No description available.

No description available.

The vast number of individuals under correctional supervision in the United States has been an area of concern for decades. The correctional population as a whole is made up of approximately six million individuals, with approximately four million serving community sentences. It is essential to provide adequate services and resources to those serving community sentences due to the large number serving such sentences. To add to the concern is the immense number of offenders with mental illness under correctional supervision. Often, offenders with mental illness receive psychiatric services, but treatment programs that address the cause of criminal activity are neglected. The goal of this study is to examine scores from two assessment instruments measuring criminal thinking and the therapeutic alliance to determine their predictability for future criminal activity using a sample of thirty-five probationers with mental illness. Probationers completed both the Psychological Inventory of Criminal Thinking Styles and the Working Alliance Inventory in order to determine the extent of criminal cognitions and measure the relationship between therapist and patient and agreement towards the goals and tasks of therapy, respectively. Results indicate that probationers who score less favorably on each of the scales were more likely to obtain a new charge following completion of the program. Further, less Agreement on the Tasks of Therapy was a significant predictor for future criminal activity. This study adds to the correctional mental health treatment literature, and illuminates areas which can be improved and provides recommendations for future research.

The nature of how we make judgments has received a great deal of attention in the last few decades. Risk communication research has indicated that risk-related messages can elicit affective responses in audiences, which can then have a significant impact on how such audiences judge risk in general. Using a 2 x 2 between-subjects factorial design, this study found that, contrary to Johnson and Tversky's (1983) findings, presenting narratives about lethal risk does not influence readers' judgments about the frequency that risks occur, nor do such narratives influence participant worry levels about the lethal risks, more generally. Additionally, the inclusion of an image alongside both positively and negatively valenced narratives demonstrated no effect on frequency estimates or worry levels. These experimental conditions, although revealing no significant effects, did illuminate the relationship between judgments of risk frequency and corresponding worry levels. Implications for future research on affect and judgments of risk, as well as the relationship between judgments of control and risk assessments, are discussed.

Recent international regulatory reforms have put more responsibility on auditors for detecting financial statement fraud. The recent changes to international auditing standards make it compulsory for members of the audit team to discuss the susceptibility of an entity to fraudulent misstatements at the audit planning stage. These standards do not stipulate the format of these group discussions, nor provide any explicit guidelines on how to carry out effective discussions. This dissertation reports on two studies that examine different discussion techniques which could lead to a better identification of audit fraud risks at the audit planning stage, and may in turn help in fraud detection. Study One tests whether two enhanced forms of interacting group processes (brainstorming guidelines and premortem instructions) have advantages over an interacting group (without brainstorming guidelines). The brainstorming group is provided with Osborn???s (1957) original brainstorming guidelines. Premortem is a variation of the mental simulation idea developed by Klein (1999) invoking a scenario where participants actively search for a flaw in their plans. The auditors in both the brainstorming group treatment and the premortem group treatment generated a larger number of potential frauds than the interacting group treatment. These results were robust across a range of dependent variables used to measure quantity and quality of fraud items. The results also show that more premortem groups listed rare frauds compared to the other two group structures. There was a negative relationship between the number of items listed and the assessed likelihood of fraud. Participants who estimated a higher likelihood of fraud provided a more complete mental simulation of how a fraud could be perpetrated. Study Two focuses on the individual brainstorming phase which may occur before the group brainstorming session. It examines whether giving additional brainstorming guidelines and task decomposing (in addition to the original brainstorming guidelines), improve performance compared to having only the original brainstorming guidelines. Both the additional brainstorming guidelines and the task decomposition treatments generated a larger number of potential frauds than the brainstorming guidelines treatment. Task decomposition helps participants focus equally on all task subcategories leading to a more diverse set of ideas.

Existing credibility models have mostly allowed for one source of claim dependence only, that across time for an individual insured risk or a group of homogeneous insured risks. Numerous circumstances demonstrate that this may be inadequate and insufficient. In this dissertation, we developed a two-level common effects model, based loosely on the Bayesian model, which allows for two possible sources of dependence, that across time for the same individual risk and that between risks. For the case of Normal common effects, we are able to derive explicit formulas for the credibility premium. This takes the intuitive form of a weighted average between the individual risk's claims experience, the group's claims experience and the prior mean. We also consider the use of copulas, a tool widely used in other areas of work involving dependence, in constructing credibility premiums. Specifically, we utilise copulas to model the dependence across time for an individual risk or group of homogeneous risks. We develop the construction with several well-known families of copulas and are able to derive explicit formulas for their respective conditional expectations. Whilst some recent work has been done on constructing credibility models with copulas, explicit formulas for the conditional expectations have rarely been made available. Finally, we calibrate these copula credibility models using a real data set. This data set relates to the claims experience of workers' compensation insurance by occupation over a 7-year period for a particular state in the United States. Our results show that for each occupation, claims dependence across time is indeed present. Amongst the copulas considered in our empirical analysis, the Cook-Johnson copula model is found to be the best fit for the data set used. The calibrated copula models are then used for prediction of the next period's claims. We found that the Cook-Johnson copula model gives superior predictions. Furthermore, this calibration exercise allowed us to uncover the importance of examining the nature of the data and comparing it with the characteristics of the copulas we are calibrating to.

There is a large quantity of literature available on longitudinal train dynamics and risk assessment but nothing that combines these two topics. This thesis is focused at assessing derailment risks developed due to longitudinal train dynamics. A key focus of this thesis is to identify strategies that can be field implemented to correctly manage these risks. This thesis quantifies derailment risk and allows a datum for comparison. A derailment risk assessment on longitudinal train dynamics was studied for a 107 vehicle train consist travelling along the Monto and North Coast Lines in Queensland, Australia. The train consisted of 103 wagons and 4 locomotives with locomotives positioned in groups of two in lead and mid train positions. The wagons were empty hopper wagons on a track gauge of 1067mm. The scenarios studied include: the effect of longitudinal impacts on wagon dynamics in transition curves; and the effects of longitudinal steady forces on wagon dynamics on curves. Simulation software packages VAMPIRE and CRE-LTS were used. The effects of longitudinal impacts from in-train forces on wagon dynamics in curves were studied using longitudinal train simulation and detailed wagon dynamics simulation. In-train force impacts were produced using a train control action. The resulting worst-case in-train forces resulting from these simulations were applied to the coupler pin of the wagon dynamics simulation model. The wagon model was used to study the effect of these in-train forces when applied in curves and transitions at an angle to the wagon longitudinal axis. The effects of different levels of coupler impact forces resulting from different levels of coupling slack were also studied. Maximum values for wheel unloading and L/V ratio for various curve radii and coupler slack conditions were identified. The results demonstrated that the derailment criteria for wheel unloading could be exceeded for a coupler slack of 50mm and 75mm on sharper curves, up to 400m radii. A detailed study of the effect of steady in-train forces on wagon dynamics on curves also was completed. Steady in-train forces were applied to a three wagon model using VAMPIRE. Maximum and minimum values of wheel unloading and L/V ratio were identified to demonstrate the level of vehicle stability for each scenario. The results allowed the worse cases of wheel unloading and L/V ratio to be studied in detail. Probability density functions were constructed for the occurrence of longitudinal forces and coupler angles for the Monto and North Coast Lines. Data was simulated for a coupler slack of 25, 50 and 75mm and force characteristics were further classified into the occurrences of impact and non-impact forces. These probability density functions were analysed for each track section to investigate the effects of coupler slack, track topography and gradient on wagon dynamics. The possible wagon instability in each of these scenarios was then assessed to give a measure of the potential consequences of the event. Risk assessment techniques were used to categorise levels of risk based on the consequences and likelihood of each event. It was found that for the train configuration simulated, the Monto Line has a higher derailment risk than the North Coast Line for many of the scenarios studies in this thesis. For a coupler slack of 25mm no derailment risks were identified, 50mm coupler slack derailment risks were only identified on the Monto track and the majority of derailment risks were identified for a 75mm coupler slack.

Thesis (M.S.)--Air Force Institute of Technology, 2007. / "March 2007." "AFIT/GRD/ENS/07-01." "ADA466575"--URL. Includes bibliographical references (leaves 99-102). Also issued in paper format.

Minority children are involved in the child welfare system at rates disproportionate to their numbers in the overall population. Prior research argues that risk assessments conducted by child welfare agencies may be racially biased, and thus contribute to disproportionality. This study seeks to explore the effect of different risk assessment models on racial disproportionality. This is done by examining the relationship between race/ethnicity and various child welfare outcomes in three states that utilize the consensus-based model and three states that utilize the actuarial model of risk assessment. Results were similar for both groups of states, suggesting that one model is not more biased than the other. The results also indicate that racial/ethnic groups enter the child welfare system at different rates. However, groups remained involved in subsequent outcomes at consistent percentages. Finally, the results suggest differential treatment among the most restrictive child welfare outcomes. / McAnulty College and Graduate School of Liberal Arts / Graduate Center for Social and Public Policy / MA / Thesis

In this dissertation I explore the application of two novel modeling techniques for improving risk analysis of vector-borne disease and discuss their potential use in integrating environmental risk assessment that guides environmental and public health decisions. Techniques for analyzing risk have been considered inadequate due to a lack of understanding of the problem and an appropriate analytic-deliberative process clarifying the meaning of analytic findings and uncertainty (National Research Council (NRC), 1996; Peterman and Anderson, 1999). Thus, new integrative risk analysis tools are needed that are responsive to more complex environmental problems. In this work, I develop a qualitative community model that combines a conventional biomathematical model of vector-borne disease transmission with recent developments in community modeling. My procedure predicts the change in risk of vector-borne disease from press perturbations, a disturbance that results in a permanent change in a growth parameter. I also use a Relational Bayesian Modeling technique to exploit existing data to determine plausible mechanisms and geospatial and temporal patterns of disease spread. I apply these tools to Lyme disease and West Nile Encephalitis as examples of two different vector-borne diseases associated with complex ecological communities. Both the qualitative modeling and Bayesian methods provide an integrated risk analysis framework that identifies relationships important in the system and thus, guide the application of quantitative models or provide sufficient information for management decisions. / Graduation date: 2003