scholarly journals An examination of change in dynamic risk of offending over time among serious juvenile offenders

2016 ◽  
Vol 45 ◽  
pp. 48-53 ◽  
Author(s):  
Edward P. Mulvey ◽  
Carol A. Schubert ◽  
Lindsey Pitzer ◽  
Samuel Hawes ◽  
Alex Piquero ◽  
...  
Keyword(s):  
Juvenile Offenders ◽  
Dynamic Risk ◽  
Over Time

Using behavioural manifestations of dynamic risk factors to assess change in incarcerated sexual offenders

2021 ◽  
Vol 2 (1) ◽  
pp. 1-20
Author(s):  
Tamara Sweller ◽  
◽  
Stuart Thomas ◽  
Michael Daffern ◽  
◽  
...  
Keyword(s):  
Risk Factors ◽  
Psychological Adjustment ◽  
Sexual Offenders ◽  
Social Adjustment ◽  
Self Report ◽  
Change Over Time ◽  
Dynamic Risk Factors ◽  
Dynamic Risk ◽  
Measure Change ◽  
Over Time

This study investigated change in behavioural manifestations of dynamic risk factors, in a sample of adult male sexual offenders who completed a custody-based treatment program. A checklist was developed to monitor and determine change in the frequency of behavioural manifestations of dynamic risk factors and prosocial equivalent behaviours. Offenders and custodial staff completed the checklist once each week for the duration of the offender’s period of treatment (range = 26-69 weeks, M = 45). Checklist scores were aggregated into domains based on the organisation of the Risk for Sexual Violence Protocol (Psychological Adjustment; Social Adjustment; Mental Disorder; Manageability). Change over time for individuals and the group was evaluated. Results showed an increase in positive behaviour in all domains, but there was only a decrease in risk-related manifestations in Psychological Adjustment, and this was only according to offenders. Offender self-report and staff observations were compared, revealing different perceptions of change. Using a behavioural checklist that incorporates self-report and observer data to measure change may provide a comprehensive measure of change over time.

Volatility Weighting over Time in the Presence of Transaction Costs

2019 ◽  
Keyword(s):  
Transaction Costs ◽  
Empirical Studies ◽  
Risk Control ◽  
Control Technique ◽  
Risk Exposure ◽  
Trading Costs ◽  
Portfolio Risk ◽  
Dynamic Risk ◽  
Weighting Strategy ◽  
Over Time

Numerous empirical studies demonstrate the superiority of dynamic strategies with a volatility-weighting-over-time mechanism. These strategies control the portfolio risk over time by adjusting the risk exposure according to updated volatility forecasts. Yet, to reap all the benefits promised by volatility weighting over time, the composition of the active portfolio must be revised rather frequently. Transaction costs represent a serious obstacle to benefiting from this dynamic risk control technique. In this article, we propose a modified volatility-weighting strategy that allows one to reduce dramatically the amount of trading costs. The empirical evidence shows that the advantages of the modified volatility-weighting strategy persist even in the presence of high transaction costs.

Religiosity, Crime, and Drug Use Among Juvenile Offenders: A Test of Reciprocal Relationships Over Time

2018 ◽  
Vol 62 (14) ◽  
pp. 4445-4464 ◽  
Author(s):  
Sung Joon Jang
Keyword(s):  
Juvenile Offenders ◽  
Drug Use ◽  
Structural Equation ◽  
Equation Modeling ◽  
Religious Activities ◽  
Hard Drug ◽  
Reciprocal Relationships ◽  
Religious Salience ◽  
The Relationship ◽  
Over Time

This article examines whether an individual’s religiosity has reciprocal relationships with crime and drug use among juvenile offenders. Structural equation modeling is applied to analyze 11-wave panel data from a study of juveniles adjudicated or found guilty of a serious offense in two states. Offenders’ religiosity is measured both objectively (participation in religious activities) and subjectively (religious salience, experiences, and efficacy). While holding constant an offender’s exposure time (the proportion of time on the street), previous levels of crime and drug use, and sociodemographic controls, this study found the relationship between religiosity and crime (i.e., nondrug offending) to be either bidirectional or unidirectional. The relationship between religiosity and drug use (binge drinking, marijuana use, and hard drug use) is, however, unidirectional over time. When unidirectional relationship is found, it is religiosity that decreases crime and drug use, not the other way around. Implications of findings are discussed.

Between Protection and Repression: A Short History of Juvenile Policing in the Netherlands

2007 ◽  
Vol 9 (3) ◽  
pp. 214-225 ◽  
Author(s):  
Manon van de Riet ◽  
Wim Bernasco ◽  
Peter van der Laan
Keyword(s):  
Twentieth Century ◽  
Juvenile Offenders ◽  
The Netherlands ◽  
European Countries ◽  
Short History ◽  
Minimal Intervention ◽  
History Of ◽  
Over Time ◽  
The Way

The police in the Netherlands have traditionally been characterised by restraint when dealing with cases involving minors. However, this policy of minimal intervention appears to be waning in recent years. This shift from welfare to justice seems to be in line with the developments in other European countries. This article comments on this development by framing it in the long-term history of juvenile policing in the Netherlands. It describes the founding and development of the Juvenile Police as an organisation, and sketches the parallel changes in juvenile policing that occurred during the twentieth century. The organisation of juvenile policing has changed considerably over time with a visible tendency away from welfare oriented policing. As such, restraint and minimal intervention may no longer characterise the way Dutch police handle juvenile offenders.

Comparing Early and Late Twentieth-Century Boston and Chicago Male Juvenile Offenders: What Changed?

2009 ◽  
Vol 104 (1) ◽  
pp. 185-198 ◽  
Author(s):  
Robert John Zagar ◽  
John Russell Hughes ◽  
Kenneth G. Busch ◽  
Jack Arbit
Keyword(s):  
Juvenile Offenders ◽  
Head Injuries ◽  
Gang Membership ◽  
Demographic Differences ◽  
Actuarial Assessment ◽  
County Public School ◽  
Biological Parents ◽  
Late Twentieth ◽  
Late Twentieth Century ◽  
Over Time

To investigate changes in characteristics of delinquents over time, randomly selected contemporary delinquents (Zagar, et al., 1980–1988; n = 2,031) were compared with 3 historical Chicago and Boston samples (Healy & Bonner, 1909–1915, n = 2,000; Healy & Bonner, 1917–1923, n = 2,000; Glueck & Glueck, 1917–1922, n = 1,000). All underwent physical, psychiatric, psychological, school, and social examinations. Contemporary delinquents had more assault, burglary, homicide, alcohol and substance abuse, gang membership, head injury, overdose, and single parents. Historical delinquent samples had more thieves and families with both biological parents. Historical delinquent mean IQ was 5 points below standardization average; modern delinquents were 22 points lower. Contemporary offenders were a greater portion of the county public school-aged population. Current more sensitive and specific examinations account for increases in observed overdoses and head injuries in the 1980s sample. Other demographic differences between contemporary and 3 historical delinquent samples were robust. Findings are discussed with respect to a need for early actuarial assessment and empirical treatment of the costliest delinquents: the dropouts, alcoholics, addicts, career delinquents-criminals, and homicide-prone youth.

scholarly journals The Relationship Between Patterns of Change in Dynamic Risk and Strength Scores and Reoffending for Men on Community Supervision

2021 ◽  
pp. 009385482199351
Author(s):  
Kayla A. Wanamaker ◽  
Shelley L. Brown
Keyword(s):  
Longitudinal Design ◽  
Dynamic Strength ◽  
Service Planning ◽  
Rate Of Change ◽  
Risk Scores ◽  
Community Supervision ◽  
Gradual Change ◽  
Dynamic Risk ◽  
Technical Violations ◽  
Over Time

Research is needed focusing on the predictive nature of dynamic risk and strength score changes. The current study includes 11,953 Canadian men under community supervision with Service Planning Instrument re-assessment data. Using a retrospective, multi-wave longitudinal design, hierarchical linear modeling (HLM) was conducted to assess patterns of change in total dynamic risk and strength scores across three to five timepoints over 30 months. Change parameters from the HLM were incorporated into regression models, linking change to three reoffending outcomes: technical violations, new charges, and new violent charges. Results indicated that total dynamic risk scores decreased over time and total dynamic strength scores increased over time, although the rate of change for both was gradual. Change in total dynamic risk scores was predictive of all outcomes, whereas change in total dynamic strength scores only predicted technical violations. Results demonstrated the utility of re-assessing dynamic risk and strength scores over time.

Change in Level of Service Inventory–Ontario Revised (LSI-OR) Risk Scores Over Time: An Examination of Overall Growth Curves and Subscale-Dependent Growth Curves

2015 ◽  
Vol 61 (14) ◽  
pp. 1606-1622 ◽  
Author(s):  
David M. Day ◽  
Holly A. Wilson ◽  
Kelly Bodwin ◽  
Candice M. Monson
Keyword(s):  
Risk Factors ◽  
Risk Score ◽  
Growth Curves ◽  
Criminal History ◽  
Rate Of Change ◽  
Level Of Service ◽  
Dynamic Risk Factors ◽  
Dynamic Risk ◽  
Over Time ◽  
Overall Risk

The dynamic nature of risk to re-offend is an important issue in the management of offenders and has stimulated extensive research into dynamic risk factors that can alter an individual’s overall risk to re-offend if addressed. However, few studies have examined the relative importance of these dynamic risk factors, complicating the task of developing case management and treatment plans that will effect the most change. Using a large, high-risk sample and multi-wave data of a common risk assessment tool, the Level of Service Inventory–Ontario Revised (LSI-OR), the current study investigated the relationship among criminogenic risk factors and their role in influencing the overall risk score. Results indicated a diverse pattern of effects on the eight subscale scores, specifically suggesting that changes on Procriminal Attitude/Orientation, Criminal History, and Leisure/Recreation subscales resulted in a quicker rate of change to the overall risk score over time. These results suggest that some factors may be driving the change in overall risk and could potentially effect the most change if prioritized for intervention. Practical implications and implications for further research are discussed.

Multi-Hazard Scenarios and Dynamic Risk

2021 ◽  
Author(s):  
Joel Gill ◽  
Ekbal Hussain ◽  
Bruce Malamud ◽  
Robert Šakić Trogrlić
Keyword(s):  
Natural Hazards ◽  
Urban Poor ◽  
Disaster Risk ◽  
Dynamic Nature ◽  
Change Over Time ◽  
The Public ◽  
Multiple Hazards ◽  
Risk Equation ◽  
Dynamic Risk ◽  
Over Time

<p>In this paper, we discuss the dynamic nature of risk through the lens of multi-hazard relationships and scenarios. Disaster risk is commonly expressed as (Risk = Hazard × Exposure × Vulnerability). This expression does not communicate the extent to which each term (and therefore risk and impact) can change over time, and any relationships between the four variables. To better convey and discuss multi-hazards and dynamic risk, in July and August 2020 we held two virtual workshops (40 and 35 participants) as part of the GCRF Tomorrow’s Cities Research Hub, which has as its focus four cities Istanbul, Kathmandu, Nairobi, and Quito, with a particular emphasis on the urban poor. During the two workshops, participants (including those from academia, NGOs, and the public sector) from each city generated multi-hazard scenarios that can be used to improve the understanding of dynamic risk and we highlighted three main examples of dynamic risk: (1) The hazard term can involve multiple hazards, with relationships between hazards, and the likelihood or magnitude of single natural hazards and multi-hazard scenarios varying over time. (2) Both the exposure and vulnerability components of the risk equation change over time, and can contribute to the triggering, amplification (or reduction) of multi-hazard events. (3) Progression through multi-hazard scenarios can influence or drive changes in both exposure and/or vulnerability terms.<strong> </strong>These three statements illustrate the dynamic nature of each component of the risk equation and the existence of relationships between each term. Furthermore, they demonstrate how understanding the multi-hazard landscape and potential multi-hazard scenarios can help to enrich understanding of dynamic risk. This understanding of multi-hazard scenarios can be used to consider potential interventions where risk is dynamic.</p>

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