Large-scale text processing pipeline with Apache Spark

In this paper, we evaluate Apache Spark for a data-intensive machine learning problem. Our use case focuses on policy diffusion detection across the state legislatures in the United States over time. Previous work on policy diffusion has been unable to make an all-pairs comparison between bills due to computational intensity. As a substitute, scholars have studied single topic areas. We provide an implementation of this analysis workflow as a distributed text processing pipeline with Spark dataframes and Scala application programming interface. We discuss the challenges and strategies of unstructured data processing, data formats for storage and efficient access, and graph processing at scale

Perceptions of door-to-door HIV counselling and testing in Botswana

Prevalence of HIV infection in Botswana is among the highest in the world, at 23.9% of 15 - 49-year-olds. Most HIV testing is conducted in voluntary counselling and testing centres or medical settings. Improved access to testing is urgently needed. This qualitative study assessed and documented community perceptions about the concept of door-to-door HIV counselling and rapid testing in two of the highest-prevalence districts of Botswana. Community members associated many positive benefits with home-based, door-to-door HIV testing, including convenience, confidentiality, capacity to increase the number of people tested, and opportunities to increase knowledge of HIV transmission, prevention and care through provision of correct information to households. Community members also saw the intervention as increasing opportunities to engage and influence family members and to role model positive behaviours. Participants also perceived social risks and dangers associated with home-based testing including the potential for conflict, coercion, stigma, and psychological distress within households. Community members emphasised the need for individual and community preparation, including procedures to protect confidentiality, provisions for psychological and social support, and links to appropriate services for HIV-positive persons

HMGB1 Mediates Endogenous TLR2 Activation and Brain Tumor Regression

Maria Castro and colleagues use cell line and transgenic mouse approaches to study the mechanisms underlying the immune response to glioblastoma multiforme

How Groups Write the Law: An Empirical Analysis of Group Influence in American State Legislatures

This dissertation empirically examines the role that organized groups play in drafting legislation in U.S. state legislatures. Using a large dataset, new data, and a variety of empirical tests, I measure the distribution of power across actors within and outside of legislatures. First, I examine the predictors of model legislation sponsorship within state legislatures. Using textual analysis to compare model bills with introduced and enacted state bills from 1995-2014, I detect the use of model bills in state legislatures. I test predictions derived from a model of strategic interaction between a group and legislature under varying legislative resources, ideological distance, and policy area complexity. Using variation across legislative bodies and across legislators, I test claims that legislators under greater resource constraints rely more heavily upon model legislation given the ease of introducing a prepackaged bill. Since the universe of model legislation is not well-defined, I use a unique reporting institution to examine the extent to which legislation originates from groups. In the California state legislature, extra-legislative groups that write legislation and secure a legislator to author the bill may be listed as sponsors. Data on group sponsorship come from bill analyses and extend from 1993-2014. This unstudied group tactic is frequently used: 37% of bills introduced and 59% of bills that become law list an extra-legislative sponsor. Group sponsorship is significantly related to passage, even after matching on a number of covariates. Also, legislators use fewer group bills and substitute out of group bills as they gain more experience. The final chapter of the dissertation explores the systematic changes that bills undergo as they pass through the legislature. I find that as the distance between a sponsor and median legislator increases, the original bill is altered more extensively. By examining how 199,200 bills change throughout the legislative process in various state legislatures, I study which actors' preferences are prioritized in legislative outcomes. In the first two chapters, I find that group input serves as an integral part of a legislative portfolio and the agenda-setting stage of legislative decision-making. The final chapter finds that legislators' bills change in systematic ways

Stone soup: using co-teaching and Photovoice to support inclusive education

The purpose of this action research project was to increase the local educational system’s capacity to teach to greater student diversity across all grades through the use of Photovoice and co-teaching. Teacher education programs in the United States have reflected a historical legacy of separation according to student achievement and were organized in discrete and independent fashions. Barriers to collaboration now appear in even greater relief due to recent changes in US educational laws. Faculty and doctoral students from multiple programs in the School of Education, along with field supervisors, student-teachers and cooperating teachers, participated in an action research project to develop innovative strategies for integrating teacher preparation programs. Using Photovoice and co-teaching, investigators identified themes discovered in the data. Results indicated that collaboration benefits our student-teachers and the pupils they will teach. Recommendations for change are discussed