Beyond The Four Walls: Why Community Is Critical to Workforce Health

This report calls for increased cross-sector collaboration to address community-level drivers of workforce health. It demonstrates the relationship between workforce and community health and reveals that certain industries are more likely to be concentrated in counties with poor health, and outlines strategies these industries can use to improve community and workforce health. The report also includes guidelines to implement effective cross-sector partnerships and overcome common barriers faced by employers and community groups.Case studies featured in the report demonstrate how:Employers are leveraging three strategies to make quality investments in community health, which benefit the business and population healthCommunity groups are leveraging these three strategies to engage businesses in local health promotio

Fake News Detection in Social Networks via Crowd Signals

Our work considers leveraging crowd signals for detecting fake news and is motivated by tools recently introduced by Facebook that enable users to flag fake news. By aggregating users' flags, our goal is to select a small subset of news every day, send them to an expert (e.g., via a third-party fact-checking organization), and stop the spread of news identified as fake by an expert. The main objective of our work is to minimize the spread of misinformation by stopping the propagation of fake news in the network. It is especially challenging to achieve this objective as it requires detecting fake news with high-confidence as quickly as possible. We show that in order to leverage users' flags efficiently, it is crucial to learn about users' flagging accuracy. We develop a novel algorithm, DETECTIVE, that performs Bayesian inference for detecting fake news and jointly learns about users' flagging accuracy over time. Our algorithm employs posterior sampling to actively trade off exploitation (selecting news that maximize the objective value at a given epoch) and exploration (selecting news that maximize the value of information towards learning about users' flagging accuracy). We demonstrate the effectiveness of our approach via extensive experiments and show the power of leveraging community signals for fake news detection

"May I borrow Your Filter?" Exchanging Filters to Combat Spam in a Community

Leveraging social networks in computer systems can be effective in dealing with a number of trust and security issues. Spam is one such issue where the "wisdom of crowds" can be harnessed by mining the collective knowledge of ordinary individuals. In this paper, we present a mechanism through which members of a virtual community can exchange information to combat spam. Previous attempts at collaborative spam filtering have concentrated on digest-based indexing techniques to share digests or fingerprints of emails that are known to be spam. We take a different approach and allow users to share their spam filters instead, thus dramatically reducing the amount of traffic generated in the network. The resultant diversity in the filters and cooperation in a community allows it to respond to spam in an autonomic fashion. As a test case for exchanging filters we use the popular SpamAssassin spam filtering software and show that exchanging spam filters provides an alternative method to improve spam filtering performance

Three Essays on Clean Water State Revolving Funds: Determinants of State Leveraging and Measurement of Debt Affordability

Leveraging is a popular option among Clean Water State Revolving Funds (CWSRFs). Most states choose to issue bonds to meet the requirement of the state match contribution, and to provide additional funding into the pool of funds available for community loan assistance. Leveraging offers short-term remedies to fill a financial resources gap; however, this raises concern about any costs associated with leveraging that might negatively influence the sustainability of CWSRFs in the long run. This dissertation comprises three essays that examine the different factors that motivate CWSRFs to leverage, and it offers a look at how they measure their affordability leveraging. Chapter Two borrows the assumptions of pecking order theory to build CWSRF’s leverage model. It focuses on the internal set of factors, and it analyses how the entity’s size, profitability, growth, reserve, and risk affect its leveraging. Chapter Three examines the relationship between leveraging and an external set of indicators, including socioeconomic, demographic, political, and institutional factors. The findings suggest that, in leveraging, internal factors appear to be more influential than external ones. The entity’s size and growth (entity-based factors) are found to be significant with both total and annual leveraging, while state wealth, state politics, and environmental needs also indicate some connection to debt share or debt per capita. Chapter Four particularly scrutinizes how leveraged states measure their debt affordability; it replicates the regression method and predicts the future debt service for New York state. The findings suggest that the regression method can be a good tool for predicting the debt affordability level for CWSRFs. The predicted values from that method can also serve as a supplemental reference source for states before they consider additional leveraging

Event Planning and Leveraging for Sport Tourism Development: The Case of a Rural Motorcycle Event

This case study focuses on planning and leveraging sport events for community-based sport tourism and economic development. It is presented from the point of view of a sport event/marketing coordinator (Ian) within the Convention and Visitors Bureau (CVB) of the fictional rural community of Panorama. He has been assigned to write a report about the potential of organizing (and leveraging) a new motorcycle event tapping into the unparalleled success and experience of two car open road races that the town hosts. Ian is a recent sport management graduate who has just been hired by CVB and hence knows little about the community and its events. He begins preparing his report by collecting information and taking notes in order to understand the community dynamics affecting events and learn from the races with the purpose of identifying what would be the best means to attain benefits from the proposed new event. Drawing upon the theoretical underpinnings of sport event leverage and multi-purpose event portfolios, the case provides the opportunity for students to apply these tenets on a realistic context, taking them through a research path of gradual exploration and discovery of issues and means entailed in event portfolio planning and leveraging

Automatic annotation of bioinformatics workflows with biomedical ontologies

Legacy scientific workflows, and the services within them, often present scarce and unstructured (i.e. textual) descriptions. This makes it difficult to find, share and reuse them, thus dramatically reducing their value to the community. This paper presents an approach to annotating workflows and their subcomponents with ontology terms, in an attempt to describe these artifacts in a structured way. Despite a dearth of even textual descriptions, we automatically annotated 530 myExperiment bioinformatics-related workflows, including more than 2600 workflow-associated services, with relevant ontological terms. Quantitative evaluation of the Information Content of these terms suggests that, in cases where annotation was possible at all, the annotation quality was comparable to manually curated bioinformatics resources.Comment: 6th International Symposium on Leveraging Applications (ISoLA 2014 conference), 15 pages, 4 figure

Modeling Infection with Multi-agent Dynamics

Developing the ability to comprehensively study infections in small populations enables us to improve epidemic models and better advise individuals about potential risks to their health. We currently have a limited understanding of how infections spread within a small population because it has been difficult to closely track an infection within a complete community. The paper presents data closely tracking the spread of an infection centered on a student dormitory, collected by leveraging the residents' use of cellular phones. The data are based on daily symptom surveys taken over a period of four months and proximity tracking through cellular phones. We demonstrate that using a Bayesian, discrete-time multi-agent model of infection to model real-world symptom reports and proximity tracking records gives us important insights about infec-tions in small populations

Disaster Planning for Vulnerable Populations: Leveraging Community Human Service Organizations Direct Service Delivery Personnel

Given the variability, complexities, and available resources for local vulnerable populations, it is clear that preparing effectively for catastrophic events cannot be accomplished with a single, simple template. Inclusion of Community Human Service Organizations’ (CHSO’s) direct service delivery personnel ensures that emergency disaster planning efforts for vulnerable populations are effective and responsive to unique needs and constraints. By leveraging existing local resources, it extends the preparedness system’s reach to the whole community