{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T02:48:23Z","timestamp":1776134903479,"version":"3.50.1"},"reference-count":111,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2023,3,15]],"date-time":"2023-03-15T00:00:00Z","timestamp":1678838400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,3,15]],"date-time":"2023-03-15T00:00:00Z","timestamp":1678838400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Artif Intell Law"],"published-print":{"date-parts":[[2024,6]]},"DOI":"10.1007\/s10506-023-09352-z","type":"journal-article","created":{"date-parts":[[2023,3,15]],"date-time":"2023-03-15T17:03:06Z","timestamp":1678899786000},"page":"369-395","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Predicting inmates misconduct using the SHAP approach"],"prefix":"10.1007","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2075-4945","authenticated-orcid":false,"given":"F\u00e1bio M.","family":"Oliveira","sequence":"first","affiliation":[]},{"given":"Marcelo S.","family":"Balbino","sequence":"additional","affiliation":[]},{"given":"Luis E.","family":"Zarate","sequence":"additional","affiliation":[]},{"given":"Fawn","family":"Ngo","sequence":"additional","affiliation":[]},{"given":"Ramakrishna","family":"Govindu","sequence":"additional","affiliation":[]},{"given":"Anurag","family":"Agarwal","sequence":"additional","affiliation":[]},{"given":"Cristiane N.","family":"Nobre","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,3,15]]},"reference":[{"issue":"103","key":"9352_CR1","first-page":"502","volume":"298","author":"K Aas","year":"2021","unstructured":"Aas K, Jullum M, L\u00f8land A (2021) Explaining individual predictions when features are dependent: more accurate approximations to shapley values. Artif Intell 298(103):502","journal-title":"Artif Intell"},{"key":"9352_CR2","doi-asserted-by":"publisher","first-page":"52,138","DOI":"10.1109\/ACCESS.2018.2870052","volume":"6","author":"A Adadi","year":"2018","unstructured":"Adadi A, Berrada M (2018) Peeking inside the black-box: A survey on explainable artificial intelligence (XAI). IEEE Access 6:52,138-52,160","journal-title":"IEEE Access"},{"key":"9352_CR3","unstructured":"Alper M, Durose MR, Markman J (2018) 2018 update on prisoner recidivism: A 9-year follow-up period (2005-2014). Tech. rep., U.S. Department of Justice - Office of Justice Programs - Bureau of Justice Statistics, https:\/\/www.bjs.gov\/index.cfm?ty=pbdetail &iid=6266"},{"key":"9352_CR4","first-page":"1","volume":"21","author":"RA Augustyn","year":"2020","unstructured":"Augustyn RA, ten Bensel T, Lytle RD et al (2020) \u201cOlder\u2019\u2019 inmates in prison: considering the tipping point of age and misconduct. Criminol Crim Just L & Soc\u2019y 21:1","journal-title":"Criminol Crim Just L & Soc\u2019y"},{"key":"9352_CR5","doi-asserted-by":"publisher","DOI":"10.21202\/1993-047X.12.2018.1.132-148","author":"K Bell","year":"2018","unstructured":"Bell K (2018) Prison violence and the intersectionality of race\/ethnicity and gender. Actual Prob Econ Law. https:\/\/doi.org\/10.21202\/1993-047X.12.2018.1.132-148","journal-title":"Actual Prob Econ Law"},{"key":"9352_CR6","unstructured":"Benecchi L (2021) Recidivism imprisons american progress. https:\/\/harvardpolitics.com\/recidivism-american-progress"},{"issue":"2","key":"9352_CR7","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1007\/s10940-006-9005-z","volume":"22","author":"RA Berk","year":"2006","unstructured":"Berk RA, Kriegler B, Baek JH (2006) Forecasting dangerous inmate misconduct: an application of ensemble statistical procedures. J Quant Criminol 22(2):131\u2013145. https:\/\/doi.org\/10.1007\/s10940-006-9005-z","journal-title":"J Quant Criminol"},{"issue":"4","key":"9352_CR8","doi-asserted-by":"publisher","first-page":"1269","DOI":"10.1086\/705330","volume":"128","author":"M Bhuller","year":"2020","unstructured":"Bhuller M, Dahl GB, L\u00f8ken KV et al (2020) Incarceration, recidivism, and employment. J Polit Econ 128(4):1269\u20131324","journal-title":"J Polit Econ"},{"issue":"1","key":"9352_CR9","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1080\/1537sps7938.2016.1261058","volume":"15","author":"HS Bonner","year":"2017","unstructured":"Bonner HS, Rodriguez FA, Sorensen JR (2017) Race, ethnicity, and prison disciplinary misconduct. J Ethn Crim Justice 15(1):36\u201351. https:\/\/doi.org\/10.1080\/1537sps7938.2016.1261058","journal-title":"J Ethn Crim Justice"},{"issue":"4","key":"9352_CR10","doi-asserted-by":"publisher","first-page":"292","DOI":"10.1080\/23774657.2018.1542284","volume":"5","author":"EJ Brooke","year":"2020","unstructured":"Brooke EJ (2020) Service experience varies: exploring the association between military service and prison misconduct among state inmates. Corrections 5(4):292\u2013313. https:\/\/doi.org\/10.1080\/23774657.2018.1542284","journal-title":"Corrections"},{"issue":"1","key":"9352_CR11","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1177\/0887403415619007","volume":"29","author":"EJ Brooke","year":"2018","unstructured":"Brooke EJ, Gau JM (2018) Military service and lifetime arrests: examining the effects of the total military experience on arrests in a sample of prison inmates. Crim Justice Policy Rev 29(1):24\u201344. https:\/\/doi.org\/10.1177\/0887403415619007","journal-title":"Crim Justice Policy Rev"},{"key":"9352_CR12","doi-asserted-by":"publisher","DOI":"10.1111\/j.1745-9133.2012.00786.x","author":"S Bushway","year":"2012","unstructured":"Bushway S, Apel R (2012) A signaling perspective on employment-based reentry programming. Criminol Public Policy. https:\/\/doi.org\/10.1111\/j.1745-9133.2012.00786.x","journal-title":"Criminol Public Policy"},{"key":"9352_CR13","doi-asserted-by":"publisher","DOI":"10.1016\/j.avb.2020.101520","volume":"60","author":"HD Butler","year":"2021","unstructured":"Butler HD, Caudill JW, Craig JM et al (2021) 99 percenters: an examination of the misconduct careers of the most violent and disruptive incarcerated delinquents. Aggress Viol Behav 60:101520. https:\/\/doi.org\/10.1016\/j.avb.2020.101520","journal-title":"Aggress Viol Behav"},{"key":"9352_CR14","doi-asserted-by":"publisher","first-page":"389","DOI":"10.1016\/j.jcrimjus.2008.07.004","volume":"36","author":"SD Camp","year":"2008","unstructured":"Camp SD, Daggett D, Kwon O et al (2008) The effect of faith program participation on prison misconduct: The life connections program. J Crim Just 36:389\u2013395. https:\/\/doi.org\/10.1016\/j.jcrimjus.2008.07.004","journal-title":"J Crim Just"},{"issue":"8","key":"9352_CR15","doi-asserted-by":"publisher","first-page":"832","DOI":"10.3390\/electronics8080832","volume":"8","author":"DV Carvalho","year":"2019","unstructured":"Carvalho DV, Pereira EM, Cardoso JS (2019) Machine learning interpretability: a survey on methods and metrics. Electronics 8(8):832","journal-title":"Electronics"},{"issue":"14","key":"9352_CR16","doi-asserted-by":"publisher","first-page":"2406","DOI":"10.1177\/0306624X19849565","volume":"63","author":"A Cihan","year":"2019","unstructured":"Cihan A, Sorensen JR (2019) Examining developmental patterns of prison misconduct: An integrated model approach. Int J Offender Ther Comp Criminol 63(14):2406\u20132421. https:\/\/doi.org\/10.1177\/0306624X19849565. (pMID: 31088194)","journal-title":"Int J Offender Ther Comp Criminol"},{"issue":"4","key":"9352_CR17","doi-asserted-by":"publisher","first-page":"431","DOI":"10.1177\/0032885517711420","volume":"97","author":"A Cihan","year":"2017","unstructured":"Cihan A, Davidson M, Sorensen J (2017) Analyzing the heterogeneous nature of inmate behavior: trajectories of prison misconduct. Prison J 97(4):431\u2013450. https:\/\/doi.org\/10.1177\/0032885517711420","journal-title":"Prison J"},{"issue":"9","key":"9352_CR18","doi-asserted-by":"publisher","first-page":"1363","DOI":"10.1177\/0093854818766974","volume":"45","author":"K Clark","year":"2018","unstructured":"Clark K (2018) The effect of mental illness on segregation following institutional misconduct. Crim Justice Behav 45(9):1363\u20131382. https:\/\/doi.org\/10.1177\/0093854818766974","journal-title":"Crim Justice Behav"},{"issue":"6","key":"9352_CR19","doi-asserted-by":"publisher","first-page":"1044","DOI":"10.1080\/07418825.2012.736526","volume":"31","author":"JC Cochran","year":"2014","unstructured":"Cochran JC, Mears DP, Bales WD et al (2014) Does inmate behavior affect post-release offending? investigating the misconduct-recidivism relationship among youth and adults. Justice Q 31(6):1044\u20131073. https:\/\/doi.org\/10.1080\/07418825.2012.736526","journal-title":"Justice Q"},{"issue":"4","key":"9352_CR20","doi-asserted-by":"publisher","first-page":"426","DOI":"10.1177\/1043986216672770","volume":"32","author":"DP Connor","year":"2016","unstructured":"Connor DP, Tewksbury R (2016) Inmates and prison involvement with drugs: examining drug-related misconduct during incarceration. J Contemp Crim Justice 32(4):426\u2013445. https:\/\/doi.org\/10.1177\/1043986216672770","journal-title":"J Contemp Crim Justice"},{"key":"9352_CR21","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/15564886.2011.534005","volume":"6","author":"H Copes","year":"2011","unstructured":"Copes H, Higgins G, Tewksbury R et al (2011) Participation in the prison economy and likelihood of physical victimization. Vict Offenders 6:1\u201318. https:\/\/doi.org\/10.1080\/15564886.2011.534005","journal-title":"Vict Offenders"},{"key":"9352_CR22","doi-asserted-by":"publisher","DOI":"10.1016\/j.avb.2019.06.002","volume":"49","author":"JM Craig","year":"2019","unstructured":"Craig JM, Trulson CR (2019) Continuity of the delinquent career behind bars: predictors of violent misconduct among female delinquents. Aggress Violent Behav 49:101,301. https:\/\/doi.org\/10.1016\/j.avb.2019.06.002","journal-title":"Aggress Violent Behav"},{"key":"9352_CR23","volume-title":"Inmate misconduct and victimization: investigating the changes over time and if the risk factors are invariant across age and victim-offender status","author":"JC Daquin","year":"2017","unstructured":"Daquin JC (2017) Inmate misconduct and victimization: investigating the changes over time and if the risk factors are invariant across age and victim-offender status. Dissertation, Georgia State University, Georgia, United States"},{"issue":"8","key":"9352_CR24","doi-asserted-by":"publisher","first-page":"1186","DOI":"10.1177\/0306624X11383956","volume":"55","author":"M DeLisi","year":"2011","unstructured":"DeLisi M, Trulson CR, Marquart JW et al (2011) Inside the prison black box: toward a life course importation model of inmate behavior. Int J Offender Ther Comp Criminol 55(8):1186\u20131207. https:\/\/doi.org\/10.1177\/0306624X11383956","journal-title":"Int J Offender Ther Comp Criminol"},{"key":"9352_CR25","doi-asserted-by":"publisher","DOI":"10.1007\/s12103-012-9196-9","author":"M Delisi","year":"2013","unstructured":"Delisi M, Spruill J, Peters D et al (2013) Half in, Half out: gang families, gang affiliation, and gang misconduct. Am J Crim Justice. https:\/\/doi.org\/10.1007\/s12103-012-9196-9","journal-title":"Am J Crim Justice"},{"issue":"10","key":"9352_CR26","first-page":"21","volume":"10","author":"M Denny","year":"2016","unstructured":"Denny M (2016) Norway\u2019s prison system: investigating recidivism and reintegration. Bridges J Stud Res 10(10):21\u201337","journal-title":"Bridges J Stud Res"},{"issue":"3","key":"9352_CR27","doi-asserted-by":"publisher","first-page":"332","DOI":"10.1177\/1477370815617191","volume":"13","author":"C D\u00e2mboeanu","year":"2016","unstructured":"D\u00e2mboeanu C, Nieuwbeerta P (2016) Importation and deprivation correlates of misconduct among romanian inmates. Eur J Criminol 13(3):332\u2013351. https:\/\/doi.org\/10.1177\/1477370815617191","journal-title":"Eur J Criminol"},{"issue":"8","key":"9352_CR28","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1177\/0011128719833359","volume":"66","author":"L Drakeford","year":"2020","unstructured":"Drakeford L (2020) Moral communities and institutional misconduct: a reassessment of religious contextual influences on inmate behavior. Crime Delinq 66(8):1137\u20131160. https:\/\/doi.org\/10.1177\/0011128719833359","journal-title":"Crime Delinq"},{"issue":"2","key":"9352_CR29","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1177\/0032885519894587","volume":"100","author":"G Duwe","year":"2020","unstructured":"Duwe G (2020) The development and validation of a classification system predicting severe and frequent prison misconduct. Prison J 100(2):173\u2013200. https:\/\/doi.org\/10.1177\/0032885519894587","journal-title":"Prison J"},{"key":"9352_CR30","doi-asserted-by":"publisher","first-page":"454","DOI":"10.1177\/0032885514548009","volume":"94","author":"G Duwe","year":"2014","unstructured":"Duwe G, Clark V (2014) The effects of prison-based educational programming on recidivism and employment. Prison J 94:454\u2013478. https:\/\/doi.org\/10.1177\/0032885514548009","journal-title":"Prison J"},{"issue":"11","key":"9352_CR31","doi-asserted-by":"publisher","first-page":"1723","DOI":"10.1177\/0093854818788590","volume":"45","author":"JM Ellison","year":"2018","unstructured":"Ellison JM, Steiner B, Wright EM (2018) Examining the sources of violent victimization among jail inmates. Crim Justice Behav 45(11):1723\u20131741. https:\/\/doi.org\/10.1177\/0093854818788590","journal-title":"Crim Justice Behav"},{"issue":"4","key":"9352_CR32","doi-asserted-by":"publisher","first-page":"1633","DOI":"10.1111\/coin.12410","volume":"37","author":"R ElShawi","year":"2020","unstructured":"ElShawi R, Sherif Y, Al-Mallah M et al (2020) Interpretability in healthcare: a comparative study of local machine learning interpretability techniques. Comput Intell 37(4):1633\u20131650","journal-title":"Comput Intell"},{"key":"9352_CR33","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/13218719.2016.1247419","volume":"24","author":"A Garc\u00eda-Gomis","year":"2016","unstructured":"Garc\u00eda-Gomis A, Villanueva L, Jara P (2016) Risk factors and youth recidivism prediction in general and property offenders. Psychiatry Psychol Law 24:1\u201311. https:\/\/doi.org\/10.1080\/13218719.2016.1247419","journal-title":"Psychiatry Psychol Law"},{"key":"9352_CR34","doi-asserted-by":"publisher","unstructured":"Gilpin LH, Bau D, Yuan BZ, et\u00a0al (2018) Explaining explanations: an overview of interpretability of machine learning. In: 2018 IEEE 5th international conference on data science and advanced analytics (DSAA), IEEE, pp 80\u201389, https:\/\/doi.org\/10.48550\/arXiv.1806.00069","DOI":"10.48550\/arXiv.1806.00069"},{"issue":"1","key":"9352_CR35","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1080\/07418825.2018.1495251","volume":"37","author":"E Glazener","year":"2020","unstructured":"Glazener E, Nakamura K (2020) Examining the link between prison crowding and inmate misconduct: evidence from prison-level panel data. Justice Q 37(1):109\u2013131. https:\/\/doi.org\/10.1080\/07418825.2018.1495251","journal-title":"Justice Q"},{"key":"9352_CR36","unstructured":"Gomes LF (2012) Noruega como modelo de reabilita\u00e7\u00e3o de criminosos. https:\/\/professorlfg.jusbrasil.com.br\/artigos\/121932086\/noruega-como-modelo-de-reabilitacao-de-criminosos"},{"issue":"3","key":"9352_CR37","doi-asserted-by":"publisher","first-page":"378","DOI":"10.1177\/0032885508322453","volume":"88","author":"AR Gover","year":"2008","unstructured":"Gover AR, P\u00e9rez DM, Jennings WG (2008) Gender differences in factors contributing to institutional misconduct. Prison J 88(3):378\u2013403. https:\/\/doi.org\/10.1177\/0032885508322453","journal-title":"Prison J"},{"key":"9352_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcrimjus.2021.101797","volume":"74","author":"JM Grosholz","year":"2021","unstructured":"Grosholz JM, Semenza DC (2021) Health conditions and victimization among incarcerated individuals in US jails. J Crim Justice 74:101,797. https:\/\/doi.org\/10.1016\/j.jcrimjus.2021.101797","journal-title":"J Crim Justice"},{"issue":"3","key":"9352_CR39","doi-asserted-by":"publisher","first-page":"271","DOI":"10.1177\/0093854819896844","volume":"47","author":"BF Henry","year":"2020","unstructured":"Henry BF (2020) Adversity, mental health, and substance use disorders as predictors and mediators of rule violations in US prisons. Crim Justice Behav 47(3):271\u2013289. https:\/\/doi.org\/10.1177\/0093854819896844","journal-title":"Crim Justice Behav"},{"key":"9352_CR40","first-page":"4778","volume":"33","author":"T Heskes","year":"2020","unstructured":"Heskes T, Sijben E, Bucur IG et al (2020) Causal shapley values: exploiting causal knowledge to explain individual predictions of complex models. Adv Neural Inf Process Syst 33:4778\u20134789","journal-title":"Adv Neural Inf Process Syst"},{"issue":"8","key":"9352_CR41","doi-asserted-by":"publisher","first-page":"1340","DOI":"10.1093\/arclin\/acz003","volume":"34","author":"KC Hewitt","year":"2019","unstructured":"Hewitt KC, Cody MW, Marker CD et al (2019) General educational development (GED) and educational attainment equivalency for demographically adjusted norms. Arch Clin Neuropsychol 34(8):1340\u20131345. https:\/\/doi.org\/10.1093\/arclin\/acz003","journal-title":"Arch Clin Neuropsychol"},{"key":"9352_CR42","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/23774657.2016.1214934","volume":"1","author":"C Hilinski-Rosick","year":"2016","unstructured":"Hilinski-Rosick C, Freiburger T (2016) Examining the correlates of prison misconduct among elderly inmates. Corrections 1:1\u201314. https:\/\/doi.org\/10.1080\/23774657.2016.1214934","journal-title":"Corrections"},{"issue":"5","key":"9352_CR43","doi-asserted-by":"publisher","first-page":"650","DOI":"10.1177\/0093854814521195","volume":"41","author":"KA Houser","year":"2014","unstructured":"Houser KA, Welsh W (2014) Examining the association between co-occurring disorders and seriousness of misconduct by female prison inmates. Crim Justice Behav 41(5):650\u2013666. https:\/\/doi.org\/10.1177\/0093854814521195","journal-title":"Crim Justice Behav"},{"key":"9352_CR44","unstructured":"Jaeger BC, Tierney NJ, Simon N (2020) When to impute? imputation before and during cross-validation. ArXiv:2010.00718"},{"key":"9352_CR45","doi-asserted-by":"publisher","DOI":"10.1080\/23774657.2017.1384707","author":"SJ Jang","year":"2017","unstructured":"Jang SJ, Johnson B, Hays J et al (2017) Images of god, religious involvement, and prison misconduct among inmates images of god, religious involvement, and prison misconduct among inmates. Correct Policy Pract Res. https:\/\/doi.org\/10.1080\/23774657.2017.1384707","journal-title":"Correct Policy Pract Res"},{"issue":"2","key":"9352_CR46","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1016\/j.jcrimjus.2004.12.007","volume":"33","author":"S Jiang","year":"2005","unstructured":"Jiang S (2005) Impact of drug use on inmate misconduct: a multilevel analysis. J Crim Justice 33(2):153\u2013163. https:\/\/doi.org\/10.1016\/j.jcrimjus.2004.12.007","journal-title":"J Crim Justice"},{"key":"9352_CR47","unstructured":"Johnson B (2019) Do criminal laws deter crime? deterrence theory in criminal justice policy: a primer. https:\/\/www.house.leg.state.mn.us\/hrd\/pubs\/deterrence.pdf"},{"key":"9352_CR48","doi-asserted-by":"publisher","unstructured":"of\u00a0Justice\u00a0Statistics USB (2019) Survey of inmates in state and federal correctional facilities, [united states], 2004. https:\/\/doi.org\/10.3886\/ICPSR04572.v6","DOI":"10.3886\/ICPSR04572.v6"},{"key":"9352_CR49","doi-asserted-by":"publisher","unstructured":"of\u00a0Justice\u00a0Statistics USB (2021) Survey of prison inmates, united states, 2016. https:\/\/doi.org\/10.3886\/ICPSR37692.v4","DOI":"10.3886\/ICPSR37692.v4"},{"key":"9352_CR50","series-title":"Methods and algorithms","volume-title":"Data mining: concepts, models","author":"M Kantardzic","year":"2002","unstructured":"Kantardzic M (2002) Data mining: concepts, models. Methods and algorithms. John Wiley & Sons Inc, New York"},{"key":"9352_CR51","unstructured":"Karim A, Mishra A, Newton M, et\u00a0al (2018) Machine learning interpretability: a science rather than a tool. arXiv preprint arXiv:1807.06722"},{"key":"9352_CR52","unstructured":"Kovacs M (2003) Children\u2019s depression inventory (CDI): technical manual update. Multi-health systems, Incorporated, https:\/\/books.google.com.br\/books?id=fZN5tAEACAAJ"},{"issue":"1","key":"9352_CR53","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1080\/14786010801972662","volume":"21","author":"A Kuanliang","year":"2008","unstructured":"Kuanliang A, Sorensen J (2008) Predictors of self-reported prison misconduct. Crim Justice Stud 21(1):27\u201335. https:\/\/doi.org\/10.1080\/14786010801972662","journal-title":"Crim Justice Stud"},{"issue":"9","key":"9352_CR54","doi-asserted-by":"publisher","first-page":"953","DOI":"10.1177\/0306624X19895969","volume":"64","author":"SY Kuo","year":"2020","unstructured":"Kuo SY (2020) The effects of mental health and substance abuse\/dependence disorders on prison misconduct among male inmates in taiwan. Int J Offender Ther Comp Criminol 64(9):953\u2013976. https:\/\/doi.org\/10.1177\/0306624X19895969. (pMID: 31884841)","journal-title":"Int J Offender Ther Comp Criminol"},{"key":"9352_CR55","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1080\/10509670802572235","volume":"48","author":"K Lahm","year":"2009","unstructured":"Lahm K (2009) Educational participation and inmate misconduct. J Offender Rehabil 48:37\u201352. https:\/\/doi.org\/10.1080\/10509670802572235","journal-title":"J Offender Rehabil"},{"key":"9352_CR56","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1300\/J076v34n02_02","volume":"34","author":"NP Langan","year":"2001","unstructured":"Langan NP, Pelissier BMM (2001) The effect of drug treatment on inmate misconduct in federal prisons. J Offender Rehabil 34:21\u201330. https:\/\/doi.org\/10.1300\/J076v34n02_02","journal-title":"J Offender Rehabil"},{"issue":"1","key":"9352_CR57","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1525\/fsr.2002.15.1.58","volume":"15","author":"PA Langan","year":"2002","unstructured":"Langan PA, Levin DJ (2002) Recidivism of prisoners released in 1994. Federal Sentenc Rep 15(1):58\u201365","journal-title":"Federal Sentenc Rep"},{"issue":"3","key":"9352_CR58","doi-asserted-by":"publisher","first-page":"343","DOI":"10.1177\/0032885519837532","volume":"99","author":"ME Leigey","year":"2019","unstructured":"Leigey ME (2019) Female institutional misconduct: a test of deprivation, importation, and gendered importation theories. Prison J 99(3):343\u2013362. https:\/\/doi.org\/10.1177\/0032885519837532","journal-title":"Prison J"},{"key":"9352_CR59","unstructured":"Lundberg SM, Lee SI (2017) A unified approach to interpreting model predictions. In: Proceedings of the 31st international conference on neural information processing systems, pp 4768\u20134777"},{"key":"9352_CR60","doi-asserted-by":"publisher","first-page":"1058","DOI":"10.3102\/0002831211405836","volume":"48","author":"V Maralani","year":"2011","unstructured":"Maralani V (2011) From ged to college: age trajectories of nontraditional educational paths. Am Educ Res J 48:1058\u20131090. https:\/\/doi.org\/10.3102\/0002831211405836","journal-title":"Am Educ Res J"},{"key":"9352_CR61","doi-asserted-by":"publisher","DOI":"10.1177\/0887403416628600","author":"D May","year":"2016","unstructured":"May D, Stives K, Wells M et al (2016) Does military service make the experience of prison less painful? voices from incarcerated veterans. Crim Justice Policy Rev. https:\/\/doi.org\/10.1177\/0887403416628600","journal-title":"Crim Justice Policy Rev"},{"key":"9352_CR62","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcrimjus.2022.101883","volume":"78","author":"S McNeeley","year":"2022","unstructured":"McNeeley S (2022) Reaffirming the relationship between routine activities and violent victimization in prison. J Crim Justice 78:101,883. https:\/\/doi.org\/10.1016\/j.jcrimjus.2022.101883","journal-title":"J Crim Justice"},{"issue":"12","key":"9352_CR63","doi-asserted-by":"publisher","first-page":"1856","DOI":"10.1177\/0011128720977440","volume":"67","author":"B Meade","year":"2021","unstructured":"Meade B, Wasileski G, Hunter A (2021) The effects of victimization prior to prison on victimization, misconduct, and sanction severity during incarceration. Crime Delinq 67(12):1856\u20131878. https:\/\/doi.org\/10.1177\/0011128720977440","journal-title":"Crime Delinq"},{"key":"9352_CR64","doi-asserted-by":"publisher","unstructured":"Miller JM (2009) Twenty first century criminology: a reference handbook. SAGE Publications, Inc. https:\/\/doi.org\/10.4135\/9781412971997","DOI":"10.4135\/9781412971997"},{"issue":"1","key":"9352_CR65","first-page":"100","volume":"3","author":"SD Mohanty","year":"2021","unstructured":"Mohanty SD, Lekan D, McCoy TP et al (2021) Machine learning for predicting readmission risk among the frail: explainable AI for healthcare. Patterns (N Y) 3(1):100\u2013395","journal-title":"Patterns (N Y)"},{"key":"9352_CR66","unstructured":"Mokhtari KE, Higdon BP, Ba\u015far A (2019) Interpreting financial time series with shap values. In: Proceedings of the 29th annual international conference on computer science and software engineering, pp 166\u2013172"},{"key":"9352_CR67","unstructured":"Molnar C (2020) Interpretable machine learning. Lulu.com, https:\/\/christophm.github.io\/interpretable-ml-book\/"},{"key":"9352_CR68","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1016\/j.patcog.2016.11.008","volume":"65","author":"G Montavon","year":"2017","unstructured":"Montavon G, Lapuschkin S, Binder A et al (2017) Explaining nonlinear classification decisions with deep taylor decomposition. Pattern Recogn 65:211\u2013222","journal-title":"Pattern Recogn"},{"key":"9352_CR69","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/07418825.2018.1528375","volume":"37","author":"D Mueller","year":"2019","unstructured":"Mueller D, Sullivan C, McManus H (2019) Disproportionate experiences in custody? An examination of minority youths\u2019 outcomes in secure facilities. Justice Q 37:1\u201326. https:\/\/doi.org\/10.1080\/07418825.2018.1528375","journal-title":"Justice Q"},{"key":"9352_CR70","doi-asserted-by":"publisher","unstructured":"Muratore MG (2014) Victimization, Springer Netherlands, Dordrecht, pp 6917\u20136921. https:\/\/doi.org\/10.1007\/978-94-007-0753-5_3156","DOI":"10.1007\/978-94-007-0753-5_3156"},{"issue":"1","key":"9352_CR71","doi-asserted-by":"publisher","first-page":"1","DOI":"10.52372\/kjps36101","volume":"36","author":"C Na","year":"2021","unstructured":"Na C, Oh G, Song J et al (2021) Do machine learning methods outperform traditional statistical models in crime prediction? A comparison between logistic regression and neural networks. Kor J Policy Stud 36(1):1\u201313","journal-title":"Kor J Policy Stud"},{"key":"9352_CR72","doi-asserted-by":"publisher","first-page":"420","DOI":"10.5281\/zenodo.2657668","volume":"13","author":"F Ngo","year":"2019","unstructured":"Ngo F, Govindu R, Agarwal A (2019) Traditional regression methods versus the utility of machine learning techniques in forecasting inmate misconduct in the united states: An exploration of the prospects of the techniques. Int J Crim Justice Sci 13:420\u2013437. https:\/\/doi.org\/10.5281\/zenodo.2657668","journal-title":"Int J Crim Justice Sci"},{"issue":"1","key":"9352_CR73","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1007\/s12103-014-9246-6","volume":"40","author":"FT Ngo","year":"2015","unstructured":"Ngo FT, Govindu R, Agarwal A (2015) Assessing the predictive utility of logistic regression, classification and regression tree, chi-squared automatic interaction detection, and neural network models in predicting inmate misconduct. Am J Crim Justice 40(1):47\u201374","journal-title":"Am J Crim Justice"},{"issue":"2","key":"9352_CR74","doi-asserted-by":"publisher","first-page":"329","DOI":"10.1111\/1745-9133.12543","volume":"20","author":"H Nguyen","year":"2021","unstructured":"Nguyen H, Midgette G, Loughran T et al (2021) Random drug testing in prisons: does a little testing go a long way? Criminol Public Policy 20(2):329\u2013349. https:\/\/doi.org\/10.1111\/1745-9133.12543","journal-title":"Criminol Public Policy"},{"issue":"6","key":"9352_CR75","doi-asserted-by":"publisher","first-page":"935","DOI":"10.1177\/0898264315614007","volume":"28","author":"KM Nowotny","year":"2016","unstructured":"Nowotny KM, Cepeda A, James-Hawkins L et al (2016) Growing old behind bars: health profiles of the older male inmate population in the united states. J Aging Health 28(6):935\u2013956. https:\/\/doi.org\/10.1177\/0898264315614007","journal-title":"J Aging Health"},{"issue":"2","key":"9352_CR76","doi-asserted-by":"publisher","first-page":"186","DOI":"10.1177\/1541204020958465","volume":"19","author":"A Oglesby-Neal","year":"2021","unstructured":"Oglesby-Neal A, Peterson B (2021) Influence of race in the deep end of the juvenile justice system. Youth Viol Juv Justice 19(2):186\u2013205. https:\/\/doi.org\/10.1177\/1541204020958465","journal-title":"Youth Viol Juv Justice"},{"key":"9352_CR77","unstructured":"Ooi EJ (2019) Evaluating the impact of the intensive drug and alcohol treatment program (idatp) on prisoner misconduct. BOCSAR NSW Crime and Justice Bulletins, p\u00a012"},{"key":"9352_CR78","unstructured":"Ozkan T (2017) Predicting recidivism through machine learning. Doctor of philosophy in criminology, The University of Texas at Dallas"},{"key":"9352_CR79","doi-asserted-by":"publisher","first-page":"515","DOI":"10.1111\/1745-9133.12290","volume":"16","author":"A Pompoco","year":"2017","unstructured":"Pompoco A, Wooldredge J, Lugo M et al (2017) Reducing inmate misconduct and prison returns with facility education programs. Criminol Public Policy 16:515\u2013547. https:\/\/doi.org\/10.1111\/1745-9133.12290","journal-title":"Criminol Public Policy"},{"issue":"3","key":"9352_CR80","doi-asserted-by":"publisher","first-page":"378","DOI":"10.1177\/0306624X09335244","volume":"54","author":"DM P\u00e9rez","year":"2010","unstructured":"P\u00e9rez DM, Gover AR, Tennyson KM et al (2010) Individual and institutional characteristics related to inmate victimization. Int J Offender Ther Comp Criminol 54(3):378\u2013394. https:\/\/doi.org\/10.1177\/0306624X09335244. (pMID: 19398588)","journal-title":"Int J Offender Ther Comp Criminol"},{"key":"9352_CR81","doi-asserted-by":"publisher","unstructured":"Pryzant R, Shen K, Jurafsky D, et\u00a0al (2018) Deconfounded lexicon induction for interpretable social science. In: Proceedings of the 2018 conference of the North American chapter of the association for computational linguistics: human language technologies, Volume 1 (Long Papers). Association for computational linguistics, New Orleans, Louisiana, pp 1615\u20131625, https:\/\/doi.org\/10.18653\/v1\/N18-1146","DOI":"10.18653\/v1\/N18-1146"},{"issue":"1","key":"9352_CR82","first-page":"1","volume":"2","author":"S Qayyum","year":"2018","unstructured":"Qayyum S, Hafsa S, Dar H (2018) Survey of data mining techniques for crime detection. Univ Sindh J Inf Commun Technol (USJICT) 2(1):1\u20136","journal-title":"Univ Sindh J Inf Commun Technol (USJICT)"},{"issue":"3","key":"9352_CR83","doi-asserted-by":"publisher","first-page":"170","DOI":"10.1080\/23774657.2017.1359126","volume":"3","author":"DA Rembert","year":"2018","unstructured":"Rembert DA, Henderson H, Threadcraft-Walker W et al (2018) Predicting staff assault in juvenile correctional facilities. Corrections 3(3):170\u2013185","journal-title":"Corrections"},{"issue":"2","key":"9352_CR84","doi-asserted-by":"publisher","first-page":"261","DOI":"10.3109\/10826084.2015.1082594","volume":"51","author":"TL Rowell-Cunsolo","year":"2016","unstructured":"Rowell-Cunsolo TL, Sampong SA, Befus M et al (2016) Predictors of illicit drug use among prisoners. Subst Use Misuse 51(2):261\u2013267. https:\/\/doi.org\/10.3109\/10826084.2015.1082594. (pMID: 26789438d)","journal-title":"Subst Use Misuse"},{"key":"9352_CR85","doi-asserted-by":"crossref","unstructured":"Rudin C (2018) Please stop explaining black box models for high stakes decisions. Proc 32nd Conf Neural Inf Process Syst (NIPS), Workshop Critiquing Correcting Trends Mach Learn pp 1\u201320. arXiv:1811.10154","DOI":"10.1038\/s42256-019-0048-x"},{"issue":"5","key":"9352_CR86","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1038\/s42256-019-0048-x","volume":"1","author":"C Rudin","year":"2019","unstructured":"Rudin C (2019) Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead. Nat Mach Intell 1(5):206\u2013215. https:\/\/doi.org\/10.1038\/s42256-019-0048-x","journal-title":"Nat Mach Intell"},{"key":"9352_CR87","unstructured":"Sawyer W, Wagner P (2020) Mass incarceration: the whole pie. http:\/\/www.bbc.com\/portuguese\/internacional-42076223"},{"issue":"1","key":"9352_CR88","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1177\/2156869315609733","volume":"6","author":"J Schnittker","year":"2016","unstructured":"Schnittker J, Bacak V (2016) Orange is still pink: mental illness, gender roles, and physical victimization in prisons. Soc Mental Health 6(1):21\u201335. https:\/\/doi.org\/10.1177\/2156869315609733","journal-title":"Soc Mental Health"},{"issue":"12","key":"9352_CR89","doi-asserted-by":"publisher","first-page":"1719","DOI":"10.1177\/0093854819869039","volume":"46","author":"RE Severson","year":"2019","unstructured":"Severson RE (2019) Gender differences in mental health, institutional misconduct, and disciplinary segregation. Crim Justice Behav 46(12):1719\u20131737. https:\/\/doi.org\/10.1177\/0093854819869039","journal-title":"Crim Justice Behav"},{"key":"9352_CR90","volume-title":"Mental health and in-prison experiences: examining socioeconomic and sex differences in the effect of mental illness on institutional misconduct and disciplinary segregation","author":"RE Severson","year":"2020","unstructured":"Severson RE (2020) Mental health and in-prison experiences: examining socioeconomic and sex differences in the effect of mental illness on institutional misconduct and disciplinary segregation. University of South Florida, Doutorado"},{"issue":"5","key":"9352_CR91","doi-asserted-by":"publisher","first-page":"351","DOI":"10.1080\/23774657.2018.1549965","volume":"5","author":"AM Sheeran","year":"2020","unstructured":"Sheeran AM, Hilinski-Rosick CM, Richie M et al (2020) Correlates of elderly inmate misconduct: a comparison of younger, middle-age, and elderly inmates. Corrections 5(5):351\u2013376. https:\/\/doi.org\/10.1080\/23774657.2018.1549965","journal-title":"Corrections"},{"key":"9352_CR92","doi-asserted-by":"crossref","unstructured":"Silva W, Fernandes K, Cardoso MJ, et\u00a0al (2018) Towards complementary explanations using deep neural networks. In: Understanding and interpreting machine learning in medical image computing applications. Springer, pp 133\u2013140","DOI":"10.1007\/978-3-030-02628-8_15"},{"key":"9352_CR93","unstructured":"Steiner B (2018) Measuring and explaining inmate misconduct. The Oxford handbook of prisons and imprisonment p 235"},{"key":"9352_CR94","doi-asserted-by":"publisher","first-page":"462","DOI":"10.1016\/j.jcrimjus.2014.08.001","volume":"42","author":"B Steiner","year":"2014","unstructured":"Steiner B, Butler H, Ellison J (2014) Causes and correlates of prison inmate misconduct: a systematic review of the evidence. J Crim Just 42:462\u2013470. https:\/\/doi.org\/10.1016\/j.jcrimjus.2014.08.001","journal-title":"J Crim Just"},{"key":"9352_CR95","unstructured":"Stekhoven DJ (2013) missForest: nonparametric missing value imputation using random forest. R Package Version 1.4"},{"issue":"1","key":"9352_CR96","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1093\/bioinformatics\/btr597","volume":"28","author":"DJ Stekhoven","year":"2011","unstructured":"Stekhoven DJ, B\u00fchlmann P (2011) MissForest-non-parametric missing value imputation for mixed-type data. Bioinformatics 28(1):112\u2013118. https:\/\/doi.org\/10.1093\/bioinformatics\/btr597","journal-title":"Bioinformatics"},{"issue":"3","key":"9352_CR97","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1177\/1541204010366619","volume":"8","author":"M Tasca","year":"2010","unstructured":"Tasca M, Griffin ML, Rodriguez N (2010) The effect of importation and deprivation factors on violent misconduct: an examination of black and latino youth in prison. Youth Viol Juv Justice 8(3):234\u2013249. https:\/\/doi.org\/10.1177\/1541204010366619","journal-title":"Youth Viol Juv Justice"},{"key":"9352_CR98","unstructured":"Taylor M (2017) Improving in-prison rehabilitation programs. Legislative Analyst\u2019s Office https:\/\/lao.ca.gov\/reports\/2017\/3720\/In-Prison-Rehabilitation-120617.pdf, accessed: January 13, 2023"},{"issue":"9","key":"9352_CR99","doi-asserted-by":"publisher","first-page":"995","DOI":"10.1177\/0306624X15572351","volume":"60","author":"B Teasdale","year":"2016","unstructured":"Teasdale B, Daigle LE, Hawk SR et al (2016) Violent victimization in the prison context: an examination of the gendered contexts of prison. Int J Offender Ther Comp Criminol 60(9):995\u20131015","journal-title":"Int J Offender Ther Comp Criminol"},{"key":"9352_CR100","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1177\/0734016814529965","volume":"39","author":"R Tewksbury","year":"2014","unstructured":"Tewksbury R, Connor D, Denney A (2014) Disciplinary infractions behind bars: an exploration of importation and deprivation theories. Crim Justice Rev 39:201\u2013218. https:\/\/doi.org\/10.1177\/0734016814529965","journal-title":"Crim Justice Rev"},{"key":"9352_CR101","unstructured":"Thomas M (2020) An exploration of recidivism based on education and race. PhD thesis, Public Policy and Administration, Walden University, Minnesota"},{"key":"9352_CR102","doi-asserted-by":"publisher","unstructured":"Thongsatapornwatana U (2016) A survey of data mining techniques for analyzing crime patterns. In: 2016 Second Asian conference on defence technology (ACDT), Chiang Mai, Tail\u00e2ndia, pp 123\u2013128, https:\/\/doi.org\/10.1109\/ACDT.2016.7437655","DOI":"10.1109\/ACDT.2016.7437655"},{"key":"9352_CR103","doi-asserted-by":"publisher","unstructured":"Tjoa E, Guan C (2020) A survey on explainable artificial intelligence (xai): toward medical xai. In: IEEE Transactions on neural networks and learning systems pp 1\u201321. https:\/\/doi.org\/10.1109\/TNNLS.2020.3027314","DOI":"10.1109\/TNNLS.2020.3027314"},{"issue":"1","key":"9352_CR104","doi-asserted-by":"publisher","first-page":"408","DOI":"10.1080\/2331186X.2019.1628408","volume":"6","author":"C T\u00f8nseth","year":"2019","unstructured":"T\u00f8nseth C, Bergsland R (2019) Prison education in norway - the importance for work and life after release. Cogent Educ 6(1):408\u20131628. https:\/\/doi.org\/10.1080\/2331186X.2019.1628408","journal-title":"Cogent Educ"},{"issue":"1","key":"9352_CR105","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1016\/j.jcrimjus.2010.10.001","volume":"39","author":"SP Varano","year":"2011","unstructured":"Varano SP, Huebner BM, Bynum TS (2011) Correlates and consequences of pre-incarceration gang involvement among incarcerated youthful felons. J Crim Justice 39(1):30\u201338. https:\/\/doi.org\/10.1016\/j.jcrimjus.2010.10.001","journal-title":"J Crim Justice"},{"issue":"5","key":"9352_CR106","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1177\/0093854806296897","volume":"34","author":"WN Welsh","year":"2007","unstructured":"Welsh WN, McGrain P, Salamatin N et al (2007) Effects of prison drug treatment on inmate misconduct: a repeated measures analysis. Crim Justice Behav 34(5):600\u2013615. https:\/\/doi.org\/10.1177\/0093854806296897","journal-title":"Crim Justice Behav"},{"key":"9352_CR107","doi-asserted-by":"publisher","first-page":"469","DOI":"10.1891\/0886-6708.24.4.469","volume":"24","author":"N Wolff","year":"2009","unstructured":"Wolff N, Shi J, Siegel J (2009) Patterns of victimization among male and female inmates: evidence of an enduring legacy. Violence Vict 24:469\u201384. https:\/\/doi.org\/10.1891\/0886-6708.24.4.469","journal-title":"Violence Vict"},{"issue":"5","key":"9352_CR108","doi-asserted-by":"publisher","first-page":"358","DOI":"10.1016\/j.jcrimjus.2012.06.011","volume":"40","author":"J Wooldredge","year":"2012","unstructured":"Wooldredge J, Steiner B (2012) Race group differences in prison victimization experiences. J Crim Justice 40(5):358\u2013369. https:\/\/doi.org\/10.1016\/j.jcrimjus.2012.06.011","journal-title":"J Crim Justice"},{"issue":"1","key":"9352_CR109","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1111\/ssqu.12039","volume":"95","author":"A Zajacova","year":"2014","unstructured":"Zajacova A, Everett BG (2014) The nonequivalent health of high school equivalents. Soc Sci Q 95(1):221\u2013238","journal-title":"Soc Sci Q"},{"key":"9352_CR110","doi-asserted-by":"crossref","unstructured":"Zeng W, Davoodi A, Topaloglu RO (2020) Explainable DRC hotspot prediction with random forest and SHAP tree explainer. In: 2020 Design, automation and test in europe conference and exhibition (DATE), IEEE, pp 1151\u20131156, https:\/\/ieeexplore.ieee.org\/abstract\/document\/9116488","DOI":"10.23919\/DATE48585.2020.9116488"},{"issue":"10","key":"9352_CR111","doi-asserted-by":"publisher","first-page":"1513","DOI":"10.1177\/0011128720974315","volume":"67","author":"Q Zhao","year":"2021","unstructured":"Zhao Q, Cepeda A, Chou CP et al (2021) Incarceration trajectories of women who are mothers: a nationally representative study of state and federal prisoners. Crime Delinq 67(10):1513\u20131535. https:\/\/doi.org\/10.1177\/0011128720974315","journal-title":"Crime Delinq"}],"container-title":["Artificial Intelligence and Law"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10506-023-09352-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10506-023-09352-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10506-023-09352-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,25]],"date-time":"2024-05-25T08:07:50Z","timestamp":1716624470000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10506-023-09352-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,15]]},"references-count":111,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2024,6]]}},"alternative-id":["9352"],"URL":"https:\/\/doi.org\/10.1007\/s10506-023-09352-z","relation":{},"ISSN":["0924-8463","1572-8382"],"issn-type":[{"value":"0924-8463","type":"print"},{"value":"1572-8382","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3,15]]},"assertion":[{"value":"19 February 2023","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 March 2023","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}