Substance use and sexual risk behaviors among adolescent detainees

There is a commonly presumed link among sexual risk behavior, substance use, and other psychosocial factors among adolescents. However, these relationships have been relatively understudied in detained, low-income, minority, substance abusing adolescents. This study addresses this gap in the literature with a secondary data analysis based on a sample of adolescent offenders in two detention and treatment centers in Miami-Dade County. Univariate, bivariate statistical analysis and multivariate logistic regressions were conducted on baseline data from structured interviews with 455 adolescents participating in an NIH funded prevention intervention. Data were analyzed to assess relationships among self-reported substance use, STD history, HIV/AIDS knowledge, condom use, condom use attitudes, and skills, peer and parental approval to use condoms, and race/ethnicity. The adolescent sample was 74.1% male, and 25.9% female and 35.4% African American, 25.1% non-African American Latino, 11.2% White, and 28.4% of other race/ethnicity categories. The mean age was 15.6 years. Results suggested that alcohol use (p < 0.001) and use of marijuana, cocaine and other drugs (p < 0.001) are significant variables when explaining the variability in sexual risk behaviors. Results also suggested that unprotected vaginal, anal, and oral sex increased with higher alcohol and drug use (p < 0.001) and that positive attitudes about personally using condoms (p < 0.001) were also significantly related to condom use. Logistic regressions showed that race/ethnicity was a significant control variable when explaining the variability of condom use. Being White and Latino were significantly associated with less condom use during oral and anal sex when compared to other racial/ethnic groups. These results indicated that risky sexual behavior and HIV infection risk are significantly associated with substance use, particularly alcohol use. Therefore, proper screening and identification of alcohol use, and condom use attitudes could maximize the efficacy of referrals to programs targeting both issues and increase the potential for appropriate primary and secondary prevention and treatment among adolescent detainees.

Assessing administrative and political factors in implementing a living wage ordinance

Since 2000, the number of living wage ordinances has steadily increased throughout the country. While most of the current research has focused on the beneficial outcomes of living wages, little has been published on their administrative practices. To address this shortcoming, this study focused on the identification of key administrative and political factors involved impacting the implementation of living wage ordinances in Miami-Dade and Broward Counties. The study utilized a triangulation of interviews, surveys, and direct observation. The author conducted interviews of administrators and members of the living wage oversight boards in both counties and observed the monthly meetings held by each county's oversight board from January 2006 to June 2007. These findings were buttressed with a national survey of senior staff in other living wage communities. The study utilized descriptive statistics, Chi Square, Cronbach's Alpha, and Spearman's Rank Correlation Coefficient (Spearman's rho). Interviews indicated that administrators in Dade and Broward are seriously under-staffed and budgeted. Ambiguities in the enabling ordinances have lead to loopholes that undermine implementation and accountability for participating contractors. Survey results showed that policy ambiguity, organizational politics, and a lack of organizational capacity were significant negative factors in the implementation process while an organizational culture emphasizing consistent enforcement was a positive factor. Without the proper inputs, an organization hinders itself from meeting its outputs and outcomes. This study finds that Broward and Miami-Dade Counties do not provide the necessary administrative support to implement a living wage effectively – in stark contrast to the high hopes and strong political support behind their passage. For a living wage to succeed, it first needs an organizational culture committed to providing the necessary resources for implementation as well as transparent, consistent accountability mechanisms.

Design strategies for an artificial neural network based algorithm for automatic incident detection on major arterial streets

Traffic incidents are non-recurring events that can cause a temporary reduction in roadway capacity. They have been recognized as a major contributor to traffic congestion on our nation’s highway systems. To alleviate their impacts on capacity, automatic incident detection (AID) has been applied as an incident management strategy to reduce the total incident duration. AID relies on an algorithm to identify the occurrence of incidents by analyzing real-time traffic data collected from surveillance detectors. Significant research has been performed to develop AID algorithms for incident detection on freeways; however, similar research on major arterial streets remains largely at the initial stage of development and testing. This dissertation research aims to identify design strategies for the deployment of an Artificial Neural Network (ANN) based AID algorithm for major arterial streets. A section of the US-1 corridor in Miami-Dade County, Florida was coded in the CORSIM microscopic simulation model to generate data for both model calibration and validation. To better capture the relationship between the traffic data and the corresponding incident status, Discrete Wavelet Transform (DWT) and data normalization were applied to the simulated data. Multiple ANN models were then developed for different detector configurations, historical data usage, and the selection of traffic flow parameters. To assess the performance of different design alternatives, the model outputs were compared based on both detection rate (DR) and false alarm rate (FAR). The results show that the best models were able to achieve a high DR of between 90% and 95%, a mean time to detect (MTTD) of 55-85 seconds, and a FAR below 4%. The results also show that a detector configuration including only the mid-block and upstream detectors performs almost as well as one that also includes a downstream detector. In addition, DWT was found to be able to improve model performance, and the use of historical data from previous time cycles improved the detection rate. Speed was found to have the most significant impact on the detection rate, while volume was found to contribute the least. The results from this research provide useful insights on the design of AID for arterial street applications.

An automatic tuning strategy for local fuzzy logic ramp metering algorithm using Particle Swarm Optimization (PSO)

Freeway systems are becoming more congested each day. One contribution to freeway traffic congestion comprises platoons of on-ramp traffic merging into freeway mainlines. As a relatively low-cost countermeasure to the problem, ramp meters are being deployed in both directions of an 11-mile section of I-95 in Miami-Dade County, Florida. The local Fuzzy Logic (FL) ramp metering algorithm implemented in Seattle, Washington, has been selected for deployment. The FL ramp metering algorithm is powered by the Fuzzy Logic Controller (FLC). The FLC depends on a series of parameters that can significantly alter the behavior of the controller, thus affecting the performance of ramp meters. However, the most suitable values for these parameters are often difficult to determine, as they vary with current traffic conditions. Thus, for optimum performance, the parameter values must be fine-tuned. This research presents a new method of fine tuning the FLC parameters using Particle Swarm Optimization (PSO). PSO attempts to optimize several important parameters of the FLC. The objective function of the optimization model incorporates the METANET macroscopic traffic flow model to minimize delay time, subject to the constraints of reasonable ranges of ramp metering rates and FLC parameters. To further improve the performance, a short-term traffic forecasting module using a discrete Kalman filter was incorporated to predict the downstream freeway mainline occupancy. This helps to detect the presence of downstream bottlenecks. The CORSIM microscopic simulation model was selected as the platform to evaluate the performance of the proposed PSO tuning strategy. The ramp-metering algorithm incorporating the tuning strategy was implemented using CORSIM's run-time extension (RTE) and was tested on the aforementioned I-95 corridor. The performance of the FLC with PSO tuning was compared with the performance of the existing FLC without PSO tuning. The results show that the FLC with PSO tuning outperforms the existing FL metering, fixed-time metering, and existing conditions without metering in terms of total travel time savings, average speed, and system-wide throughput.

Development of risk based treatability and engineering measures for reducing exposure to lead contaminated media in the Miami inner city, Florida

A major consequence of contamination at the local level’s population as it relates to environmental health and environmental engineering is childhood lead poisoning. Environmental contamination is one of the pressing environmental concerns facing the world today. Current approaches often focus on large contaminated industrial size sites that are designated by regulatory agencies for site remediation. Prior to this study, there were no known published studies conducted at the local and smaller scale, such as neighborhoods, where often much of the contamination is present to remediate. An environmental health study of local lead-poisoning data in Liberty City, Little Haiti and eastern Little Havana in Miami-Dade County, Florida accounted for a disproportionately high number of the county’s reported childhood lead poisoning cases. An engineering system was developed and designed for a comprehensive risk management methodology that is distinctively applicable to the geographical and environmental conditions of Miami-Dade County, Florida. Furthermore, a scientific approach for interpreting environmental health concerns, while involving detailed environmental engineering control measures and methods for site remediation in contained media was developed for implementation. Test samples were obtained from residents and sites in those specific communities in Miami-Dade County, Florida (Gasana and Chamorro 2002). Currently lead does not have an Oral Assessment, Inhalation Assessment, and Oral Slope Factor; variables that are required to run a quantitative risk assessment. However, various institutional controls from federal agencies’ standards and regulation for contaminated lead in media yield adequate maximum concentration limits (MCLs). For this study an MCL of .0015 (mg/L) was used. A risk management approach concerning contaminated media involving lead demonstrates that the linkage of environmental health and environmental engineering can yield a feasible solution.

Effective knowledge integration in emergency response organizations

Natural and man-made disasters have gained attention at all levels of policy-making in recent years. Emergency management tasks are inherently complex and unpredictable, and often require coordination among multiple organizations across different levels and locations. Effectively managing various knowledge areas and the organizations involved has become a critical emergency management success factor. However, there is a general lack of understanding about how to describe and assess the complex nature of emergency management tasks and how knowledge integration can help managers improve emergency management task performance. ^ The purpose of this exploratory research was first, to understand how emergency management operations are impacted by tasks that are complex and inter-organizational and second, to investigate how knowledge integration as a particular knowledge management strategy can improve the efficiency and effectiveness of the emergency tasks. Three types of specific knowledge were considered: context-specific, technology-specific, and context-and-technology-specific. ^ The research setting was the Miami-Dade Emergency Operations Center (EOC) and the study was based on the survey responses from the participants in past EOC activations related to their emergency tasks and knowledge areas. The data included task attributes related to complexity, knowledge area, knowledge integration, specificity of knowledge, and task performance. The data was analyzed using multiple linear regressions and path analyses, to (1) examine the relationships between task complexity, knowledge integration, and performance, (2) the moderating effects of each type of specific knowledge on the relationship between task complexity and performance, and (3) the mediating role of knowledge integration. ^ As per theory-based propositions, the results indicated that overall component complexity and interactive complexity tend to have a negative effect on task performance. But surprisingly, procedural rigidity tended to have a positive effect on performance in emergency management tasks. Also as per our expectation, knowledge integration had a positive relationship with task performance. Interestingly, the moderating effects of each type of specific knowledge on the relationship between task complexity and performance were varied and the extent of mediation of knowledge integration depended on the dimension of task complexity. ^

Against all odds: Success stories of Latino students who survived the educational pipeline

The purpose of this interview study was to explore the experiences of Latino students, from their perspectives, as they journeyed through the educational pipeline, particularly the part focusing on the transfer experience from a 2-year college to a 4-year institution. This was accomplished by conducting in-depth interviews with 17 self-identified Latino men and women. All of the participants had attended Florida International University for at least 1 semester and had transferred from Miami Dade College. The participants varied in age, generational status, and cultural identity.^ The participants were asked to reflect on the external and internal influences that lead them to the 4-year institution. Tinto's (1993) model of student departure theory provided the theoretical framework for data collection and analysis. Based on the coding of the interviews, numerous themes emerged, including the role of the family, the impact of early education, the experiences of being Latino in Miami, the decisions to choose a college, the experience at the 2-year institution, the experience with the transfer process, and the obstacles and strategies the participants used for overcoming obstacles. These themes were furthered developed to determine which influences were most important for a successful journey through the educational pipeline. ^ The study found that viewing the pipeline via the students' perspectives juxtaposed with Tinto's (1993) model of student departure gave greater insight into the experiences of a population of students who have been underrepresented in higher education. The findings of this case study indicate that the transfer process for Latinos attending a Hispanic Serving Institution such as Florida International University, situated in a majority-minority city, is complex, with participants having to rely on peers and significant others for pertinent information and support. Several factors, including the importance of positive support networks and increased confidence nurtured by the 2-year institution, influenced the students' transfer to a 4-year institution. For professionals in the field, the findings of this study may lead to a broader understanding of the experiences of Latino students in the pipeline and, more importantly, assist college administrators and faculty in successfully guiding a population through a 4-year institution who first came via a 2-year institution. ^

A methodological framework for modeling pavement maintenance costs for projects with performance-based contracts

Performance-based maintenance contracts differ significantly from material and method-based contracts that have been traditionally used to maintain roads. Road agencies around the world have moved towards a performance-based contract approach because it offers several advantages like cost saving, better budgeting certainty, better customer satisfaction with better road services and conditions. Payments for the maintenance of road are explicitly linked to the contractor successfully meeting certain clearly defined minimum performance indicators in these contracts. Quantitative evaluation of the cost of performance-based contracts has several difficulties due to the complexity of the pavement deterioration process. Based on a probabilistic analysis of failures of achieving multiple performance criteria over the length of the contract period, an effort has been made to develop a model that is capable of estimating the cost of these performance-based contracts. One of the essential functions of such model is to predict performance of the pavement as accurately as possible. Prediction of future degradation of pavement is done using Markov Chain Process, which requires estimating transition probabilities from previous deterioration rate for similar pavements. Transition probabilities were derived using historical pavement condition rating data, both for predicting pavement deterioration when there is no maintenance, and for predicting pavement improvement when maintenance activities are performed. A methodological framework has been developed to estimate the cost of maintaining road based on multiple performance criteria such as crack, rut and, roughness. The application of the developed model has been demonstrated via a real case study of Miami Dade Expressways (MDX) using pavement condition rating data from Florida Department of Transportation (FDOT) for a typical performance-based asphalt pavement maintenance contract. Results indicated that the pavement performance model developed could predict the pavement deterioration quite accurately. Sensitivity analysis performed shows that the model is very responsive to even slight changes in pavement deterioration rate and performance constraints. It is expected that the use of this model will assist the highway agencies and contractors in arriving at a fair contract value for executing long term performance-based pavement maintenance works.

The effects of the use of technology in mathematics instruction on student achievement

The purpose of this study was to examine the effects of the use of technology on students’ mathematics achievement, particularly the Florida Comprehensive Assessment Test (FCAT) mathematics results. Eleven schools within the Miami-Dade County Public School System participated in a pilot program on the use of Geometers Sketchpad (GSP). Three of these schools were randomly selected for this study. Each school sent a teacher to a summer in-service training program on how to use GSP to teach geometry. In each school, the GSP class and a traditional geometry class taught by the same teacher were the study participants. Students’ mathematics FCAT results were examined to determine if the GSP produced any effects. Students’ scores were compared based on assignment to the control or experimental group as well as gender and SES. SES measurements were based on whether students qualified for free lunch. The findings of the study revealed a significant difference in the FCAT mathematics scores of students who were taught geometry using GSP compared to those who used the traditional method. No significant differences existed between the FCAT mathematics scores of the students based on SES. Similarly, no significant differences existed between the FCAT scores based on gender. In conclusion, the use of technology (particularly GSP) is likely to boost students’ FCAT mathematics test scores. The findings also show that the use of GSP may be able to close known gender and SES related achievement gaps. The results of this study promote policy changes in the way geometry is taught to 10th grade students in Florida’s public schools.

Relationships among dietary intake, dietary patterns, dietary quality and nutrient adequacy and substance use in Latina mother/daughter dyads

This study examined the relationships among dietary intake, substance use, socioeconomic and acculturation-related factors among Latinas in Miami-Dade County. Substance abuse is rising among Latinas. A fuller understanding of this problem is needed given the rise of the Hispanic population and the role of women in Latin society. A better understanding between substance use and dietary intake can guide nutrition interventions to reduce negative substance-related health consequences. A purposeful sample of 320 Latina mother/daughter dyads were recruited and interviewed face-to-face as part of the Latino Women's Study. Dietary intake was collected via a 24-hour recall and examined by (1) nutrient intake, (2) dietary patterns using cluster analysis, (3) quality of diet using the Healthy Eating Index (HEI) and (4) the Dietary Reference Intakes to determine nutrient adequacy. Substance use was measured with the Drug Use Frequency and the Healthy and Daily Living Form. Acculturation was measured with the Cultural Identity Scale. Three dietary patterns emerged based on the number of servings from the food groups established in MyPyramid. None were associated with substance use. Latinas who reported using cannabis, cocaine, sedatives without prescription and/or more than five alcoholic drinks on an occasion at least once a month during the previous twelve months had significantly lower HEI scores (64 vs. 60; F = 7.8, p = .005) and consumed fewer fruits (F = 16, p < .001) than non-users. Latinas classified as mothers whom reported consuming cannabis at least 1-7 times a week had significantly lower HEI scores (F = 4.23, p = .015, η2 = .027) than daughters with the same frequency of substance use. One dimension of acculturation, greater familiarity with Latin culture, was associated with good dietary quality (β = .142, p = .012) regardless of any type of substance used or income level. There was a high prevalence of inadequacy of folic acid intake (50-75%) regardless of substance use. Substance users consumed significantly more energy (1,798 vs. 1,615; p = .027) than non-users. Although effect sizes were small, associations between dietary intake and substance use among Latinas deserve further exploration while acknowledging the combined association with acculturation. ^

Improving Analytical Travel Time Estimation for Transportation Planning Models

This dissertation aimed to improve travel time estimation for the purpose of transportation planning by developing a travel time estimation method that incorporates the effects of signal timing plans, which were difficult to consider in planning models. For this purpose, an analytical model has been developed. The model parameters were calibrated based on data from CORSIM microscopic simulation, with signal timing plans optimized using the TRANSYT-7F software. Independent variables in the model are link length, free-flow speed, and traffic volumes from the competing turning movements. The developed model has three advantages compared to traditional link-based or node-based models. First, the model considers the influence of signal timing plans for a variety of traffic volume combinations without requiring signal timing information as input. Second, the model describes the non-uniform spatial distribution of delay along a link, this being able to estimate the impacts of queues at different upstream locations of an intersection and attribute delays to a subject link and upstream link. Third, the model shows promise of improving the accuracy of travel time prediction. The mean absolute percentage error (MAPE) of the model is 13% for a set of field data from Minnesota Department of Transportation (MDOT); this is close to the MAPE of uniform delay in the HCM 2000 method (11%). The HCM is the industrial accepted analytical model in the existing literature, but it requires signal timing information as input for calculating delays. The developed model also outperforms the HCM 2000 method for a set of Miami-Dade County data that represent congested traffic conditions, with a MAPE of 29%, compared to 31% of the HCM 2000 method. The advantages of the proposed model make it feasible for application to a large network without the burden of signal timing input, while improving the accuracy of travel time estimation. An assignment model with the developed travel time estimation method has been implemented in a South Florida planning model, which improved assignment results.

The role of community college faculty in teaching and learning for sustainable development

The purpose of this study was to explore the attitudes, beliefs, and practices of community college professors regarding education for sustainable development (ESD). In-depth interviews with 14 professors from different disciplines were conducted. The participants taught at Miami Dade College, Florida, a Talloires Declaration signatory since 2006, and all had attended Green Studies professional development workshops. Written documents such as assignments and samples of student work were used for triangulation. The annual report of the college’s Earth Ethics Institute and its Web site served as additional sources. The interviews were recorded, transcribed, and analyzed for common themes. The Talloires Declaration’s 10-point action plan and the key characteristics of ESD (UN DESD, 2006) served as the conceptual framework. The study found that the professors considered ESD an essential issue. The majority discussed the economic and social aspects of ESD; however, the environmental aspect was mentioned most frequently. The professors’ conceptualizations of ESD were influenced by their experiences and evidenced by the metaphors they used. Although their engagement with ESD differed, the professors expressed optimism toward ESD related teaching and learning. They regarded ESD as compatible with their subjects, and most had already been infusing sustainability into their courses or planned to do so. Additionally, the participants’ teaching practices reflected many of the characteristics of ESD. Even though the professors considered ESD challenging, they believed that they could make contributions to the college’s effort. The metaphor of “Planting a Seed” was frequently used to describe this holistic approach. The study also found that many professors regarded interpersonal relationships and communication significant factors for the advancement of ESD. The participants described several challenges to integrating ESD at their college. These related to time constraints, density of curriculum, institutional size and fragmentation, dearth of administrative support and incentives, students’ lack of academic preparation and sustainability awareness, students’ inability to focus on ESD because of personal, social, or economic circumstances, and professors’ frustration about a divisive atmosphere as a result of their engagement with sustainability. Despite these obstacles, the professors believed that ESD could be successfully woven into the community college experience.

An improved framework for dynamic origin-destination (O-D) matrix estimation

This dissertation aims to improve the performance of existing assignment-based dynamic origin-destination (O-D) matrix estimation models to successfully apply Intelligent Transportation Systems (ITS) strategies for the purposes of traffic congestion relief and dynamic traffic assignment (DTA) in transportation network modeling. The methodology framework has two advantages over the existing assignment-based dynamic O-D matrix estimation models. First, it combines an initial O-D estimation model into the estimation process to provide a high confidence level of initial input for the dynamic O-D estimation model, which has the potential to improve the final estimation results and reduce the associated computation time. Second, the proposed methodology framework can automatically convert traffic volume deviation to traffic density deviation in the objective function under congested traffic conditions. Traffic density is a better indicator for traffic demand than traffic volume under congested traffic condition, thus the conversion can contribute to improving the estimation performance. The proposed method indicates a better performance than a typical assignment-based estimation model (Zhou et al., 2003) in several case studies. In the case study for I-95 in Miami-Dade County, Florida, the proposed method produces a good result in seven iterations, with a root mean square percentage error (RMSPE) of 0.010 for traffic volume and a RMSPE of 0.283 for speed. In contrast, Zhou's model requires 50 iterations to obtain a RMSPE of 0.023 for volume and a RMSPE of 0.285 for speed. In the case study for Jacksonville, Florida, the proposed method reaches a convergent solution in 16 iterations with a RMSPE of 0.045 for volume and a RMSPE of 0.110 for speed, while Zhou's model needs 10 iterations to obtain the best solution, with a RMSPE of 0.168 for volume and a RMSPE of 0.179 for speed. The successful application of the proposed methodology framework to real road networks demonstrates its ability to provide results both with satisfactory accuracy and within a reasonable time, thus establishing its potential usefulness to support dynamic traffic assignment modeling, ITS systems, and other strategies.

Understanding the relationship between the Talented Twenty program and college aspirations for high ranking students at a high priority school

Percentage plans such as the Talented Twenty program purport to assist and motivate high ranking students to attend college and grant access to higher education. This type of plan is particularly important to students enrolled in high priority schools who might not view themselves as potential college students. This study examined the relationship between Florida’s Talented Twenty program that begins intervention with juniors and the college aspirations for high ranking students at a high priority school. Numerous studies have established that increased levels of education lead to higher salaries, career mobility, and an increased quality of life (e.g., Bowen, 1997; Leslie & Brinkman 1988; Pascarella & Terenzini, 1991, Swail, 2000). Given the importance of students’ decisions regarding whether or not they will attend college, understanding how and when they make decisions about attending college is important for them, their parents, advisors, and educational administrators. This research examined students’ perceptions and insights via interviews. The overarching research question was: How do high ranking high school students attending a high priority school in a south Florida district perceive their college opportunities? Sixteen high ranking students, grades nine – 12 from a high priority school in Miami-Dade County participated in the study. Participants were identified by a school counselor and individual semi structured interviews were conducted at the school. Utilizing a student development theoretical framework developed by Hossler and Gallagher (1987) that centered on students’ predisposition, search strategies and choices, data were organized and emergent themes analyzed. The analysis of the data revealed that in alignment with the framework (a) parents were the strongest influence in the development of these students’ college aspirations, (b) these students formalized their higher education plans between eighth and 10th grade, (c) these students actively engaged in academic searches and learning opportunities that increased their chances to be admitted into college, and (d) there was no relationship between knowledge regarding the Talented Twenty program and their educational decisions. This study’s findings suggest that interventions and programs intended to influence the educational aspirations of students are more likely to succeed if they take place by the eighth or ninth grade.

Development of an instrument to measure high school students' global awareness and attitudes: Looking through the lens of social sciences

The purpose of this study was to develop an instrument to measure high school students’ perspectives on global awareness and attitudes toward social issues. The research questions that guided this study were: (a) Can acceptable validity and reliability estimates be established for an instrument developed to measure high schools students' global awareness? (b) Can acceptable validity and reliability estimates be established for an instrument developed to measure high schools students' attitudes towards global social issues? (c) What is the relationship between high school students’ GPA, race/ethnicity, gender, socio-economic status, parents’ education, getting the news, reading and listening habits, the number of classes taken in the social sciences, whether they speak a second language, and have experienced living in or visiting other countries, and their perception of global awareness and attitudes toward global social issues. ^ An ex post facto research design was used and the data were collected using a 4-part Likert-type survey. It was administered to 14 schools in the Miami-Dade County, Florida area to 704 students. A factor analysis with an orthogonal varimax rotation was vii used to select the factors that best represented the three constructs – global education, global citizenship, and global workforce. This was done to establish construct validity. Cronbach’s alpha was used to determine the reliability of the instrument. Descriptive statistics and a hierarchical multiple regression were used for the demographics to establish their relationship, if any, to the findings. ^ Key findings of the study were that reliable and valid estimates can be developed for the instrument. The multiple regression analysis for model 1 and 2 accounted for a variance of 3% and 5% for self-perceptions of global awareness (factor 1). The regression model also accounted for a 5% and 13% variance in the two models for attitudes toward global social issues (factor 2). The demographics that were statistically significant were: ethnicity, gender, SES, parents’ education, listening to music, getting the news, speaking a second language, GPA, classes taken in the social sciences, and visiting other countries. An important finding for the study was those attending public schools (as opposed to private schools) had more positive attitudes towards global social issues (factor 2) The statistics indicated that these students had taken history, economics, and social studies – a curriculum infused with global perspectives.^