A Behavior Analysts' Journey into Data Science in Law Enforcement: A Call to Action

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Casella Jones This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7614427/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Discussion articles in behavioral sciences have been non-existent in the review of data science (DS) techniques employed overall, but more specifically for law enforcement (LE) and crime analysis. For this review, the author analyzed eight behavior science peer-reviewed journals for the presence and relevance of specific keywords to identify DS usage in law enforcement articles. Overall, this author found an underwhelming amount of DS techniques being utilized within the field and zero research articles employed specifically from a law enforcement lens. Furthermore, in 2012, it was surprising to find that keywords for DS overall began appearing the behavioral science journals, but not in the LE area. Further discussion about the results of this literature review will lead to suggestions to increase the use of DS methods in behavioral science research in LE environments. behavioral science data science law enforcement crime analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction National crime reports are essential for law enforcement (LE) agencies to have an understanding of crime rates across the country. According to the Federal Bureau of Investigation's (2024: FBI) Unformed Crime Reports (UCR) from the National Incident-Based Reporting System (NIBRS) data release from 2022 to 2023, violent crime (e.g., homicide, rape, robbery, and aggravated assault) rates has decreased by an estimate of 3% and property crime (e.g., burglary, larceny, and motor vehicle theft) rates have decreased by an estimate of 2.4%. However, motor vehicle theft did increase to 12.6% since 2022 (FBI U.S. Department of Justice, 2024).A possible solution could be to use data science (DS) methodologies as a behavioral science tool to further explain these changes in crime rates. A handful of behavioral science research efforts have addressed LE directly (e.g., Carvalho et al., 2022; Casella, 2012; Christens & Speer, 2005; Domash et al., 1980; Ghezzi et al., 2022; Gingles et al., 2022; Kirchner et al., 1980; Leland & Stockwell, 2022; Machado & Lugo, 2021; Machado et al., 2021; Mattaini & Holtschneider, 2017; Morris & Hollins, 2022; Nevin, 2018; O'Neill et al., 2018, 2019, 2019; Parks & Kirby 2022; Schnelle et al., 1975, 1977, 1978, 1979; Wilson et al., 1997), while other research articles were identified as related to LE (e.g., Crowe & Drew, 2021; De Balcazar, et al., 1988; Dixon et al., 2014; Hughes, 2009; Larson et al., 1980; Lavelle et al., 1992; Marlowe et al., 2008; McNees et al., 1976; Milan et al., 1976; Nietzel & Himelein, 1987; Niland & Ortu, 2020; Pavlacic et al., 2022; Rafacz et al., 2011; Rose et al., 2022; Rung et al., 2019; Sanguinetti & Reyes, 2011; Signal & Taylor, 2008; Van Houten & Malenfant, 2004; Weatherly & Kehn, 2013): The purpose of this literature review is to focus on how introducing DS applications into the behavioral methodologies can assist in predictive policing efforts on crime deterrence. The author analyzed these results and was able to provide data-driven conclusions on how DS was underwhelmingly represented in behavioral science literature in conjunction with LE research. Future directions are identified and reviewed in the discussion section. Method Design and Procedure A full literature review of eight behavioral science peer-reviewed literature for specific keywords present and relevant in the following journals along with the timeframes searched: Behavior Analyst (BA), Behavior Analysis in Practice (BAP), Behavior and Social Issues (BSJ), Journal of Applied Behavior Analysis (JABA), Journal of Organizational Behavior Management (JOBM), Journal of Contextual Behavioral (JOCB), Perspectives on Behavior Science (PoBS) , and The Psychological Record (TPR). The keywords used in the examinations of these peer- reviewed journals were the following: "Police", "crime", "terrorism", "law enforcement", "data science", "big data", and "machine learning". The time ranges for each peer-reviewed journal were from the journal's inception to 2022, or 45 years in total. Dependent Variables and Interobserver Agreement The dependent variable was the percentage of times a keyword was present and relevant in a peer-reviewed article. Present meaning that the specific keyword was identified but not the subject of the article. Relevant means that that specific keyword was identified and was the subject of that article. For example, the keyword of “police” was present in JOBM four articles, but relevant in three articles. This author used the present data calculations for total values and percentages for each measure for each journal and keyword. Present I (Relevant + Present ) x 100 To assess interobserver agreement (IOA), a second observer recorded data for 100% of each session. IOA was calculated separately by keywords present and relevant. Agreement was slightly higher for present keywords, ranging from 86% to 100% (M = 95%) compared to relevant keywords, ranging from 71% to 100% (M = 88%). Results Assessment Table 1 shows the number and percentage of articles found per keyword per publication. This author identified 228 articles with keywords present , only 77 in total, or 34%, were relevant to the article. Keywords across all publications are as follows: Crime was 47% presence with 8% relevance; law enforcement was 9% presence with 3% relevance; police were 30% presence with 12% relevance; terrorism was 6% presence with 4% relevance; big data 0.4% for both presence and 1 relevance; DS had 1% in presence and a 0.4% in relevance; and ML had 6% in both presence and relevance. Journal publications for all keywords presence and relevance are as follows: BA had 5% presence with 4% relevance; BAP had 11% presence and 5% relevance; BSI had 15% presence with 7% relevance; JABA had 54% present with 8% relevance; JOBM had both a 4% in presence and relevance; JOCB had 2% presence and 1% relevance; PoBS had both 4% presence and relevance; and TPR had 4% presence and 1% relevance. Dependent Variable Behavioral and Data Science Keywords Per Journal The results in Fig. 1 displays a bar plot of the percentage bins (i.e., 0–25%, 25–50%, etc.) of keywords per the years of articles were relevant in the journals selected. For example, if the keyword of "police" was relevant in JABA in 1975, then that would be counted towards the 0–25% percentage bin. It would be remiss to mention that a lack of DS key terms was used in LE compared to behavioral science. Behavioral and Data Science Journals Per Keyword The results in Fig. 2 depicts a bar plot of journals per the years of articles were relevant in the keywords selected. For example, if the JABA had relevant keywords, then that would be counted towards the 0–25% percentage bin. An item of note would be that TPR provided the most relevant keywords overall up to the 50–75% range. However, to identify which keywords were relevant , Fig. 3 provides a treemap view of the percentage of keywords per journal. For example, the large box in the top left for "crime" in Behavior Analyst (BA) indicates that "crime" was relevant to that specific journal. A notable item is that DS keywords weren't as prevalent as behavioral science across the journals identified. Meaning, that the keywords of "big data", "data science", "machine learning" were found only in BA, JABA, JOCB, PoBS , and TRP. Changes in Keywords Per Journal Overtime To dive a bit deeper, Fig. 4 provides a time series view of keywords per journal per publication year. Interesting items of note are that throughout the publication years displayed, in the years leading up to the 9/11 terrorist attacks on Manhattan, NY and the Pentagon, the keywords were more LE focused. Since then, the keyword searches haven't changed except with the addition of terrorism" post-9/11. However, in 2012, TPR was the first behavioral journal to include keywords for DS methods have increased (Ninness et al., 2012) but not related to behavioral science in LE. Out of the entirety of these results, there were no keywords in behavioral journal articles that contained any research related to behavioral and DS in LE. Discussion In this literature review, the author identified a gap in the behavioral science literature on DS techniques used in the LE area. Although several research articles focus on behavioral science in law enforcement and separately in DS research, no articles identified a research study with both a behavioral and DS purpose. This author concluded that if additional information been obtained in both behavioral and DS, the results of these behavioral law enforcement articles could have had a different outcome by using predictive methods. It was somewhat of a surprise to the author that any DS key words were found in behavioral science research at all. Although none were applicable to LE, behavioral sciences could use more DS methodologies in research studies. Turgron and Lanovaz (2020) employed a step-by-step application of using ML algorithms to address research questions, but more specifically with educators and clinicians. Future research would suggest that behavior analysts could assist in DS research by reviewing their observational data, but more focused in the LE environment. Another and the ideal area for behavioral DS is the use in national security and the Intelligence Community. Future DS research in behavioral DS could use different data sources, such as social media interactions, targeted advertising, behavioral patterns of life, immigrant border crossings, etc., to better understand their targets and dissemination throughout the IC. Once these data are collected over time, a behavioral profile will emerge, and future research should employ DS methodologies to identify these behavioral patterns. Data science ethics are also in the front for all users of DS in any environment. As Lanovaz (2022) have concerns about whom, the human or the machine, would take responsibility if the machine in use "behaved" in an odd manner. Where would a user file an ethics complaint to their certification or licensing board? Lanovaz (2022) and don't have an answer today but in future explorations can attempt to address this question. However, this research has limitations. Some behavioral articles attempted to provide some predictability but fell short of crime prediction. Possible limitations could be technology at the time of these studies was not current with today's understanding. An additional limitation could be that law enforcement agencies don't share across jurisdictional lines. Future research could remove these barriers and provide a predictive outcome for LE agencies. On limitation is that Artificial Intelligence (AI) was not one of the keywords. In Al's definition indicates a human-interactive system in which case human behavior is being observed by technology where a human would interpret the observation(s) (National Artificial Intelligence Initiative Act, 2020). AI as a keyword could be explored in future research. This author finds these results to be dishearten, but not unexpected. This is a call to action for all behavior analysts to conduct more empirical research in the area of LE and employing DS methods along the way. For those who are interested in saving the world with behavior analysis (Skinner, 1982) by doing something for your country and its LE missions, go out and explore more about DS and its overlap with behavioral science. Declarations Clinical trial number not applicable. Funding This research received no external funding. Author Contribution S.E.C.J. wrote the main manuscript text and prepared table 1 and figures 1-4. All authors reviewed the manuscript. References Carvalho, A. A. S., Mizael, T. M., & Sampaio, A. A. (2022). Racial prejudice and police stops: A systematic review of the empirical literature. Behavior Analysis in Practice, 15( 4), 1213-1220. https://psyarxiv.com/qbpv5/download?format=pdf Casella, S. (2012). A behavioral approach to modus operandi : Incident form completion and its effect on predictive analysis (Publication No. 4-2012) [Doctoral Dissertation, Western Michigan University]. Scholar Works. https://scholarworks.wmich.edu/cgi/viewcontcnt.cgi?article=l025&context=dissertations Christens, B., & Speer, P. W. (2005). Predicting violent crime using urban and suburban densities. Behavior and Social Issues , 14(2), 113-127. https://link.springer.com/content/pdf/10.5210/bsi.vl 4i2.334.pdf Crowe, B., & Drew, C. (2021). Orange is the new asylum: Incarceration of individuals with disabilities. Behavior Analysis in Practice , 14(2), 387-395. https://link.springer.com/article/10.1007/s40617-020-00533-9 De Balcazar, Y. S., Fawcett, S. B., & Balcazar, F. E. (1988). Effects of environmental design and police enforcement on violations of a handicapped parking ordinance. Journal of Applied Behavior Analysis, 21 (3), 291-298. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1286126/pdf/j aba00097-0069.pdf Dixon, M. R., Loukus, A. K., Bogdanovich, T., Doctor, K., Marlett, K., Stocks, R., & Westlake, S. (2014). Naturalistic experimental analysis of driver compliance with posted speed limits. Journal of Organizational Behavior Management, 34(3), 196-206. https://www.tandfonline.com/doi/abs/10.1080/01608061.2014.944743 Domash, M. A., Schnelle, J. F., Stromatt, E. L., Carr, A. F., Larson, L. D., Kirchner, R. E., & Risley, T. R. (1980). Police and prosecution systems: An evaluation of a police criminal case preparation program. Journal of Applied Behavior Analysis, 13(3), 397-406. https://doi.org / 10.1901/jaba.1980.13- 397 Federal Bureau of Investigation. (2024, September 23). FBI releases 2023 crime on national statistics. https://www.tbi.gov/news/press-releases/tbi-releases-2023-crime-in-the-nation­ statistics Federal Bureau of Investigation, U.S. Department of Justice. (2024, September). UCR summary of crime in the nation, 2023. Uniform Crime Reporting (UCR) Program. https://elements.visualcapitalist.com/wp- content/uploads/2024 / 09/UCR Summary of Crime in -Nation 2023.pdf Ghezzi, E. L., Funk, J. A., & Houmanfar, R. A. (2021). Restructuring law enforcement agencies to support prosocial values: A behavior-scientific model for addressing police brutality. Behavior Analysis in Practice, 1-9. https://link.springer.com/article/10.1007/s40617-020- 00530- y Gingles, D., Watson-Thompson, J., Anderson-Carpenter, K. D., Tarbox, J., & Peterson, S. M. (2022). Leading the Charge: A look inside the behavior analysis in practice emergency series of publications on systemic racism and police brutality. Behavior Analysis in Practice, 1-8. https://link.springer.com/article/I0.1007/s40617-022-00759-9 Hughes, J. (2009). A pilot study of naturally occurring high-probability request sequences in hostage negotiations. Journal of Applied Behavior Analysis, 42(2), 491-496. https://doi.org/10.1901/jaba.2009.42- 491 Kirchner, R. E., Schnelle, J. F., Domash, M., Larson, L., Carr, A., & McNees, M. P. (1980). The applicability of a helicopter patrol procedure to diverse areas: a cost-benefit evaluation. Journal of Applied Behavior Analysis, 13(1), 143-148. https://doi.org/10.190 l/jaba.1980.13-143 Lanovaz, M.J. (2022). Some characteristics and arguments in favor of a science of machine behavior analysis. Perspectives on Behavior Science, 45, 399-419. https://doi.org/10.1007/s40614-022-00332-3 Larson, L. D., Schnelle, J. F., Kirchner Jr, R., Carr, A. F., Domash, M., & Risley, T. R. (1980). Reduction of police vehicle accidents through mechanically aided supervision. Journal of Applied Behavior Analysis, 13(4), 571-581. https:// www.ncbi.nlm.nih.gov/pmc / articles / PMCl 308l 64/pdf/jaba00050-0037 .pdf Leland, W., & Stockwell, A. (2021). Anti-oppressive restorative justice: Behavior analysis in alternatives to policing. Behavior Analysis in Practice, l-5. https://psyarxiv.com/wq9g2/download?format=pdf Lavelle, J. M., Hovell, M. F., West, M. P., & Wahlgren, D. R. (1992). Promoting law enforcement for child protection: A community analysis. Journal of Applied Behavior Analysis, 25(4), 885-892. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1279773/pdtijaba00018-0134.pdf Machado, M. A., & Lugo, A. M. (2021). A behavioral analysis of two strategies to eliminate racial bias in police use of force. Behavior Analysis in Practice, 1-11. https ://www.researchgate.net/profi le / Mychal- Machado/publication/350022930 A Behavioral Analysis of Two Strategies to Elimin ate Racial Bias in Police Use of Force/links/6190a3e86l f098772093cac2/A- Behavioral-Analysis-of-Two-Strategies-to-Eliminate-Racial-Bias-in-Police-Use-of­ Force.pdf Marlowe, D. B., Festinger, D.S., Dugosh, K. L., Arabia, P. L., & Kirby, K. C. (2008). An effectiveness trial of contingency management in a felony preadjudication drug court. Journal of Applied Behavior Analysis, 41(4), 565-577. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2606594/ Mattaini, M., & Holtschneider, C. (2017). Collective leadership and circles: Not invented here. Journal of Organizational Behavior Management, 37(2), 126-141. https://doi.org/10.1080/01608061.2017.1309334 McNees, M. P., Egli, D.S., Marshall, R. S., Schnelle, J. F., & Risley, T. R. (1976). Shoplifting prevention: Providing information through signs. Journal of Applied Behavior Analysis, 9(4), 399--405. https://doi.org/10.1901/jaba.1976.9-399 Milan, M. A., & McKee, J. M. (1976). The cellblock token economy: Token reinforcement procedures in a maximum security correctional institution for adult male felons. Journal of Applied Behavior Analysis, 9(3), 253-275. https://doi.org/10.1901/jaba.1976.9-253 Morris, C., & Hollins, N. A. (2022). On the uncanny similarities between police brutality and client mistreatment. B e havior Analysis in Practice, 15(4), 1106-1111. https://psyarxiv.com/adf5m/download?format=pdf National Artificial Intelligence Initiative Act (2020). https://uscode.house.gov/view.xhtml?req=(title:15%20section:9401%20edition:prclim) Nevin, J. A. T. (2018). Variation, selection, and social action. Behavior and Social Issues, 27, AA1-AA3. https://link.springer.com/content/pdfi'l 0.5210/bsi.v27i0.8275.pdf Nietzel, M. T., & Himelein, M. J. (1987). Crime prevention through social and physical environmental change. The Behavior Analyst, 10(1), 69-74. https://doi.org/10.1007/BF03392408 Niland, H., & Ortu, D. (2020). Confessions selected by consequences: An operant analysis of false confessions and interrogation techniques. Behavior and Social Issues, 29, 162-194. https://www.researchgate.net/profile/Haven-Niland- 2/publication/338496960 Confessions Selected by Consequences An Operant Analys is of False Confessions and Interrogation Techniques/links/60b6ccde92851cde884a6f 68/Confessions-Selected-by-Consequences-An-Operant-Analysis-of-False-Confessions­ and-Interrogation-Techniques.pdf Ninness, C., Lauter, J. L., Coffee, M., Clary, L., Kelly, E., Rumph, M., Rumph, R., Kyle, B., & Ninness, S. K. (2012). Behavioral and physiological neural network analyses: A common pathway toward pattern recognition and prediction. The Psychological Record, 62( 4), 579-598. https://doi.org/10.1007/BF03395822 O'Neill, J. (2018). Functional behavior assessment of the unintentional discharge of firearms in law enforcement. Journal of Organizational Behavior Management, 38(4), 275-287. https://doi.org/10.1080/01608061.2018.1514348 O'Neill, J., O'Neill, D. A., Weed, K., Hartman, M. E., Spence, W., & Lewinski, W. J. (2019). Correction to: Police academy training, performance, and learning. Behavior Analysis in Practice, 12(2), 373-374. https://doi.org/10.1007/s40617-0l 9-00332- x O'Neill, J., O'Neill, D.A., Weed, K., Hartman, M.E., Spence, W., & Lewinski, W.J. (2019). Police academy training, performance, and learning. Behavior Analysis in Practice , 12, 353-372. https://doi.org/10.1007/s406l7-018-00317-2 Parks, N., & Kirby, B. (2022). The function of the police force: A behavior-analytic review of the history of how policing in America came to be. Behavior Analysis in Practice, 15(4), 1205-1212. https://psyarxiv.com/eqbh2/download?format=pdf Pavlacic, J.M., Kellum, K. K., & Schulenberg, S. E. (2022). Advocating for the use of restorative justice practices: Examining the overlap between restorative justice and behavior analysis. Behavior Analysis in Practice, 15(4), 1237-1246. https://link.springer.com/article/10.1007/s40617-021-00632-1 Rafacz, S. D., Boyce, T. E., & Williams, W. L. (2011). Examining the effects of a low-cost prompt to reduce retail theft. Journal of Organizational Behavior Management, 31 (2), 150-160. https://doi.org/10.1080/01608061.2011.570087 Rose, J. C., MacManus, C., MacDonald, J., & Parry-Cruwys, D. (2022). Mitigating racial inequity by addressing racism in the criminal justice system: A behavior analytic approach. Behavior Analysis in Practice, 15(2), 635-641. https://link.springer.com/article/10.1007/s40617-021-00670-9 Rung, J.M., Peck, S., Hinnenkamp, J.E., Preston, E., & Madden, G.J. (2019). Changing delay discounting and impulsive choice: Implications for addictions, prevention, and human health. Perspectives on Behavior Science, 42, 397-417. https://doi.org/10.1007/s40614-019-00200- 7 Sanguinetti, A., & Reyes, W. (2011). Functional assessment of drug trafficking terms: A substantive and methodological expansion of a verbal behavior research program. Behavior and Social Issues, 20, 102-117. https://link.springer.com/content/pdf/10.5210/bsi.v20i0.3739.pdf Schnelle, J. F., Kirchner Jr, R. E., Casey, J. D., Uselton Jr, P.H., & McNees, M. P. (1977). Patrol evaluation research: a multiple-baseline analysis of saturation police patrolling during day and night hours. Journal of Applied Beha vior Analysis, 10(1), 33-40. https://doi.org/10.1901/jaba.l 977.10-33 Schnelle, J. F., Kirchner, R. E., Galbaugh, F., Domash, M., Carr, A., & Larson, L. (1979). Program evaluation research: An experimental cost-effectiveness analysis of an armed robbery intervention program. Journal of Applied Behavior Analysis, 12(4), 615-623. https://doi.org/10.190 l/jaba.1979.12-615 Schnelle, J. F., Kirchner, R. E., Macrae, J. W., McNees, M. P., Eck, R.H., Snodgrass, S., Casey, J. D., & Uselton Jr, P.H. (1978). Police evaluation research: an experimental and cost­ benefit analysis of a helicopter patrol in a high crime area. Journal of Applied Behavior Analysis, 11 (1), 11-21. https://doi.org/10.190 l/jaba.1978.11-11 Schnelle, J. F., Kirchner, R. E., McNees, M. P., & Lawler, J.M. (1975). Social evaluation research: The evaluation of two police patrolling strategies. Journal of Applied Behavior Analysis, 8(4 ), 353-365. https://doi.org/1O. l 901/jaba.1975.8-353 Signal, T., & Taylor, N. (2008). Propensity to report intimate partner violence in Australia: Community demographics. Behavior and Social Issues, 17, 8-19. https://link.springer.com/content/pdtJ'l 0.5210/bsi.vl 7i1.1759.pdf Skinner B. F. (1982, August). Why we are not acting to save the world [Conference session]. American Psychological Association, Washington, DC, United States. http: // www.tvburkey.org / document s/ Why . pdf Turgeon, S., Lanovaz, M.J. (2020). Tutorial: Applying Machine Learning in Behavioral Research. Perspectives on Behavior Science, 43, 697-723. https://doi.org/10.1007/s40614-020-00270-y Van Houten, R., & Malenfant, J. L. (2004). Effects of a driver enforcement program on yielding to pedestrians. Journal of Applied Behavior Analysis, 37(3), 351-363. https:// www . ncbi . nlm.nih . gov / pmc / articles/PMC1284509 / pdf / 15529891.pdf Weatherly, J. N., & Kehn, A. (2013). Probability discounting of legal and non-legal scenarios: Discounting varies as a function of the outcome, the recipient's race, and the discounter's sex. Behavior and Social Issues, 22, 74-86. https://link.springer.com/content/pdf/10.5210/bsi.v22i0.4717.pdf Wilson, C., Boni, N., & Hogg, A. (1997). The effectiveness of task clarification, positive reinforcement and corrective feedback in changing courtesy among police staff. Journal of Organizational Behavior Management, 17(1), 65-99. https://doi.org/10.1300/J075vl 7n01 04 Table 1 Table 1 Percent and Number of Articles with Keywords Per Peer Reviewed Journal Note . N = l00% for present and N =3 4% for relevant. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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published.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7614427/v1/0bd94b7620cda0109555fe65.jpg"},{"id":93031510,"identity":"adbe21b5-4e74-4cb9-9513-2ea763ff6b57","added_by":"auto","created_at":"2025-10-08 10:14:01","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":66693,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003ePercent Counts of Journals Identified Per Keywords Per Year Bins\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote. \u003c/em\u003eThe percents of journal counts were binned by year published.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7614427/v1/d2af8a7fba218eaf6681f814.jpg"},{"id":93031888,"identity":"4e73a30e-df0f-4664-a4ff-ce57c3470348","added_by":"auto","created_at":"2025-10-08 10:22:01","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":171020,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003ePercentage of Keywords Per Journal Treemap\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote. \u003c/em\u003eThe larger the keyword boxes indicates the highest percentage per the journal. Conversely, the smaller the keyword box indicates a lower percentage per the journal.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7614427/v1/184b627b3991fb40a4d10c45.jpg"},{"id":93031513,"identity":"614723f0-8b37-4afe-bbea-866aeb1a7420","added_by":"auto","created_at":"2025-10-08 10:14:01","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":67168,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eTime Series Plot Depicting the Counts of Keywords per Publication Year\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote. \u003c/em\u003eThe publication years are binned in 10 publication year chunks except for the final bin which is six publication years.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7614427/v1/219ee89475236e5d107dd46f.jpg"},{"id":106961782,"identity":"ffbe36ed-a6be-4c19-b087-af6eeb450a65","added_by":"auto","created_at":"2026-04-15 09:27:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":934940,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7614427/v1/27a04015-7364-469e-8d9e-ede6d1a0b546.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Behavior Analysts' Journey into Data Science in Law Enforcement: A Call to Action","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNational crime reports are essential for law enforcement (LE) agencies to have an understanding of crime rates across the country. According to the Federal Bureau of Investigation\u0026apos;s (2024: FBI) Unformed Crime Reports (UCR) from the National Incident-Based Reporting System (NIBRS) data release from 2022 to 2023, violent crime (e.g., homicide, rape, robbery, and aggravated assault) rates has decreased by an estimate of 3% and property crime (e.g., burglary, larceny, and motor vehicle theft) rates have decreased by an estimate of 2.4%. However, motor vehicle theft did increase to 12.6% since 2022 (FBI U.S. Department of Justice, 2024).A possible solution could be to use data science (DS) methodologies as a behavioral science tool to further explain these changes in crime rates.\u003c/p\u003e\n\u003cp\u003eA handful of behavioral science research efforts have addressed LE directly (e.g., Carvalho et al., 2022; Casella, 2012; Christens \u0026amp; Speer, 2005; Domash et al., 1980; Ghezzi et al., 2022; Gingles et al., 2022; Kirchner et al., 1980; Leland \u0026amp; Stockwell, 2022; Machado \u0026amp; Lugo, 2021; Machado et al., 2021; Mattaini \u0026amp; Holtschneider, 2017; Morris \u0026amp; Hollins, 2022; Nevin, 2018; O\u0026apos;Neill et al., 2018, 2019, 2019; Parks \u0026amp; Kirby 2022; Schnelle et al., 1975, 1977, 1978, 1979; Wilson et al., 1997), while other research articles were identified as related to LE (e.g., Crowe \u0026amp; Drew, 2021; De Balcazar, et al., 1988; Dixon et al., 2014; Hughes, 2009; Larson et al., 1980; Lavelle et al., 1992; Marlowe et al., 2008; McNees et al., 1976; Milan et al., 1976; Nietzel \u0026amp; Himelein, 1987; Niland \u0026amp; Ortu, 2020; Pavlacic et al., 2022; Rafacz et al., 2011; Rose et al., 2022; Rung et al., 2019; Sanguinetti \u0026amp; Reyes, 2011; Signal \u0026amp; Taylor, 2008; Van Houten \u0026amp; Malenfant, 2004; Weatherly \u0026amp; Kehn, 2013): \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe\u0026nbsp;purpose\u0026nbsp;of\u0026nbsp;this\u0026nbsp;literature\u0026nbsp;review\u0026nbsp;is\u0026nbsp;to\u0026nbsp;focus\u0026nbsp;on\u0026nbsp;how\u0026nbsp;introducing DS\u0026nbsp;applications into the\u0026nbsp;behavioral methodologies can\u0026nbsp;assist in\u0026nbsp;predictive policing efforts on crime deterrence. The author analyzed these results and was\u0026nbsp;able\u0026nbsp;to provide data-driven conclusions on\u0026nbsp;how\u0026nbsp;DS was underwhelmingly represented in\u0026nbsp;behavioral science literature in\u0026nbsp;conjunction with LE\u0026nbsp;research.\u003c/p\u003e\n\u003cp\u003eFuture directions are identified and reviewed in the discussion section.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003ch2\u003eDesign and Procedure\u003c/h2\u003e\u003cp\u003eA full literature review of eight behavioral science peer-reviewed literature for specific keywords present and \u003cem\u003erelevant\u003c/em\u003e in the following journals along with the timeframes searched: \u003cem\u003eBehavior Analyst (BA), Behavior Analysis in Practice (BAP), Behavior and Social Issues (BSJ), Journal of Applied Behavior Analysis (JABA), Journal of Organizational Behavior Management (JOBM), Journal of Contextual Behavioral (JOCB), Perspectives on Behavior Science (PoBS)\u003c/em\u003e, and \u003cem\u003eThe Psychological Record (TPR).\u003c/em\u003e The keywords used in the examinations of these peer- reviewed journals were the following: \"Police\", \"crime\", \"terrorism\", \"law enforcement\", \"data science\", \"big data\", and \"machine learning\". The time ranges for each peer-reviewed journal were from the journal's inception to 2022, or 45 years in total.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eDependent Variables and Interobserver Agreement\u003c/h2\u003e\u003cp\u003eThe dependent variable was the percentage of times a keyword was \u003cem\u003epresent\u003c/em\u003e and \u003cem\u003erelevant\u003c/em\u003e in a peer-reviewed article. \u003cem\u003ePresent\u003c/em\u003e meaning that the specific keyword was identified but not the subject of the article. \u003cem\u003eRelevant\u003c/em\u003e means that that specific keyword was identified and was the subject of that article. For example, the keyword of \u0026ldquo;police\u0026rdquo; was \u003cem\u003epresent\u003c/em\u003e in \u003cem\u003eJOBM\u003c/em\u003e four articles, but \u003cem\u003erelevant\u003c/em\u003e in three articles. This author used the \u003cem\u003epresent\u003c/em\u003e data calculations for total values and percentages for each measure for each journal and keyword.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003ePresent I (Relevant\u003c/em\u003e\u0026thinsp;+\u0026thinsp;\u003cem\u003ePresent\u003c/em\u003e ) x 100\u003c/p\u003e\u003cp\u003eTo assess interobserver agreement (IOA), a second observer recorded data for 100% of each session. IOA was calculated separately by keywords \u003cem\u003epresent\u003c/em\u003e and \u003cem\u003erelevant.\u003c/em\u003e Agreement was slightly higher for \u003cem\u003epresent\u003c/em\u003e keywords, ranging from 86% to 100% (M\u0026thinsp;=\u0026thinsp;95%) compared to \u003cem\u003erelevant\u003c/em\u003e keywords, ranging from 71% to 100% (M\u0026thinsp;=\u0026thinsp;88%).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eAssessment\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;1 shows the number and percentage of articles found per keyword per publication. This author identified 228 articles with keywords \u003cem\u003epresent\u003c/em\u003e, only 77 in total, or 34%, were \u003cem\u003erelevant\u003c/em\u003e to the article. Keywords across all publications are as follows: Crime was 47% \u003cem\u003epresence\u003c/em\u003e with 8% \u003cem\u003erelevance;\u003c/em\u003e law enforcement was 9% \u003cem\u003epresence\u003c/em\u003e with 3% \u003cem\u003erelevance;\u003c/em\u003e police were 30% \u003cem\u003epresence\u003c/em\u003e with 12% \u003cem\u003erelevance;\u003c/em\u003e terrorism was 6% \u003cem\u003epresence\u003c/em\u003e with 4% \u003cem\u003erelevance;\u003c/em\u003e big data 0.4% for both \u003cem\u003epresence\u003c/em\u003e and 1 \u003cem\u003erelevance;\u003c/em\u003e DS had 1% in \u003cem\u003epresence\u003c/em\u003e and a 0.4% in \u003cem\u003erelevance;\u003c/em\u003e and ML had 6% in both \u003cem\u003epresence\u003c/em\u003e and \u003cem\u003erelevance.\u003c/em\u003e Journal publications for all keywords \u003cem\u003epresence\u003c/em\u003e and \u003cem\u003erelevance\u003c/em\u003e are as follows: \u003cem\u003eBA\u003c/em\u003e had 5% \u003cem\u003epresence\u003c/em\u003e with 4% \u003cem\u003erelevance; BAP\u003c/em\u003e had 11% \u003cem\u003epresence\u003c/em\u003e and 5% \u003cem\u003erelevance; BSI\u003c/em\u003e had 15% \u003cem\u003epresence\u003c/em\u003e with 7% \u003cem\u003erelevance; JABA\u003c/em\u003e had 54% present with 8% \u003cem\u003erelevance; JOBM\u003c/em\u003e had both a 4% in \u003cem\u003epresence\u003c/em\u003e and \u003cem\u003erelevance; JOCB\u003c/em\u003e had 2% \u003cem\u003epresence\u003c/em\u003e and 1% \u003cem\u003erelevance; PoBS\u003c/em\u003e had both 4% \u003cem\u003epresence\u003c/em\u003e and \u003cem\u003erelevance;\u003c/em\u003e and \u003cem\u003eTPR\u003c/em\u003e had 4% \u003cem\u003epresence\u003c/em\u003e and 1% \u003cem\u003erelevance.\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eDependent Variable\u003c/h3\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eBehavioral and Data Science Keywords Per Journal\u003c/h2\u003e\u003cp\u003eThe results in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e displays a bar plot of the percentage bins (i.e., 0\u0026ndash;25%, 25\u0026ndash;50%, etc.) of keywords per the years of articles were relevant in the journals selected. For example, if the keyword of \"police\" was \u003cem\u003erelevant\u003c/em\u003e in \u003cem\u003eJABA\u003c/em\u003e in 1975, then that would be counted towards the 0\u0026ndash;25% percentage bin. It would be remiss to mention that a lack of DS key terms was used in LE compared to behavioral science.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eBehavioral and Data Science Journals Per Keyword\u003c/h2\u003e\u003cp\u003eThe results in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e depicts a bar plot of journals per the years of articles were relevant in the keywords selected. For example, if the \u003cem\u003eJABA\u003c/em\u003e had \u003cem\u003erelevant\u003c/em\u003e keywords, then that would be counted towards the 0\u0026ndash;25% percentage bin. An item of note would be that \u003cem\u003eTPR\u003c/em\u003e provided the most \u003cem\u003erelevant\u003c/em\u003e keywords overall up to the 50\u0026ndash;75% range.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eHowever, to identify which keywords were \u003cem\u003erelevant\u003c/em\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e provides a treemap view of the percentage of keywords per journal. For example, the large box in the top left for \"crime\" in \u003cem\u003eBehavior Analyst (BA)\u003c/em\u003e indicates that \"crime\" was \u003cem\u003erelevant\u003c/em\u003e to that specific journal. A notable item is that DS keywords weren't as prevalent as behavioral science across the journals identified. Meaning, that the keywords of \"big data\", \"data science\", \"machine learning\" were found only in \u003cem\u003eBA, JABA, JOCB, PoBS\u003c/em\u003e, and \u003cem\u003eTRP.\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eChanges in Keywords Per Journal Overtime\u003c/h3\u003e\n\u003cp\u003eTo dive a bit deeper, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e provides a time series view of keywords per journal per publication year. Interesting items of note are that throughout the publication years displayed, in the years leading up to the 9/11 terrorist attacks on Manhattan, NY and the Pentagon, the keywords were more LE focused. Since then, the keyword searches haven't changed except with the addition of terrorism\" post-9/11. However, in 2012, \u003cem\u003eTPR\u003c/em\u003e was the first behavioral journal to include keywords for DS methods have increased (Ninness et al., 2012) but not related to behavioral science in LE.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eOut of the entirety of these results, there were no keywords in behavioral journal articles that contained any research related to behavioral and DS in LE.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this literature review, the author identified a gap in the behavioral science literature on DS techniques used in the LE area. Although several research articles focus on behavioral science in law enforcement and separately in DS research, no articles identified a research study with both a behavioral and DS purpose. This author concluded that if additional information\u003c/p\u003e\u003cp\u003ebeen obtained in both behavioral and DS, the results of these behavioral law enforcement articles could have had a different outcome by using predictive methods.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eIt was somewhat of a surprise to the author that any DS key words were found in\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ebehavioral science research at all. Although none were applicable to LE, behavioral sciences could use more DS methodologies in research studies. Turgron and Lanovaz (2020) employed a step-by-step application of using ML algorithms to address research questions, but more specifically with educators and clinicians. Future research would suggest that behavior analysts could assist in DS research by reviewing their observational data, but more focused in the LE environment.\u003c/p\u003e\u003cp\u003eAnother and the ideal area for behavioral DS is the use in national security and the Intelligence Community. Future DS research in behavioral DS could use different data sources, such as social media interactions, targeted advertising, behavioral patterns of life, immigrant border crossings, etc., to better understand their targets and dissemination throughout the IC. Once these data are collected over time, a behavioral profile will emerge, and future research should employ DS methodologies to identify these behavioral patterns.\u003c/p\u003e\u003cp\u003eData science ethics are also in the front for all users of DS in any environment. As Lanovaz (2022) have concerns about whom, the human or the machine, would take responsibility if the machine in use \"behaved\" in an odd manner. Where would a user file an\u003c/p\u003e\u003cp\u003eethics complaint to their certification or licensing board? Lanovaz (2022) and don't have an answer today but in future explorations can attempt to address this question.\u003c/p\u003e\u003cp\u003eHowever, this research has limitations. Some behavioral articles attempted to provide some predictability but fell short of crime prediction. Possible limitations could be technology at the time of these studies was not current with today's understanding. An additional limitation could be that law enforcement agencies don't share across jurisdictional lines. Future research could remove these barriers and provide a predictive outcome for LE agencies.\u003c/p\u003e\u003cp\u003eOn limitation is that Artificial Intelligence (AI) was not one of the keywords. In Al's definition indicates a human-interactive system in which case human behavior is being observed by technology where a human would interpret the observation(s) (National Artificial Intelligence Initiative Act, 2020). AI as a keyword could be explored in future research.\u003c/p\u003e\u003cp\u003eThis author finds these results to be dishearten, but not unexpected. This is a call to action for all behavior analysts to conduct more empirical research in the area of LE and employing DS methods along the way. For those who are interested in saving the world with behavior analysis (Skinner, 1982) by doing something for your country and its LE missions, go out and explore more about DS and its overlap with behavioral science.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eClinical trial number\u003c/h2\u003e\u003cp\u003enot applicable.\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis research received no external funding.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eS.E.C.J. wrote the main manuscript text and prepared table 1 and figures 1-4. All authors reviewed the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCarvalho, A. A. S., Mizael, T. M., \u0026amp; Sampaio, A. A. (2022). Racial prejudice and police stops: A systematic review of the empirical literature. \u003cem\u003eBehavior Analysis in Practice, 15( \u003c/em\u003e4), 1213-1220. https://psyarxiv.com/qbpv5/download?format=pdf\u003c/li\u003e\n\u003cli\u003eCasella, S. (2012). \u003cem\u003eA behavioral approach \u003c/em\u003e\u003cem\u003eto modus operandi\u003c/em\u003e\u003cem\u003e: \u003c/em\u003e\u003cem\u003eIncident form completion \u003c/em\u003e\u003cem\u003eand its \u003c/em\u003e\u003cem\u003eeffect on predictive analysis \u003c/em\u003e(Publication No. 4-2012) [Doctoral Dissertation, Western Michigan University]. Scholar Works. \u003cu\u003ehttps://scholarworks.wmich.edu/cgi/viewcontcnt.cgi?article=l025\u0026amp;context=dissertations\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eChristens, B., \u0026amp; Speer, P. W. (2005). Predicting violent crime using urban and suburban densities. \u003cem\u003eBehavior and Social Issues\u003c/em\u003e\u003cem\u003e, \u003c/em\u003e\u003cem\u003e14(2), \u003c/em\u003e113-127. https://link.springer.com/content/pdf/10.5210/bsi.vl 4i2.334.pdf\u003c/li\u003e\n\u003cli\u003eCrowe, B., \u0026amp; Drew, C. (2021). Orange is the new asylum: Incarceration of individuals with disabilities. \u003cem\u003eBehavior Analysis in \u003c/em\u003e\u003cem\u003ePractice\u003c/em\u003e\u003cem\u003e, \u003c/em\u003e\u003cem\u003e14(2), \u003c/em\u003e387-395. https://link.springer.com/article/10.1007/s40617-020-00533-9\u003c/li\u003e\n\u003cli\u003eDe Balcazar, Y. S., Fawcett, S. B., \u0026amp; Balcazar, F. E. (1988). Effects of environmental design and police enforcement on violations of a handicapped parking ordinance. \u003cem\u003eJournal of \u003c/em\u003e\u003cem\u003eApplied Behavior Analysis, 21\u003c/em\u003e(3), 291-298. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1286126/pdf/j aba00097-0069.pdf \u003c/li\u003e\n\u003cli\u003eDixon, M. R., Loukus, A. K., Bogdanovich, T., Doctor, K., Marlett, K., Stocks, R., \u0026amp; Westlake, S. (2014). Naturalistic experimental analysis of driver compliance with posted speed limits. \u003cem\u003eJournal of Organizational \u003c/em\u003e\u003cem\u003eBehavior Management, \u003c/em\u003e\u003cem\u003e34(3), \u003c/em\u003e196-206. https://www.tandfonline.com/doi/abs/10.1080/01608061.2014.944743\u003c/li\u003e\n\u003cli\u003eDomash, M. A., Schnelle, J. F., Stromatt, E. L., Carr, A. F., Larson, L. D., Kirchner, R. E., \u0026amp; Risley, T. R. (1980). Police and prosecution systems: An evaluation of a police criminal case preparation program. \u003cem\u003eJournal of Applied Behavior Analysis, 13(3), \u003c/em\u003e397-406. \u003cu\u003ehttps://doi.org\u003c/u\u003e\u003cu\u003e/\u003c/u\u003e\u003cu\u003e10.1901/jaba.1980.13-\u003c/u\u003e\u003cu\u003e397\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eFederal Bureau of Investigation. (2024, September 23). \u003cem\u003eFBI releases 2023 crime on national statistics. \u003c/em\u003e\u003cu\u003ehttps://www.tbi.gov/news/press-releases/tbi-releases-2023-crime-in-the-nation\u0026shy;\u003c/u\u003e \u003cu\u003estatistics\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eFederal Bureau of Investigation, U.S. Department of Justice. (2024, September). UCR summary of crime in the nation, 2023. Uniform Crime Reporting (UCR) Program. \u003cu\u003ehttps://elements.visualcapitalist.com/wp-\u003c/u\u003e\u003cu\u003econtent/uploads/2024\u003c/u\u003e\u003cu\u003e/\u003c/u\u003e\u003cu\u003e09/UCR Summary of Crime in -Nation 2023.pdf\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eGhezzi, E. L., Funk, J. A., \u0026amp; Houmanfar, R. A. (2021). Restructuring law enforcement agencies to support prosocial values: A behavior-scientific model for addressing police brutality. \u003cem\u003eBehavior Analysis in \u003c/em\u003e\u003cem\u003ePractice, \u003c/em\u003e1-9. \u003cu\u003ehttps://link.springer.com/article/10.1007/s40617-020-\u003c/u\u003e\u003cu\u003e00530-\u003c/u\u003e\u003cu\u003ey\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eGingles, D., Watson-Thompson, J., Anderson-Carpenter, K. D., Tarbox, J., \u0026amp; Peterson, S. M. (2022). Leading the Charge: A look inside the behavior analysis in practice emergency series of publications on systemic racism and police brutality. \u003cem\u003eBehavior Analysis in \u003c/em\u003e\u003cem\u003ePractice, \u003c/em\u003e1-8. \u003cu\u003ehttps://link.springer.com/article/I0.1007/s40617-022-00759-9\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eHughes, J. (2009). A pilot study of naturally occurring high-probability request sequences in hostage negotiations. \u003cem\u003eJournal of Applied Behavior Analysis, \u003c/em\u003e42(2), 491-496. \u003cu\u003ehttps://doi.org/10.1901/jaba.2009.42-\u003c/u\u003e\u003cu\u003e491\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eKirchner, R. E., Schnelle, J. F., Domash, M., Larson, L., Carr, A., \u0026amp; McNees, M. P. (1980). The applicability of a helicopter patrol procedure to diverse areas: a cost-benefit evaluation. \u003cem\u003eJournal of Applied Behavior Analysis, \u003c/em\u003e\u003cem\u003e13(1), \u003c/em\u003e143-148. \u003cu\u003ehttps://doi.org/10.190 l/jaba.1980.13-143\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eLanovaz, M.J. (2022). Some characteristics and arguments in favor of a science of machine behavior analysis. \u003cem\u003ePerspectives on \u003c/em\u003e\u003cem\u003eBehavior Science, \u003c/em\u003e\u003cem\u003e45, \u003c/em\u003e399-419. \u003cu\u003ehttps://doi.org/10.1007/s40614-022-00332-3\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eLarson, L. D., Schnelle, J. F., Kirchner Jr, R., Carr, A. F., Domash, M., \u0026amp; Risley, T. R. (1980). Reduction of police vehicle accidents through mechanically aided supervision. \u003cem\u003eJournal of \u003c/em\u003e\u003cem\u003eApplied \u003c/em\u003e\u003cem\u003eBehavior Analysis, 13(4), \u003c/em\u003e571-581. \u003cu\u003ehttps://\u003c/u\u003e\u003cu\u003ewww.ncbi.nlm.nih.gov/pmc\u003c/u\u003e\u003cu\u003e/\u003c/u\u003e\u003cu\u003earticles\u003c/u\u003e\u003cu\u003e/\u003c/u\u003e\u003cu\u003ePMCl 308l 64/pdf/jaba00050-0037\u003c/u\u003e\u003cu\u003e.pdf\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eLeland, W., \u0026amp; Stockwell, A. (2021). Anti-oppressive restorative justice: Behavior analysis in alternatives to policing. \u003cem\u003eBehavior \u003c/em\u003e\u003cem\u003eAnalysis in Practice, \u003c/em\u003el-5. \u003cu\u003ehttps://psyarxiv.com/wq9g2/download?format=pdf\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eLavelle, J. M., Hovell, M. F., West, M. P., \u0026amp; Wahlgren, D. R. (1992). Promoting law enforcement for child protection: A community analysis. \u003cem\u003eJournal of Applied Behavior Analysis, 25(4), \u003c/em\u003e885-892. \u003cu\u003ehttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC1279773/pdtijaba00018-0134.pdf\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eMachado, M. A., \u0026amp; Lugo, A. M. (2021). A behavioral analysis of two strategies to eliminate racial bias in police use of force. \u003cem\u003eBehavior \u003c/em\u003e\u003cem\u003eAnalysis \u003c/em\u003e\u003cem\u003ein Practice, \u003c/em\u003e1-11. \u003cu\u003ehttps\u003c/u\u003e\u003cu\u003e://www.researchgate.net/profi\u003c/u\u003e\u003cu\u003ele\u003c/u\u003e\u003cu\u003e/\u003c/u\u003e\u003cu\u003eMychal-\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003e\u003cu\u003eMachado/publication/350022930\u003c/u\u003e \u003cu\u003eA Behavioral Analysis of Two Strategies to Elimin\u003c/u\u003e\u003cu\u003eate Racial Bias in Police Use of Force/links/6190a3e86l f098772093cac2/A-\u003c/u\u003e\u003cu\u003eBehavioral-Analysis-of-Two-Strategies-to-Eliminate-Racial-Bias-in-Police-Use-of\u0026shy; \u003c/u\u003e\u003cu\u003eForce.pdf\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eMarlowe, D. B., Festinger, D.S., Dugosh, K. L., Arabia, P. L., \u0026amp; Kirby, K. C. (2008). An effectiveness trial of contingency management in a felony preadjudication drug court. \u003cem\u003eJournal of Applied Behavior Analysis, \u003c/em\u003e41(4), 565-577. \u003cu\u003ehttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC2606594/\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eMattaini, M., \u0026amp; Holtschneider, C. (2017). Collective leadership and circles: Not invented here. \u003cem\u003eJournal\u003c/em\u003e\u003cem\u003eof\u003c/em\u003e\u003cem\u003eOrganizational\u003c/em\u003e\u003cem\u003e Behavior Management, \u003c/em\u003e37(2), 126-141. \u003cu\u003ehttps://doi.org/10.1080/01608061.2017.1309334\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eMcNees, M. P., Egli, D.S., Marshall, R. S., Schnelle, J. F., \u0026amp; Risley, T. R. (1976). Shoplifting prevention: Providing information through signs. \u003cem\u003eJournal of Applied Behavior Analysis, \u003c/em\u003e\u003cem\u003e9(4), \u003c/em\u003e399--405. \u003cu\u003ehttps://doi.org/10.1901/jaba.1976.9-399\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eMilan, M. A., \u0026amp; McKee, J. M. (1976). The cellblock token economy: Token reinforcement procedures in a maximum security correctional institution for adult male felons. \u003cem\u003eJournal \u003c/em\u003e\u003cem\u003eof Applied Behavior \u003c/em\u003e\u003cem\u003eAnalysis, \u003c/em\u003e\u003cem\u003e9(3), \u003c/em\u003e253-275. \u003cu\u003ehttps://doi.org/10.1901/jaba.1976.9-253\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eMorris, C., \u0026amp; Hollins, N. A. (2022). On the uncanny similarities between police brutality and client mistreatment. \u003cem\u003eB\u003c/em\u003e\u003cem\u003ee\u003c/em\u003e\u003cem\u003ehavior Analysis in Practice, 15(4), \u003c/em\u003e1106-1111. \u003cu\u003ehttps://psyarxiv.com/adf5m/download?format=pdf\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eNational Artificial Intelligence Initiative Act (2020). \u003cu\u003ehttps://uscode.house.gov/view.xhtml?req=(title:15%20section:9401%20edition:prclim)\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eNevin, J. A. T. (2018). Variation, selection, and social action. \u003cem\u003eBehavior and Social Issues, 27, \u003c/em\u003eAA1-AA3. \u003cu\u003ehttps://link.springer.com/content/pdfi\u0026apos;l 0.5210/bsi.v27i0.8275.pdf\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eNietzel, M. T., \u0026amp; Himelein, M. J. (1987). Crime prevention through social and physical environmental change. \u003cem\u003eThe \u003c/em\u003e\u003cem\u003eBehavior \u003c/em\u003e\u003cem\u003eAnalyst, 10(1), \u003c/em\u003e69-74. \u003cu\u003ehttps://doi.org/10.1007/BF03392408\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eNiland, H., \u0026amp; Ortu, D. (2020). Confessions selected by consequences: An operant analysis of false confessions and interrogation techniques. \u003cem\u003eBehavior and \u003c/em\u003e\u003cem\u003eSocial Issues, 29, \u003c/em\u003e162-194. \u003cu\u003ehttps://www.researchgate.net/profile/Haven-Niland-\u003c/u\u003e\u003cu\u003e2/publication/338496960\u003c/u\u003e \u003cu\u003eConfessions Selected by Consequences An Operant Analys \u003c/u\u003e\u003cu\u003eis of False Confessions and Interrogation Techniques/links/60b6ccde92851cde884a6f\u003c/u\u003e\u003cu\u003e68/Confessions-Selected-by-Consequences-An-Operant-Analysis-of-False-Confessions\u0026shy;\u003c/u\u003e\u003cu\u003eand-Interrogation-Techniques.pdf\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eNinness, C., Lauter, J. L., Coffee, M., Clary, L., Kelly, E., Rumph, M., Rumph, R., Kyle, B., \u0026amp; Ninness, S. K. (2012). Behavioral and physiological neural network analyses: A common pathway toward pattern recognition and prediction. \u003cem\u003eThe Psychological Record, 62( \u003c/em\u003e4), 579-598. \u003cu\u003ehttps://doi.org/10.1007/BF03395822\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eO\u0026apos;Neill, J. (2018). Functional behavior assessment of the unintentional discharge of firearms in law enforcement. \u003cem\u003eJournal of Organizational \u003c/em\u003e\u003cem\u003eBehavior Management, \u003c/em\u003e\u003cem\u003e38(4), \u003c/em\u003e275-287. \u003cu\u003ehttps://doi.org/10.1080/01608061.2018.1514348\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eO\u0026apos;Neill, J., O\u0026apos;Neill, D. A., Weed, K., Hartman, M. E., Spence, W., \u0026amp; Lewinski, W. J. (2019). Correction to: Police academy training, performance, and learning. \u003cem\u003eBehavior Analysis \u003c/em\u003e\u003cem\u003ein \u003c/em\u003e\u003cem\u003ePractice,\u003c/em\u003e\u003cem\u003e12(2),\u003c/em\u003e373-374. \u003cu\u003ehttps://doi.org/10.1007/s40617-0l\u003c/u\u003e\u003cu\u003e9-00332-\u003c/u\u003e\u003cu\u003ex\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eO\u0026apos;Neill, J., O\u0026apos;Neill, D.A., Weed, K., Hartman, M.E., Spence, W., \u0026amp; Lewinski, W.J. (2019). Police academy training, performance, and learning. \u003cem\u003eBehavior \u003c/em\u003e\u003cem\u003eAnalysis \u003c/em\u003e\u003cem\u003ein Practice\u003c/em\u003e\u003cem\u003e, \u003c/em\u003e\u003cem\u003e12,\u003c/em\u003e353-372. \u003cu\u003ehttps://doi.org/10.1007/s406l7-018-00317-2\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eParks, N., \u0026amp; Kirby, B. (2022). The function of the police force: A behavior-analytic review of the history of how policing in America came to be. \u003cem\u003eBehavior Analysis in Practice, \u003c/em\u003e15(4), 1205-1212. \u003cu\u003ehttps://psyarxiv.com/eqbh2/download?format=pdf\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003ePavlacic, J.M., Kellum, K. K., \u0026amp; Schulenberg, S. E. (2022). Advocating for the use of restorative justice practices: Examining the overlap between restorative justice and behavior analysis. \u003cem\u003eBehavior Analysis in Practice, \u003c/em\u003e15(4), 1237-1246. \u003cu\u003ehttps://link.springer.com/article/10.1007/s40617-021-00632-1\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eRafacz, S. D., Boyce, T. E., \u0026amp; Williams, W. L. (2011). Examining the effects of a low-cost prompt to reduce retail theft. \u003cem\u003eJournal of Organizational Behavior Management, 31\u003c/em\u003e(2), 150-160. \u003cu\u003ehttps://doi.org/10.1080/01608061.2011.570087\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eRose, J. C., MacManus, C., MacDonald, J., \u0026amp; Parry-Cruwys, D. (2022). Mitigating racial inequity by addressing racism in the criminal justice system: A behavior analytic approach. \u003cem\u003eBehavior Analysis in Practice, 15(2), \u003c/em\u003e635-641. \u003cu\u003ehttps://link.springer.com/article/10.1007/s40617-021-00670-9\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eRung, J.M., Peck, S., Hinnenkamp, J.E., Preston, E., \u0026amp; Madden, G.J. (2019). Changing delay discounting and impulsive choice: Implications for addictions, prevention, and human health. \u003cem\u003ePerspectives on Behavior Science, \u003c/em\u003e\u003cem\u003e42, \u003c/em\u003e397-417. \u003cu\u003ehttps://doi.org/10.1007/s40614-019-00200- 7\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eSanguinetti, A., \u0026amp; Reyes, W. (2011). Functional assessment of drug trafficking terms: A substantive and methodological expansion of a verbal behavior research program. \u003cem\u003eBehavior and Social Issues, 20, \u003c/em\u003e102-117. \u003cu\u003ehttps://link.springer.com/content/pdf/10.5210/bsi.v20i0.3739.pdf\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eSchnelle, J. F., Kirchner Jr, R. E., Casey, J. D., Uselton Jr, P.H., \u0026amp; McNees, M. P. (1977). Patrol evaluation research: a multiple-baseline analysis of saturation police patrolling during day and night hours. \u003cem\u003eJournal of Applied Beha\u003c/em\u003e\u003cem\u003evior Analysis, 10(1), \u003c/em\u003e33-40. \u003cu\u003ehttps://doi.org/10.1901/jaba.l 977.10-33\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eSchnelle, J. F., Kirchner, R. E., Galbaugh, F., Domash, M., Carr, A., \u0026amp; Larson, L. (1979). Program evaluation research: An experimental cost-effectiveness analysis of an armed robbery intervention program. \u003cem\u003eJournal \u003c/em\u003e\u003cem\u003eof Applied \u003c/em\u003e\u003cem\u003eBehavior Analysis, 12(4), \u003c/em\u003e615-623. \u003cu\u003ehttps://doi.org/10.190 l/jaba.1979.12-615\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eSchnelle, J. F., Kirchner, R. E., Macrae, J. W., McNees, M. P., Eck, R.H., Snodgrass, S., Casey, J. D., \u0026amp; Uselton Jr, P.H. (1978). Police evaluation research: an experimental and cost\u0026shy; benefit analysis of a helicopter patrol in a high crime area. \u003cem\u003eJournal of Applied Behavior \u003c/em\u003e\u003cem\u003eAnalysis, 11\u003c/em\u003e(1), 11-21. \u003cu\u003ehttps://doi.org/10.190 l/jaba.1978.11-11\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eSchnelle, J. F., Kirchner, R. E., McNees, M. P., \u0026amp; Lawler, J.M. (1975). Social evaluation research: The evaluation of two police patrolling strategies. \u003cem\u003eJournal of Applied Behavior \u003c/em\u003e\u003cem\u003eAnalysis, 8(4\u003c/em\u003e), 353-365. \u003cu\u003ehttps://doi.org/1O. l 901/jaba.1975.8-353\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eSignal, T., \u0026amp; Taylor, N. (2008). Propensity to report intimate partner violence in Australia: Community demographics. \u003cem\u003eBehavior \u003c/em\u003e\u003cem\u003eand Social \u003c/em\u003e\u003cem\u003eIssues, 17, \u003c/em\u003e8-19. \u003cu\u003ehttps://link.springer.com/content/pdtJ\u0026apos;l 0.5210/bsi.vl 7i1.1759.pdf\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eSkinner B. F. (1982, August). \u003cem\u003eWhy \u003c/em\u003e\u003cem\u003ewe \u003c/em\u003e\u003cem\u003eare \u003c/em\u003e\u003cem\u003enot acting to \u003c/em\u003e\u003cem\u003esave the \u003c/em\u003e\u003cem\u003eworld \u003c/em\u003e[Conference session]. American Psychological Association, Washington, DC, United States. \u003cu\u003ehttp:\u003c/u\u003e\u003cu\u003e//\u003c/u\u003e\u003cu\u003ewww.tvburkey.org\u003c/u\u003e\u003cu\u003e/\u003c/u\u003e\u003cu\u003edocument\u003c/u\u003e\u003cu\u003es/\u003c/u\u003e\u003cu\u003eWhy\u003c/u\u003e\u003cu\u003e.\u003c/u\u003e\u003cu\u003epdf\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eTurgeon, S., Lanovaz, M.J. (2020). Tutorial: Applying Machine Learning in Behavioral Research. \u003cem\u003ePerspectives on Behavior Science, 43, \u003c/em\u003e697-723. \u003cu\u003ehttps://doi.org/10.1007/s40614-020-00270-y\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eVan Houten, R., \u0026amp; Malenfant, J. L. (2004). Effects of a driver enforcement program on yielding to pedestrians. \u003cem\u003eJournal of \u003c/em\u003e\u003cem\u003eApplied \u003c/em\u003e\u003cem\u003eBehavior \u003c/em\u003e\u003cem\u003eAnalysis, \u003c/em\u003e37(3), 351-363. \u003cu\u003ehttps://\u003c/u\u003e\u003cu\u003ewww\u003c/u\u003e\u003cu\u003e.\u003c/u\u003e\u003cu\u003encbi\u003c/u\u003e\u003cu\u003e.\u003c/u\u003e\u003cu\u003enlm.nih\u003c/u\u003e\u003cu\u003e.\u003c/u\u003e\u003cu\u003egov\u003c/u\u003e\u003cu\u003e/\u003c/u\u003e\u003cu\u003epmc\u003c/u\u003e\u003cu\u003e/\u003c/u\u003e\u003cu\u003earticles/PMC1284509\u003c/u\u003e\u003cu\u003e/\u003c/u\u003e\u003cu\u003epdf\u003c/u\u003e\u003cu\u003e/\u003c/u\u003e\u003cu\u003e15529891.pdf\u003c/u\u003e \u003c/li\u003e\n\u003cli\u003eWeatherly, J. N., \u0026amp; Kehn, A. (2013). Probability discounting of legal and non-legal scenarios: Discounting varies as a function of the outcome, the recipient\u0026apos;s race, and the discounter\u0026apos;s sex. \u003cem\u003eBehavior and Social Issues, 22, \u003c/em\u003e74-86. \u003cu\u003ehttps://link.springer.com/content/pdf/10.5210/bsi.v22i0.4717.pdf\u003c/u\u003e\u003c/li\u003e\n\u003cli\u003eWilson, C., Boni, N., \u0026amp; Hogg, A. (1997). The effectiveness of task clarification, positive reinforcement and corrective feedback in changing courtesy among police staff. \u003cem\u003eJournal of Organizational Behavior Management, \u003c/em\u003e17(1), 65-99. \u003cu\u003ehttps://doi.org/10.1300/J075vl 7n01 04\u003c/u\u003e\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 1","content":"\u003cp\u003eTable 1\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePercent and\u0026nbsp;\u003c/em\u003e\u003cem\u003eNumber\u0026nbsp;\u003c/em\u003e\u003cem\u003eof Articles\u0026nbsp;\u003c/em\u003e\u003cem\u003ewith\u0026nbsp;\u003c/em\u003e\u003cem\u003eKeywords\u0026nbsp;\u003c/em\u003e\u003cem\u003ePer Peer\u0026nbsp;\u003c/em\u003e\u003cem\u003eReviewed Journal\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cimg width=\"588\" height=\"334\" 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analysis","lastPublishedDoi":"10.21203/rs.3.rs-7614427/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7614427/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDiscussion articles in behavioral sciences have been non-existent in the review of data science (DS) techniques employed overall, but more specifically for law enforcement (LE) and crime analysis. For this review, the author analyzed eight behavior science peer-reviewed journals for the \u003cem\u003epresence\u003c/em\u003e and \u003cem\u003erelevance\u003c/em\u003e of specific keywords to identify DS usage in law enforcement articles. Overall, this author found an underwhelming amount of DS techniques being utilized within the field and zero research articles employed specifically from a law enforcement lens. Furthermore, in 2012, it was surprising to find that keywords for DS overall began appearing the behavioral science journals, but not in the LE area. Further discussion about the results of this literature review will lead to suggestions to increase the use of DS methods in behavioral science research in LE environments.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e","manuscriptTitle":"A Behavior Analysts' Journey into Data Science in Law Enforcement: A Call to Action","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-08 10:13:57","doi":"10.21203/rs.3.rs-7614427/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5181e3f6-b8f4-49f4-9f6e-e77184fd1447","owner":[],"postedDate":"October 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-15T00:09:09+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-08 10:13:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7614427","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7614427","identity":"rs-7614427","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}