Characterizing 311 System Reactions to a Global Health Emergency

Communities are complex, multi-dimensional systems that react to crises in a variety of different ways. Based on the municipal services provided to a community, 311 calls can be used as indicators of the different dimensions of that community’s reaction to a crisis situation. To improve Citizen Relationship Management, municipalities can analyze and even augment their 311 systems to capture specific types of information about an ongoing crisis. New York City did this by adding specific category types and descriptors to their 311 system, in response to the evolving COVID-19 pandemic. This paper provides an initial look at the 311 data for New York City and the variety of community behaviors that it is able to capture as a reaction to the pandemic and the associated actions taken by the authorities to respond to the situation

Examining User Access Options for eGovernment Services During a Crisis from a Digital Inequality Perspective

City governments incorporate ICTs into government services to improve citizen participation and access to those services. Too much dependence on technology, however, can lead to concerns about creating a digital divide between different groups of citizens. The potential for digital inequality is a critical issue that can be exacerbated by insufficient attention being paid to vulnerabilities across communities. Given that socio-economically vulnerable populations are the ones who need government services the most, especially during disaster events, it is critical to investigate the extent to which digital inequality is an issue for technology-based government services. With this in mind, this paper analyzes the use of different technology-enabled access options for a representative eGovernment service system, the New York City 311 service system, in the early stages of the COVID-19 pandemic. Two sets of socio-economically distinct locations in New York City are compared, using average income as a proxy for vulnerability, to draw conclusions about potential inequalities in such a system during a crisis

Allocating Resources to Enhance Resilience, with Application to Superstorm Sandy and an Electric Utility

This article constructs a framework to help a decisionmaker allocate resources to increase his or her organization\u27s resilience to a system disruption, where resilience is measured as a function of the average loss per unit time and the time needed to recover full functionality. Enhancing resilience prior to a disruption involves allocating resources from a fixed budget to reduce the value of one or both of these characteristics. We first look at characterizing the optimal resource allocations associated with several standard allocation functions. Because the resources are being allocated before the disruption, however, the initial loss and recovery time may not be known with certainty. We thus also apply the optimal resource allocation model for resilience to three models of uncertain disruptions: (1) independent probabilities, (2) dependent probabilities, and (3) unknown probabilities. The optimization model is applied to an example of increasing the resilience of an electric power network following Superstorm Sandy

Topic Maps For Improving Services In Disaster Operations Management

Disaster operations management is an increasingly important application area for the developing techniques of service science. This paper examines the use of topic maps, a semantic technology, within this environment, and provides a preliminary discussion of the benefits that its implementation can provide in the capture and exchange of contextual information. The discussion is motivated by a look at the different phases of disaster operations management in a services context, and focuses on the need for effective and relevant information exchange as an important part of the services process. As the amount and complexity of information increases within such processes, semantic technologies are becoming increasingly important as a means representing and managing contextual information. This paper seeks to help further the understanding of the relevance of such tools as part of the study of service science

Creating Offshore-ready IT Professionals: A global perspective and strong collaborative skills are needed

Outsourcing of IT functions has become a widespread corporate practice, which has naturally led to concerns among IT works about how this affects their jobs. The issue is complex, and many companies are bringing their IT functions back inhouse. In light of this complexity, what skills do IT workers need to be com-petitive? We address this question first by reviewing the literature and then by examining two corporate case studies that have dealt with outsourcing issues. Based on this view of outsourcing, we discuss the skills that can provide a com-petitive advantage in the current environment

Establishing a frame of reference for measuring disaster resilience

Due to the increasing occurrence of disruptions across our global society, it has become critically important to understand the resilience of different socio-economic systems, i.e., to what extent those systems exhibit the ability both to resist a disruption and to recover from one once it occurs. In order to characterize this ability, however, one must be able to quantitatively measure the relative level of resilience that a given system displays in response to a disruptive event. Such a measurement should be easily understandable and straightforward to implement, but it should also utilize a consistent frame of reference so that one can properly compare the relative performance of different systems and assess the relative effectiveness of different resilience investments. With this in mind, this paper presents an improved approach for measuring system resilience that supports better decision making by providing both consistency and flexibility across different contexts. The theoretical basis for the approach is developed first, and then its advantages and limitations are illustrated in the context of several different practical examples

Human-AI Teaming During an Ongoing Disaster: How Scripts Around Training and Feedback Reveal this is a Form of Human-Machine Communication

Humans play an integral role in identifying important information from social media during disasters. While human annotation of social media data to train machine learning models is often viewed as human-computer interaction, this study interrogates the ontological boundary between such interaction and human-machine communication. We conducted multiple interviews with participants who both labeled data to train machine learning models and corrected machine-inferred data labels. Findings reveal three themes: scripts invoked to manage decision-making, contextual scripts, and scripts around perceptions of machines. Humans use scripts around training the machine—a form of behavioral anthropomorphism—to develop social relationships with them. Correcting machine-inferred data labels changes these scripts and evokes self-doubt around who is right, which substantiates the argument that this is a form of human-machine communication

The Grizzly, February 11, 1991

Fraternity Pledging Returns Again • Wachtel Explains the Poverty of Affluence • The Changing War • Peer Educators and Community Service • Alumni Visit the Ballet • Study Abroad Memorable • A Valentine History • Side Winders • Dance Marathon • Get Shorty • Triumph of the Spirit • Gymnasts Fare Well at Ithaca, Reach Team Goal • Track Women Place Third at PAIAW Championships • Hoopsters Rounding Out Season • Fro Scores Point, Swimmers Wash Out Widener • Wrestlers Excel • Letters: Bring Becker Back; Praise From Florida; Oh no, Mr. Bill!; Respect Yourself and Your Major • War: A Personal Experience on the Homefront • Who Wants the Persian Gulf War? • The Mephisto of Calculus • This Spill No Mistakehttps://digitalcommons.ursinus.edu/grizzlynews/1270/thumbnail.jp

Research questions to facilitate the future development of European long-term ecosystem research infrastructures : A horizon scanning exercise

Distributed environmental research infrastructures are important to support assessments of the effects of global change on landscapes, ecosystems and society. These infrastructures need to provide continuity to address long-term change, yet be flexible enough to respond to rapid societal and technological developments that modify research priorities. We used a horizon scanning exercise to identify and prioritize emerging research questions for the future development of ecosystem and socio-ecological research infrastructures in Europe. Twenty research questions covered topics related to (i) ecosystem structures and processes, (ii) the impacts of anthropogenic drivers on ecosystems, (iii) ecosystem services and socio-ecological systems and (iv), methods and research infrastructures. Several key priorities for the development of research infrastructures emerged. Addressing complex environmental issues requires the adoption of a whole-system approach, achieved through integration of biotic, abiotic and socio-economic measurements. Interoperability among different research infrastructures needs to be improved by developing standard measurements, harmonizing methods, and establishing capacities and tools for data integration, processing, storage and analysis. Future research infrastructures should support a range of methodological approaches including observation, experiments and modelling. They should also have flexibility to respond to new requirements, for example by adjusting the spatio-temporal design of measurements. When new methods are introduced, compatibility with important long-term data series must be ensured. Finally, indicators, tools, and transdisciplinary approaches to identify, quantify and value ecosystem services across spatial scales and domains need to be advanced.Peer reviewe