to exist on the serial killer database? 767 00:38:37,239 --> 00:38:39,480 Speaker 4: Yeah, they don't exist. The mass killers don't exist in 768 00:38:39,480 --> 00:38:40,119 our database. 769 00:38:40,159 --> 00:38:41,400 Speaker 3: Oh they don't, Okay, don't. 770 00:38:41,679 --> 00:38:44,719 Speaker 4: And I know that there are several researchers that have 771 00:38:44,880 --> 00:38:47,960 developed databases on mass killers, and so I think that's 772 00:38:48,079 --> 00:38:51,039 well taken care of by some other folks. The one 773 00:38:51,039 --> 00:38:54,480 that was more difficult for spree killers because again with 774 00:38:54,559 --> 00:38:57,440 the FBI basically said that they don't really distinguish between 775 00:38:57,480 --> 00:39:00,760 cereal and spree in terms of the motives and those 776 00:39:00,800 --> 00:39:04,599 types of things, and so we will include those but 777 00:39:04,719 --> 00:39:07,559 labeled them as within our database as spree and again, 778 00:39:07,639 --> 00:39:10,400 researchers can make their own decision about whether they want 779 00:39:10,400 --> 00:39:11,760 to include them or not. One of the things we've 780 00:39:11,760 --> 00:39:14,679 tried to do is be overly inclusive and then let 781 00:39:14,719 --> 00:39:17,440 researchers who use the database make their decisions about who 782 00:39:17,480 --> 00:39:19,159 stays and who goes, and whether they have to have 783 00:39:19,199 --> 00:39:20,400 a certain type of motive or not. 784 00:39:20,920 --> 00:39:23,519 Speaker 2: Do you know if any serial killers who are currently 785 00:39:23,519 --> 00:39:28,320 incarcerated have ever been permitted to access the database. I 786 00:39:28,400 --> 00:39:30,880 know that there are people that are currently incarcerated that 787 00:39:30,960 --> 00:39:34,639 do have internet access that actually have made use of 788 00:39:34,679 --> 00:39:37,480 their time, but I didn't know if they ever had 789 00:39:37,719 --> 00:39:40,440 looked themselves or other people up in the database. 790 00:39:40,840 --> 00:39:42,480 Speaker 4: To have access, they would have had to make a 791 00:39:42,480 --> 00:39:45,840 formal request, and if we saw, for example, that it 792 00:39:45,920 --> 00:39:49,000 was coming from a prison, it would be declined. But 793 00:39:49,079 --> 00:39:51,000 it doesn't mean that again that they don't can't get 794 00:39:51,000 --> 00:39:54,000 somebody else to request it for them. I've noticed that 795 00:39:54,119 --> 00:39:57,159 I've had several requests from students where I've said, yeah, 796 00:39:57,360 --> 00:39:59,880 we'll give you this part of the database. Here's the condition, 797 00:40:00,559 --> 00:40:02,679 So you need to agree to those and please copy 798 00:40:02,719 --> 00:40:05,320 your advisor on the email and the way I can 799 00:40:05,320 --> 00:40:07,679 look up the advisor make sure they exist. I've had 800 00:40:07,719 --> 00:40:10,480 several times where the student didn't get back. I thought, yes, 801 00:40:10,559 --> 00:40:12,320 because it's not for a class project. 802 00:40:12,599 --> 00:40:14,599 Speaker 3: That must mean you have people trying to access the 803 00:40:14,679 --> 00:40:17,920 database just for I'm interested in serial killers, but not 804 00:40:18,000 --> 00:40:18,960 in an academic way. 805 00:40:19,440 --> 00:40:21,480 Speaker 4: What we do and the one where I struggle with 806 00:40:21,519 --> 00:40:24,079 now is I get requests from students who are in 807 00:40:24,360 --> 00:40:27,960 data science programs, so they need a database to be 808 00:40:28,000 --> 00:40:31,079 able to do a class project for data science, and 809 00:40:31,119 --> 00:40:33,599 they think serial killers are interesting, but they're not really 810 00:40:33,599 --> 00:40:36,840 trying to study serial killers. And so in those situations, 811 00:40:36,880 --> 00:40:39,719 I'll usually ask them what fields do you want and 812 00:40:39,719 --> 00:40:42,400 give them maybe a smaller number of fields. We don't 813 00:40:42,440 --> 00:40:44,159 give them the whole thing, and then I don't give 814 00:40:44,159 --> 00:40:46,159 them the names of the serial killers. That way they 815 00:40:46,159 --> 00:40:48,880 can run their data and not worry about privacy aspects. 816 00:40:49,559 --> 00:40:52,559 Speaker 3: Mike, what can we do to help you with data 817 00:40:52,599 --> 00:40:56,599 on Alan Wade Wilmer Senior so that we can round 818 00:40:56,639 --> 00:40:59,039 out his entry in your database. We want to give 819 00:40:59,079 --> 00:41:01,599 you as much help as possible because obviously we have 820 00:41:01,679 --> 00:41:04,760 invested interest in his activities. So tell us how we 821 00:41:04,800 --> 00:41:06,679 can help you. We would love to be able. 822 00:41:06,440 --> 00:41:09,920 Speaker 4: To that's and I appreciate that. Probably the easiest thing 823 00:41:09,960 --> 00:41:12,760 would be if I sent you both the victim and 824 00:41:12,880 --> 00:41:15,840 the serial killer data that we already have. Have you 825 00:41:15,840 --> 00:41:17,760 take a look to see if there are fields that 826 00:41:17,800 --> 00:41:19,880 you can fill in that I have blank, and that 827 00:41:19,920 --> 00:41:21,960 would be great perfect. 828 00:41:22,239 --> 00:41:23,719 Speaker 3: We would love to be able to help in any 829 00:41:23,719 --> 00:41:24,599 way we can on that. 830 00:41:25,360 --> 00:41:26,000 Speaker 4: How long do you. 831 00:41:25,960 --> 00:41:28,960 Speaker 3: See yourself continuing to do work on the databasis? Is 832 00:41:29,000 --> 00:41:31,119 just going to be an all the time thing or 833 00:41:31,280 --> 00:41:33,360 is this your baby and you're invested in it. 834 00:41:33,360 --> 00:41:35,760 Speaker 4: It's my baby and I'm invested in it, so I 835 00:41:35,760 --> 00:41:38,039 will all continue to do it. But I think that's 836 00:41:38,119 --> 00:41:41,199 why the kind of the relationships or the partnerships with 837 00:41:41,280 --> 00:41:44,280 Florida Gulf Coast and Norwich are important because they can 838 00:41:44,280 --> 00:41:46,920 take it to a different level. So I'm going to 839 00:41:47,000 --> 00:41:49,480 still work on it because it's fun. It's like being 840 00:41:49,519 --> 00:41:52,000 a little detective. And it's terrible when you get excited 841 00:41:52,039 --> 00:41:55,360 because you found a birth date, but it makes my day, 842 00:41:55,400 --> 00:41:58,679 and so I'll continue to do that even after I retire. 843 00:41:58,960 --> 00:42:01,679 But I think that again, with those two universities, they're 844 00:42:01,679 --> 00:42:03,119 going to take it to that next level. 845 00:42:03,840 --> 00:42:08,440 Speaker 3: Doctor Mike ah Mottz, formerly of Redford University, the inventor, 846 00:42:08,519 --> 00:42:11,280 shall I say, of the Radford University of Florida Gulf 847 00:42:11,280 --> 00:42:14,840 Coast University serial Killer Research Database. Mike, thank you so 848 00:42:14,920 --> 00:42:18,559 much for joining us today and lending us your considerable expertise. 849 00:42:18,599 --> 00:42:19,320 We appreciate it. 850 00:42:19,519 --> 00:42:21,360 Speaker 4: Oh, I enjoyed it. It was great to meet both 851 00:42:21,400 --> 00:42:21,559 of you. 852 00:42:21,960 --> 00:42:23,800 Speaker 3: Thank you so much. That is going to do it 853 00:42:23,840 --> 00:42:26,199 for this episode of Mind over Murder. Thank you so 854 00:42:26,280 --> 00:42:28,280 much for listening. We'll see you next time. 855 00:42:37,800 --> 00:42:41,320 Speaker 1: Mind Over Murder is a production of Absolute Zero and 856 00:42:41,400 --> 00:42:42,840 Another Dog Productions. 857 00:42:43,400 --> 00:42:46,719 Speaker 2: Our executive producers are Bill Thomas and Kristin Dilley. 858 00:42:47,079 --> 00:42:49,480 Speaker 1: Our logo art is by Pamela Arnois. 859 00:42:50,159 --> 00:42:52,239 Speaker 2: Our theme music is by Kevin McLeod. 860 00:42:52,760 --> 00:42:56,760 Speaker 1: Mind Over Murder is distributed in partnership with crawl Space Media. 861 00:42:57,440 --> 00:43:00,599 Speaker 2: You can follow us on Facebook, Twitter, or in Instagram. 862 00:43:00,760 --> 00:43:03,360 Speaker 1: You can also follow our page on the Colonial Parkway 863 00:43:03,440 --> 00:43:05,239 Murders on Facebook. 864 00:43:05,039 --> 00:43:08,039 Speaker 2: And finally, you can follow Bill Thomas on Twitter at 865 00:43:08,119 --> 00:43:09,719 Bill Thomas. Five six. 866 00:43:10,199 --> 00:43:13,320 Speaker 1: Thank you for listening to mind Over Murder.