Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-cd9895bd7-dzt6s Total loading time: 0 Render date: 2024-12-27T18:48:24.917Z Has data issue: false hasContentIssue false

Part IV - Postconviction Phase Decisions

Published online by Cambridge University Press:  22 February 2024

Edited by
Monica K. Miller ,
Logan A. Yelderman ,
Matthew T. Huss  and
Jason A. Cantone
Monica K. Miller
Affiliation:
University of Nevada, Reno
Logan A. Yelderman
Affiliation:
Prairie View A & M University, Texas
Matthew T. Huss
Affiliation:
Creighton University, Omaha
Jason A. Cantone
Affiliation:
George Mason University, Virginia
Get access

Summary

A summary is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Chapter
Information
The Cambridge Handbook of Psychology and Legal Decision-Making , pp. 425 - 522
Publisher: Cambridge University Press
Print publication year: 2024

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

References

Abram, K. M., Teplin, L. A., Charles, D. R., et al. (2004). Posttraumatic stress disorder and trauma in youth in juvenile detention. Archives of General Psychiatry, 61(4), 403–410. https://doi.org/fktqt3.Google Scholar
Ambrosini, P. J. (2000). Historical development and present status of the Schedule for Affective Disorders and Schizophrenia for School-Age Children (K-SADS). Journal of American Academy of Child and Adolescent Psychiatry, 39(1), 49–58. https://doi.org/dr2mtw.Google Scholar
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). American Psychiatric Association.Google Scholar
Angold, A., & Costello, J. (2000). The Child and Adolescent Psychiatric Assessment (CAPA). Journal of the American Academy of Child and Adolescent Psychiatry, 39(1), 49–58. https://doi.org/c535gd.Google Scholar
Benedek, E., & Schetky, D. (2002). Principles and practice of child and adolescent psychiatry. American Psychiatric Publishing.Google Scholar
Cauffman, E., & Stienberg, L. (2000). (Im)maturity of judgement in adolescence: Why adolescents may be less culpable than adults. Behavioral Sciences and the Law, 18(6), 741–760. https://doi.org/dw7kns.Google Scholar
Cicchetti, D. (1984). The emergence of developmental psychopathology. Child Development, 55(1), 1–7. https://doi.org/dr27z4.Google Scholar
Colins, O. F., Vermeiren, R., Schuyten, G., Broekaert, E., & Soyez, V. (2008). Informant agreement in the assessment of disruptive disorders in detained minors in Belgium: A diagnosis-level and symptom-level examination. Journal of Clinical Psychiatry, 69(1), 141–148. https://doi.org/d7zf2x.Google Scholar
Dattilio, F. M., & Fromm, L. (2011). Juvenile delinquency and decertification. In Drogin, E. Y., Dattilio, F. M., Sadoff, R. L., and Gutheil, T. G. (Eds.), Handbook of forensic assessment: Psychological and psychiatric perspectives (pp. 227–253). Wiley.Google Scholar
Dierkhising, C. B., Ko, S. J., Woods-Jaeger, B., et al. (2013). Trauma histories among justice-involved youth: Findings from the National Child Traumatic Stress Network. European Journal of Psychotraumatology, 4(1), 20274. https://doi.org/gjzkhv.Google Scholar
Ewing, C. P. (1990). Juveniles or adults? Forensic assessment of juveniles considered for trial in criminal court. Forensic Reports, 3, 3–13.Google Scholar
Folk, J. B., Ramos, L. M. C., Bath, E. P., et al. (2021). The prospective impact of adverse childhood experiences on justice-involved youth’s psychiatric symptoms and substance use. Journal of Consulting and Clinical Psychology, 89(6), 483–498. https://doi.org/hvdp.Google Scholar
Graham v. Florida, 560, US 48 (2010).Google Scholar
Grisso, T. (2013). Forensic evaluation of juveniles (2nd ed.). Professional Resources Press.Google Scholar
In re Gault, 387, US 1, 87 S. Ct, 1428 (1967).Google Scholar
Insel, C., Tabashneck, S., Shen, F. X., Edersheim, J. G., & Kinscherff, R. T. (2022). White paper on the science of late adolescence: A guide for judges, attorneys, and policy makers. Center for Law Brain and Behavior.Google Scholar
Kaufman, J., Birmaher, B., Brent, D., et al. (1997). Schedule for affective disorders and schizophrenia for school-aged children-present and lifetime version (K-SADS-PL): Initial reliability and validity data. Journal of the American Academy of Child & Adolescent Psychiatry, 36(7), 980–988. https://doi.org/10.1097/00004583-199707000-00021.Google Scholar
Kent v. United States, 383, US 541 (1966).Google Scholar
Kerig, P. K., & Becker, S. P. (2010). From internalizing to externalizing: Theoretical models of the processes linking PTSD to juvenile delinquency. In Egan, S. J. (Ed.), Posttraumatic stress disorder (PTSD): Causes, symptoms and treatment (pp. 33–78). Nova Science.Google Scholar
Kinscherff, R. T. (2016). Distinguishing and assessing treatment needs and amenability to rehabilitation. In Heilbrun, K., DeMatteo, D., & Goldstein, N. E. S. (Eds.), APA handbook of psychology and juvenile justice (pp. 385–404). American Psychological Association. https://doi.org/hvdm.Google Scholar
Koenen, K. C., Fu, Q. J., Lyons, M. J., et al. (2005). Juvenile conduct disorder as a risk factor for trauma exposure and posttraumatic stress disorder. Journal of Traumatic Stress, 18(1), 23–32. https://doi.org/bmk3pf.CrossRefGoogle ScholarPubMed
Kraemer, H. C., Measelle, J. R., Ablow, J. C., et al. (2003). A new approach to integrating data from multiple informants in psychiatric assessment and research: Mixing and matching contexts and perspectives. American Journal of Psychiatry, 160(9), 1566–1577. https://doi.org/bjk8jm.Google Scholar
Lahey, B. B., Moffitt, T. E., & Caspi, A. (2003). Causes of conduct disorder and juvenile delinquency. Guilford Press.Google Scholar
Leistico, A-M. R., & Salekin, R. T. (2003). Testing the reliability and validity of the Risk, Sophistication-Maturity, and Treatment Amenability instrument (RST-I): An assessment tool for juvenile offenders. International Journal of Forensic Mental Health, 2(2), 101–117. https://doi.org/hvdq.Google Scholar
Loeber, R., Slot, N. W., & Stouthamer-Loeber, M. (2006). A three dimensional, cumulative developmental model of serious delinquency. In Wikstrom, P-O. H and Sampson, R. J (Eds.), The explanation of crime: Context, mechanism, and development (pp. 153–194). Cambridge University Press.Google Scholar
MacDougall, E., & Salekin, R. T. (2015). Amenability to treatment. In Cautin, R. L. & Lilienfeld, S. O. (Eds.), The encyclopedia of clinical psychology (pp. 1–6). John Wiley and Sons. https://doi.org/hvdr.Google Scholar
Martin, G. A. (1992). The delinquent and the juvenile court: Is there still a place for rehabilitation? University of Connecticut Law Review, 25, 57–88.Google Scholar
Miller v. State of Alabama, 567 US (2012).Google Scholar
Mills, K. L., Goddings, A-L., Clasen, L. S., Giedd, J. N., & Blakemore, S-J. (2014). The developmental mismatch in structural brain maturation during adolescence. Developmental Neuroscience, 36(3–4), 147–160. https://doi.org/f6cnvt.Google Scholar
Mulvey, E. P. (1984). Judging amenability to treatment in juvenile offenders. In Reppucci, D. N., Weithorn, L. A., Mulvey, E. P., & Monahan, J. (Eds.), Children, mental health, and the law (pp. 195–210). Sage.Google Scholar
Mulvey, E. P., & Iselin, A-M. R. (2008). Improving professional judgments of risk and amenability in juvenile justice. The Future of Children, 18(2), 35–57. https://doi.org/cdp6p2.Google Scholar
Mulvey, E. P., Steinberg, L., Fagan, J., et al. (2004). Theory and research on desistance from antisocial activity among serious adolescent offenders. Youth Violence and Juvenile Justice, 2(3), 213–236. https://doi.org/bnk88k.Google Scholar
Reich, W. (2000). Diagnostic Interview for Children and Adolescents (DICA). Journal of the American Academy of Child & Adolescent Psychiatry, 39(1), 59–66. https://doi.org/cfcc2k.Google Scholar
Roper v. Simmons, 543 US 551 (2005).Google Scholar
Salekin, R. T. (2004). Risk-Sophistication-Treatment-Inventory (RST-I) professional manual. Psychological Assessment Resources.Google Scholar
Salekin, R. T. (2015). Forensic evaluation and treatment of juveniles: Innovation and best practice. American Psychological Association. https://doi.org/hvdt.Google Scholar
Salekin, R. T. (2016). Psychopathy in children: Why should we care about grandiose-manipulative and daring-impulsive traits? British Journal of Psychiatry, 209, 189–191. https://doi.org/10.1192/bjp.bp.115.179051.Google Scholar
Salekin, R. T., Rogers, R., & Ustad, K. L. (2001). Juvenile waiver to adult criminal courts: Prototypes for dangerousness, sophistication-maturity, and amenability to treatment. Psychology, Public Policy, and Law, 7(2), 381–408. https://doi.org/bqx385.Google Scholar
Salekin, R. T., Tippey, J. G., & Allen, A. D. (2012). Treatment of conduct problem youth with interpersonal callous traits using mental models: Measurement of risk and change. Behavioral Sciences and the Law, 30(4), 470–486. https://doi.org/f364cv.Google Scholar
Salekin, R. T., Yff, R. A., Neumann, C. S., Leistico, A-M. R., & Zalot, A. A. (2002). Juvenile transfer to adult courts: A look at the prototypes for dangerousness, sophistication-maturity, and amenability to treatment through a legal lens. Psychology, Public Policy, and Law, 8(4), 373–410. https://doi.org/bt9fsk.Google Scholar
Sanislow, C. A., Pine, D. S., Quinn, K. J., et al. (2010). Developing constructs for psychological research: Research domain criteria. Journal of Abnormal Psychology, 119(4), 631–639. https://doi.org/bgc6xf.Google Scholar
Schubert, C. A., Mulvey, E. P., Loughran, T. A., et al. (2010). Predicting outcomes for youth transferred to adult court. Law and Human Behavior, 34(6), 460–475. https://doi.org/dstff8.Google Scholar
Shaffer, D., Fisher, P., Lucas, C. P., Dulcan, M. K., & Schwab-Stone, M. E. (2000). NIMH Diagnostic Interview Schedule for Children Version IV (IMH DISC-IV): Description, differences from previous versions, and reliability of some common diagnoses. Journal of the American Academy of Child and Adolescent Psychiatry, 39(1), 28–38. https://doi.org/frcq9z.Google Scholar
Shaffer, D., Schwab-Stone, M., Fisher, P., et al. (1993). The Diagnostic Interview Schedule for Children-Revised Version (DISC-R): I. Preparation, field testing, interrater reliability, and acceptability. Journal of the American Academy of Child and Adolescent Psychiatry, 32(3), 643–650. https://doi.org/dm64cm.Google Scholar
Shufelt, J. L., & Cocozza, J. J. (2006). Youth with mental health disorders in the juvenile justice system: Results from a multi-state prevalence study (pp. 1–6). National Center for Mental Health and Juvenile Justice.Google Scholar
Teplin, L. A., Abram, K. M., McClelland, G. M., Dulcan, M. K., & Mericle, A. A. (2002). Psychiatric disorders in youth in juvenile detention. Archives of General Psychiatry, 59(12), 1133–1143. https://doi.org/dvjwpr.Google Scholar
Tillman, R., Geller, B., Craney, J. L., et al. (2003). Temperament and character factors in a prepubertal and early adolescent bipolar disorder phenotype compared to attention deficit hyperactive and normal controls. Journal of Child and Adolescent Psychopharmacology, 13(4), 531–543. https://doi.org/bfw3mz.Google Scholar
Wasserman, G. A., McReynolds, L. S., Lucas, C. P., Fisher, P., & Santos, L. (2002). The Voice DISC-IV with incarcerated male youths: Prevalence of disorder. Journal of the American Academy of child and Adolescent Psychiatry, 41(3), 314–321. https://doi.org/fn4q5g.Google Scholar
Wasserman, G. A., McReynolds, L. S., Schwalbe, C. S., Keating, J. M., & Jones, S. A. (2010). Psychiatric disorder, comorbidity, and suicidal behavior in juvenile justice youth. Criminal Justice and Behavior, 37(12), 1361–1376. https://doi.org/d7t279.Google Scholar
Weller, E. B., Weller, R. A., Fristad, M. A., Rooney, M. T., & Schecter, J. (2000). Children’s Interview for Psychiatric Syndromes (ChIPS). Journal of the American Academy of Child and Adolescent Psychiatry, 39(1), 76–84. https://doi.org/d9xmm4.Google Scholar
Weller, E. B., Weller, R. A., Rooney, M. T., & Fristad, M. A. (1999). Children’s Interview for Psychiatric Syndromes (ChIPS). American Psychiatric Press.Google Scholar

References

Allen, M., Mabry, E., & McKelton, D. (1998). Impact of juror attitudes about the death penalty on juror evaluations of guilt and punishment: A meta-analysis. Law and Human Behavior, 22(6), 715–731. https://doi.org/10.1023/A:1025763008533.Google Scholar
Alvarez, M., & Miller, M. (2017). How defendants’ legal status and ethnicity and participants political orientation relate to death penalty sentencing decisions. Translational Issues in Psychological Science, 3(3), 298–311. https://doi.org/10.1037/tps0000128.Google Scholar
Antonio, M. (2006). Arbitrariness and the death penalty: How the defendant’s appearance during trial influences capital jurors’ punishment decisions. Behavioral Sciences and the Law, 24(2), 215–234. https://doi.org/10.1002/bsl.673.Google Scholar
Atiq, E., & Miller, E. (2018). The limits of law in the evaluation of mitigating evidence. Journal of Criminal Law, 45(1), 167–201.Google Scholar
Atkins v. Virginia, 536 US 304 (2002).Google Scholar
Bakhshay, S., & Haney, C. (2018). The media’s impact on the right to a fair trial: A content analysis of pretrial publicity in capital cases. Psychology, Public Policy, and Law, 24(3), 326–346. http://dx.doi.org/10.1037/law0000174.Google Scholar
Barner, J. (2014). Life or death decision making: Qualitative analysis of death penalty jurors. Qualitative Social Work, 13(6), 842–858. https://doi.org/10.1177/1473325013507304.Google Scholar
Barnett, M., Brodsky, S., & Davis, C. (2004). When mitigation evidence makes a difference: Effects of psychological mitigating evidence in sentencing decisions in capital trials. Behavioral Sciences and the Law, 22(6), 751–770. https://doi.org/10.1002/bsl.591.Google Scholar
Barnett, M., Brodsky, S., & Price, J. (2007). Differential impact of mitigating evidence in capital sentencing. Journal of Forensic Psychology Practice, 7(1), 39–45. https://doi.org/10.1300/J158v07n01_04.Google Scholar
Baumgartner, F., De Boef, S., & Boydstun, A. (2008). The decline of the death penalty and the discovery of innocence. Cambridge University Press.Google Scholar
Bell Holleran, L., Vaughan, T., & Vandiver, D. (2016). Juror decision-making in death penalty sentencing when presented with defendant’s history of child abuse or neglect. Behavior Sciences and the Law, 34(6), 742–766. https://doi.org/10.1002/bsl.2271.Google Scholar
Bowers, W. (1995). The Capital Jury Project: Rationale, design, and preview of early findings. Indiana Law Journal, 70(4), 1043–1102.Google Scholar
Bowers, W., & Foglia, W. (2003). Still singularly agonizing: Law’s failure to purge arbitrariness from capital sentencing. Criminal Law Bulletin, 39(1), 51–86.Google Scholar
Bowers, W., Sandys, M., & Steiner, B. (1998). Foreclosed impartiality in capital sentencing: Jurors’ predispositions, guilt-trial experience, and premature decision making. Cornell Law Review, 83(6), 1476–1556.Google Scholar
Bowers, W., Steiner, B., & Sandys, M. (2001). Death sentencing in Black and White: An empirical analysis of the role of jurors’ race and jury racial composition. University of Pennsylvania Journal of Constitutional Law, 3(1), 171–274.Google Scholar
Brewer, T. (2004). Race and jurors’ receptivity to mitigation in capital cases: The effect of jurors’, defendants’, and victims’ race in combination. Law and Human Behavior, 28(5), 529–545. https://doi.org/10.1023/B:LAHU.0000046432.41928.2b.Google Scholar
Bronson, E. (1970). On the conviction proneness and unrepresentativeness of the death-qualified jury: A study of Colorado veniremen. University of Colorado Law Review, 42(1), 1–32.Google Scholar
Butler, B. (2007a). Death qualification and prejudice: The effect of implicit racism, sexism, and homophobia on capital defendants’ right to due process. Behavioral Sciences and the Law, 25(6), 857–867. https://doi.org/10.1002/bsl.791.Google Scholar
Butler, B. (2007b). The role of death qualification in jurors’ susceptibility to pretrial publicity. Journal of Applied Social Psychology, 37(1), 115–123. https://doi.org/10.1111/j.0021-9029.2007.00150.x.Google Scholar
Butler, B. (2008) The role of death qualification in venirepersons’ susceptibility to victim impact statements. Psychology, Crime & Law, 14(2), 133–141. https://doi.org/10.1080/10683160701483534.Google Scholar
Butler, B. & Moran, G. (2002). The role of death qualification in venirepersons perceptions of aggravating and mitigating circumstances in capital trials. Law and Human Behavior 26(2), 175–184. https://doi.org/10.1023/A:1014640025871.Google Scholar
Caldwell v. Mississippi, 472 US 320 (1985).Google Scholar
California v. Brown, 479 US 538 (1987).Google Scholar
Cho, S. (1994) Capital confusion: The effect of jury instructions on the decision to impose death. Journal of Criminal Law and Criminology, 85(2), 532–561.Google Scholar
Cochran, J., & Chamlin, M. (2006). The enduring racial divide in death penalty support. Journal of Criminal Justice, 34(1), 85–99. https://doi.org/10.1016/j.jcrimjus.2005.11.007.Google Scholar
Conley, R. (2013). Living with the decision that someone will die: Linguistic distance and empathy in jurors’ death penalty decisions. Language in Society, 42(5), 503–526. https://doi.org/10.1017/S004740451300064X.Google Scholar
Cowan, C., Thompson, W., & Ellsworth, P. (1984). The effects of death qualification on jurors’ predisposition to convict and on the quality of deliberation. Law and Human Behavior, 8(1–2), 53–79. https://doi.org/10.1007/BF01044351.Google Scholar
Devine, D., & Kelly, C. (2015). Life or death: An examination of jury sentencing with the Capital Jury Project database. Psychology, Public Policy, and Law, 21(4), 393–406. https://doi.org/10.1037/law0000060.Google Scholar
Dutton, D., & Hart, S. (1992) Evidence for long-term, specific effects of childhood abuse and neglect on criminal behavior in men, International Journal of Offender Therapy & Comparative Criminology, 36, 129–137. https://doi.org/10.1177/0306624X9203600205.Google Scholar
Eddings v. Oklahoma, 455 US 104 (1982).Google Scholar
Eisenberg, T., & Wells, M. (1993). Deadly confusion: Juror instructions in capital cases. Cornell Law Review, 79(1), 1–17.Google Scholar
Espinoza, W., & Willis-Esqueda, C. (2015). The influence of mitigation evidence, ethnicity, and SES on death penalty decisions by European American and Latino venirepersons. Cultural Diversity and Ethnic Minority Psychology, 21(2), 288–299. https://doi.org/10.1037/a0037646.Google Scholar
Fitzgerald, R., & Ellsworth, P. (1984). Due process vs. crime control: Death qualification and jury attitudes. Law and Human Behavior, 8(1–2), 31–51. https://doi.org/10.1007/BF01044350.Google Scholar
Furman v. Georgia, 408 US 238 (1972).Google Scholar
Gasperetti, M. (2022). Crime and punishment: An empirical study of the effects of racial bias on capital sentencing decisions. University of Miami Law Review, 76(2), 525–611.Google Scholar
Gillespie, L., Smith, M., Bjerregaard, B., & Fogel, S. (2014). Examining the impact of proximate culpability mitigation in capital punishment sentencing recommendations: The influence of mental health mitigators. American Journal of Criminal Justice, 39(4), 698–715. https://doi.org/10.1007/s12103-014-9255-5.Google Scholar
Gregg v. Georgia, 428 US 153 (1976).Google Scholar
Haney, C. (Ed.) (1984a). Special Issue on death qualification. Law & Human Behavior, 8, 1–195.Google Scholar
Haney, C. (1984b). On the selection of capital juries: The biasing effects of the death qualification process. Law and Human Behavior, 8(1–2), 121–132. https://doi.org/10.1007/BF01044355.Google Scholar
Haney, C. (1984c). Examining death qualification: Further analysis of the process effect. Law and Human Behavior, 8(1–2), 133–151. https://doi.org/10.1007/BF01044356.Google Scholar
Haney, C. (1995). The social context of capital murder: Social histories and the logic of capital mitigation. Santa Clara Law Review, 35(2), 547–609.Google Scholar
Haney, C. (1997). Violence and the capital jury: Mechanisms of moral disengagement and the impulse to condemn to death. Stanford Law Review, 49(6), 1447–1486.Google Scholar
Haney, C. (2004). Condemning the other in death penalty trials: Biographical racism, structural mitigation, and the empathic divide. DePaul Law Review, 53(4), 1557–1590.Google Scholar
Haney, C. (2005). Death by design: Capital punishment as a social psychological system. Oxford University Press.Google Scholar
Haney, C. (2006). Exoneration and wrongful condemnations: Expanding the zone of perceived injustice in capital cases. Golden Gate Law Review, 37(1), 131–173.Google Scholar
Haney, C. (2008a). Evolving standards of decency: Advancing the nature and logic of capital mitigation. Hofstra Law Review, 36(3), 835–882.Google Scholar
Haney, C. (2008b). Media criminology and the death penalty. DePaul Law Review, 58(3), 689–740.Google Scholar
Haney, C. (2020). Criminality in context: the psychological foundations of criminal justice reform. APA Books.Google Scholar
Haney, C. (2009). On mitigation as counter-narrative: A case study of the hidden context of prison violence. University of Missouri–Kansas City Law Review, 77(4), 911–946.Google Scholar
Haney, C., Hurtado, A., & Vega, L. (1994). “Modern” death qualification. Law and Human Behavior, 18(6), 619–633. https://doi.org/10.1007/BF01499328.Google Scholar
Haney, C., & Lynch, M. (1994). Comprehending life and death matters: A preliminary study of California’s capital penalty instructions. Law and Human Behavior, 18(4), 411–436. https://doi.org/10.1007/BF01499048.Google Scholar
Haney, C., Sontag, L., & Costanzo, S. (1994). Deciding to take a life: Capital juries, sentencing instructions, and the jurisprudence of death. Journal of Social Issues, 50(2), 149–176. https://doi.org/10.1111/j.1540-4560.1994.tb02414.x.Google Scholar
Haney, C., Zurbriggen, E., & Weill, J. (2022). The continuing unfairness of death qualification: Changing death penalty attitudes and capital jury selection. Psychology, Public Policy, and Law, 28(1), 1–31. https://doi.org/10.1037/law0000335.Google Scholar
Holbert, R., Shah, D., & Kwak, N. (2004). Fear, authority, and justice: Crime-related viewing and endorsements of capital punishment and gun ownership. Journalism and Mass Communication Quarterly, 81(2), 343–363. https://doi.org/10.1177/107769900408100208.Google Scholar
Johnson, D. (2008). Racial prejudice, perceived injustice, and the Black–White gap in punitive attitudes. Journal of Criminal Justice, 36, 198–206. https://doi.org/10.1016/j.jcrimjus.2008.02.009.Google Scholar
Kadane, J. (1984). After Hovey: A note on taking account of the automatic death penalty jurors. Law and Human Behavior, 8(1–2), 115–120. https://doi.org/10.1007/BF01044354.Google Scholar
Kort-Butler, L. A. and Hartshorn, K. J. S. (2011). Watching the detectives: Crime programming, fear of crime, and attitudes about the criminal justice system. Sociological Quarterly, 52(1), 36–55. https://doi.org/10.1111/j.1533-8525.2010.01191.x.Google Scholar
Lockett v. Ohio, 438 US 586 (1978).Google Scholar
Lockhart v. McCree, 476 US 162 (1986).Google Scholar
Luginbuhl, J., & Howe, J. (1995). Discretion in capital sentencing instructions: Guided or misguided? Indiana Law Review, 70, 1161–1181.Google Scholar
Luginbuhl, J., & Middendorf, K. (1988). Death penalty beliefs and jurors’ responses to aggravating and mitigating circumstances in capital trials. Law and Human Behavior, 12(3), 263–281. https://doi.org/10.1007/BF01044384.Google Scholar
Lynch, M., & Haney, C. (2000). Discrimination and instructional comprehension: Guided discretion, racial bias, and the death penalty. Law and Human Behavior, 24(3), 337–358. https://doi.org/10.1023/A:1005588221761.Google Scholar
Lynch, M., & Haney, C. (2009). Capital jury deliberation: Effects on death sentencing, comprehension, and discrimination. Law and Human Behavior, 33(6), 481–496. https://doi.org/10.1007/s10979-008-9168-2.Google Scholar
Lynch, M., & Haney, C. (2018). Death qualification in black and white: Racialized decision-making and death-qualified juries. Law & Policy, 40(2), 148–171. https://doi.org/10.1111/lapo.12099.Google Scholar
McCord, D. (2005). Lightening still strikes: Evidence from the popular press that death sentencing continues to be unconstitutionally arbitrary more than three decades after Furman. Brooklyn Law Review, 71(2), 797–870.Google Scholar
Miley, L., Heiss-Moses, E., Cochran, J., et al. (2020). An examination of the effects of mental disorders as mitigating factors in sentencing outcomes. Behavioral Sciences & and the Law, 38(4), 381–405. https://doi.org/10.1002/bsl.2477.Google Scholar
Miller, M., & Bornstein, B. (2006). The use of religion in death penalty sentencing trials. Law and Human Behavior, 30(6), 675–684. https://doi.org/10.1007/s10979-006-9056-6.Google Scholar
Moran, G., & Cutler, B. (1991). The prejudicial impact of pretrial publicity. Journal of Applied Social Psychology, 21(5), 345–367.Google Scholar
Morgan v. Illinois, 504 US 719 (1993).Google Scholar
O’Neil, K., Patry, M., & Penrod, S. (2004). Exploring the effects of attitudes toward the death penalty on capital sentencing verdicts. Psychology, Public Policy and Law, 10(4), 443–470. https://doi.org/10.1037/1076-8971.10.4.443.Google Scholar
Osofsky, M., Bandura, A., & Zimbardo, P. (2005). The role of moral disengagement in the execution process. Law and Human Behavior, 29(4), 374–393. https://doi.org/10.1007/s10979-005-4930-1.Google Scholar
Patry, M., & Penrod, S. (2013). Death penalty decisions: Instruction comprehension, attitudes, and decision mediators. Journal of Forensic Psychology Practice, 13(3), 204–244. https://doi.org/10.1080/15228932.2013.795816.Google Scholar
Ring v. Arizona, 586 US 584 (2002).Google Scholar
Rompilla v. Beard, 545 US 374 (2005).Google Scholar
Roper v. Simmons, 543 US 551 (2005).Google Scholar
Rose, M., & Rountree, M. (2021). The focal concerns of jurors evaluating mitigation: Evidence from federal capital jury forms. Law & Society Review, 56(2), 213–236. https://doi.org/10.1111/lasr.12602.Google Scholar
Sampson, J., & Laub, J. (1993). Crime in the making: Pathways and turning points through life. Harvard University Press.Google Scholar
Sandys, M. & Chermak, C. (1996). A journey into the unknown: Pretrial publicity and capital cases. Communication, Law and Policy, 1(4), 533–577. https://doi.org/10.1080/10811689609368615.Google Scholar
Semeraro, S. (2002). Responsibility in capital sentencing. San Diego Law Review, 39(1), 79–150.Google Scholar
Slater, M., Rouner, D., & Long, M. (2006). Television dramas and support for controversial public policies: Effects and mechanisms. Journal of Communication, 56(2), 235–252. https://doi.org/10.1111/j.1460-2466.2006.00017.x.Google Scholar
Smith, A., & Haney, C. (2011). Getting to the point: Attempting to improve juror comprehension of capital penalty phase instructions. Law and Human Behavior, 35(5), 339–350. https://doi.org/10.1007/s10979-010-9246-0.Google Scholar
Soss, J., Langbein, L., & Metelko, A. (2003). Why do White Americans support the death penalty? Journal of Politics, 65(2), 397–421. https://doi.org/10.1111/1468-2508.t01-2-00006.Google Scholar
Stetler, R. (2018). The past, present, and future of the mitigation profession: Fulfilling the constitutional requirement of individualized sentencing in capital cases. Hofstra Law Review, 46(4), 1161–1247.Google Scholar
Stetler, R. (2021). Death penalty keynote: Why mitigation matters, now and for the future. Santa Clara Law Review, 61(3), 699–743.Google Scholar
Sundby, S. (2003). Capital jury and empathy: The problem of worthy and unworthy victims. Cornell Law Review, 88(2), 343–381.Google Scholar
Thompson, W., Cowan, C., Ellsworth, P., & Harrington, J. (1984). Death penalty attitudes and conviction proneness: The translation of attitudes into verdicts. Law and Human Behavior 8(1–2), 85–113. https://doi.org/10.1007/BF01044353.Google Scholar
Unnever, J., & Cullen, F. (2007). Reassessing the racial divide in support for capital punishment: The continuing significance of race. Journal of Research in Crime and Delinquency, 44, 124–158. https://doi.org/10.1177/0022427806295837.Google Scholar
Vitriol, J., & Kovera, M. (2018). Exposure to capital voir dire may not increase convictions despite increasing pretrial presumption of guilt. Law and Human Behavior, 42(5), 472–483. https://doi.org/10.1037/lhb0000304.Google Scholar
Wainwright v. Witt, 460 US 412 (1985).Google Scholar
West, M., Wood, E., Miller, M., & Bornstein, B. (2021). How mock jurors’ cognitive processing and defendants’ immigrant status and ethnicity relate to decisions in capital trials. Journal of Experimental Criminology, 17, 423–432. https://doi.org/10.1007/s11292-020-09411-4.Google Scholar
Wiggins v. Smith, 539 US 510 (2003).Google Scholar
Wiener, R. L., Pritchard, C. C., & Weston, M. (1995). Comprehensibility of approved jury instructions in capital murder cases. Journal of Applied Psychology, 80(4), 455–467. https://doi.org/10.1037/0021-9010.80.4.455.Google Scholar
Witherspoon v. Illinois, 391 US 510 (1968).Google Scholar
Wu, S. (2022). The effect of wrongful conviction rate on death penalty support and how it closes the racial gap. American Journal of Criminal Justice, 47, 1006–1024. https://doi.org/10.1007/s12103-021-09637-6.Google Scholar
Yelderman, L., West, M., & Miller, M. (2019). Death penalty decision-making: Fundamentalist beliefs and the evaluation of aggravating and mitigating circumstances. Legal and Criminological Psychology, 24(1), 103–122. https://doi.org/10.1111/lcrp.12141.Google Scholar

References

Bail Reform Act of 1984, Publ. L. No. 89–465, (1984). www.congress.gov/bill/98th-congress/house-bill/5865.Google Scholar
Barbaree, H. E., Langton, C. M., & Peacock, E. J. (2006). Different actuarial risk measures produce different risk rankings for sexual offenders. Sexual Abuse: A Journal of Research and Treatment, 18(4) , 423–440. https://doi.org/10.1177/107906320601800408.Google Scholar
Batastini, A. B., Vitacco, M. J., Coaker, L. C., & Lester, M. E. (2019). Communicating violence risk during testimony: Do different formats lead to different perceptions among jurors? Psychology, Public Policy, and Law, 25(2), 92–106. https://doi.org/10.1037/law0000196.Google Scholar
Baughman, S. B. & McIntyre, F. (2011). Predicting violence. Texas Law Review, 90, 548. https://ssrn.com/abstract=1756506.Google Scholar
Blais, J., Babchishin, K. M. , & Hanson, R. K. (2022). Improving our risk communication: Standardized risk levels for brief assessment of recidivism risk-2002R. Sexual Abuse, 34(6), 667–698. https://doi.org/10.1177/10790632211047185.Google Scholar
Blais, J., & Forth, A. E. (2014). Prosecution-retained versus court-appointed experts: Comparing and contrasting risk assessment reports in preventative detention hearings. Law and Human Behavior, 38(6), 531–543. https://doi.org/10.1037/lhb0000082.Google Scholar
Borges, M. (2020). California rejects proposition to end cash bail. Jurist. www.jurist.org/news/2020/11/california-rejects-proposition-to-end-cash-bail/.Google Scholar
Carson, E. A. (2020). Prisoners in 2019. US Department of Justice.Google Scholar
Costanzo, M. & Krauss, D. (2021). Forensic and legal psychology: Psychological science applied to the law. 4th ed. Worth Publishers.Google Scholar
DeMatteo, D. , Murphy, M. , Galloway, M. , & Krauss, D. (2015). A national survey of sexually violent predator legislation: Procedures, policy, and practice. International Journal of Law and Mental Health, 14, 245–266.Google Scholar
DeMichele, M., Baumgartner, P., Barrick, K., etal. (2018). What do criminal justice professionals think about risk assessment at pretrial? Federal Probation, 83(1), 32–41. https://doi.org/10.2139/ssrn.3168490.Google Scholar
Douglas, K. S., Hart, S. D., Webster, C. D., & Belfrage, H. (2013). HCR-20V3: Assessing risk for violence – user guide. Mental Health, Law, and Policy Institute, Simon Fraser University.Google Scholar
Douglas, K. & Shaffer, C. (2021). The science of and practice with the HCR-20 V3 (Historical-Clinical-Risk Management-20, Version 3). In Douglas, K. & Otto, R. (Eds.), Handbook of violence risk assessment (pp. 253–293). Routledge/Taylor & Francis Group.Google Scholar
Garrett, B., Jakubow, A., & Monahan, J. (2018). Nonviolent risk assessment in Virginia sentencing: The Sentencing Commission Data. A report of the Virginia Criminal Justice Policy Reform project. University of Virginia School of Law. www.vcsc.virginia.gov/2018meetings/UVA%20Law%20School%20-%20NVRA%20Sentencing%20Analysis%20and%20Judicial%20Survey%20(Mar%201%202018).pdf.Google Scholar
Garrett, B., Jakubow, A., & Monahan, J. (2019). Judicial reliance on risk assessment in sentencing drug and property offender: A test of the treatment resource hypothesis. Criminal Justice and Behavior, 46(6), 799–810. https://doi.org/10.1177/0093854819842589.Google Scholar
Garrett, B. & Monahan, J. (2020). Judging risk. California Law Review, 108(2), 439–493. https://doi.org/10.15779/Z38B56D515.Google Scholar
Green, B. & Chen, Y. (2019). Disparate interactions: An algorithm-in-the-loop analysis of fairness in risk assessments. In Proceedings of the Conference of Fairness, Accountability, and Transparency (pp. 90-99). ACM Digital Library. https://doi.org/10.1145/3287560.3287563.Google Scholar
Grove, W. M., & Meehl, P. E. (1996). Comparative efficiency of informal (subjective, impressionistic) and formal (mechanical, algorithmic) prediction procedures: The clinical–statistical controversy. Psychology, Public Policy, and Law, 2(2), 293–323. https://doi.org/10.1037/1076-8971.2.2.293.Google Scholar
Hanson, R. K. & Anderson, D. (2021). Static-99 R: An empirical-actuarial risk tool for adult males with a history of sexual offending. In Douglas, K. & Otto, R. (Eds.), Handbook of violence risk assessment (pp. 106–130). Routledge/Taylor & Francis Group.Google Scholar
Hanson, R. K., Babchishin, K. M., Helmus, L. M., Thornton, D., & Phenix, A. (2017). Communicating the results of criterion referenced prediction measures: Risk categories for the Static-99 R and Static-2002 R sexual offender risk assessment tools. Psychological Assessment, 29(5), 582–597. https://doi.org/10.1037/pas0000371.Google Scholar
Hanson, R. K., Bourgon, G., McGrath, R. J., et al. (2017). A five-level risk and needs system: Maximizing assessment results in corrections through the development of a common language. Washington, DC: Justice Center Council of State Governments.Google Scholar
Hanson, R. K., & Morton-Bourgon, K. (2009). The accuracy of recidivism risk assessments for sexual offenders: A meta-analysis of 118 prediction studies. Psychological Assessment, 21(1), 1–21. https://doi.org/10.1037/a0014421.Google Scholar
Harris, H., Goss, J., & Gumbs, A. (2019). Pretrial risk assessment in California. Public Policy Institute of California. www.ppic.org/publication/pretrial-risk-assessment-in-california/.Google Scholar
Heilbrun, K., Dvoskin, J., Hart, S., & McNiel, D. (1999). Violence risk communication: Implications for research, policy, and practice. Health, Risk & Society, 1(1), 91–105. https://doi.org/10.1080/13698579908407009.Google Scholar
Hilton, Z. N., Carter, A. M., Harris, G. T., & Sharpe, A. J. (2008). Does using nonnumerical terms to describe risk aid violence risk communication? Clinician agreement and decision making. Journal of Interpersonal Violence, 23(2), 171–188. https://doi.org/10.1177/0886260507309337.Google Scholar
Hogan, N. (2021). Critical considerations in the development and interpretation of common risk language. Psychiatry, Psychology, and Law, 28, 218–234. https://doi.org/10.1080/13218719.2020.1767719.Google Scholar
Hyatt, J. & Chanenson, S. (2016). The use of risk assessment at sentencing: Implications for research and policy. US Department of Justice. http://digitalcommons.law.villanova.edu/wps/art193.Google Scholar
Jurek v. Texas, 428 US 262 (1976).Google Scholar
Karsjens v. Jesson, 109 F. Supp. 3d 1139 (2015).Google Scholar
Kansas SVP Statute, 59-29a02, 2012. https://codes.findlaw.com/ks/chapter-59-probate-code/ks-st-sect-59-29a02.html.Google Scholar
Kansas v. Crane, 534 US 407 (2002).Google Scholar
Kansas v. Hendricks, 521 US 346 (1997).Google Scholar
Krauss, D., Cook, G., & Klapatch, L. (2018). Risk assessment communication difficulties: An empirical examination of the effects of categorical versus probabilistic risk communication in sexually violent predator decisions. Behavioral Sciences and the Law, 36, 532–553. https://doi.org/10.1002/bsl.2379.Google Scholar
Krauss, D., Cook, G., Song, E., & Umanath, S. (2021). The public’s perception of crime control theater laws: It’s complicated. Psychology, Public Policy, and Law, 27, 316–327. https://doi.org/10.1037/law0000302.Google Scholar
Krauss, D. & Sales, B. D. (2001). The effects of clinical and scientific expert testimony on juror decision-making in capital sentencing. Psychology, Public Policy, & Law, 7, 267–310.Google Scholar
Krauss, D. & Scurich, N. (2014). The Impact of case factors on jurors’ decisions in a sexual violent predator hearing. Psychology, Public Policy, and Law, 20, 135–145.Google Scholar
Kwartner, P., Lyons, P. M., & Boccaccini, M.T. (2006). Judges’ risk communication preferences in risk for future violence cases. International Journal of Forensic Mental Health, 5, 185–194.Google Scholar
Lee, S. C., & Hanson, R. K. (2021). Updated 5-year and new 10-year sexual recidivism rate norms for Static-99R with routine/complete samples. Law and Human Behavior, 45(1), 24–38. https://doi.org/10.1037/lhb0000436.Google Scholar
Lowenkamp, C. & Latessa, E. (2004). Increasing the effectiveness of correctional programming through the risk principle: Identifying offenders for residential treatment. Criminology & Public Policy, 4(1), 263–290. https://doi.org/10.1111/j.1745-9133.2005.00021.x.Google Scholar
Milgram, A., Holsinger, A. M., Vannostrand, M., & Alsdorf, M. W. (2015). Pretrial risk assessment: Improving public safety and fairness in pretrial decision-making. Federal Sentencing Reporter, 27(4), 216–221. https://doi.org/10.1525/fsr.2015.27.4.216.Google Scholar
Monahan, J., & Skeem, J. (2016). Risk assessment in criminal sentencing. Annual Review of Law and Social Sciences, 12, 489–513. https://doi.org/10.1146/annurev-clinpsy-021815-092945.Google Scholar
Neal, T. M. S., & Grisso, T. (2014). Assessment practices and expert judgment methods in forensic psychology and psychiatry: An international snapshot. Criminal Justice and Behavior, 41(12), 1406–1421. https://doi.org/10.1177/0093854814548449.Google Scholar
Picard, S., Watkins, M., Rempel, M., & Kerodal, A., (2019). Beyond the algorithm: Pretrial reform, risk assessment, and racial fairness. Center for Court Innovation. www.courtinnovation.org/publications/beyond-algorithm.Google Scholar
Rachlinski, J. & Wistrich, A. (2017). Judging the judiciary by the numbers: Empirical research on judges. Annual Review of Law and Social Science, 13, 203–229. https://doi.org/10.1146/annurev-lawsocsci-110615-085032.Google Scholar
Sawyer, W. & Wagner, P. (2020). Mass incarceration: The whole pie 2020. Prison Policy Initiative. www.prisonpolicy.org/reports/pie2020.html.Google Scholar
Scurich, N. (2016a). An introduction to the assessment of violence risk. In Singh, J. P., Bjørkly, S., & Fazel, S. (Eds.), International perspectives on violence risk assessment (pp. 3–15). Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199386291.003.0001.Google Scholar
Scurich, N. (2016b). Structured risk assessment and legal decision-making. In Miller, M. K. & Bornstein, B. H. (Eds.), Advances in psychology and law (pp. 159–183). Springer International Publishing.Google Scholar
Scurich, N. (2018). The case against categorical risk estimates. Behavioral Sciences & the Law, 36(5), 554–564. https://doi.org/10.1002/bsl.2382.Google Scholar
Scurich, N., & John, R. S. (2019). The dark figure of sexual recidivism. Behavioral Sciences & the Law, 37(2), 158–175.Google Scholar
Scurich, N. & Krauss, D. A. (2020). Public’s views of risk assessment Algorithms and pretrial decision-making. Psychology, Public Policy, and Law, 26(1), 1–9. https://doi.org/10.1037/law0000219.Google Scholar
Singh, J. P., Desmarais, S. L., Hurducas, C., et al. (2014). International perspectives on the practical application of violence risk assessment: A global survey of 44 countries. International Journal of Forensic Mental Health, 13(3), 193–206. https://doi.org/10.1080/14999013.2014.922141.Google Scholar
Singh, J., Fazel, S., Gueorguieva, R., & Buchanan, A. (2014). Rates of violence in patients classified as high risk by structured risk assessment instruments. The British Journal of Psychiatry, 204(3), 180–187. https://doi.org/10.1192/bjp.bp.113.131938.Google Scholar
Slobogin, C. (2021). Just algorithms: Using science to reduce incarceration and inform the jurisprudence of risk. Cambridge University Press.Google Scholar
Stevenson, M. (2018). Distortion of justice: How the inability to pay bail affects case outcomes. The Journal of Law, Economics, and Organization, 34(4), 511–542. https://doi.org/10.1093/jleo/ewy019.Google Scholar
Stevenson, M. & Doleac, J. (2021). Algorithmic risk assessment in the hands of humans. https://dx.doi.org/10.2139/ssrn.3489440.Google Scholar
Storey, J. E. , Watt, K. A. , & Hart, S. D. (2015). An examination of violence risk communication in practice using a structured professional judgment framework. Behavioral Sciences and the Law, 33(1), 39–55.Google Scholar
Subramanian, R., Delaney, R., Roberts, S., Fishman, N., McGarry, P. (2015). Incarceration’s front door: The misuse of jails in America. Vera Institute of Justice. www.vera.org/downloads/publications/incarcerations-front-door-report_02.pdf.Google Scholar
US Department of Justice – Federal Bureau of Investigation (2019). Uniform crime report: Crime in the United States 2019. https://ucr.fbi.gov/crime-in-the-u.s/2019/crime-in-the-u.s.-2019/topic-pages/persons-arrested.pdf.Google Scholar
United States v. Salerno, 481 US 739 (1987).Google Scholar
Van Orden v. Schafer, 129 F. Supp. 3d 839 (2015).Google Scholar
Viljoen, J., Johnson, M., Cochrane, D., Vargen, L., & Vincent, G. (2019). Impact of risk assessment instruments on rates of pretrial detention, postconviction placements, and release: A systematic review and meta-analysis. Law and Human Behavior, 43(5), 397–420. http://dx.doi.org/10.1037/lhb0000344.Google Scholar
Virginia Criminal Sentencing Commission. 2021 annual report. www.vcsc.virginia.gov/2021AnnualReport.pdf.Google Scholar
Widgery, A. (2015). Trends in pretrial release: State legislation. National Conference of State Legislatures. https://nicic.gov/resources/nic-library/all-library-items/trends-pretrial-release-state-legislation.Google Scholar

References

Abadinsky, H. (2012). Probation and parole: Theory and practice. Pearson.Google Scholar
Anderson, D. B., Schumacker, R. E. , & Anderson, S. L. (1991). Releasee characteristics and parole success. Journal of Offender Rehabilitation, 17(1–2), 133–145. https://doi.org/10.1300/J076v17n01_10.Google Scholar
Anderson, P. R., & Slate, R. N. (2011). The decision-making network: An introduction to criminal justice. Carolina Academic Press.Google Scholar
Australia Research Data Commons. (2022). Norfolk Island Penal Establishment. State Records Authority of New South Wales. www.nsw.gov.au/.Google Scholar
Berk, R. (2017). An impact assessment of machine learning risk forecasts on parole board decisions and recidivism. Journal of Experimental Criminology, 13, 193–216. https://doi.org/10.1007/s11292-017-9286-2.Google Scholar
Borden, H. G. (1928). Factors for predicting parole success. Journal of the American Institute of Criminal Law and Criminology, 19(3), 328–336. https://doi.org/10.2307/1134622.Google Scholar
Bowman, E. L., & Ely, K. (2017). Examining the predictors of parole release in a rural jail population. The Prison Journal, 97(5), 543–561. https://doi.org/10.1177/0032885517728868.Google Scholar
Burns, R., Phillips, S., Leone, M. C., & Kinkade, P. (1999). Perspectives on parole: The board members’ viewpoint. Federal Probation, 63(1), 16–22.Google Scholar
Caplan, J. M. (2007). What factors affect parole: A review of empirical research. Federal Probation, 71(1), 16–19.Google Scholar
Caplan, J. M. (2010). Parole release decisions: Impact of victim input on a representative sample of inmates. Journal of Criminal Justice, 38(3), 291–300. https://doi.org/10.1016/j.jcrimjus.2010.02.012.Google Scholar
Carroll, J. S. (1978a). Causal attributions in expert parole decisions. Journal of Personality and Social Psychology, 36(12), 1501–1511. https://doi.org/10.1037/0022-3514.36.12.1501.Google Scholar
Carroll, J. S. (1978b). Causal theories of crime and their effect upon expert parole decisions. Law and Human Behavior, 2(4), 377–388. https://doi.org/10.1007/BF01038989.Google Scholar
Carroll, J. S., & Payne, J. W. (1977). Crime seriousness, recidivism risk, and causal attributions in judgments of prison term by students and experts. Journal of Applied Psychology, 62(5), 595–602. http://dx.doi.org/10.1037/0021-9010.62.5.595.Google Scholar
Carroll, J. S., Wiener, R. L., Coates, D., & Galegher, J. (1982). Evaluation, diagnosis, and prediction in parole decision making. Law & Society Review, 17(1), 199–228.Google Scholar
Clear, T., & Cole, G. (1997). American corrections. Wadsworth Publishing.Google Scholar
Cohen, L. (2014). Freedom’s road: Youth, parole, and the promise of Miller v. Alabama and Graham v. Florida. Cardozo Law Review, 35, 1031–1089.Google Scholar
Cromwell, P. F., & del Carmen, R. V. (1999). Community-based corrections (4th ed.). Wadsworth Publishing.Google Scholar
Cunius, M. K., Meyer, A. R., Moody, S. A., Cerfoglio, A., & Miller, M. K. (2022, March). The effects of an apology’s timing and type on parole board decision-making. Paper presented at the American Psychology-Law Society conference, Denver, CO.Google Scholar
Cunius, M. K. , & Miller, M. K. (2023, March). The effects of a prisoner’s age and type of crime on parole members’ decision-making. Paper presented at the American Psychology-Law Society conference, Philadelphia, PA.Google Scholar
Cunius, M. K. , & Miller, M. K. (in press). The effects of an incarcerated person’s gender identity and crime type on parole members’ decisions. Criminology, Criminal Justice, Law & Society.Google Scholar
Danzinger, S., Levav, J., & Avnaim-Pesso, L. (2011). Extraneous factors in judicial decisions. Proceedings of the National Academy of Sciences, 108, 6889–6892. https://doi.org/10.1073/pnas.1018033108.Google Scholar
Dawson, R. O. (1966). The decision to grant or deny parole: A study of parole criteria in law and practice. Washington University Law Quarterly, 3, 243–303.Google Scholar
Duffy, S., & Smith, J. (2014). Cognitive load in the multi-player prisoner’s dilemma game: Are there brains in the games? Journal of Behavioral and Experimental Economics, 51, 47–56. https://doi.org/10.1016/j.socec.2014.01.006.Google Scholar
ElBassiouny, A., Ayala, R., & Sircy, K. (2022). Factors influencing mock parole board members: The impact of an incarcerated person’s race/ethnicity, conversion while in prison, and mental health status. Analyses of Social Issues and Public Policy, 22(1), 286–303. https://doi.org/10.1111/asap.12286.Google Scholar
Ellis, T., & Marshall, P. (2000). Does parole work? A post-release comparison of reconviction rates for paroled and non-paroled prisoners. Australian & New Zealand Journal of Criminology, 33(3), 300–317. https://doi.org/10.1177/000486580003300304.Google Scholar
Estrada-Reynolds, V. C., Schweitzer, K. A., Nuñez, N., & Culhane, S. (2016). Male and female parole decisions: Is paying your dues or saying you’re sorry more important? Psychiatry, Psychology and Law, 23(6), 893–907. https://doi.org/10.1080/13218719.2016.1164640.Google Scholar
Feder, L. (1994). Psychiatric hospitalization history and parole decisions. Law and Human Behavior, 18(4), 395–410. https://doi.org/10.1007/BF01499047.Google Scholar
Freiberg, A., Bartels, L., Fitzgerald, R., & Dodd, S. (2018). Parole, politics and penal policy. QUT Law Review, 18(1), 191–215.Google Scholar
Gawronski, B., & Creighton, L. A. (2013). Dual-process theories. In Carlston, D. E. (Ed.), The Oxford handbook of social cognition (pp. 282–312). Oxford University Press.Google Scholar
Glaser, D. (1954). A reconsideration of some parole prediction factors. American Sociological Review, 19(3), 335–341. https://doi.org/10.2307/2087767.Google Scholar
Grattet, R., Petersilia, J., Lin, J., & Beckman, M. (2009). Parole violations and revocations in California: Analysis and suggestions for action. Federal Probation, 73(1), 2–11.Google Scholar
Hannah-Moffat, K., & Yule, C. (2011). Gaining insight, changing attitudes and managing “risk”: Parole release decisions for women convicted of violent crimes. Punishment & Society, 13(2), 149–175. https://doi.org/10.1177/1462474510394961.Google Scholar
Hart, H. (1923). Predicting parole success. Journal of the American Institute of Criminal Law and Criminology, 14(3), 405–413.Google Scholar
Hinson, J. M., Jameson, T. L., & Whitney, P. (2003). Impulsive decision making and working memory. Journal of Experimental Psychology, 29, 298–306. https://doi.org/10.1037/0278-7393.29.2.298.Google Scholar
Houser, K. A., Vîlcică, E. R., Saum, C. A., & Hiller, M. L. (2019). Mental health risk factors and parole decisions: Does inmate mental health status affect who gets released. International Journal of Environmental Research and Public Health, 16(16), 2950. https://doi.org/10.3390/ijerph16162950.Google Scholar
Huebner, B. M., & Bynum, T. S. (2006). An analysis of parole decision making using a sample of sex offenders: A focal concerns perspective. Criminology, 44(4), 961–991. https://doi.org/10.1111/j.1745-9125.2006.00069.x.Google Scholar
Huebner, B. M., & Bynum, T. S. (2008). The role of race and ethnicity in parole decisions. Criminology, 46, 907–938. https://doi.org/10.1111/j.1745-9125.2008.00130.x.Google Scholar
Hughes, WT. A., Wilson, D. J., & Beck, A. J. (2001). Trends in state parole, 1990–2000. Bureau of Justice Statistics. bjs.odp.gov.Google Scholar
Ireland, C. S., & Prause, J. (2005). Discretionary parole release: Length of imprisonment, percent of sentence served, and recidivism. Journal of Crime and Justice, 28(2), 27–49. https://doi.org/10.1080/0735648X.2005.9721637.Google Scholar
Kastenmeier, R. W., & Eglit, H. C. (1973). Parole release decision-making: rehabilitation, expertise, and the demise of mythology. American University Law Review, 22(3), 477–526.Google Scholar
Kastenmeier, R. W., & Eglit, H. C. (1975). Parole release decision-making: Rehabilitation, expertise, and the demise of mythology. In Amos, W. E. & Newman, C. L. (Eds.), Parole: legal issues, decision-making, research (pp. 76–129). Federal Legal Publications.Google Scholar
King, R. S., & Maur, M. (2002). State sentencing and corrections policy in an era of fiscal restraint. The Sentencing Project. Washington, DC. www.sentencingproject.org/.Google Scholar
Kuziemko, I. (2013). How should inmates be released from prison? An assessment of parole versus fixed-sentence regimes. The Quarterly Journal of Economics, 128(1), 371–424. https://doi.org/10.1093/qje/qjs052.Google Scholar
Lacombe, D. (2013). “Mr. S., you do have sexual fantasies?” The parole hearing and prison treatment of a sex offender at the turn of the 21st century. Canadian Journal of Sociology/Cahiers canadiens de sociologie, 38(1), 33–63.Google Scholar
Lanterman, J. L., Miller, M. K., & Moody, S. A. (2022). Public opinions of parole release decisions vary based on age and illness of prisoner. Manuscript in preparation.Google Scholar
Lawrence, T. (2020). Emotions, Mental illness, and mock parole release. Unpublished Master’s thesis; Prairie View A&M University.Google Scholar
Lindsey, S. C., & Miller, M. K. (2011). Discretionary release decisions of actual and mock parole board members: Implications for community sentiment and parole decision-making research. Psychiatry, Psychology, and Law, 18, 498–516. https://doi.org/10.1080/13218719.2011.625619.Google Scholar
Lynch, M. (2000). Rehabilitation as rhetoric: The ideal of reformation in contemporary parole discourse and practices. Punishment & Society, 2(1), 40–65. https://doi.org/10.1177/14624740022227854.Google Scholar
Mackenzie, D. L. (2001). Sentencing and corrections in the 21st century: Setting the stage for the future. National Institute of Justice.Google Scholar
Macrae, C. N., Milne, A. B., & Bodenhausen, G. V. (1994). Stereotypes as energy-saving devices: A peek inside the cognitive toolbox. Journal of Personality and Social Psychology, 66, 37–47. https://doi.org/10.1037/0022-3514.66.1.37.Google Scholar
Martinson, R. (1974). What works? – Questions and answers about prison reform. The Public Interest, 35, 22–54.Google Scholar
Maruschak, L. M., & Bonczar, T. P. (2013). Probation and parole in the United States, 2012. Bureau of Justice Statistics. www.bjs.gov/.Google Scholar
Matejkowski, J. (2011). Exploring the moderating effects of mental illness on parole release decisions. Federal Probation, 75(1), 19–26.Google Scholar
Matejkowski, J., Caplan, J. M., & Wiesel Cullen, S. (2010). The impact of severe mental illness on parole decisions: Social integration within a prison setting. Criminal Justice and Behavior, 37(9), 1005–1029. https://doi.org/10.1177/0093854810372898.Google Scholar
Matejkowski, J., Draine, J., Solomon, P., & Salzer, M. S. (2011). Mental illness, criminal risk factors and parole release decisions. Behavioral Sciences and the Law, 29(4), 528–553. https://doi.org/10.1002/bsl.991.Google Scholar
Mathews, B., Walker, A., & Rhine, E. E. (2020). Awakening the sleeping giant: The future of paroling authorities in America. Corrections, 5(3), 206–221. https://doi.org/10.1080/23774657.2018.1470478.Google Scholar
Medwed, D. S. (2007). The innocent prisoner’s dilemma: Consequences of failing to admit guilt at parole hearings. Iowa Law Review, 93(2), 491–557.Google Scholar
Meredith, T., Speir, J. C., & Johnson, S. (2007). Developing and implementing automated risk assessments in parole. Justice Research and Policy, 9(1), 1–24. https://doi.org/10.3818/JRP.9.1.2007.1.Google Scholar
Miller, M. K., Lindsey, S. C., & Kaufman, J. (2014). The religious conversion and race of a prisoner: Mock parole board members’ decisions, perceptions, and emotions. Legal and Criminological Psychology, 19, 104–130. https://doi.org/10.1111/j.2044-8333.2012.02063.x.Google Scholar
Morgan, K., & Smith, B. L. (2005a). Victims, punishment, and parole: The effect of victim participation on parole hearings. Criminology & Public Policy, 4(2), 333–360. https://doi.org/10.1111/j.1745-9133.2005.00025.x.Google Scholar
Morgan, K. D., & Smith, B. (2005b). Parole release decisions revisited: An analysis of parole release decisions for violent inmates in a southeastern state. Journal of Criminal Justice, 33(3), 277–287. https://doi.org/10.1016/j.jcrimjus.2005.02.007.Google Scholar
Morgan, K. D., & Smith, B. (2008). The impact of race on parole decision‐making. Justice Quarterly, 25(2), 411–435. https://doi.org/10.1080/07418820802024986.Google Scholar
National Advisory Commission on Criminal Justice Standards and Goals (1975). The parole grant hearing. In Amos, W. E & Newman, C. L. (Eds.), Parole (pp. 5–21). Federal Legal Publications.Google Scholar
National Parole Resource Center (2012, June). Vignettes from the national parole resource center learning sites. Bureau of Justice Assistance. http://nationalparoleresourcecenter.org/nprcdocuments/NPRC%20Vignettes.pdf.Google Scholar
Nevada Board of Parole Commissions (2011, June). Operation of the board. http://parole.nv.gov/uploadedFiles/parolenvgov/content/Hearings/OperationOfTheBoard.PDF.Google Scholar
Newman, D. J. (1975). Parole. In Amos, W. E & Newman, C. L. (Eds.), Parole: Legal issues, decision-making, research (pp. 22–75). Federal Legal Publications.Google Scholar
Newman, J. O., Genego, W. J., Goldberger, P. D., & Jackson, V. C. (1975). Project: Parole release decisionmaking and the sentencing process. The Yale Law Journal, 84(4), 810–902. https://doi.org/10.2307/795394.Google Scholar
O’Keefe, D. J. (2015). Elaboration likelihood model. In Donsbach, W. (Ed.), Concise encyclopedia of communication (pp. 168–169). Wiley-Blackwell.Google Scholar
Ostermann, M. (2011). Parole? Nope, not for me: Voluntarily maxing out of prison. Crime & Delinquency, 57(5), 686–708. https://doi.org/10.1177/0011128710372194.Google Scholar
Ostermann, M. (2015). How do former inmates perform in the community? A survival analysis of rearrests, reconvictions, and technical parole violations. Crime & Delinquency, 61(2), 163–187. https://doi.org/10.1177/0011128710396425.Google Scholar
Oudekerk, B., & Kaeble, D. (2021). Probation and parole in the United States, 2019. Bureau of Justice Statistics. bjs.ojp.gov,Google Scholar
Paparozzi, M. A., & Guy, R. (2009). The giant that never woke: Parole authorities as the lynchpin to evidence-based practice and prisoner re-entry. Journal of Contemporary Criminal Justice, 25, 397–411. https://doi.org/10.1177/1043986209344561.Google Scholar
Petersilia, J. (1999). Parole and prisoner reentry in the United States. Crime and Justice, 26, 479–529. https://doi.org/10.1086/449302.Google Scholar
Petersilia, J. (2000). Parole and prisoner reentry in the United States. Perspectives, 24, 32–46.Google Scholar
Petty, R. E., & Cacioppo, J. T. (1996). Attitudes and persuasion: Classic and contemporary approaches. Westview Press.Google Scholar
Reitz, K. R., & Rhine, E. E. (2020). Parole release and supervision: Critical drivers of American prison policy. Annual Review of Criminology, 3, 281–298. https://doi.org/10.1146/annurev-criminol-011419-041416.Google Scholar
Rhine, E. E., Petersilia, J., & Reitz, K. R. (2015). Improving parole release in America. Federal Sentencing Reporter, 28(2), 96–104.Google Scholar
Ruhland, E. L. (2020). Philosophies and decision making in parole board members. The Prison Journal, 100(5), 640–661. https://doi.org/10.1177/0032885520956566.Google Scholar
Schumacker, R. E., Anderson, D. B., & Anderson, S. L. (1990). Vocational and academic indicators of parole success. Journal of Correctional Education, 41(1), 8–13.Google Scholar
Schwalbe, C. S. J., & Koetzle, D. (2021). What the COVID-19 pandemic teaches about the essential practices of community corrections and supervision. Criminal Justice and Behavior, 48(9), 1300–1316. https://doi.org/10.1177/00938548211019073.Google Scholar
Senate Research Center (1999). Parole: Then & now. https://senate.texas.gov/_assets/srcpub/ib0599.pdf.Google Scholar
Schlager, M. D., & Robbins, K. (2008). Does parole work? – revisited: Reframing the discussion of the impact of postprison supervision on offender outcome. The Prison Journal, 88(2), 234–251. https://doi.org/10.1177/0032885508319164.Google Scholar
Shammas, V. L. (2019). The perils of parole hearings: California lifers, performative disadvantage, and the ideology of insight. PoLAR: Political and Legal Anthropology Review, 42(1), 142–160. https://doi.org/10.1111/plar.12275.Google Scholar
Slovic, P., Finucane, M. L., Peters, E., & MacGregor, D. G. (2004). Risk as analysis and risk as feelings: Some thoughts about affect, reason, risk, and rationality. Risk Analysis, 24, 311–321. https://doi.org/10.1111/j.0272-4332.2004.00433.x.CrossRefGoogle ScholarPubMed
Slovic, P., & Peters, E. (2006). Risk perception and affect. Current Directions in Psychological Science, 15, 322–325. https://doi.org/10.1111/j.1467-8721.2006.00461.x.Google Scholar
Solomon, A. L., Kachnowski, V., & Bhati, A. (2005). Does parole work? Analyzing the impact of postprison supervision on rearrest outcomes. The Urban Institute Press.Google Scholar
Southern Center for Human Rights (2012). Parole handbook: A guide to the parole consideration process for people in Georgia prisons and their families. www.schr.org/files/post/ParoleHandbook.pdf.Google Scholar
Steen, S., & Opsal, T. (2007). Punishment on the installment plan: Individual-level predictors of parole revocation in four states. The Prison Journal, 87(3), 344–366. https://doi.org/10.1177/0032885507304526.Google Scholar
Ten Bensel, T., Gibbs, B., & Lytle, R. (2015). A propensity score approach towards assessing neighborhood risk of parole revocation. American Journal of Criminal Justice, 40(2), 377–398. https://doi.org/10.1007/s12103-014-9269-z.Google Scholar
Tewksbury, R., & Connor, D. P. (2012). Predicting the outcome of parole hearings. Corrections Today, 74(3), 54–56.Google Scholar
Texas Board of Pardons and Paroles (2013). Parole/mandatory supervision information. www.tdcj.texas.gov.Google Scholar
Todorov, A., Chaiken, S., & Henderson, M. D. (2002). The heuristic-systematic model of social information processing. In Dillard, J. P., & Pfau, M. (Eds.), The persuasion handbook: Developments in theory and practice (pp. 195–211). Sage.Google Scholar
Tonry, M. (2005). Obsolescence and immanence in penal theory and policy. Columbia Law Review, 105(4), 1233–1275.Google Scholar
Travis III, L. F., & Stacey, J. (2010). A half century of parole rules: Conditions of parole in the United States, 2008. Journal of Criminal Justice, 38(4), 604–608. https://doi.org/10.1016/j.jcrimjus.2010.04.032.Google Scholar
Veysey, B. M., Ostermann, M., & Lanterman, J. L. (2014). The effectiveness of enhanced parole supervision and community services: New Jersey’s Serious and Violent Offender Reentry Initiative. The Prison Journal, 94(4), 435–453. https://doi.org/10.1177/0032885514548007.Google Scholar
Wan, , W., Poynton, , S., van Doorn, , G., & Weatherburn, , D. (2014). Parole supervision and re-offending: A propensity score matching analysis. Report to the Criminology Research Advisory Council.Google Scholar
West-Smith, M., Pogrebin, M. R., & Poole, E. D. (2000). Denial of parole: An inmate perspective. Federal Probation, 64(2), 3–10.Google Scholar
Williams III, F. P., McShane, M. D., & Dolny, H. M. (2000). Predicting parole absconders. The Prison Journal, 80(1), 24–38. https://doi.org/10.1177/0032885500080001002.Google Scholar
Yelderman, L. A., Estrada-Reynolds, V., & Lawrence, T. I. (2022). Release or denial: Evaluating the roles of emotion and risk in parole decisions. Psychological Reports, 125(4), 2088–2108. https://doi.org/10.1177/00332941211007929.Google Scholar
Yelderman, L. A., Lawrence, T. I., Lyons, C. E., & DeVault, A. (2021). Actor-observer asymmetry in perceptions of parole board release decisions. Psychiatry, Psychology and Law, 28(5), 623–644. https://doi.org/10.1080/13218719.2020.1821826.Google Scholar
Young, K. M., Mukamal, D. A., & Favre-Bulle, T. (2016). Predicting parole grants: An analysis of suitability hearings for California’s lifer inmates. Federal Sentencing Reporter, 28(4), 268–277. https://doi.org/10.1525/fsr.2016.28.4.268.Google Scholar

References

Antenangeli, L. & Durose, M. R. (2021). Recidivism of prisoners released in 24 states in 2008: A 10-year follow-up period (2008–2018). Bureau of Justice Statistics. https://bjs.ojp.gov/.Google Scholar
Berecochea, J. E., Himelson, A. N., & Miller, D. E. (1972). The risk of failure during the early parole period: A methodological note. Journal of Criminal Law and Criminology, 63(1), 93–96. https://doi.org/10.2307/1142275.Google Scholar
Bonta, J., Rugge, T., Scott, T. L., Bourgon, G., & Yessine, A. K. (2008). Exploring the black box of community supervision. Journal of Offender Rehabilitation, 47(3), 248–270. https://doi.org/10.1080/10509670802134085.Google Scholar
Bourgon, G., Gutierrez, L., & Ashton, J. (2011). The evolution of community supervision practice: The transformation from case manager to change agent. Irish Probation Journal, 8, 28–48.Google Scholar
Brown, S. L., St. Amand, M. D., & Zamble, E. (2009). The dynamic prediction of criminal recidivism: A three‐wave prospective study. Law and Human Behavior, 33(1), 25–45. https://doi.org/10.1007/s10979-008-9139-7.Google Scholar
Brown, S. L. , Robinson, D. , Wanamaker, K. A. , & Wagstaff, M. (2020). Strengths matter: Evidence from five separate cohorts of justice-involved youth and adults across North America. Criminal Justice and Behavior, 47(11), 1428–1447. https://doi.org/10.1177/0093854820931549.Google Scholar
Center for Effective Public Policy. (2017). The evidence-based decision making initiative: An overview for probation. https://cepp.com/wp-content/uploads/2021/04/The-Evidence-Based-Decision-Making-Initiative-An-Overview-for-Probation-2017.pdf.Google Scholar
Council of State Governments. (2019). Confined and costly: How supervision violations are filling prisons and burdening budgets. Council of State Governments. https://csgjusticecenter.org/wp-content/uploads/2020/01/confined-and-costly.pdf.Google Scholar
Desmarais, S. L., Johnson, K. L., & Singh, J. P. (2016). Performance of recidivism risk assessment instruments in US correctional settings. Psychological Services, 13(3), 206–222. https://doi.org/10.1037/ser0000075.Google Scholar
Dowden, C., & Andrews, D. A. (2004). The importance of staff practice in delivering effective correctional treatment: A meta-analytic review of core correctional practices. International Journal of Offender Therapy and Comparative Criminology, 48(2), 203–214. https://doi.org/10.1177/0306624X03257765.Google Scholar
Cohen, T. H., Lowenkamp, C. T., Bechtel, K., & Flores, A. W. (2020). Risk assessment overrides: Shuffling the risk deck without any improvements in prediction. Criminal Justice and Behavior, 47(12), 1609–1629. https://doi.org/10.1177/0093854820953449.Google Scholar
Cohen, T. H., Lowenkamp, C. T., & VanBenschoten, S. W. (2016). Does change in risk matter? Examining whether changes in offender risk characteristics influence recidivism outcomes. Criminology & Public Policy, 15(2), 263–296. http://dx.doi.org/10.2139/ssrn.2621267.Google Scholar
DeLisi, M., Drury, A., & Elbert, M. (2021). Who are the compliant correctional clients? New evidence on protective factors among federal supervised releases. International Journal of Offender Therapy and Comparative Criminology, 65(13–14), 1536–1553. https://doi.org/10.1177/0306624X21992681.Google Scholar
Douglas, K. S., & Skeem, J. L. (2005). Violence risk assessment: Getting specific about being dynamic. Psychology, Public Policy, and Law, 11(3), 347–383. https://doi.org/10.1037/1076-8971.11.3.347.Google Scholar
Grattet, R., Petersilia, J., Lin, J., & Beckman, M. (2009). Parole violations and revocations in California: Analysis and suggestions for action. Federal Probation, 73(1), 2–11.Google Scholar
Gray, K. M., Fields, M., & Royo Maxwell, S. (2001). Examining probation violations: Who, what, and when. Crime & Delinquency, 47(4), 537–557. https://doi.org/10.1177/0011128701047004003.Google Scholar
Hanson, R. K., & Harris, A. J. (2000). Where should we intervene? Dynamic predictors of sexual offense recidivism. Criminal Justice and Behavior, 27(1), 6–35. https://doi.org/10.1177/0093854800027001002.Google Scholar
Hanson, R. K., Harris, A. J. R., Scott, T. L., & Helmus, L. (2007). Assessing the risk of sexual offenders on community supervision: The Dynamic Supervision Project (Corrections Research User Report No. 2007–05). Ottawa, ON: Public Safety Canada. www.publicsafety.gc.ca/cnt/rsrcs/pblctns/ssssng-rsk-sxl-ffndrs/index-en.aspx.Google Scholar
Johnson, J. L., Treviño, P., Lowenkamp, C. T., & Serin, R. C. (2016). Enhancing community supervision through the application of dynamic risk assessment. Federal Probation, 80(2), 16–20.Google Scholar
LaVigne, N., Bieler, S., Cramer, L., et al. (2014). Justice Reinvestment Initiative State Assessment Report. www.urban.org/.Google Scholar
Lawrence, A. (2008). State sentencing and corrections legislation 2007 action, 2008 outlook. National Conference of State Legislatures. www.ncsl.org/.Google Scholar
LeBel, T.P., Burnett, R., Maruna, S., & Bushway, S. (2008). The “chicken and egg” of subjective and social factors in desistance from crime. European Journal of Criminology, 5(2), 131–159. https://doi.org/10.1177/1477370807087640.Google Scholar
Lloyd, C. D., Hanson, R. K., Richards, D. K., & Serin, R. C. (2020). Reassessment improves prediction of criminal recidivism: A prospective study of 3,421 individuals in New Zealand. Psychological Assessment, 32(6), 568–581. https://doi.org/10.1037/pas0000813.Google Scholar
Lloyd, C. D., & Serin, R. C. (2012). Agency and outcome expectancies for crime desistance: Measuring offenders’ personal beliefs about change. Psychology, Crime, and Law, 18(6), 543–565. https://doi.org/10.1080/1068316X.2010.511221.Google Scholar
Lowenkamp, C. T., Holsinger, A. M., & Cohen, T. H. (2015). PCRA revisited: Testing the validity of the Federal Post Conviction Risk Assessment (PCRA). Psychological Services, 12(2), 149–157. https://doi.org/10.1037/ser0000024.Google Scholar
Lowenkamp, C. T., Johnson, J. L., Holsinger, A. M., VanBenschoten, S. V., & Robinson, C. R. (2013). The federal Post Conviction Risk Assessment (PCRA): A construction and validation study. Psychological Services, 10(1), 87–96. https://doi.org/10.1037/a0030343.Google Scholar
McMurran, M. (2011). Motivational interviewing with offenders: A systematic review. Legal and Criminological Psychology, 14(1), 83–100. https://doi.org/10.1348/135532508X278326.Google Scholar
Miller, J., & Maloney, M. (2013). Practitioner compliance with risk/needs assessment tools: a theoretical and empirical assessment. Criminal Justice and Behavior, 40(7), 716–736. https://doi.org/10.1177/0093854812468883.Google Scholar
Mowen, T. J., Wodahl, E., Brent, J. J., & Garland, B. (2018). The role of sanctions and incentives in promoting successful reentry: Evidence from the SVORI data. Criminal Justice and Behavior, 45(8), 1288–1307. https://doi.org/10.1177/0093854818770695.Google Scholar
Oudekerk, B., & Kaeble, D. (2021). Probation and Parole in the United States, 2019. Bureau of Justice Statistics. https://bjs.ojp.gov/.Google Scholar
Paternoster, R., & Bushway, S. (2009). Desistance and the feared self: Toward an identity theory of criminal desistance. Journal of Criminal Law and Criminology, 99(4), 1103–1156.Google Scholar
Pettus-Davis, C., & Kennedy, S. (2020). Early lessons from the multistate study of the 5-key model for reentry. Perspectives: The Journal of the American Probation and Parole Association, 44, 19–31.Google Scholar
PEW Charitable Trusts. (2008). Policy framework can strengthen community corrections. www.pewtrusts.org/-/media/legacy/uploadedfiles/pcs_assets/2008/policy20frameworkpdf.pdf.Google Scholar
PEW Charitable Trusts. (2020). Policy reforms can strengthen community supervision: A framework to improve probation and parole. www.pewtrusts.org/-/media/assets/2020/04/policyreform_communitysupervision_report_final.pdf.Google Scholar
Robina Institute of Criminal Law and Criminal Justice (2020). Use of structured sanctions and incentives in probation and parole supervision. https://robinainstitute.umn.edu/sites/robinainstitute.umn.edu/files/2022-02/sanctions_and_incentives.pdf.Google Scholar
Rydberg, J., & Grommon, E. (2016). A multimethod examination of the dynamics of recidivism during reentry. Corrections: Policy, Practice, and Research, 1(1), 40–60. https://doi.org/10.1080/23774657.2016.1105660.Google Scholar
Serin, R. C. (2007). The Dynamic Risk Assessment for Offender Reentry (DRAOR) [unpublished user manual].Google Scholar
Serin, R. C., Chadwick, N., & Lloyd, C. D. (2016). Dynamic risk and protective factors. Psychology, Crime & Law, 22(1–2), 151–170. https://doi.org/10.1080/1068316X.2015.1112013.Google Scholar
Serin, R. C., Chadwick, N., & Prell, L. (manuscript submitted). Assessing dynamic risk and protective factors among probationers and parolees in Iowa: The utility of the dynamic risk assessment for offender re-entry. Department of Psychology, Carleton University.Google Scholar
Serin, R. C., Lloyd, C. D., & Hanby, L. J. (2010). Enhancing offender re-entry: An integrated model for enhancing offender re-entry. European Journal of Probation, 2(2), 53–75.Google Scholar
Serin, R. C., Lloyd, C. D., Helmus, L., Derkzen, D., & Luong, D. (2013). Does intra-individual change predict offender recidivism? Searching for the holy grail in a review of offender change. Aggression and Violent Behavior, 18(1), 32–53. https://doi.org/10.1016/j.avb.2012.09.002.Google Scholar
Skeem, J. L., Eno Louden, J., Camp, J., & Polaschek, D. (2007). Assessing relationship quality in mandated community treatment: Blending care with control. Psychological Assessment, 19(4), 397–410. https://doi.org/10.1037/1040-3590.19.4.397.Google Scholar
Skeem, J. L., & Lowenkamp, C. T. (2016). Risk, race, and recidivism: Predictive bias and disparate impact. Criminology, 54(4), 680–712. https://doi.org/10.1111/1745-9125.12123.Google Scholar
Skeem, J. L., & Lowenkamp, C. T. (2020). Using algorithms to address trade-offs inherent in predicting recidivism. Behavioral Sciences & the Law, 38(3), 259–278. https://doi.org/10.1002/bsl.2465.Google Scholar
Skeem, J., Monahan, J., & Lowenkamp, C. (2016). Gender, risk assessment, and sanctioning: The cost of treating women like men. Law and Human Behavior, 40(5), 580–593. https://doi.org/10.1037/lhb0000206.Google Scholar
Stone, A. G., Lloyd, C. D., & Serin, R. C. (2021). Dynamic risk factors reassessed regularly after release from incarceration predict imminent violent recidivism. Law and Human Behavior, 45(6), 512–523. https://doi.org/10.1037/lhb0000463.Google Scholar
Stone, A. G., Spivak, B. L., Lloyd, C. D., Papalia, N. L., & Serin, R. C. (2022). Clients’ current presentation yields best prediction of criminal recidivism: Jointly modelling repeated assessments of risk and recidivism outcomes in a community sample of paroled New Zealanders. Journal of Consulting and Clinical Psychology, 90(11), 872–883. https://doi.org/10.1037/ccp0000766.Google Scholar
Trotter, C. (1996). The impact of different supervision practices in community corrections: Cause for optimism. Australian and New Zealand Journal of Criminology, 29(1), 29–46. https://doi.org/10.1177/000486589602900103.Google Scholar
Ullrich, S., & Coid, J. (2011). Protective factors for violence among released prisoners‐effects over time and interactions with static risk. Journal of Consulting and Clinical Psychology, 79(3), 381–390. https://doi.org/10.1037/a0023613.Google Scholar
Viglione, J., Rudes, D. S., & Taxman, F. S. (2017). Probation officer use of client-centered communication strategies in adult probation setting. Journal of Offender Rehabilitation, 56(1), 38–60. https://doi.org/10.1080/10509674.2016.1257534.Google Scholar
Viljoen, J. L., Cochrane, D. M., & Jonnson, M. R. (2018). Do risk assessment tools help manage and reduce risk of violence and reoffending? A systematic review. Law and Human Behavior, 42(3), 181–214. https://doi.org/10.1037/lhb0000280.Google Scholar
Viljoen, J. L., & Vincent, G. M. (2020). Risk assessments for violence and reoffending: Implementation and impact on risk management. Clinical Psychology: Science and Practice. Advance online publication. https://doi.org/10.1111/cpsp.12378.Google Scholar

References

Arkes, H. A., Dawes, R. M., & Christensen, C. (1986). Factors influencing the use of a decision rule in a probabilistic task. Organizational Performance and Human Decision Processes, 37, 93–110. https://doi.org/10.1016/0749-5978(86)90046-4.Google Scholar
Boccaccini, M. T., Murrie, D., Rufino, C., Gardner, K. A., B. O. (2014). Evaluator differences in Psychopathy Checklist-Revised factor and facet scores. Law and Human Behavior, 38(4), 337–345. https://doi.org/10.1037/lhb0000069.Google Scholar
Brown, B., & Rakow, T. (2015). Understanding clinicians’ use of cues when assessing the future risk of violence: A clinical judgment analysis in the psychiatric setting. Clinical Psychology and Psychotherapy, 23, 125–141. https://doi.org/10.1002/cpp.1941.Google Scholar
Brunswick, E., (1956). Perception and the representative design of psychological experiments. University of California Press. https://doi.org/10.1525/9780520350519.Google Scholar
Collins, C., Martin, K., & Marshall, L. (2019). Do review tribunals consider protective factors in decisions about patients found not criminal responsible? Journal of Forensic Psychiatry and Psychology, 30(5), 894–907. https://doi.org/10.1080/14789949.2019.1650097.Google Scholar
Cooper, R. P., & Werner, P. D. (1990). Predicting violence in newly admitted inmates: A lens model analysis of staff decision making. Criminal Justice and Behavior, 17(4), 431–447. https://doi.org/10.1177/0093854890017004004.Google Scholar
Côté, G., Crocker, A. G., Nicholls, T. L., & Seto, M. C. (2012). Risk assessment instruments in clinical practice. The Canadian Journal of Psychiatry/La Revue Canadienne de Psychiatrie, 57(4), 238–244. https://doi.org/10.1177/070674371205700407.Google Scholar
Coupland, R. B. A., & Olver, M. E. (2020). Assessing dynamic violence in a high-risk treated sample of violent offenders. Assessment, 27(8), 1886–1900. https://doi.org/10.1177/1073191118797440.Google Scholar
Dawes, R. M., Faust, D., & Meehl, P. E. (1989). Clinical versus actuarial judgment. Science, 243, 1668–1674. https://doi.org/10.1126/science.2648573.Google Scholar
Douglas, K. S., & Belfrage, H. (2015). The structured professional judgment approach to violence risk assessment and management: Why it is useful, how to use it, and its empirical support. In Pietz, C. A. & Mattson, C. A. (Eds.), Violent offenders: Understanding and assessment (pp. 360–383). Oxford University Press.Google Scholar
Douglas, K. S., & Ogloff, J. R. P. (2003). The impact of confidence on the accuracy of structured professional and actuarial violence risk judgments in a sample of forensic psychiatric patients. Law and Human Behavior, 27(6), 573–587. https://doi.org/10.1023/b:lahu.0000004887.50905.f7.Google Scholar
Duwe, G., & Rocque, M. (2018). The home-field advantage and the perils of professional judgment: Evaluating the performance of the Static-99 R and the MnSOST-3 in predicting sexual recidivism. Law and Human Behavior, 42(3), 269–279. https://doi.org/10.1037/lhb0000277.Google Scholar
Elbogen, E. B. (2016). The process and context of violence risk assessment. In Singh, J. P., Bjørkly, S., and Fazel, S. (Eds.), International perspectives on violence risk assessment (pp. 53–75). Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199386291.003.0005.Google Scholar
Elbogen, E. B., Huss, M. T., Tomkins, A. J., & Scalora, M. J. (2005). Clinical decision making about psychopathy and violence risk assessment in public sector mental health settings. Psychological Services, 2(2), 133–141. https://doi.org/10.1037/1541-1559.2.2.133.Google Scholar
Elbogen, E. B., Mercado, C. C., Scalora, M. J., & Tomkins, A. J., (2002). Perceived relevance of factors for violence risk assessment: A survey of clinicians. The International Journal of Forensic Mental Health, 1, 37–47. https://doi.org/10.1080/14999013.2002.10471159.Google Scholar
Elbogen, E. B., Williams, A. L., Kim, D., Tomkins, A. J., & Scalora, M. J. (2001). Gender and perceptions of dangerousness in civil psychiatric patients. Legal and Criminological Psychology, 6, 215–228. https://doi.org/10.1348/135532501168299.Google Scholar
Hilton, N. Z., Harris, G. T., Rawson, K., Beach, C. A. (2005). Communicating violence risk information to forensic decision makers. Criminal Justice and Behavior, 32, 97–116. https://doi.org/10.1177/0093854804270630.Google Scholar
Hilton, N. Z., & Simmons, J. L. (2001). The influence of actuarial risk assessment in clinical judgments and tribunal decisions about mentally disordered offenders in maximum security. Law and Human Behavior, 25, 393–408. https://doi.org/10.1023/A:1010607719239.Google Scholar
Huss, M. T. (2014). Forensic psychology: Research, clinical practice, and applications. Wiley.Google Scholar
Klassen, D., & O’Connor, W. A. (1989). Assessing the risk of violence in released mental patients: A cross-validation study. Psychological Assessment: A Journal of Consulting and Clinical Psychology, 1(2), 75–81. https://doi.org/10.1037/1040-3590.1.2.75.Google Scholar
Kroner, D. G. , & Sam, L. (2022). Risk assessment among adults. Routledge. https://doi.org/10.4324/9780367198459-REPRW151-1.Google Scholar
McKee, S. A., Harris, G. T., & Rice, M. E. (2007). Improving forensic tribunal decisions: The role of the clinician. Behavioral Sciences & the Law, 25(4), 485–506. https://doi.org/10.1002/bsl.768.Google Scholar
McNeil, D. E, . & Binder, R. L. (2007) Effectiveness of a mental health court in reducing criminal recidivism and violence. American Journal of Psychiatry, 164(9), 1395–1403. https://doi.org/10.1176/appi.ajp.2007.06101664.Google Scholar
Miller, A. K., Rufino, K. A., Boccaccini, M. T., Jackson, R. L., & Murrie, D. C. (2011). On individual differences in person perception: Raters’ personality traits relate to their Psychopathy Checklist-Revised scoring tendencies. Assessment, 18(2), 253–260. https://doi.org/10.1177/1073191111402460.Google Scholar
Mills, J. F. (2017). Violence risk assessment: A brief review, current issues, and future directions. Canadian Psychology, 58, 40–49. https://doi.org/10.1037/cap0000100.Google Scholar
Monahan, J. (1981). The clinical prediction of violent behavior. Crime & Delinquency Issues: A Monograph Series, ADM, 81–921, 134.Google Scholar
Monahan, J. (1988). Risk assessment of violence among the mentally disordered: Generating useful knowledge. International Journal of Law and Psychiatry, 11(3), 249–257. https://doi.org/10.1016/0160-2527(88)90012-X.Google Scholar
Monahan, J. (1992). Risk assessment: Commentary on Poythress and Otto. Forensic Reports, 5(1), 151–154. https://doi.org/10.1016/0160-2527(88)90012-X.Google Scholar
Mulvey, E. P., & Lidz, C. W. (1985). Back to basics: A critical analysis of dangerousness research in a new legal environment. Law and Human Behavior, 9(2), 209–219. https://doi.org/10.1007/BF01067052.Google Scholar
Murray, J., Charles, K. E., & Cooke, D. J., & Thompson, M. E. (2014). Investigating the influence of causal attributions on both the worksheet and checklist versions of the HCR-20. The International Journal of Forensic Mental Health, 13(1), 8–17. https://doi.org/10.1080/14999013.2014.890978.Google Scholar
Murrie, D. C., Boccaccini, M. T., Guarnera, L. A., & Rufino, K. A. (2013). Are forensic experts biased by the side that retained them? Psychological Science, 24(10), 1889–1897. https://doi.org/10.1177/0956797613481812.Google Scholar
Murrie, D. C., Boccaccini, M. T., Turner, D. B., et al. (2009). Rater (dis)agreement on risk assessment measures in sexually violent predator proceedings: Evidence of adversarial allegiance in forensic evaluations? Psychology, Public Policy, and Law, 15, 19–53. https://doi.org/10.1037/a0014897.Google Scholar
Odeh, M. S., Zeiss, R. A., & Huss, M. T. (2006). Cues they use: Clinicians’ endorsement of risk cues in predictions of dangerousness. Behavioral Sciences & the Law, 24(2), 147–156. https://doi.org/10.1002/bsl.672.Google Scholar
Otto, R. K. (1992). Prediction of dangerous behavior: A review and analysis of “second generation” research. Forensic Reports, 5(1), 103–133.Google Scholar
Padgett, R., Webster, C. D., & Robb, M. K. (2005). Unavailable essential archival data: A major limitation in the conduct of clinical practice and research in violence risk assessment. The Canadian Journal of Psychiatry/La Revue Canadienne de Psychiatrie, 50(14), 937–940. https://doi.org/10.1177/070674370505001408.Google Scholar
Quinsey, V. L., & Maguire, A. (1983). Offenders remanded for a psychiatric examination: Perceived treatability and disposition. International Journal of Law and Psychiatry, 6(2), 193–205. https://doi.org/10.1016/0160-2527(83)90015-8.Google Scholar
Segal, S., Watson, M., Goldfinger, S., & Averbuck, D. (1988). Civil commitment in the psychiatric emergency room: I The assessment of dangerousness by emergency room clinicians. Archives of General Psychiatry, 45, 753–758. https://doi.org/10.1001/archpsyc.1988.01800320064008.Google Scholar
Singh, J. P., Desmarais, S. L., Hurducas, C., et al. (2014). International perspectives on the practical application of violence risk assessment: A global survey of 44 countries. International Journal of Forensic Mental Health, 13(3), 193–206. https://doi.org/10.1080/14999013.2014.922141.Google Scholar
Slovic, P., Monahan, J., & MacGregor, D. G. (2000). Violence risk assessment and risk communication: The effects of using actual cases, providing instructions, and employing probability versus frequency formats. Law and Human Behavior, 24, 271–296. https://doi.org/10.1023/a:1005595519944.Google Scholar
van Leeuwen, M. E., & Harte, J. M. (2015). Violence against mental health care professionals: Prevalence, nature and consequences. The Journal of Forensic Psychiatry & Psychology, 26, 1–18. https://doi.org/10.1080/14789949.2015.1012533.Google Scholar
Viljoen, J. L., Cochrane, D. M., & Jonnson, M. R. (2018). Do risk assessment tools help manage and reduce risk of violence in reoffending? A systematic review. Law and Human Behavior, 42(3), 181–214. https://doi.org/10.1037/lhb0000280.Google Scholar
Viljoen, J. L., Jonnson, M. R., Cochrane, D. M., Vargen, L. M., & Vincent, G. M. (2019). Impact of risk assessment instruments on rates of pretrial detention, postconviction placements, and release: A systematic review and meta-analysis. Law and Human Behavior, 43(5), 397–420. https://doi.org/10.1037/lhb0000344.Google Scholar
Viljoen, J. L. , Vargen, L. M. , Cochrane, D. M., et al. (2021). Do structured risk assessments predict violent, any, and sexual offending better than unstructured judgment? An umbrella review. Psychology, Public Policy, and Law, 27(1), 79–97. https://doi.org/10.1037/law0000299.Google Scholar
Werner, P., & Meloy, J. (1992). Decision making about dangerousness in releasing patients from long-term hospitalizations. Journal of Psychiatry and Law, 20, 25–47.Google Scholar
Werner, P., Rose, T., L., & Yesavage, J. A. (1983). Reliability, accuracy, and decision-making strategy in clinical predictions of imminent dangerousness. Journal of Consulting and Clinical Psychology, 51(6), 816–825. https://doi.org/10.1037//0022-006x.51.6.815.Google Scholar
Wormith, J. S., Hogg, S., Guzzo, L. (2012). The predictive validity of a general risk/needs assessment inventory on sexual offender recidivism and an exploration of the professional override. Criminal Justice and Behavior, 39(12), 1511–1538. https://doi.org/10.1177/0093854812455741.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×