The Jeff-alytics Podcast

Turning Policing Research into Real-World Action With Carlee Ruiz

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I talk a lot about crime analysis and analyzing crime data, but I realized that I’ve never actually talked to a crime analyst yet. To correct this, I’m talking with Carlee Ruiz, a former crime analyst and policing researcher, discussing how she bridges the gap between academic research and real-world law enforcement through her platform, Police Research Hub.

Carlee highlights how valuable evidence-based insights are often inaccessible or underused, and explores the growing role of data, AI, and technologies like real-time crime centers in policing. The conversation also examines the balance between anecdotal experience and empirical evidence, emphasizing that context and implementation matter. Ruiz further discusses recruitment and retention challenges, pointing to leadership and organizational culture as key drivers of officer turnover.

Carlee Ruiz is a former crime and intelligence analyst with the Modesto Police Department and now works in research and technical assistance for law enforcement agencies at RTI International. She saw firsthand that much of the research useful to officers wasn’t easily accessible, which inspired her to create a website that translates peer-reviewed studies into practical, actionable insights for policing.

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SPEAKER_01

I'm Jeff Asher and this is the Jeffalytics Podcast. For most people, research about policing lives in academic journals, buried behind paywalls, written in a way that almost guarantees it won't be used by the people making decisions in the field. But that research actually matters. It shapes how departments think about crime, how they deploy resources, and what strategies work or don't. Carly Ruiz has made it her mission to close that gap. She's a former crime analyst, turned researcher, and the creator of the Police Research Hub, where she translates academic studies into insights that policymakers, law enforcement professionals, and interested members of the public can actually use. In this episode, we talk about what crime analysts really do, why data visualizations play such a critical role in decision making, and how emerging tools are changing the landscape in criminal justice. We also get into the limits of that research, the tensions between data and lived experience, and what the evidence actually says about important topics like surveillance technology and police recruitment and retention. Let's get started. My guest today is Carly Ruiz. Carly, thanks for joining me.

SPEAKER_00

Hi, hi Jeff. How are you doing?

SPEAKER_01

I'm great. As you can see, uh I am freezing in my house. So I'm I'm giving up the game that uh not only do I not have great insulation, apparently, but uh apparently I have a low tolerance for heat. So we're in a giant, giant sweatshirt right now. Um so now that I've already totally gotten off track, uh Carly, what is your background? What what brings you here today?

SPEAKER_00

I guess the biggest thing that brings me here today is that I host a little website called Police Research Hub, where I take peer-reviewed research, policing research that usually stays up with the ivory tower and the academics and bring it down to make it actually actionable and bring insights from that to law enforcement or law enforcement adjacent profession. So a little bit of my background, I was a crime and intelligence analyst with an agency here in California for four years. And I think I was in almost every single department there at one point where I worked in their RTCC, I worked in investigations, I worked in the chief's office, I worked in their intelligence area. But a lot of times I was the one that was tagged for a like, hey, we're doing this project, can you see if it's working? Um, and you know, doing kind of these like low-level research projects. And that's kind of really where I shined and really had a great interest in. So I wanted to take that to the national stage. So I joined RTI as a justice researcher in their policing research program, where I do a lot of projects around like fatal, non-fatal shootings for increasing clearance rates, helping with police retention, peer support programs. I also evaluate organized retail theft, you know, violence intervention, you know, all these little things. If it involves a law enforcement agency, I will probably hop on it because I love working with law enforcement. From there, I especially realized both from my experience within working in the agency and then kind of working outside as a researcher, is that a lot of this like really good academic research that has really, you know, key findings that can be really helpful for law enforcement is just not accessible. It's either locked behind a paywall or just in somewhere that really most law enforcement wouldn't even think to look when they're trying to think of, oh, how do we solve this problem? And so I wanted to be able to bring that out out of those journals and bring it into somewhere that's accessible and usable and actionable for law enforcement.

SPEAKER_01

I'm embarrassed to say that you are the first crime analyst or former crime analyst that I've had on the podcast to this point.

SPEAKER_00

I'm surprised.

SPEAKER_01

Um I I just thought this is a bit of a tangent, but can you just sort of describe like what is a crime analyst? What does they what does a crime analyst do for a police department? I I realize some people in the audience may not just be aware of this as a profession.

SPEAKER_00

Yeah, definitely. Have the honor. Um so yeah, crime intelligence analysts. So if the role will vary depending on the law enforcement agency, but overall, it kind of fits into two buckets, I would put. So there is the crime or the crime part to where you look at the crime stats. A lot of times it's looking at weekly, bi-weekly, monthly, um, helping prepare for Comstat meetings or ILP meetings, you know, seeing what's up, what's down, looking at the individual crimes to see if there's a method that's the same across these crimes, maybe they're connected and kind of doing a deep dive in there. And then also sometimes doing this like research background, looking in the data and looking at what's the problem and if we can find a solution, is our solution working? And then there's the kind of more what I would call the intelligence side where a lot of times you'll work with the investigators. So a lot of times like homicide investigators, you're right where with them, pulling up, doing workups, so doing a deep dive into a person's background or an address or a car and trying to help them find leads to solve their case, or even helping that at the patrol level, especially in a real-time crime center. So it's really a crime intelligence analyst, you're you're deep in the data, you're deep in the computer, either looking at crime stats or looking in someone's background and you know, trying to like support the department that way.

SPEAKER_01

All right. That tangent aside, yeah. I wanted to get back to the police research hub and and talk a lot about this because it's such a great tool. It's it's such a great resource. And you kind of answered like, what is it? Where did the genesis come from? But who, when you built this, who is sort of the client? Who do you see as the person using this, or is it not just one person that you kind of built this in mind for?

SPEAKER_00

When I built this, I started trial testing this on LinkedIn. Like my first one was posting Ian Adams study on that, hey, AI report writing software is not as efficient as you think it is. Um, and that got a lot of traction and I realized with law enforcement, they weren't aware of that study. And, you know, there was positive people who were appreciative of being posted and others who were not. But, you know, it kind of showed like, oh, law enforcement, especially, you know, is not aware of these, you know, studies that maybe academics are aware that have come out. And so most of the time I re I frame it for a law enforcement officer, especially with I usually provide resources towards the end of like whether it's a training or whether it's a guide. So a lot of times I frame it probably more for the sergeant or higher um command staff level. But I also, I mean, anyone of any level, and even civilians, um, can read this. I've I've done some things on data that could help with the crime analysts, and I've done some, you know, some things with you're maybe someone like a victim advocate coming from you're still part of maybe a police department or out like in that sphere, uh, but maybe not working directly with the police department can be uh useful. But a lot of times it's I write it more towards the, hey, you're as a law enforcement professional, you know, this is something you should be aware of or know, or here's a resource for.

SPEAKER_01

So you mentioned Ian, who is a recent guest of the pod as well, which immediately brings to mind how do you come up with the research and is there a role for AI in not necessarily doing what you do because you bring your expertise, but in in making things easier for identifying research for any part of this, or is this all a, you know, a human needs to sort of bring this to bear?

SPEAKER_00

It depends. So as far as the AI piece, I mean, a lot of times with the police departments that I've worked with in my my own experience, they usually have something where it's like, we have a problem. Like, let's say, like, oh, we're seeing a large increase in calls related to homelessness. What do we do to solve this problem? And a lot of times right now it's like, well, what is our neighboring agency doing? You know, who have I talked to? Which is a great way to get information of like who's doing what, but it's not a really great way to get like what has evidence-based found to work and how you can implement that. So I guess I mean AI could be useful in being able to at least give you the research articles or at least get you, hey, there is an evidence base on this particular topic that could be helpful when you're developing your program, you know, and pulling articles for you. But I would still recommend reading them because sometimes it does like to fabricate citations. And so I would make sure that, you know, hey, give me the actual article. Don't just give me the answers because it might give you something that's incorrect. But it it could definitely give you a nice starting point of like, I have this question, what's out there? And then from there you can jump from other to other things.

SPEAKER_01

When you're putting all this together, having done this now for a little while, what are the biggest challenges of taking what can be really inaccessible research? I mean, you know, academics can write in a way that makes it almost impossible for anyone that's not themselves to understand it to an audience, like, especially if your target is police leadership, that like is the complete polar opposite of that sometimes.

SPEAKER_00

No. And I mean, sometimes I'm like, whew, I'm reading this and I'm just like, man, I am struggling. Um, but I would say a lot of times, especially the data pieces, like I've done a couple pieces on like predictive data or AI, if you're not in that realm, can be difficult to understand. You know, for a lot of people, AI is still this black box of mystery. And I don't, you know, you put in something and then it puts something, and I don't know how you did it. So for especially for academic research articles, it could be difficult to understand what it does, but there's some really good, interesting things coming out about predictive analytics that can be useful to law enforcement, but also is very key to understand how it does that. I do ask when people subscribe to my website, what topics do you want to hear? And using data is my most popular like topic that mostly law enforcement who subscribe want to hear about. So it is something that they're very interested in and want to learn more about, you know, using data and tech and tools, but you know, and I think those articles especially are the most difficult to understand as a layperson.

SPEAKER_01

What kind of feedback have you gotten on all of this?

SPEAKER_00

As far as feedback, most of it's been positive as far as bringing light to some uh findings that have, you know, that people were not aware of before. I add a lot of storytelling elements, or if I have personal experience, I'll add that and people, you know, like that kind of realism in there. You know, I have got, especially when whenever I bring up AI, there's always a little bit of like the debate of, you know, usefulness or, you know, is it here, take our jobs, you know, like there's always some sort of kind of squabble uh there. But most of the time the feedback's been very positive. There is a few resources out there that do something similar. I know the um like the applied policing briefs, Dr. Radcliffe has his podcasts where he interviews people as well. So there is resources out there like like mine, but there's not enough, I would say. And so I think people are very hungry for this kind of information.

SPEAKER_01

Yeah, absolutely. So can we can we dive into what you found? I'm putting you on the spot. I don't know that you have an encyclopedic memory of all of the things you've written, but have any of the research topics that you've covered really jumped out as like either unexpected or have you think translating it to a wider audience has had a bigger impact?

SPEAKER_00

I think, okay, so one I will use I always surprised when I'll think something like, I don't know, this will be popular, but I want to get this out there and then it explodes. One, I did a post on data visualization and what's the best way to display graphs in a Comstat meeting, you know? And something as a crime analyst, I was very like die on this hill to, you know, let's not do week-to-week comparison, what's up, what's down. I think this was one of Renee Mitchell's articles doing a study of like, hey, let's show these different types of data visualization graphs to a law enforcement leadership and see if they can make decisions, what which graph helped them make the better decision in terms of response? And had did they understand it better? Instead of like, let's just do normal percent change graphs, let's do one that shows the median for this time and a standard deviation above and below, you know, to show, hey, crime does fluctuate, but hey, let's oh, this is above our norm. This is about out of the standard one standard deviation. Maybe we should do something about that. And, you know, with that kind of graph, leadership was able to at least deploy a better solution to address that increase in crime versus just using a normal percent change. And which maybe this is not the most exciting finding, but for me, but like that's something that that I don't think law enforcement is aware of of like, yeah, there is a study on what's the best data visualization to use to help you make decisions. And maybe that there's better ways and there's not so bad, you know, not so good ways. And that, I mean, that was probably one of my more popular posts. A lot of people were commenting on it and sharing it and reposting it and showing that like this is of some great interest. And I don't think a lot of law enforcement was aware that there's other ways to do this than just doing percent change.

SPEAKER_01

Sometimes I'll post a graph that'll be like percent change because that's it's just easiest sometimes that it's for the public audience. And if you'll be like, well, you should really use z-scores. Like, if you can like trying to describe that to an audience, I mean it's very difficult.

SPEAKER_00

How do you balance it to I made the mistake as when I was a crime analyst, I I told my chief I was like, oh, and the poison z-score is this, and then they never let me forget about it for years on end. You know? I mean, it was like they were impressed, but also like you know, sometimes you don't use the terminology and just keep the stats language out and try to keep it as plain language as possible so they understand.

SPEAKER_01

Yeah, it it sounds fancy. Yes, not really, but one one of the things, uh just again going by like some of the research that's available, uh a couple of them, especially the recent ones, talk about sort of the role of real-time crime centers, the role of cameras. Have you uh like synthesized a bunch of these? And um, I'm just looking at like uh there was one on I I forget the name of it, but ha the actual like review of real-time crime centers, one on prioritizing burglary cases that have CCTV. Have you thought about like synthesizing some of these? Have you put all of them together into like a larger analysis in your head? Or how does that work?

SPEAKER_00

Yeah, so at least with the RTCC camera ones, I worked for a long time in an RTCC, so like that's a that's a really good background I can pull from as far as like I know how these work and how what would be useful for a law enforcement agency to know about RTCCs. I have an interest. I do want to so like what you said, like pull together all the resources on one topic, um, do like basically like a literature review like on RTCCs, like what's all the research out there. I do have a goal of doing that. Maybe RTCC would be my first topic. It's just it takes a long time to be able to find all the research that's out there, pull it together in a in a cohesive form that doesn't make it into a 50-page report. You know, I I have been working on that and I do hope to eventually post at least uh a couple of those a year, or maybe like one a quarter, uh, of like, hey, this is all the current research on this one topic, uh, you know, AI report writing or uh, you know, RTCC camera-based topic. That is a future goal, not currently what I have right now.

SPEAKER_01

Can you sort of give me your impressions of sort of RTCCs and kind of that synthesis of what the research shows and not just RTCCs, but the these are real-time crime centers, um, but just like surveillance cameras and like the role that surveillance cameras can play for police departments with all of this experience? Have you sort of do you have a general idea of like what's the best way to balance success and and privacy concerns and all that?

SPEAKER_00

As far as so for real-time crime centers, they're still relatively new in terms of the evidence base. Um we are seeing some research come out that does show as far as like case clearance-wise, they can help increase, you know, the solving of cases, which logically that makes sense. There's more cameras, you're more likely to capture evidence. With it being staffed, your eyes on the scene faster. And you know, the sooner you respond to the scene, the more likely you are to solve cases. Especially that in that case, RTCs really shine. There's a lot of other metrics though, the RTCCs like, you know, whether it's officer safety, you know, awareness of what's going on in your community. It's really hard to capture with data. Um, and so that's that's a harder point of like when you're building an RTCC, you really have to figure out what do you want this to do for your agency and know that is and understand that metric might not be easy to capture. There is evidence that are coming out that at least helping solve cases, they can do that. Now, crime reduction has varied results, but there's not a lot of research out there yet on evaluation of RTCC. Now, cameras have been around a lot longer than RTCCs, and again, more on that case, they do help with case clearances. Now, crime reduction, I think there is varied results depending, you know, if the camera is visible, it can't work as a deterrent, but you know, does that push it off to other areas? It it kind of depends on the research in the area. Um, but I think overall, you know, real-time crime centers, license plate readers, putting all those technology pieces together is, you know, there is more evidence and it's starting to grow that like, you know, this can be very helpful in solving cases, in getting situational awareness in in your community and what's happening in your community.

SPEAKER_01

Looking more broadly, how do you respond when sort of the anecdote leads rather than the research? When you run into people, you're explaining what the research shows, and they say that their life experience or their opinion says X and actually the data says Y. How do you have that discussion?

SPEAKER_00

Yeah, so I mean, always validate the antidote. I mean, people have their own experiences, and especially with policing, officers have lived it and experienced it. And so, you know, their anecdotes are are valid in what they're experiencing. And I also, with different techniques, different technology works differently in different cities. What works in one city might not work in another, or the city has to adjust because their community is not the same as Chicago is, you know, Chicago and Oakland are not the same. And so what might work in one might not work in the other. And so it works for them because of their personality and who they interact with, and maybe they have rapport, where in this other area, like other city, the officer doesn't have the same rapport and it doesn't work. And so that is like I I hesitate to shut down anecdotes because things will differ. And also the field of policing research is relatively new. And so we haven't, you know, one study might say this doesn't work, but if we look at it in a different context, it might work. And so to shut down anything means like I I hesitate to to do that.

SPEAKER_01

Is there a question or a data set or an answer that you it isn't answered something that isn't answered by policing research that you really wish was available? Like is there something that you're just dying to write about and think about, or some things that you're dying to write about and think about, and it just there's just nothing there?

SPEAKER_00

I mean, okay, so I I do a lot right now. I have a big project on AI and policing. So it's very new. So we don't have a lot. Um so loved more of like a lot of this technology, more of how is especially like data analytics, integrated data analytics, how does you know uh that help law enforcement if you bring all these data sources together and you know, give them LPR and their CAD data and their RMS and their neighboring agencies and you know, OTSINT and all that stuff, you know, does that really help them solve cases? There's nothing on that now, you know, and so and a lot of it it has a lot of potential. And as an analyst, I'm like, I can see the potential of it, but you know, there's no research on it. And then also like license plate readers, there's not a lot of license, there's not a lot of research out there on them because a lot it's very difficult to identify like every agency who dubs on LPR, I always try to say, hey, you know, if you make an arrest, make a note that it was because you pulled it from LPR, it was an LPR hit. And that's always been difficult to to uh you know get across to agencies of like track that info so you can prove that LPR works for you. It helps you, you know, with your auto theft cases or with you know your warrants and whatnot. I mean, I even talked to a couple guys at Flock Safety who are like trying to get agencies to track this data, and it's it's very difficult even from their end. So that's something also with LPR and AI and how that's changing the policing field, we need so much more research on.

SPEAKER_01

Sort of at the other end of the spectrum, how do you handle research that you know it's not obvious what the what the answer is, what the finding is, or potentially it's a really interesting finding, but it's potentially not the strongest finding, or even potentially a bad finding. Like obviously there's a wide range of quality and research. How how do you sort of work through that?

SPEAKER_00

What comes to mind is um so Jerry Radcliffe ran a study in Philadelphia.

SPEAKER_01

Also also a former podcast.

SPEAKER_00

Uh he he ran a study in Philadelphia where they had um, I think it was like within their transit unit, they signed a um like a social worker with an officer. And especially when this was in the height of like alternative policing programs, instead of having the officers show up, you have someone else show like someone that's of either a psychiatric care social worker show up. And I think, yeah, like his his finding was like you know, officers who like the officer only actually had better results, or they're about the same result as an officer with a social worker. And when you look at it on the surface, you're like, oh, so social workers. Don't really work. But when you dive deeper into his study, he, you know, brings out the point of, well, okay, these actually these officers who are working have been trained in like multiple things of like with like a social worker. Like many had a social worker background, and they've been trained in like how to interact with people who are, you know, having mental episodes, who are dealing with addiction and drugs. So they've been specially trained. And then the social worker side, there was a lot of turnover because the way the position was advertised, you know, they didn't realize how how much work would go into it. They just had a really hard time keeping these social workers employed in these shifts. And so it's kind of like, well, does that speak to the, you know, social workers don't work? Or does it speak more to, well, these officers are specially trained so they do better, but also these social workers weren't really given a good shot because they had a lot of turnover, they didn't have a great amount of training. And so, you know, so that's like a mixed finding where it's brought out of like maybe something we can learn from this is when you're implementing something, make sure it's given its best foot forward. And so that's something I I emphasize a lot, and sometimes in implementation research that I talk about is if you're implementing a solution, consider all these factors. Because sometimes a lot of times I see with law enforcement, they'll just let's just start something, get it going, run, run with it. And then they there's a lot of issues that pop up, and then they say, well, it didn't work. And you're like, well, it might not have worked because it wasn't implemented well. And so that's you know, always come kind of a consideration when we see mixed findings are not working is how well was it implemented? How can we better implement it? You know, was enough forethought and consideration put into it at the at the beginning for it to, you know, actually have a chance.

SPEAKER_01

Which sort of brings up the question of how do you how do you communicate to your audience that like, here's what we found, this was a study, it it's not like every experience, the you know, your results may vary, sort of thing, in terms of this is what the research shows, but the research is not perfect. How do you how do you communicate that to people that don't they say, oh, somebody did research, it must be true.

SPEAKER_00

So for the instance for the uh Radcliffe study, I did display the results of like, okay, you know, they're either like the same or the officers actually did a little better. But I did go into as a part of reading the full study, is going into, hey, these were the downsides of like basically kind of what I just told you of like the social workers had a lot of high turnover, they didn't have clear enough job description, not a lot of training, and these officers have had a lot of training that more than general officers do. So I brought it a point of like, if you're interested in doing this program, even though it was kind of a a null, that here's a ways that maybe you can have more success with it. I also write a lot of different one studies looking at implementation science and kind of like stepping up like law enforcement of like if you're trying to do a reform on a certain thing, hey, this is a good case study of like how to do like how to do reform, how to how to implement a solution and do it in the right way the first time. Talk more about how they did it versus the findings. Um I I kind of we'll talk more on that.

SPEAKER_01

The the last kind of like big area I want to get into is sort of near and dear to my heart, and I think you've got some experience with this, which is um police recruitment and retention. And I'll sort of set the stage for the audience. Um, I'm sure you know this, but the vast majority of police departments lost a ton of officers between 2019 and that sort of 2022 to 2023 period, and are really struggling to start to grow. And I have a substack that I'll eventually publish that it looks like they maybe started to grow a little bit in 2025, but still most big police departments are well below where they were six years ago. And obviously, from a um resource allocation standpoint, how many detectives you can put on the streets, how your response times will look, how your clearance rates will look, all of these things are impacted. Your service delivery, police departments as service delivery organizations are very much impacted by the fall of officers. I swear there's a question in this. Um What have you found? What are the the key issues facing departments? How can they start to grow and stem the tide of resignations and of and improve retention? Is is there research findings in this?

SPEAKER_00

Yeah. So there is a lot of recent stuff that's come out in terms of policing retention and even a little bit of what I've been involved in. I mean, from what I've read and from what some of the projects that I've done around police retention, the big number one is leadership. Is for one of my projects, I did a deep dive in like Glassdoor and uh Reddit data and looking at police retention and what officers were saying in regards to why are they leaving or you know, why, you know, why why they're considering and leaving and leadership, the way that leadership treats them, especially when there's an incident that happens, and then a lot of times officers feel like, oh, so-and-so was thrown under the bus as a scapegoat, or I feel like because I received a complaint, now I'm being put through the ringer, I'm I'm guilty before proof and you know, I have to prove my innocence. That kind of feeling was at least what I've been seeing is a big driver of uh retention. I know I've posted a couple studies that show that, like, you know, one of the big points for like officer wellness is like, oh, PTSD, you know, you're being exposed to very traumatic incidents, especially as a law enforcement officer, you know, that's driving that. And while that PTSD is a major component of officer wellness that needs to be considered and that needs to be um, you know, given resources for and understanding for, that these organizational factors of how your leadership is, how your scheduling is, how how safe you feel talking to your sergeant or to your lieutenant, you don't feel like your organization supports you, you're way more likely to leave. And also way more likely to feel like your PTSD symptoms like are exaggerated. There's a lot of research out there that a lot of times it's not just like, oh, it's because of what happened, they can't handle what's happening out in the field. It's actually because they don't have the support of their leadership behind them, but the support of their organization behind them that's driving them out or driving them to have, you know, burnout. Good thing is is that can be changed. I definitely had a few, a few articles on that.

SPEAKER_01

Going, you know, full into opinion mode. Do you think that it's possible for police departments to grow substantially, or is this just not an environment that's conducive to that and we have to learn to live with what we have?

SPEAKER_00

Um I mean, I would say like mass hiring, I mean never is really that good of a thing, but the way the recruit matters. And I think as far as recruitment-wise, especially with like the efforts of 30 by 30, which is if you're not aware, is you know, for in the US to get if you're a 30 by 30 agency, you're trying to get 30% of your recruits um to be women by 2030. There's a lot of different like recruitment efforts are towards that way. It's a little harder to say if there is like a growing mass that you'll be able to get to the numbers you were in 2018. I know some departments are, some departments are back to where they were. And definitely the departments that I've spoken to have either done some wellness initiatives or really made sure to keep their guys and focus on retention. And retention bonuses don't necessarily work, but you know, to make sure that their officers are heard and more of a focus on that versus recruitment. But if you're down on your officers, I mean, you need to focus on recruitment and try to focus on diversity recruitment. And there is a few studies out there, at least, that show, depending on like the videos that you have, what type of traits you show will change how what people who will apply.

SPEAKER_01

So if you're show, you know, showing a lot of the the SWAT to your your promotional video of everybody smiling and doing their hard work.

SPEAKER_00

So, you know, there is studies out there if like if you show, you know, officers who are helping the community and yeah, they are doing the smiling, like playing with the kids, but also, you know, helping the community members and showing that kind of front, you're more likely to get more women. Um, versus if you're showing the the SWAT machine and the helicopter and the guns and like, oh, we're gonna beat the bad guys, you're less likely to get women. And so, like, there's different techniques depending on who you're trying to recruit for.

SPEAKER_01

Well, that's fascinating. And uh it's all great. Um, policeresearchhub.com is the website, right?

SPEAKER_00

Yes, yes.

SPEAKER_01

Yeah. So so what's next?

SPEAKER_00

My goal is to keep continuing posting, finding all these the research articles that at least I think I find interesting, and I know hopefully other people will find interesting and keep going with that. I'm I'm also pretty prevalent on LinkedIn as well, and I will post questions to the group and see who's what's it people are interested in. And uh hopefully eventually we'll be able to do those deep dives on a single topic because that's like my next big goal that I want to do on that.

SPEAKER_01

It's wild how like each little community has found different websites now in 2026, 2025. So, yeah, it's a vibrant police research community on LinkedIn. So and you're one of the more prolific posters in talking about the research, so it's great to follow. All right, Carly, thank you so much for joining the show and uh keep up the great work. It's it's fabulous. Uh, police researchhub.com.

SPEAKER_00

Thank you for having me.

SPEAKER_01

Thanks for listening to the Jeffalytics Podcast. Be sure to subscribe and to learn more, head on over to ahdatalytics.com for more information and previous episodes. If you like what you heard, please leave a glowing review, which will help others to discover the show. Till next time, I'm Jeff Asher.