LPRC - CrimeScience Episode 68 – Dr. Aili Malm

Episode Date: August 16, 2021

On this episode of CrimeScience we talk with Cal State Long Beach Criminologist Dr. Aili Malm on social networking analysis or SNA to create more focused and efficacious crime control. Leveraging SNA to potentially build better bonds with community influencers to boost citizen appreciation and cooperation. Dr Malm and Dr Hayes also discuss social networks and offending, the CLOAK DAGGER concept, and how they play into better protecting retail and other places. The post CrimeScience Episode 68 – Dr. Aili Malm appeared first on Loss Prevention Research Council.

Hi, everyone, and welcome to Crime Science. In this podcast, we explore the science of crime and the practical application of this science for loss prevention and asset protection practitioners, as well as other professionals. We would like to thank Bosch for making this episode possible. Take advantage of the advanced video capabilities offered by Bosch to help reduce your shrink risk. Integrate video recordings with point-of-s sale data for visual verification of transactions and exception reporting. Use video analytics for immediate notification of important AP related events and leverage analytics metadata for fast forensic searches for evidence and to

improve merchandising and operations. Learn more about extending your video system beyond simple surveillance in zones one through four of LPRC's zones of influence by visiting Bosch online at boschsecurity.com. Welcome everybody to another episode of Crime Science Podcast. Today we're joined by Dr. Eileen Maum, Professor of Criminology and Criminal Justice at Cal State, California State University, Long Beach. And we thought we'd try and spend a little time Beach. And we thought we'd try and spend a little time with Dr. Mom, with Eileen, and talking about a few neat things that she's involved in that she's helped start and grow. And so, Eileen, welcome to Crime Science. No, well, thank you for having me, Reed. All right. So maybe this, if we really do this well, it might end up this episode on Crimcom. So let's talk a little bit about Crimcom.

Tell us a little bit about the genesis, you know, obviously the objectives. What are you guys trying to do? How did this start? Where are we right now and where are you guys taking this? You know, as Crimcom is the perfect example of why networks matter. And I know we're going to be talking about networks here, but I got an ominous email from Laura Huey, who I go back, Laura and I did our undergraduates together

at Simon Fraser University. And she said, can I call you? And whenever Laura says, can I call you? You know, it's going to be something that's going to be amazing, but it's going to be a lot of work. So Laura gave me a call and she said, you know, I'm really ready for a new challenge. I'm thinking about this idea of a

criminology version of SciComm. And I'm not sure if you're too familiar in SciComm, but SciComm's been around for a while now and it's express purposes to get, make science understandable and fun. So to make research, get research into hands of the people that really need it, the policymakers, the practitioners, and just make it easily understandable. So that's what we want to do with criminology research, is get it out from behind the journal paywalls, get it into the hands of practitioners, into policymakers that can actually make a difference,

and to give voice to the people doing the research so that they're not just churning out, you know, article after article after article, but they're actually putting it into mediums that people can understand. And they can look in 30 seconds and say, this is a really neat study. I think it might inform some of the work that I'm doing

on the practitioner policy level. Yeah, it's fantastic because we know that I think at might inform some of the work that I'm doing on the practitioner policy level. Yeah, it's fantastic because we know that I think at the end of the day, we would all like to have an effect on the practitioners and the policymakers. And that means they need some good evidence, some logic models around the evidence. But as you're describing, access to all this great work, but access to the work in a way that's readily understandable and transmissible, I guess. And that sounds like that's it. Yeah. How often have you, you know, I'm on Twitter a lot and I tweet about my research and it's so frustrating when you get a policymaker or practitioner saying, I can't access it. Can you send me a copy?

And of course, I'm going to send them a copy. But it is really frustrating that they don't have more ready access to information that could really help inform what they're trying to do. Yeah, perfect. Yep. Influencing the influencers. So and that's really been a big part of our group for 20 years now. And that's to this S2P, right?

Science to Practice. But how do you do it? It sounds easy and it's like everything else. It's not. So I really applaud you and we're excited about it. And I see on Twitter and I hear it all the time, the same thing. How do I read this? But we also know even if they can get behind paywalls, it's really difficult to get beyond the abstract of a journal

article, right? It is. I mean, gosh, I've been victim of this as well in some of my early work, just using too much jargon, talking like an academic because you think that's the way that we should talk, just trying to talk to sound important, to sound smart, rather than to speak to be understood. And it's taken me years to really wrap my head around that and to make my writing much more accessible than it used to be. Yeah, it's almost, don't try this at home, but you know, don't run with sharp objects, right? Actually, it's the opposite. So, good. So that's a little bit about Crimcom.

How do, any advice, how does someone find Crimcom? How does someone participate in Crimcom? Well, we've got a website called crimcom.net. And it's, you know, it just has a bunch of resources for blogs and YouTube videos and TikToks and how to do these things, how to better make your research accessible. But what's really going to be the success of this program is getting all criminologists to participate. So we don't, we're, Laura and I don't want to be creating all the content. We want you to create the content. Give us an interesting TikTok you've done. If you've made a GIF about a recent article that you've published, send it to

us. We'll tweet about it. We'll put it on the website. We'll get it out there as much as we can. So what we're hoping to do is just increase visibility and to, you know, just give people's research a boost. So that's fantastic. So we want to put this out there and encourage everybody to do what you're saying, not only access and use, harness, leverage, um, crimcom, but, uh, if you're a practitioner or a policymaker, but also if you're a criminologist or researcher, um, to get that out there, um,

as well and to expose others to what you're up to besides the narrow groups that are able to and actually do read the entire article that you're putting out there. So we're all about that. So let me, if we could switch gears a little bit, evidence-based practice. It's been around for, we know, since the fifties in medicine, my father and grandfather being physicians, I grew up looking at these journals, reading them, believe it or not, or parts of them anyway, and listening to these horrific tapes everywhere we rode around in his car and so on with my dad. But I get it, you I, and so that's been our mantra for 20 years now is we've tried to help move the loss prevention and asset protection community. And they're large and they're global. And as you know, I mean, every store, everything weird that happens, happens in a retail property or environment, everything. happens in a retail property or environment, everything. And so evidence-based practice has been great. So I wanted to get an idea, what does it mean to you, evidence-based strategy

and evidence-based action? And how can CRIMCOM help? How can all of us help the practitioner and policymaker move to a little more of an evidence-based model? and policymaker move to a little more of an evidence-based model? I mean, evidence-based in general, it just means using evidence to inform what you're doing and constantly evaluating. So just because you have one piece of evidence that shows that something that you're doing worked in one context doesn't necessarily mean it's going to work where you are. And that could be in a retail outfit, or it could be in a city with a police department. So it's understanding what the evidence is telling us, where it's worked, when it's worked, why it's worked, and when it hasn't worked,

but also constant evaluation. So being able to say, this worked in Philadelphia, is it going to work in Long Beach? Being able to constantly monitor a program, not only through an outcome evaluation, I don't want to throw out all this jargon right now, but not only seeing if it does reduce crime, which is usually our ultimate outcome for as criminologists, but also doing really in-depth policy evaluations. So going in and saying, this is how the program or this is how the policy was implemented. And this is what was good about the implementation, or this is where the implementation fell apart. I have a, I'm just involved in so many different programs at the moment, different evaluations. I think my mind is stretched in so many different directions, but one of the sort of linking the threads that goes through all of my

evaluations is making sure that I'm not only measuring impact, but I'm measuring process. Because if you don't keep track of how the program is implemented, you're never going to know why it fails or why it succeeds. That's great advice. It's huge. And I think it kind of leads me to my next question or thought anyway, discussion point. And that is, I believe in evidence-based, clearly, I even like the term a lot, but it does sort of assume evidence that there's been some systematic observation, hopefully fairly rigorous. And then it did something, it maybe confirmed or didn't what we were hoping or thought, or somebody else thought. But it almost so leaves out the other part of the scientific method that the logic, the logic model, you know, and even the mechanisms of action and things like that.

And I just want to kind of run that by you, particularly because, as you and I know, there's not a lot of evidence-based anything out there in our discipline. On the one hand, there have been hundreds or thousands of studies done. Most of the research, the research it seems like in criminology are secondary data sets, and that's helpful. That's directional, that gives us some good hypotheses, but it's not experimental. It's not a lot of evidence around like you're talking about to help us understand the outcome measures and how come they did or didn't come about. Any thoughts on that? And I'm not advocating for a better way to say it than evidence-based,

but it does seem to preclude that. Yeah, no, I think that's a really, really good point. And boy, this area of realistic evaluation has been pushed in the UK, probably more so in the US. but this idea that, and you mentioned mechanism, this idea that we have to understand that context is all important. So you have to understand that you're going to have impacts or you're not, but they could be different in different contexts. And as long as you've got some reason to believe that there's a mechanism for change, too often, I think as evaluators and researchers and absolutely too often as policymakers, we just jumped straight to the outputs, right? Did it affect the outputs?

Did it affect the outcome? Without really thinking through why it would affect the outcome, what are the mechanisms? You mentioned secondary data sets, and that's where the majority of the published research in our field has been. And I agree, we haven't had enough evaluation research. We need more. But where some of that theoretical work that relies on secondary data sets is really important is getting at the mechanism. I'll give you an example. I do a ton of research and there's been a ton of research done in body-worn cameras and probably more body-worn camera research than any other evaluation research in the last five or six years in criminology. We've seen upwards of,

you know, 80 or 90 articles now coming out about it and some of them really rigorous, randomized controlled trials. And we're seeing, you know, that the research is pushing us in one direction. It's showing us that for the most part, we're seeing some beneficial impacts of body warm cameras in certain outputs like use of force or complaints, but there's no absolutes. And some agencies, huge ones like Washington, DC, we saw absolutely no impact at all of body-worn cameras. Well, why is that? And that's where we have to go back to what you're talking about, back to the context and really back to the mechanism. Why do we think body-worn cameras are going to impact an outcome like complaints or like use of force?

And if you don't have a clear idea of what that mechanism is, you might lose something in implementation. So you might, if you think that the mechanism of body-worn cameras is that, you know, people are, officers are going to behave better if they know that they're going to be watched. Officers are going to behave better if they know that they're going to be watched. And on the other side of it, citizens might behave better because they know that they're being watched or that they're being recorded. Well, that mechanism, if true, relies on a few implementation practices, doesn't it? It relies on the officer turning their camera on. It relies on the citizen knowing that they're being recorded. And it relies on the fact that there's going to be some kind of back-end accountability. If the camera wasn't

turned on, what did the police department do about it? Anything? Did they, you know, was there an enforcement procedure for enforcing certain policies and practices. That outcome evaluation can have very, very different results depending on what you think the mechanism of action is and how all of those moderators, they're called in sort of this realistic evaluation framework, how the moderators are implemented in your program. Fantastic. That was just what I was looking for and I appreciate it. And it's been probably the biggest area that I know our team's worked on. You can imagine it's trying to understand the modes of action. In that case, we're just using situational crime prevention. Does it increase effort or reduce potential reward or increase potential risk of some kind of sanction, formal or informal?

But then with those types of mechanisms that are going on, dig deeper and deeper. But then also on the marketing of those, and we think that's part of it. And I was listening to you. I love the body-worn camera research that you and others are doing. And, and there's actually a push in retail to use it, not only for the asset protection person, that's maybe having to confront somebody because they're running around without a mask on and intimidating people, or of course they're stealing or other, other types of deviance there, but on customer service on store managers and so on too. And also for training use. But, but are the marketing pieces, how do we get the would be offender not to initiate their crime attempt? And okay,

how do they notice this body worn camera or this fixed camera or whatever it is? How do we get them to notice it? Since they're mostly staring at phones now or whatever they're doing zoned out, how do we help them recognize what this is and how it might negatively affect them in this case? That's what we call it. See, get, you know, they got to see it. They got to get it. And then the last part, get the response we're hoping for. Some failure to launch or we've disrupted them enough and so they desist or whatever. That fear part.

So we call it see, get, notice recognize and respond but I didn't know what you thought but that's kind of where we've been going and doing a lot of the fender interviews and watching a lot of video footage where we are treating these locations and not these where we're gathering data on overall responses but we're also watching the behavior to see, are the, okay, what dosing option helps them notice it, that better notice it. If they do notice it, that they know what it is. They don't think a camera is a smoke detector or whatever it is. And again, it's credible to them. It's not, it is noticeable, recognizable, and credible instead of, well, yeah, I know what that is, a camera, but nobody ever does anything.

Sure. And then, you know, like in policing, you're probably always balancing risks and rewards, too. You're probably always balancing, well, we have to have people that are in the stores understand that there's a camera there and why it's there, but you also don't want them to feel like they're constantly being surveilled, because that's going to have a negative effect for a retail establishment. You know, most retail establishments want people to feel comfortable, want people to feel welcome so that they spend their money. And you could see how too much surveillance would have a negative impact there. No, I couldn't agree more.

And I think it's the same thing we see with law enforcement. The same thing you see in medicine, too. If we're going to actively search for potential problems or in medicine, if we're going to actively search for potential problems or problematic people, if we're going to do things in a somewhat active way, like you say, the first obligation is do no harm. And so in our case, we use the red and green shopper, the green so the shopper could be an employee, but the legitimate place user. And then we've got the red that's not. They're the victimizer. And so how do we, like you say, balance that so that just enough

so the red guy gets it and desists or goes somewhere else and not the green. But I think the good news that we found in our research is that as much as the red person is zoned out and not seeing and getting and so on, neither is the green. They don't seem to be as offended as people might think, particularly if you pose options. Well, you know, I'm not really comfortable with that. You say, what if the option was, this is here to maintain this item on the shelf because it

hasn't been stolen, or we have to lock it up and then you just need to seek somebody to help you unlock it never mind just leave the camera i'm good so you just never know how people respond to you get out there as you don't get evidence we've seen that in in the bottom on camera research as well with policing is that most uh individuals don't know don't even notice the camera and when when they're asked, we asked, we called up citizens actually in a number of different cities who had had interactions with officers who some were wearing body-worn cameras and some weren't and asked them if they, if the officer was wearing a camera. And I think we had 10% recall rate that was accurate.

I'm nervously laughing, but yes. So that's why I like what you're saying though about body-worn cameras and all these deterrent measures, these countermeasures to how do we put them in context? We talk all the time with our practitioners, look, it's never really what you do, it's how you do it. It's that dosing and let's help, let's kind of dial that in and reach that balance you mentioned a while ago too. So we get the deterrence, but we don't get the disruption of the green person or, or repel them. But also how do we look at this? It's not a thing. It's a process. Nothing is a thing. It's a process.

And probably the same, I guess, right. With body worn cameras that, okay, how do we better market the presence and the utility, but the value to you, to the officer and so on. I don't know. I'm just thinking out loud, but you know, the, the balance, the positives and the negatives and body worn cameras is huge. And it's not just on citizens too, but it's on the police department itself. The cost can be tremendous for both the storage and buying the cameras and just how much benefit does it give you? And how do you measure benefit too? I mean, it might be a little bit more

straightforward in the retail environment, but for policing, my gosh, you want to measure it monetarily. Is it going to reduce the amount of complaints that you get, my gosh, you want to measure it monetarily. Is it going to reduce the amount of complaints that you get? Is it, you know, we want a humanitarian effort there too. Is it going to reduce the amount of use of force that you're using, but then does it increase accountability and, and transparency and lead to increased citizen trust? There's so many different possible outcomes that are out there when we're

talking about something as, you know, complex in one hand as a body-worn camera, but then simple. It's just a piece of technology. And I think that's where people have been a little disenchanted or disillusioned with body-worn cameras in the last five or six years. of people and a lot of policymakers saw them as they're going to be able to solve our problems policing in america with its accountability accountability and legitimacy issues and all it is is a piece of technology it all comes down to how it's enforced and how it's used in every department yes he answered my question there's no silver bullet then you're saying um right um no okay so i that's the parallels are eerie and and i agree with you there um and and also another comment you make was was um very it was right on par with what we're saying and then and that is around um you know the how we use it what the

outcomes are um but also the fact that it's just technology. And so we need to find a process and we need to understand. But the biggest point I think was it is easier in retail if we're talking about theft events because unfortunately they're so common. And as you know, we can find a signal. We can sometimes do our power estimates. We don't have as many type two errors, which you know, we can find this signal. We can sometimes do our power estimates. We don't have as many type two errors, which you do see in these experiments, false negative. But when we research robbery and some of the other more violent crimes, like you're talking about,

we have to go to softer, less rigorous research. And now we're just looking for directional data in the same way you probably are with bodyboard cameras. It's just, it's happens too much, but it doesn't necessarily happen enough to get good measurement. Right. I guess. Right. So maybe going to a major thing that our team is aware of that you work on, and that's how people relate to each other

how they who they hang out with or don't or at least communicate with and um relate to um in a lot of different ways in our case like yours we're interested in those that might be somewhat organized or opportunistic but they they move together a little bit, not like a bunch of fish moving in concert or birds. But let's talk about social networks if we can and how they relate to offending and maybe start there. Sure. Well, I think like you at my heart, I'm an opportunity and a network theorist. I think both of these theories fit together really, really well. I think these both of these theories fit together really, really well. And, you know, I think my leaning towards them was a mix of sort of experiences I had when I was growing up, but then also my academic training. When I was growing up, I was I grew up in lower mainland.

Well, after I moved from a really small island where I grew up on a fish boat, essentially. I moved to the lower mainland of British Columbia. And I was in middle school and high school at a time where our biggest illicit economy was, believe it or not, it was illicit marijuana. And we were cultivating, British Columbia was known for this really high quality illicit marijuana. And a lot of people started making a lot of money there. So a lot of the friends that I was going to school with straight out of high school, they started doing illicit marijuana cultivation. And some of them got involved with criminal organizations. Some just went into business for themselves, but was so apparent to me. And this was straight out of high school, was that it was all a

combination of who you knew and the opportunities that were afforded to you because of who you knew. You know, my friend knew someone who knew someone who was connected to the Hells Angels, and all of a sudden they were set up in a million dollar marijuana girl operation. And, you know, another person might have been connected to another organized crime unit through a, you know, through friend of a friend of a friend. And all of a sudden they're driving Porsches and living in these huge homes and managing multiple operations. So it was just fascinating to me how these kids, 19, 20, 21, were making a ton

of money all because they just happened to know someone who knew someone who could get them started in an illicit market. It was fascinating. So I was going to university at the time and I was dabbling around in a number of different majors and took a crim class and was fascinated by it. It was taught by Patricia Branningham up at Simon Fraser University, and she was talking all about networks and opportunity and how who we know can shape the opportunities that we're presented with, whether those opportunities are criminal, illegitimate, or whether they're legitimate opportunities can open up to a really great job too. And this just jived with my understanding of people. I think of myself as a people person,

and I love being around people. And then after that, because it sort of staked that curiosity, I took a class in network analysis. And this is more like a mathematical sociology class. And they were talking about how it wasn't just who you were connected to, but how you were connected to those people. And the people that were really good at networking, either illicitly or illicitly, found themselves in a bunch of different types of networks. So all of this made so much sense just intuitively to me that when I started going into regular criminal justice classes and doing your standard download a data set and try to figure out if the independent variable has an impact on the dependent variable, it just felt like something was missing.

Like all of this analysis was treating our data as independent actors, individuals being independent from one another. And that is completely counter to what social network analysis does, which it treats individuals as being dependent, interdependent on one another. The more people you know, the more different you're going to act. If I'm surrounded by a bunch of people who are committing crime, I'm more likely to commit crime too. Whereas if I'm surrounded by a bunch of people who are, you know,

have negative connotations or negative ideas about crime and don't commit or aren't involved in delinquent acts, then I'm less likely to do that. So it really was, it was a mix of personal experience and academic training that led me to network analysis. Excellent. Well, now retired colleague here at UF, Dr. Ron Akers would appreciate some of the roots there. But yeah, so I think that that's great background and how your personal observations got you thinking and then as you went into academia. And I can relate so much because I think probably courses that would have either been boring or maybe seemed overly difficult, or maybe they were for me,

weren't as tough because, wait, I kind of understand what you're trying to say, or actually, I'm not sure you're saying it the right way. There's probably more here, just based on my anecdotal experience, but I think there's something there. So that's really an interesting, you know, genesis of how it came came about your interest in this social networks. So maybe going on a little bit, Ily, if you would talk a little bit about, okay, so you're starting to put things together. There are others that obviously are thinking somewhat similarly, and there's some similarly, there's some work out there. How did this how did this start to evolve? And where we're headed is to, I love the cloak and dagger model. So if you could kind of keep rolling, that'd be great. Sure. Yeah. I mean, there's a lot of people that we're thinking

along the same lines, but social networks and crime were in infancy and I'm going to age myself a little bit here, but you know, this is back in 2004, 2005, when I'm starting to put all these ideas together in my own head and actually having access to research where I can test some of these ideas. So I'm working with the, through the Browninghams, I started working with the Royal Canadian Mounted Police, and they were doing something called an organized crime threat assessment. Essentially, they were gathering information on all of, you know, as many organized crime groups that were operating in the province of British Columbia at the time.

This was a coordinated effort through the RCMP, through the entire country. Each province would do their own threat assessment. And I was lucky enough to be given this data. It was anonymized, obviously, but, or de-identified. And I was able to do network analysis. Basically, the RCMP wanted to say, you know, do some analysis. Show us how some of these networks work together or how insular are they? Maybe you can help us pick out the techniques to pick out key individuals in these networks. Just play around with us and tell us what you find. It was amazing. It was just this treasure trove of data. And as I started talking to the intelligence analysts,

and as I started working with the data, what became so apparent is that networks are built on different types of relationships. Just because someone co-offends with someone doesn't mean they've got a long-standing relationship. And we define co-offending just as being arrested at the same time or being in the same police file as a perpetrator, as someone else is. When we dig down into some of those relationships, and we get this through threat assessments, because intelligence analysts dig beyond just surface level co-offending sometimes, we find that other types of relationships are really important for us to look at too. So in addition to co-offending, what about people that own businesses together? And you might think, well, that's legitimate.

Why does that have anything to do with organized crime? But it does. Some of these businesses can be fronts for criminal opportunity, and some of them could just be the way people got to know one another. Obviously, kinship, families, people that are related to one another are going to have very strong relationships with one another, and how they interact criminally could be based on those relationships. So I started looking at how these different types of relationships laid on top of one another, how people were, how strong the relationship could be based on the different type of link that they had to each other. So much of the research that was going on at the time, and like I said, there wasn't much, was just looking at, do you have a relationship or don't you? It was all binary.

It was all zero for no and one for yes. And my research was pushing me into the direction that, gosh, it's not that simple. It really depends. What is the nature of your relationship? How many different types of ties do you share with someone? Or do you share with people in your organization? That can have a real impact on how strong the relationships are and how cohesive the networks are that you're working in. And when we start talking about how strong networks are, you get issues of trust, you get issues of resiliency. So just how easy it is to break those networks down. You get at issues of informants who might be a good person to give you information on illicit activity in a network and who might not. So it opened up all these doors to me that I had never

thought about. And not to sound like I'm tooting my own horn, but not a lot of other people had thought about that as well. I was starting to do work in the area. Prior to me, about a year or two before that, someone named Carlo Morselli, who is one of the greats in crime and networks, was starting to think about this over at the University of Montreal. One of his students who moved over to Simon Fraser University, where I was just leaving at the time, Martin Bouchard, was starting to think about this stuff. Andrew Papachristos down in, he was at the University of Massachusetts at the time and since moved to Yale, was starting to think about it in a different way. He was looking at how violence, firearms violence, really, firearms homicide was being spread through people's social networks and how, you know, your network, how many victims of firearms violence there were in your network was the best predictor of whether you were going to become a victim of firearms violence, better than

anything else, better than location, better than demographics, better than criminal history. The number of people you knew in your network who had been shot was the best predictor of you being shot. So all at the same time, pretty much between 2005 and 2009 or 10, a bunch of us are starting to do the same type of work. But prior to that, there had been theoretical work in this area, but it didn't incorporate social network analysis per se. And I love the way you're walking through that. And there's action points there, like you talked about, you know, bonding, resiliency, and probably the strength of the relationships and probably the persistence of those relationships and probably the opportunistic

nature. But by looking at resiliency, look at how committed are they maybe, or the trust between the different people that actually has to exist. Those are aiming points, right? I think you were alluding to that. Those are aiming points to maybe disrupt, to disentangle, to help protect certain people or places. Is that a little bit about also some of the coming out of your good work, some of the opportunity for us? Oh, yeah. No, absolutely. So it's not just picking out those key players, right?

The people that you think are maybe the figureheads, the ones that would be great to look at to reduce the crime that's occurring. But it's also how resilient those networks are. So if you think someone's really important, you're going to target them, you're going to try to get them out of your stores or in the case of my work, out of the organization, out of the networks, off the streets per se to reduce crime, how easily replaced are they? Are they going to have someone that's going to swoop in in a month or two to take over their business? And it's going to be like all the work that you put in to that investigation is going to be for naught because you've only had this lasting disruption for a week or

two or a month. Other people, if we really look at the intelligence and if we look at these types of links that they have to one another can be really hard to replace. And then as I was mentioning too, it's informants as well. Someone that is going to be more turnable in an organization is going to be able to give you more evidence, act as an informant for you. They're less likely to do so if they share a number of different relationships with a lot of people in the network. If you're in an organized crime network that is really strongly family-oriented, it's going to be much more difficult to get, as a law enforcement, as an investigator, someone to turn information on that network than it would be if it's just a loosely connected group of people that are

opportunistically related. They met each other in a number of different ways, and they figured, oh, you've got connections to this area of the commodity chain. You've got access to this area of the illicit network. Let's work together. Let's make some money. Much, much different types of relationships. And as network and crime researchers, that's where we're moving towards. We're moving towards this idea of, boy, being linked or not, it's not that simple. It's what your relationship is. And knowing more about what those relationships are is going to allow us to best target investigations or best target protective efforts. You know, it doesn't always need to be removing someone, putting them in jail, and getting them off the streets.

It might be getting them into diversion programs. It might be getting them connected to community organizations so that they are less likely to engage in violence or to engage in organized crime. Yeah, present them options. No, that's excellent. That's the heart and soul. And I'm wondering too, and before we started recording, you and I, or I did anyway, I guess I mentioned you place-based and how I really believe that these social networks-based, that this networking has to exist in a lot of cases. And we know regardless it does. And within retail loss prevention or asset protection, they have ORC, organized retail crime teams, most of the major retailers, because I'm sure you well know, I mean, a lot of the fraud and a lot of the significant theft that

they experience is somewhat organized, right? And so the groups come together opportunistically, or some are more persistent. A lot of them already have other businesses and they use those as fences and on and on. So, but you've probably read over the years, I mean, there are multimillion dollar takedowns of these ORC groups and it's kind of incredible. But I think now tying in the idea of networks and offending and then kind of, could you go a little bit into cloak and dagger and what does that stand for? How does that help us make sense of the world? And then maybe using that, take action. Sure. No, absolutely. So like I said, it kind of goes back to that RCMP research that I was doing and understanding that, you know, just because relationships aren't simple,

understanding that, you know, just because relationships aren't simple, they're complex, and they can be multi-dimensional. And I was sitting down, I was talking to some colleagues and having a conversation with Jerry Ratcliffe, who does a lot in intelligence-led policing, I'm sure you've heard of him. And he was, we were, I was saying, you know, in social networks, he goes, what's the most important thing you talk to when you talk to crime analysts about the importance of social networks? And I said exactly what I just said to you. Well, it's not just that someone is linked. It's how they're linked. What is the nature of those relationships?

And we just started talking and I started talking about these different types of relationships. And he said, you need an acronym. started talking about these different types of relationships. And he said, you need an acronym. You need an acronym that's going to stick so that analysts remember. And it's something easily recalled. And I've got to look at relationships in a multifaceted way. So then I really, I took that back and I started sketching out, really thinking about the different types of relationships I've done in my research. And that just seemed to be popping up over and over and over again in intelligence files, played around with the words and CLOAK came up. And CLOAK stands for co-offending. So people can be connected to each other in co-offending

relationships. L are those legitimate relationships that I was mentioning, you know, whether someone owns a business with one another, or whether they just work together in a legitimate place of employment. O stands for organizations. And these are the formal criminal organizations, like a Hells Angels chapter, or like a, you know, a street gang. A stands for acquaintances and friends. And you can see I took some liberties in the acronym a little bit. But again, just that quick recall really stuck with me. And we all know investigators and law enforcement love acronyms. And then finally, the K was kinship. So families. All these different types of relationships and networks are important for analysts to think about when they're collecting data and for them to keep them separate. And then you can also collapse them all in on one another.

But the importance of keeping these networks separate is that you can lay them on top of one another and without getting too quantitative and statsy on you. By laying them on top of one another, you getting too quantitative and statsy on you, by laying them on top of one another, you can start to see when someone's relationship becomes multifaceted. When not only have they co-offended with one another, but they also own a legitimate business together. Say they own a nail salon that's used as a fencing operation together. They are also second cousins. It's all of these relationships or, you know, they might be, one might be a brother-in-law or sister-in-law to someone else. All these different types of relationships have their own importance, but when

you layer them on top of one another, you can start to see the really strong links to one another. And if you cut out, if you say, you know, I'm not interested in people that only have one relationship, one link to each other. I want to find the really strong links. So I'm going to say, you've got to have two or three, at least of these relationships types for me to think of you as the core of the organization. So you can start to play around with social network analysis there to really find interesting things about the nature of how people are connected to one another and where we might be able to target disruption efforts. The dagger part of it came after. So I was, it's funny, I was walking on the street and I saw a poster for a movie and it was

called Cloak and Dagger. I never even saw the movie, but it said, and it just triggered that, you know, this is something that's used all the time in mystery novels, sort of as a reference to something being hidden and something being covert. And I thought, gosh, I've got, I've got to be able to do something with that because I've already got cloak. And then I started thinking, well, different types of relationships are different in different types of illicit markets. For instance, you can have an illicit drug market that operates much, much differently than an illicit art and

antiquities market, or than the illicit firearms market, or than street gangs for that matter. firearms market or than street gangs for that matter. So the types of relationships that are important and the emphasis that we should place on collecting information from different elements of the cloak model differ depending on what illicit market you're looking at. And that's where Dagger came in. D stands for the drug, illicit drug market. A is art and antiquities. G, guns. Another G for gangs, street gangs. I get a little creative here. E is for exploitation in that sense for human trafficking or sexual exploitation and the like. And then R at the bottom is religious extremism and terrorism. All of these things. And you could argue that that last one is difference in kind, but that only emphasizes my point, that it really depends on the area, on the market, on the type of crime that you're looking at, to how we should be emphasizing or investigating, really gathering intelligence on each of these different types of networks on these different types of relationships. So put it together, cloak and dagger. And I think it's, it's like I said, I took liberties,

but I love the acronym. I think everyone remembers it once they hear about it. Well, it's a one data point, but I definitely do. So it's fantastic. And so one other thing on that is I wanted to see about, just for our sake, trying to tie some of this excellent work together. So we've got Cloak & Dagger, all the research that you've got around leveraging how human relationships work in the real world, as well as obviously theoretically should reflect that. And then helping us find what we just call aiming points for whatever solution sets that we start to dial in there and then evaluate. But then now starting to move to, we talk about our risk-trained modeling and other ways to maybe assess from more of the physical environment, but how that helps drive social and antisocial behavior. We've got the likely or motivated offenders and how

they're working together with your concepts. But I'm wondering, does Crime Place Networks, you know, what Tamara Maddison-Herald works on and so on, and she's been on this podcast a couple of times now, does that help? We're thinking right now with these organized retail crime investigators in any way that that's somewhat of a bridge for us between social networks and cloak and dagger issues and then the actual terrain, and then finally using these place crime networks

because they're related because the people are related. And they also have to be there to facilitate the different components of a crime. Sure. No, absolutely. And I think Tamara's work is a perfect example of that. But if you think about it, what comes first, it really doesn't matter. I mean, I'm pretty confident that networks come first, but you could also argue that people are more likely to form networks because they live

spatially close to one another. But if we think about Tamara's idea of these areas, these networked spaces that are out there, think of flea markets, for instance, and I'm trying to put this into sort of the retail crime aspect. Flea markets are incredibly important in the commodity chain of fencing, right? Of getting rid of stolen goods. And do people, do networks support that? They absolutely do. You can have flea markets, people that they meet at the market, and this is where they're getting rid of their goods. Or on the other hand, they could all go to the same market because they already had a pre-existing network. They could meet one another. They could see, oh, that person's selling something. I have a great market for that good. So they meet each other at a space, at a place. Doesn't need to be at a flea market. It could be, you know, a different type of hot space if you were. And then they form this network of individuals that's going to procure goods, stolen goods for one another, because those people might have access to a better market.

access to a better market. In a flea market, you might not get the best price for what you want, but it can be a great place for people to meet one another, people who might have access to these goods. And you probably know more about the hot spaces and hot people in retail theft than I do. Actually, I'm certain you do, but I can see implementation and how something like social network analysis would help you out here in your investigations? No, absolutely. It's making things much more three-dimensional because that's the reality on the ground and ways that they can be addressed. And I think law enforcement are tightly bound here with these ORC investigations at all levels really here in the United States and up in Canada, by the way.

So we're just looking for very visible, tangible tools. So clearly with risk terrain modeling and to a certain extent now with the crime place networks, we can sort of draw things out and help understand, okay, where should we be looking and what should we be doing here to deter and disrupt and document and so forth? How might we, any thoughts, just this is just thoughts, ways that we can visualize using social network analysis, using cloak and dagger to overlay or, you know, I'm just, again, thinking out loud with you, Eileen, any thoughts there? or, you know, I'm just, again, thinking out loud with you,

Eileen, any thoughts there? Sure. I mean, you can, and, you know, this is one area that you'd think more research had been done. There was a lot of us thinking about how social networks and space overlaid a while ago, and there's been little things, but really it wasn't until Tamara did the network spaces that we ever had to put into practice. And really we saw that it was making a difference to a certain extent in Andy Papachristo's work with street gangs and firearm violence as well.

But let's think about this. If you've got intelligence, as I'm sure most loss prevention investigative units would, right? They keep track of who and where and what, what's being stolen, where it's being stolen from, and who's doing it. You can look into and who's being caught with one another. You can overlay the people onto the spaces. You can say, well, where are they working together? And you can start to look at, you know, these two people that are working together all the time, They always seem to be caught with one another. And the space that's connecting them is this hot space. Think about Tamara's idea. Well, then you not only want to focus on the two people,

but to stop that networking, to stop just someone, if you take that one person out, if you get them arrested, or if you stop them from committing crime, chances are someone else is going to fill in for them. Why is that? Well, that's where the space comes in, because they just meet someone else at that place where they had met the original person,

all depending on the relationship, right? It's multifaceted. It's how the relationship was started to begin with. But if you can not only look at how the people are connected, but looking at where they were meeting, where they were committing their crime, and then you can pull opportunity theory in, then you can pull that crime triangle in. All right, so let's focus on these three people, because we're seeing that these three people are really the core of the network, and we've used social network analysis to do that. Geographically, perhaps the risk terrain modeling or some other geographic GIS technique, you're looking at, well, these are the places that they're having a meeting.

These are the places that they're fencing. Or these are the places that, for whatever reason, you've got a hot location. So you focus on that. And then you start to target-harden that space. So it's this idea of the crime triangle, the hot place and the hot people all coming together. I hope that wasn't too broad. No, no, that was it. I mean, we can't go too narrowly. I don't think right now, we don't have enough data and we don't have a case study here, but that was exactly what I was

looking for is kind of going through the social networks and what they are. And we did that and you did that. And then, OK, now how we start pulling together. Now, what's a what's a framework? You know, we've got cloak and dagger to help us think about it and remember, recall it and start to make sense. And then, OK, now we pull in other, you know, tools like crime place networks, like wrist drain modeling. And as you said, other, you know, geospatial type tools that we've got. And now start overlaying all these and understanding at greater depth and what's greater, hopefully, precision and accuracy. Who are the real players that are important? But what are the things they do and how they do it?

And like you said, where and when do they do it? Now we're starting to get some more aiming points. And, you know, the old idea of, well, you just cut the head off the snake. Well, what, but crime networks are not snakes, right? And people are actually replaceable. Like you said, some may be less so than others, and it may not be the leader that we want to go after in the first place. So. Sure. It might not, right leader that we want to go after in the first place. Sure, or it might not, right? You might want to go after the leader or you might not. It all depends on the specific situation and what you're trying to do, what you're trying to accomplish.

And what social network analysis does, and it's the same thing that spatial analysis does, is it allows us not to be broad-based, right? And that goes back to what we were talking about at the very beginning of this discussion, is the last thing you want to do is just throw up a bunch of cameras and survey all the heck out of everybody and have everyone feel like they're being focused on. Because we know the law of concentration, it's very few places and very few people that are committing the majority of crime. If we can get better at targeting, we're less likely to infringe on people's personal space. We're less likely to infringe on their rights. We're less likely to make them feel like they're suspects. And boy, in the retail setting, that's the last thing you'd want to do.

I totally agree. Yes. And we're wearing, we're just wearing people out for no reason. Sometimes with that type of approach. So, and it goes back to anthrax, right? We had some in the DC area, we know around 2000. And then the suggestion was made in somebody in Congress, hey, let's inoculate it. Wait a minute, you know, 330 million people, this is very isolated, and just negative reactions or responses from the vaccines. Let's not even, we don't want to run those numbers. So we are about precision and accuracy. We're, you know, so, okay, well, this has been fantastic. I'm sorry, Eileen, go ahead. No, it's okay. In policing, we have to be. And I think that's become so much more apparent now, hasn't it? Some of the techniques that spatial

analysis and social network analysis, some of the actual on the ground implementations have really backfired because you end up having concentration in specific communities and that concentration is backfired because communities start to feel like they're targets. The more precise, the more accurate data collection that we have and the less people we're affecting, the better. Yes. Precision. Let's not kill the patient with the cure. And, you know, I think maybe we'll leave it on this. What, you know, and this is just thinking broadly, but we all want to go to evidence-based practice. And in all these disciplines, we do work every day with law enforcement. And we can see clearly a difference. I did a couple of stints actually way back in the day in law enforcement too, but what might be some advice or at least some thoughts that you all have around, okay, how do we really shape this? There's a lot of law enforcement officers and analysts that are out there. They really, really, really want to protect people. They want to protect the vulnerable. Those that are out there making noise may or may not represent everybody else

that may be victimized or at least feel intimidated, not by the police in this case, but just by what else is going on around them. How are ways that we can affect law enforcement? I know we've got 18 or 19,000 alone just in the United States, but is it through leadership training? I mean, we're hearing these, well, we need reform, reform. Any thoughts on for real reform? No. Well, you've just hit me with a really easy question at the end, Reed. Okay. No, I'm kidding. I mean, who in policing and who in criminology hasn't thought about this over the summer? It's hit us like a ton of bricks.

And as a policing researcher, as a criminologist, I think we're all really weighing this. Like I said, it weighs on us. And I think we have to take a certain amount of responsibility, too. And I think we have to take a certain amount of responsibility too. I've been, I think most of us for the last, you know, decades have been saying evaluation. And certainly in the last five or six years, we need to constantly evaluate, update programs, make sure we have rigorous evaluations. But an area where I know I've really failed, and I think a lot of policing researchers have failed too, is that outreach piece, you know, just talking to the affected communities and making sure that

when you're designing the program, and absolutely when you're evaluating the program, you're not leaving out some costs, community costs. And I think this is an area that we failed, and I certainly know I've failed, where you can be evaluating monetary costs, you can be evaluating the outcomes that I talked about earlier, so the reduction of specific types of crimes. But were we talking to the people affected? Were we talking to how is this type of program, how is this type of policing affecting the community? Really talking to the people that are affected. And I think all of us moving forward are going to start to do that more. We have to start to do it more.

Otherwise, you're going to think you're doing good work as a police department, as criminologists, as policymakers. Our evaluations might show that we're doing good work. Hopefully they do, but it might be having unanticipated consequences. So how do I see the way out of this? It's not, I mean, there is no direct way out of this, but the most important thing I think all of us researchers have to do is to take a step back and to talk to the affected people right away. And in loss prevention, that can be a number of stakeholders, right? It can be your customers, probably first and foremost, but then it's also, you know, all of the different people that have stake in what's being lost in a policing environment,

it's obviously those communities that are being disproportionately affected by policing programs. We have to talk to them. We have to understand, first of all, who they are, because the idea of community is not easy. There's not just one community. There's a number of different communities. So try to get a handle on that voice. Try to listen to it and to understand what kind of output they want, how they would measure success and make sure we incorporate that. It doesn't mean that your outputs and your outcomes need to be completely directed that way, but it certainly has to be a part of your evaluation.

certainly has to be a part of your evaluation. So bringing it right back to the beginning of what I was talking about, your outcome and your process evaluations and your cost evaluations have to incorporate community outcomes, community process, and community cost in addition to crime reduction. Fantastic. And it is kind of ironic, I saw some pushback by some criminologists out there. When this administration appointed a new director at NIJ, who actually, the main emphasis is now on evaluation research. So yeah, it was kind of interesting that the evaluation scientists thought it was a positive move and those that weren't, weren't so sure. But I couldn't agree more that, you know, if we really spend some time with the right people and think through the mechanisms of action of what our logic model, what's the logic model, what might the mechanisms be? Like you and I talked about at the beginning. And then now we might tease out some options and let's

go and let's maybe conduct some initial and then later maybe larger scale and more rigorous RCTs. We've done, I think we've done 32, 33 place-based RCTs. They're a nightmare, but they really help us understand and by where we can have cameras and interview people before and after. And so they don't have to be in a black box, right? We've kind of understand what we think the mechanism of actions are of the different options go and conduct for real RCTs. And then, hey, here's what we found. So, so I really appreciate this. And particularly though, you know, Dr. Malm, how you've helped us tie together and understand social behavior, social networking, what that might mean in any context, but especially in what we're dealing with at the different scales here, and then how we might start

to tie that in to places and so on to get better and better at what we do and be much more focused. And as you said a minute ago, everything has side effects. Neutral, good, not so good. So we want to be precise. Well, thank you very, very much for your time today and all your insights. It's been incredible. Went by fast. Good discussion.

Please, please keep up the good work and stay in touch. And we might start sending some of the propaganda that we're generating here to CREMCOM. I think it's pretty, a lot of it's pretty relevant to what you all are hopefully trying to help us all get done here. Oh, well, please do. I hope we can help you guys out. And thank you for talking to me. It was a lot of fun. A lot of fun. Thanks so much.

Stay safe and stay in touch. Thank you. Okay. You too. Bye-bye. Bye. All right. And for everybody, we want to thank you for tuning in to another episode of Crime Science

Podcast. And again, please, everybody, stay safe. Thanks for listening to the Crime Science Podcast, presented by the Loss Prevention Research Council and sponsored by Bosch Security. If you enjoyed today's episode, you can find more crime science episodes and valuable information at lpresearch.org. The content provided in the Crime Science Podcast is for informational purposes only and is not a substitute for legal, financial, or other advice. Views expressed by guests of the Crime Science Podcast are those of the authors and do not reflect the opinions or positions of the Loss Prevention Research Council.