Factors predicting recommendations for civil commitment of sexually violent predators under Florida's Jimmy Ryce Act

This study investigated the factors considered by forensic examiners when evaluating sexually violent predators (SVP) for civil commitment under Florida's “Jimmy Ryce Act.” The project was funded by a pre-doctoral research grant awarded by the Association for the Treatment of Sexual Abusers (ATSA). ^ This study proposed two specific research questions. First, what is the direct relationship between actuarial risk assessment scores and recommendations for sex offender civil commitment? Second, which other variables are likely to influence SVP commitment decisions, and to what degree? The purpose of the study was to determine if risk assessment practices are evidence-based, and whether offenders selected for commitment meet statutory criteria. ^ The purposive sample of 450 SVPs was drawn from the population of sex offenders evaluated for civil commitment in Florida between July 1, 2000 and June 30, 2001. Data were extracted from SVP evaluations provided by the Florida Department of Children and Families. Using multivariate logistic regression, this correlational research design examined the relationship between the dependent variable, commitment decision, and several sets of independent variables. The independent variables were derived from a review of the literature, and were grouped conceptually according to their degree of correlation with sex offense recidivism. Independent variables included diagnoses, actuarial risk assessment scores, empirically validated static and dynamic risk factors, consensus based risk factors, evaluator characteristics, and demographics. This study investigated the degree to which the identified variables predicted civil commitment decisions. ^ Logistic regression results revealed that the statistically significant predictors of recommendations for sex offender civil commitment were actuarial risk assessment scores, diagnoses of Pedophilia and Paraphilia NOS, psychopathy, younger age of victim, and non-minority race. Discriminant function analysis confirmed that these variables correctly predicted commitment decisions in 90% of cases. ^ It appears that civil commitment evaluators in Florida used empirically-based assessment procedures, and did not make decisions that were heavily influenced by extraneous factors. SVPs recommended for commitment consistently met the criteria set forth by the U.S. Supreme Court in Hendricks v. Kansas (1997): they suffered from a mental abnormality predisposing them to sexual violence, and risk assessment determined that they were likely to reoffend. ^

Forecasting enrollment in differential assessment programs using cellular automata

Urban growth models have been used for decades to forecast urban development in metropolitan areas. Since the 1990s cellular automata, with simple computational rules and an explicitly spatial architecture, have been heavily utilized in this endeavor. One such cellular-automata-based model, SLEUTH, has been successfully applied around the world to better understand and forecast not only urban growth but also other forms of land-use and land-cover change, but like other models must be fed important information about which particular lands in the modeled area are available for development. Some of these lands are in categories for the purpose of excluding urban growth that are difficult to quantify since their function is dictated by policy. One such category includes voluntary differential assessment programs, whereby farmers agree not to develop their lands in exchange for significant tax breaks. Since they are voluntary, today’s excluded lands may be available for development at some point in the future. Mapping the shifting mosaic of parcels that are enrolled in such programs allows this information to be used in modeling and forecasting. In this study, we added information about California’s Williamson Act into SLEUTH’s excluded layer for Tulare County. Assumptions about the voluntary differential assessments were used to create a sophisticated excluded layer that was fed into SLEUTH’s urban growth forecasting routine. The results demonstrate not only a successful execution of this method but also yielded high goodness-of-fit metrics for both the calibration of enrollment termination as well as the urban growth modeling itself.

A relationship between the Florida Comprehensive Assessment Test 2.0 mathematics scores and racial and ethnic concentration when considering socio-economic status, ESOL student population, and school climate

From the moment children are born, they begin a lifetime journey of learning about themselves and their surroundings. With the establishment of the No Child Left Behind Act of 2001, it mandates that all children receive a high-quality education in a positive school climate. Regardless of the school the child attends or the neighborhood in which the child lives, proper and quality education and resources must be provided and made available in order for the child to be academically successful. The purpose of this ex post facto study was to investigate the relationship between the FCAT 2.0 mathematics scores of public middle school students in Miami-Dade County, Florida and the concentrations of a school's racial and ethnic make-up (Whites, Blacks, and Hispanics), English for Speakers of other Languages (ESOL) population, socio-economic status (SES), and school climate. The research question of this study was: Is there a significant relationship between the FCAT 2.0 Mathematics scores and racial and ethnic concentration of public middle school students in Miami-Dade County when controlling SES, ESOL student population, and school climate for the 2010-2011 school year? The instruments used to collect the data were the FCAT 2.0 and Miami-Dade County Public Schools (M-DCPS) School Climate Survey. The study found that Economically Disadvantaged (SES) students socio-economic status had the strongest correlation with the FCAT 2.0 mathematics scores (r = -.830). The next strongest correlation was with the number of students who agreed that their school climate was positive and helped them learn (r = .741) and the third strongest correlation was a school percentage of White students (r = .668). The study concluded that the FCAT 2.0 mathematics scores of M-DCPS middle school students have a significant relationship with socio-economic status, school climate, and racial concentration.

Understanding the Impact of the Property Tax Appeal Process on Assessment Uniformity: Procedures, Structures, and Outcomes

Property taxes serve as a vital revenue source for local governments. The revenues derived from the property tax function as the primary funding source for a variety of critical local public service systems. Property tax appeal systems serve as quasi-administrative-judicial mechanisms intended to assure the public that property tax assessments are correct, fair, and equitable. Despite these important functions, there is a paucity of empirical research related to property tax appeal systems. This study contributes to property tax literature by identifying who participates in the property tax appeal process and examining their motivations for participation. In addition, the study sought to determine whether patterns of use and success in appeal systems affected the distribution of the tax burden. Data were collected by means of a survey distributed to single-family property owners from two Florida counties. In addition, state and county documents were analyzed to determine appeal patterns and examine the impact on assessment uniformity, over a three-year period. The survey data provided contextual evidence that single-family property owners are not as troubled by property taxes as they are by the conduct of local government officials. The analyses of the decision to appeal indicated that more expensive properties and properties excluded from initial uniformity analyses were more likely to be appealed, while properties with homestead exemptions were less likely to be appealed. The value change analyses indicated that appeals are clustered in certain geographical areas; however, these areas do not always experience a greater percentage of the value changes. Interestingly, professional representation did not increase the probability of obtaining a reduction in value. Other relationships between the variables were discovered, but often with weak predictive ability. Findings from the assessment uniformity analyses were also interesting. The results indicated that the appeals mechanisms in both counties improved assessment uniformity. On average, appealed properties exhibited greater horizontal and vertical inequities, as compared to non-appealed properties, prior to the appeals process. After, the appeal process was completed; the indicators of horizontal and vertical equity were largely improved. However, there were some indications of regressivity in the final year of the study.