An Empirical Assessment of Alternative Models of Risky Decision Making

In this paper, we assess the degree to which four of the most commonly used models of risky decision making can explain the choices individuals make when faced with risky prospects. To make this assessment, we use experimental evidence for two random samples of young adults. Using a robust, nonlinear least squares procedure, we estimate a model that is general enough to approximate Kahnenman and Tversky's prospect theory and that for certain parametric values will yield the expected utility model, a subjective expected utility model and a probability-transform model. We find that the four models considered explain the decision-making behavior of the majority of our subjects. Surprisingly, we find that the choice behavior of the largest number of subjects is consistent with a probability-transform model. Such models have only been developed recently and have not been used in applied settings. We find least support for the expected utility model -- the most widely used model of risky decision making.

Labor Trafficking Victimization among Farmworkers in North Carolina: Role of Demographic Characteristics and Acculturation

Human trafficking is a hidden domestic and international problem of unknown numbers and unsubstantiated estimates. Most research on labor trafficking has focused on known cases through conducting stakeholder interviews and reviewing police and court case files. This limited prior research suggests that demographic characteristics and level of acculturation may impact one’s risk for labor trafficking victimization. However, these relationships have not been consistently demonstrated. The current research explores two primary research questions: (1) how prevalent is labor trafficking and other labor exploitation among farmworkers in North Carolina; and (2) do individual-level characteristics or circumstances place a person at greater risk of labor trafficking or other labor exploitation. This was accomplished by conducting 380 inperson interviews with migrant farmworkers in North Carolina. We used three strategies to identify migrant farmworkers: (1) attendance at community events; (2) lists of labor camps known to advocacy organizations; and (3) other public venues farmworkers visit. Based on descriptive statistics and a logistic regression analysis, we present results on the extent of farmworker abuse and exploitation, and discuss future research in this area

Experimental Assessment of the Effect of Vocational Training on Youthful Property Offenders

In this paper we report results that suggest that carefully integrated and implemented vocational training and re-entry programs for youthful property offenders can reduce the rate at which such individuals are arrested after release. This result is important since most evaluations of programs for such offenders show no significant effects. The question has been "Why have programs rarely been shown to have significant effects on the behavior of offenders?". Our results suggest that the major reasons may be that programs evaluated to date have been weak and implementation poor. Even with substantial backing from correctional management only 16 percent of the experimental group participated in all aspects of the vocational Delivery System (VDS). Members of the experimental group were most likely to participate in early aspects of the VDS (e.g., a three-week evaluation of vocational interests and aptitudes) than in later elements (e.g., work with the Employment Security Commission to find a job). Even with relatively weak implementation, the experimental group subjects were significantly less likely to be arrested that control group subjects.

The Influence Of Probability on Risky Choice: A parametric Examination

The appeal of expected utility theory as a basis for a descriptive model of risky decision making has diminished is a result of empirical evidence which suggests that individuals do not behave in a manner consistent with the prescriptive tenets of EUT. In this paper, we explore the influence of probability on risky choice. by proposing and estimating a parametric model of risky decision making. Our results suggest that models which provide for probability transformations are most appropriate for the majority of subjects. Further. we find that the transformation differs for most subjects depending upon whether the risky outcomes are gains or losses. Most subjects are considerably less sensitive to changes in mid-range probability than is proposed by the expected utility model and risk-seeking behavior over "long-shot" odds is common

A Consideration of the Factors Contributing to Indigenous Suicide in Guatemala: Qualitative Case Study in Nebaj, Quiché

Antecedentes: El municipio guatemalteco de Nebaj es una comunidad indígena maya con tasas de suicidio percibidas como superiores al promedio nacional. Objetivos: Este artículo evalúa las percepciones de los factores relacionados con el suicidio en Nebaj para informar las estrategias de prevención frente a este. Métodos: Esta investigación utiliza métodos cualitativos y cuantitativos. Los datos provienen de 19 entrevistas semiestructuradas con partes interesadas en Nebaj, junto con revisiones de casos de registros administrativos oficiales de la Policía Nacional Civil (pnc) y estadísticas agregadas de registros oficiales de suicidios recopilados por la pnc y el hospital de Nebaj. Resultados: Las partes interesadas locales vinculan el suicidio con deudas pendientes, la disolución de relaciones románticas, problemas de salud mental, conflictos intrafamiliares y abuso de sustancias. A nivel comunitario, los entrevistados relacionan la disolución de familias a través de la migración y las deudas resultantes. Limitaciones: Las instituciones públicas que abordan el suicidio están aisladas y no trabajan juntas ni recopilan datos con los mismos fines. Los datos disponibles están fragmentados y son difíciles de contrastar entre fuentes. Conclusión: Las entrevistas revelan temas comunes en la percepción de factores contribuyentes al suicidio en Nebaj. Los datos empíricos muestran que es más probable que los jóvenes participen en intentos de suicidio fatales y no fatales. Los análisis también indican que el método de suicidio más común es la ingestión de pesticidas agrícolas.The Guatemalan municipality of Nebaj is an indigenous Mayan community with higher suicide rates than the national average. This article evaluates the perceptions of factors related to suicide in Nebaj in order to suggest prevention strategies against this phenomenon. The research applies qualitative and quantitative methods, collecting data through 19 semi-structured interviews with different stakeholders, along with case reviews of official administrative records of the National Civil Police (pnc) and aggregated statistics of official suicide records collected by this institution and Nebaj’s local hospital. Participant stakeholders link suicide with money debts, the dissolution of romantic relationships, mental health problems, intra-family conflicts, and substance abuse. At the community level, interviewees relate the dissolution of families due to migration reasons and the resulting debts of this process as the main motivations for suicide. Evidence shows that public institutions in charge of addressing this phenomenon work independently and do not collect data cooperatively for the same purposes. Hence, one of the limitations of this study is that the available data is fragmented and difficult to contrast among sources. Despite this, findings reveal common issues in the perception of factors contributing to suicide in Nebaj. Additionally, empirical data shows that young people are more likely to participate in fatal and non-fatal suicide attempts and that the most common method is the intake of agricultural pesticides

The Impact of Traumatic Brain Injury on the Receipt of Services Following Release from Prison

Traumatic brain injury (TBI) is found at substantially higher rates among incarcerated individuals compared to the general adult population. Individuals with TBI report a higher likelihood to experience a range of deleterious outcomes including substance abuse, depression, post-traumatic stress disorder, aggressive behavior, and violence. Thus, a history of TBI is likely to lead to the types of behaviors that will significantly increase the odds of an individual returning to incarceration post-release, as supported by recent research with a cohort of state prisoners. TBI has largely gone unaddressed by prison reentry programs that are integral to rehabilitating individuals returning to the community. Relatively little is known, however, about the effects of TBI on the receipt of services post-release. Additionally, few studies have examined sex differences in the prevalence of TBI in reentry populations. This chapter uses data from a multi-state prisoner reentry program randomized control trial to examine whether individuals with TBI are significantly different than their peers without TBI with respect to a variety of demographic and psychological metrics and in expressions of needs for and participation in services and programming during the transition from incarceration to the community

TranscriptomeBrowser: A Powerful and Flexible Toolbox to Explore Productively the Transcriptional Landscape of the Gene Expression Omnibus Database

International audienceAs public microarray repositories are constantly growing, we are facing the challenge of designing strategies to provide productive access to the available data.\ We used a modified version of the Markov clustering algorithm to systematically extract clusters of co-regulated genes from hundreds of microarray datasets stored in the Gene Expression Omnibus database (n = 1,484). This approach led to the definition of 18,250 transcriptional signatures (TS) that were tested for functional enrichment using the DAVID knowledgebase. Over-representation of functional terms was found in a large proportion of these TS (84%). We developed a JAVA application, TBrowser that comes with an open plug-in architecture and whose interface implements a highly sophisticated search engine supporting several Boolean operators (http://tagc.univ-mrs.fr/tbrowser/). User can search and analyze TS containing a list of identifiers (gene symbols or AffyIDs) or associated with a set of functional terms.\ As proof of principle, TBrowser was used to define breast cancer cell specific genes and to detect chromosomal abnormalities in tumors. Finally, taking advantage of our large collection of transcriptional signatures, we constructed a comprehensive map that summarizes gene-gene co-regulations observed through all the experiments performed on HGU133A Affymetrix platform. We provide evidences that this map can extend our knowledge of cellular signaling pathways

Forecasting Demand Using Survival Modeling: an application to US prisons

A systems approach to modeling demand which incorporates survival modeling is applied to the problem of prison population projection. The approach models the flow of inmates through the prison system and differs from earlier approaches by exploiting the differences in the incarceration hazard rates of individuals in the general population and those who have previously been incarcerated and explicitly considering the impact of constrained prison capacity on release policy and future admissions. The methodology capitalizes on the impact of recursion in the prison population and reduces the amount and complexity of data required for long-term forecasts.. First-time arrivals to prison are modeled as a Poisson process arising from the general population; recidivist arrivals are modeled using a failure model, where the reincarceration hazard rate is a function of age and race. The model is demonstrated for the state of North Carolina located in the Southeastern region of the United States. The effect of limited prison capacity on the mean of the time-served distribution is shown. The results demonstrate that an early release policy will generate an increase in prison admissions through the return to prison of former inmates. Further, the results show that a systems approach to modeling of prison demand which includes the non-linear effect of recidivism, i.e., survival modeling, has a significant impact on the accuracy of forecasts

Forecasting Demand Using Survival Modeling: an application to US prisons

A systems approach to modeling demand which incorporates survival modeling is applied to the problem of prison population projection. The approach models the flow of inmates through the prison system and differs from earlier approaches by exploiting the differences in the incarceration hazard rates of individuals in the general population and those who have previously been incarcerated and explicitly considering the impact of constrained prison capacity on release policy and future admissions. The methodology capitalizes on the impact of recursion in the prison population and reduces the amount and complexity of data required for long-term forecasts.. First-time arrivals to prison are modeled as a Poisson process arising from the general population; recidivist arrivals are modeled using a failure model, where the reincarceration hazard rate is a function of age and race. The model is demonstrated for the state of North Carolina located in the Southeastern region of the United States. The effect of limited prison capacity on the mean of the time-served distribution is shown. The results demonstrate that an early release policy will generate an increase in prison admissions through the return to prison of former inmates. Further, the results show that a systems approach to modeling of prison demand which includes the non-linear effect of recidivism, i.e., survival modeling, has a significant impact on the accuracy of forecasts