The unintended [or intended?] political consequences of electoral systems: The case of Bolivia

The present study was concerned with evaluating one basic institution in Bolivian democracy: its electoral system. The study evaluates the impact of electoral systems on the interaction between presidents and assemblies. It sought to determine whether it is possible to have electoral systems that favor multipartism but can also moderate the likelihood of executive-legislative confrontation by producing the necessary conditions for coalition building. ^ This dissertation utilized the case study method as a methodology. Using the case of Bolivia, the research project studied the variations in executive-legislative relations and political outcomes from 1985 to the present through a model of executive-legislative relations that provided a typology of presidents and assemblies based on the strategies available to them to bargain with each other for support. A complementary model that evaluated the state of their inter-institutional interaction was also employed. ^ Results indicated that executive-legislative relations are profoundly influenced by the choice of the electoral system. Similarly, the project showed that although the Bolivian mixed system for legislative elections, and executive formula favor multipartism, these electoral systems do not necessarily engender executive-legislative confrontation in Bolivia. This was mainly due to the congressional election of the president, and the formulas utilized to translate the popular vote into legislative seats. However, the study found that the electoral system has also allowed for anti-systemic forces to emerge and gain political space both within and outside of political institutions. ^ The study found that government coalitions in Bolivia that are promoted by the system of congressional election of the president and the D'Hondt system to allocate legislative seats have helped ameliorate one of the typical problems of presidential systems in Latin America: the presence of a minority government that is blocked in its capacity to govern. This study was limited to evaluating the impact of the electoral system, as the independent variable, on executive-legislative interaction. However, the project revealed a need for more theoretical and empirical work on executive-legislative bargaining models in order to understand how institutional reforms can have an impact on the incentives of presidents and legislators to form coherent coalitions. ^

Responses of neotropical mangrove seedlings grown in monoculture and mixed culture under treatments of hydroperiod and salinity

We investigated the combined effects of salinity and hydroperiod on seedlings of Rhizophora mangle and Laguncularia racemosa grown under experimental conditions of monoculture and mixed culture by using a simulated tidal system. The objective was to test hypotheses relative to species interactions to either tidal or permanent flooding at salinities of 10 or 40 g/l. Four-month-old seedlings were experimentally manipulated under these environmental conditions in two types of species interactions: (1) seedlings of the same species were grown separately in containers from September 2000 to August 2001 to evaluate intraspecific response and (2) seedlings of each species were mixed in containers to evaluate interspecific, competitive responses from August 2002 to April 2003. Overall, L. racemosa was strongly sensitive to treatment combinations while R. mangle showed little effect. Most plant responses of L. racemosa were affected by both salinity and hydroperiod, with hydroperiod inducing more effects than salinity. Compared to R. mangle, L. racemosa in all treatment combinations had higher relative growth rate, leaf area ratio, specific leaf area, stem elongation, total length of branches, net primary production, and stem height. Rhizophora mangle had higher biomass allocation to roots. Species growth differentiation was more pronounced at low salinity, with few species differences at high salinity under permanent flooding. These results suggest that under low to mild stress by hydroperiod and salinity, L. racemosa exhibits responses that favor its competitive dominance over R. mangle. This advantage, however, is strongly reduced as stress from salinity and hydroperiod increase.

Comparison of Belowground Biomass in C3- and C4-Dominated Mixed Communities in a Chesapeake Bay Brackish Marsh

Belowground biomass is a critical factor regulating ecosystem functions of coastal marshes, including soil organic matter (SOM) accumulation and the ability of these systems to keep pace with sea-level rise. Nevertheless, belowground biomass responses to environmental and vegetation changes have been given little emphasis marsh studies. Here we present a method using stable carbon isotopes and color to identify root and rhizomes of Schoenoplectus americanus (Pers.) Volk. ex Schinz and R. Keller (C3) and Spartina patens (Ait.) Muhl. (C4) occurring in C3− and C4-dominated communities in a Chesapeake Bay brackish marsh. The functional significance of the biomass classes we identified is underscored by differences in their chemistry, depth profiles, and variation in biomass and profiles relative to abiotic and biotic factors. C3 rhizomes had the lowest concentrations of cellulose (29.19%) and lignin (14.43%) and the lowest C:N (46.97) and lignin:N (0.16) ratios. We distinguished two types of C3 roots, and of these, the dark red C3 roots had anomalously high C:N (195.35) and lignin:N (1.14) ratios, compared with other root and rhizome classes examined here and with previously published values. The C4-dominated community had significantly greater belowground biomass (4119.1 g m−2) than the C3-dominated community (3256.9 g m−2), due to greater total root biomass and a 3.6-fold higher C3-root:rhizome ratio in the C4-dominated community. C3 rhizomes were distributed significantly shallower in the C4-dominated community, while C3 roots were significantly deeper. Variability in C3 rhizome depth distributions was explained primarily by C4 biomass, and C3 roots were explained primarily by water table height. Our results suggest that belowground biomass in this system is sensitive to slight variations in water table height (across an 8 cm range), and that the reduced overlap between C3 and C4 root profiles in the C4-dominated community may account for the greater total root biomass observed in that community. Given that future elevated atmospheric CO2 and accelerated sea-level rise are likely to increase C3 abundance in Atlantic and Gulf coast marshes, investigations that quantify how patterns of C3 and C4 belowground biomass respond to environmental and biological factors stand to improve our understanding of ecosystem-wide impacts of global changes on coastal wetlands.

The impact of a Classroom Performance System on learning gains in a biology course for science majors

This study was conducted to determine if the use of the technology known as Classroom Performance System (CPS), specifically referred to as "Clickers", improves the learning gains of students enrolled in a biology course for science majors. CPS is one of a group of developing technologies adapted for providing feedback in the classroom using a learner-centered approach. It supports and facilitates discussion among students and between them and teachers, and provides for participation by passive students. Advocates, influenced by constructivist theories, claim increased academic achievement. In science teaching, the results have been mixed, but there is some evidence of improvements in conceptual understanding. The study employed a pretest-posttest, non-equivalent groups experimental design. The sample consisted of 226 participants in six sections of a college biology course at a large community college in South Florida with two instructors trained in the use of clickers. Each instructor randomly selected their sections into CPS (treatment) and non-CPS (control) groups. All participants filled out a survey that included demographic data at the beginning of the semester. The treatment group used clicker questions throughout, with discussions as necessary, whereas the control groups answered the same questions as quizzes, similarly engaging in discussion where necessary. The learning gains were assessed on a pre/post-test basis. The average learning gains, defined as the actual gain divided by the possible gain, were slightly better in the treatment group than in the control group, but the difference was statistically non-significant. An Analysis of Covariance (ANCOVA) statistic with pretest scores as the covariate was conducted to test for significant differences between the treatment and control groups on the posttest. A second ANCOVA was used to determine the significance of differences between the treatment and control groups on the posttest scores, after controlling for sex, GPA, academic status, experience with clickers, and instructional style. The results indicated a small increase in learning gains but these were not statistically significant. The data did not support an increase in learning based on the use of the CPS technology. This study adds to the body of research that questions whether CPS technology merits classroom adaptation.

Mixed spatial and nonspatial problems in location based services

With hundreds of millions of users reporting locations and embracing mobile technologies, Location Based Services (LBSs) are raising new challenges. In this dissertation, we address three emerging problems in location services, where geolocation data plays a central role. First, to handle the unprecedented growth of generated geolocation data, existing location services rely on geospatial database systems. However, their inability to leverage combined geographical and textual information in analytical queries (e.g. spatial similarity joins) remains an open problem. To address this, we introduce SpsJoin, a framework for computing spatial set-similarity joins. SpsJoin handles combined similarity queries that involve textual and spatial constraints simultaneously. LBSs use this system to tackle different types of problems, such as deduplication, geolocation enhancement and record linkage. We define the spatial set-similarity join problem in a general case and propose an algorithm for its efficient computation. Our solution utilizes parallel computing with MapReduce to handle scalability issues in large geospatial databases. Second, applications that use geolocation data are seldom concerned with ensuring the privacy of participating users. To motivate participation and address privacy concerns, we propose iSafe, a privacy preserving algorithm for computing safety snapshots of co-located mobile devices as well as geosocial network users. iSafe combines geolocation data extracted from crime datasets and geosocial networks such as Yelp. In order to enhance iSafe's ability to compute safety recommendations, even when crime information is incomplete or sparse, we need to identify relationships between Yelp venues and crime indices at their locations. To achieve this, we use SpsJoin on two datasets (Yelp venues and geolocated businesses) to find venues that have not been reviewed and to further compute the crime indices of their locations. Our results show a statistically significant dependence between location crime indices and Yelp features. Third, review centered LBSs (e.g., Yelp) are increasingly becoming targets of malicious campaigns that aim to bias the public image of represented businesses. Although Yelp actively attempts to detect and filter fraudulent reviews, our experiments showed that Yelp is still vulnerable. Fraudulent LBS information also impacts the ability of iSafe to provide correct safety values. We take steps toward addressing this problem by proposing SpiDeR, an algorithm that takes advantage of the richness of information available in Yelp to detect abnormal review patterns. We propose a fake venue detection solution that applies SpsJoin on Yelp and U.S. housing datasets. We validate the proposed solutions using ground truth data extracted by our experiments and reviews filtered by Yelp.

Pedagogical Perceptions of Classroom Performance in the Teacher Evaluative Process: A Mixed Methods Study

This sequential explanatory, mixed methods research design examines the role teachers should enact in the development process of the teacher evaluation system in Louisiana. These insights will ensure teachers are catalysts in the classroom to significantly increase student achievement and allow policymakers, practitioners, and instructional leaders to direct as learned decision makers.

The Impact of a Classroom Performance System on Learning Gains in a Biology Course for Science Majors

This study was conducted to determine if the use of the technology known as Classroom Performance System (CPS), specifically referred to as “Clickers”, improves the learning gains of students enrolled in a biology course for science majors. CPS is one of a group of developing technologies adapted for providing feedback in the classroom using a learner-centered approach. It supports and facilitates discussion among students and between them and teachers, and provides for participation by passive students. Advocates, influenced by constructivist theories, claim increased academic achievement. In science teaching, the results have been mixed, but there is some evidence of improvements in conceptual understanding. The study employed a pretest-posttest, non-equivalent groups experimental design. The sample consisted of 226 participants in six sections of a college biology course at a large community college in South Florida with two instructors trained in the use of clickers. Each instructor randomly selected their sections into CPS (treatment) and non-CPS (control) groups. All participants filled out a survey that included demographic data at the beginning of the semester. The treatment group used clicker questions throughout, with discussions as necessary, whereas the control groups answered the same questions as quizzes, similarly engaging in discussion where necessary. The learning gains were assessed on a pre/post-test basis. The average learning gains, defined as the actual gain divided by the possible gain, were slightly better in the treatment group than in the control group, but the difference was statistically non-significant. An Analysis of Covariance (ANCOVA) statistic with pretest scores as the covariate was conducted to test for significant differences between the treatment and control groups on the posttest. A second ANCOVA was used to determine the significance of differences between the treatment and control groups on the posttest scores, after controlling for sex, GPA, academic status, experience with clickers, and instructional style. The results indicated a small increase in learning gains but these were not statistically significant. The data did not support an increase in learning based on the use of the CPS technology. This study adds to the body of research that questions whether CPS technology merits classroom adaptation.

Mixed Spatial and Nonspatial Problems in Location Based Services

With hundreds of millions of users reporting locations and embracing mobile technologies, Location Based Services (LBSs) are raising new challenges. In this dissertation, we address three emerging problems in location services, where geolocation data plays a central role. First, to handle the unprecedented growth of generated geolocation data, existing location services rely on geospatial database systems. However, their inability to leverage combined geographical and textual information in analytical queries (e.g. spatial similarity joins) remains an open problem. To address this, we introduce SpsJoin, a framework for computing spatial set-similarity joins. SpsJoin handles combined similarity queries that involve textual and spatial constraints simultaneously. LBSs use this system to tackle different types of problems, such as deduplication, geolocation enhancement and record linkage. We define the spatial set-similarity join problem in a general case and propose an algorithm for its efficient computation. Our solution utilizes parallel computing with MapReduce to handle scalability issues in large geospatial databases. Second, applications that use geolocation data are seldom concerned with ensuring the privacy of participating users. To motivate participation and address privacy concerns, we propose iSafe, a privacy preserving algorithm for computing safety snapshots of co-located mobile devices as well as geosocial network users. iSafe combines geolocation data extracted from crime datasets and geosocial networks such as Yelp. In order to enhance iSafe's ability to compute safety recommendations, even when crime information is incomplete or sparse, we need to identify relationships between Yelp venues and crime indices at their locations. To achieve this, we use SpsJoin on two datasets (Yelp venues and geolocated businesses) to find venues that have not been reviewed and to further compute the crime indices of their locations. Our results show a statistically significant dependence between location crime indices and Yelp features. Third, review centered LBSs (e.g., Yelp) are increasingly becoming targets of malicious campaigns that aim to bias the public image of represented businesses. Although Yelp actively attempts to detect and filter fraudulent reviews, our experiments showed that Yelp is still vulnerable. Fraudulent LBS information also impacts the ability of iSafe to provide correct safety values. We take steps toward addressing this problem by proposing SpiDeR, an algorithm that takes advantage of the richness of information available in Yelp to detect abnormal review patterns. We propose a fake venue detection solution that applies SpsJoin on Yelp and U.S. housing datasets. We validate the proposed solutions using ground truth data extracted by our experiments and reviews filtered by Yelp.