Globalization and Immigration: How a Changing Demographic Landscape Influenced the 2016 Presidential Election

The 2016 presidential election results varied significantly from many forecasts. The media proposes that the radically atypical candidacy of Donald Trump motivated pockets of the electorate to support the Republican Party more so than they had in past elections. This paper examines the following questions: Which traditional predictors of the election failed to foresee a Republican victory? If the traditional predictors were unsuccessful, can the results be explained using county level economic and demographic data? Is there evidence to support the media’s proposed explanations of the results? By utilizing the Census Bureau’s American Community Survey data, this paper examines some major economic and demographic determinants of the 2012 and 2016 election outcomes with a particular emphasis on the role of globalization and immigration. Further, this paper examines how changes in these county level features affected differences in county level support of the two Republican nominees. Thus, this paper finds that sociotropic economic perceptions remain as a significant determinant of voter behavior, even at the county level. Trump’s campaign may have failed to muster more support in counties with a high concentration of secondary sector occupations and higher inflows of immigrants. However, the results support the media’s conventional narratives that white Americans more heavily supported Trump, while educated Americans increasingly disapproved of the Republican nominee

Simulation-based Cognitive Workload Modeling And Evaluation Of Adaptive Automation Invoking And Revoking Strategies

In human-computer systems, such as supervisory control systems, large volumes of incoming and complex information can degrade overall system performance. Strategically integrating automation to offload tasks from the operator has been shown to increase not only human performance but also operator efficiency and safety. However, increased automation allows for increased task complexity, which can lead to high cognitive workload and degradation of situational awareness. Adaptive automation is one potential solution to resolve these issues, while maintaining the benefits of traditional automation. Adaptive automation occurs dynamically, with the quantity of automated tasks changing in real-time to meet performance or workload goals. While numerous studies evaluate the relative performance of manual and adaptive systems, little attention has focused on the implications of selecting particular invoking or revoking strategies for adaptive automation. Thus, evaluations of adaptive systems tend to focus on the relative performance among multiple systems rather than the relative performance within a system. This study takes an intra-system approach specifically evaluating the relationship between cognitive workload and situational awareness that occurs when selecting a particular invoking-revoking strategy for an adaptive system. The case scenario is a human supervisory control situation that involves a system operator who receives and interprets intelligence outputs from multiple unmanned assets, and then identifies and reports potential threats and changes in the environment. In order to investigate this relationship between workload and situational awareness, discrete event simulation (DES) is used. DES is a standard technique in the analysis iv of systems, and the advantage of using DES to explore this relationship is that it can represent a human-computer system as the state of the system evolves over time. Furthermore, and most importantly, a well-designed DES model can represent the human operators, the tasks to be performed, and the cognitive demands placed on the operators. In addition to evaluating the cognitive workload to situational awareness tradeoff, this research demonstrates that DES can quite effectively model and predict human cognitive workload, specifically for system evaluation. This research finds that the predicted workload of the DES models highly correlates with well-established subjective measures and is more predictive of cognitive workload than numerous physiological measures. This research then uses the validated DES models to explore and predict the cognitive workload impacts of adaptive automation through various invoking and revoking strategies. The study provides insights into the workload-situational awareness tradeoffs that occur when selecting particular invoking and revoking strategies. First, in order to establish an appropriate target workload range, it is necessary to account for both performance goals and the portion of the workload-performance curve for the task in question. Second, establishing an invoking threshold may require a tradeoff between workload and situational awareness, which is influenced by the task’s location on the workload-situational awareness continuum. Finally, this study finds that revoking strategies differ in their ability to achieve workload and situational awareness goals. For the case scenario examined, revoking strategies based on duration are best suited to improve workload, while revoking strategies based on revoking thresholds are better for maintaining situational awareness

Predicting Cost and Schedule Growth for Military and Civil Space Systems

Military and civil space acquisitions have received much criticism for their inability to produce realistic cost and schedule estimates. This research seeks to provide space systems cost estimators with a forecasting tool for space system cost and schedule growth by identifying factors contributing to growth, quantifying the relative impact of these factors, and establishing a set of models for predicting space system cost and schedule growth. The analysis considers data from both Department of Defense (DoD) and National Aeronautics and Space Administration (NASA) space programs. The DoD dataset includes 21 space programs that submitted developmental Selected Acquisition Reports between 1969 and 2006. The analysis uses multiple regression to assess 22 predictor variables, finding that communications missions, ground equipment, firm-fixed price contracts, and increased program manager tenure are all predictive of lower cost growth for military space systems. The NASA analysis includes 71 satellites and spacecraft developed between 1964 and 2004. The analysis uses a two-stage logistic and multiple regression approach to analyze 31 predictor variables finding that smaller programs (by total cost), more massive spacecraft, microgravity missions, and space physics missions are predictive of higher cost growth. For schedule growth, the study finds that larger programs and those developed by the Jet Propulsion Laboratory, Northrop Grumman, or international developers are predictive of increased schedule growth, whereas those programs developed by Johns Hopkins University are predictive of reduced schedule growth

Bolzano and uniform continuity

AbstractIt has often been thought that the distinction between pointwise and uniform continuity was a relatively late arrival to real analysis, due to the mathematicians associated with Weierstrass. In this note, it is argued that Bolzano, in his work on real function theory dating from the 1830s, had grasped the distinction and stated two key theorems concerning uniform continuity

We’re Not Barbie Girls: Tweens Transform a Feminine Icon

“Reinventing Barbie” was a workshop for middle-school girls to discuss, critique, and reflect on the construction of female bodies and feminine identities in popular culture by remaking Barbie dolls. The workshop was designed to foster conversations with and among girls about what it means to be embodied as female in American culture. The girls reconstructed Barbies based on their reflections, and then they came together to discuss their dolls as expressions of their visions for transforming the feminine. The article analyzes the collaborative process of the workshop, which was grounded in women’s studies scholarship and developed by an interdisciplinary group of feminist academics

Applying Control Abstraction to the Design of Human–Agent Teams

Levels of Automation (LOA) provide a method for describing authority granted to automated system elements to make individual decisions. However, these levels are technology-centric and provide little insight into overall system operation. The current research discusses an alternate classification scheme, referred to as the Level of Human Control Abstraction (LHCA). LHCA is an operator-centric framework that classifies a system’s state based on the required operator inputs. The framework consists of five levels, each requiring less granularity of human control: Direct, Augmented, Parametric, Goal-Oriented, and Mission-Capable. An analysis was conducted of several existing systems. This analysis illustrates the presence of each of these levels of control, and many existing systems support system states which facilitate multiple LHCAs. It is suggested that as the granularity of human control is reduced, the level of required human attention and required cognitive resources decreases. Thus, it is suggested that designing systems that permit the user to select among LHCAs during system control may facilitate human-machine teaming and improve the flexibility of the system

Human-Centered Design Using System Modeling Language

The human user is important to consider during system design. However, common system design models, such as the system modeling language, typically represent human users and operators as external actors, rather than as internal to the system. This research presents a method for integrating human considerations into system models through human-centered design. A specific system is selected to serve as the case study for demonstrating the methodology. The sample system is analyzed to identify the task and information flow. Then, both system- and human-centered diagrams are separately created to represent different viewpoints of the system. These diagrams are compared and analyzed, and new diagrams are created that incorporate both system and human considerations into one concordant representation of the system model. These new views allow systems engineers and human factors engineers to effectively communicate the role of the user during early system design trades

Final Report of the AFIT Quality Initiative Internal Discovery Committee

This document contains results of a study designed to document the key elements for student success at AFIT in our continuing education and graduate programs and discover to what degree they exist at AFIT. The effort represents an attempt to guide improvement of our graduate and continuing education programs through experience available from our faculty, staff and students. The process outlined herein was designed to achieve success by allowing the participants to define what it means to succeed and then self-assess the presence of these factors at AFIT. It’s therefore a true internal discovery process since its output reflects the state of our internal understanding of teaching and learning excellence. This inclusive approach, which garnered participation from 400 people across AFIT’s schools, will be used in conjunction with the external committee\u27s recommendations to determine a course of action to invest into AFIT\u27s instructional capabilities

The Modern Census: Evolution, Examples and Evaluation

A national census provides important information on a country's population that is used in government planning and to underpin the national statistical system. Therefore, the quality of such information is paramount but is not as simple as the crude accuracy of population totals. Furthermore, changes in the pace and nature of modern life, such as the growing geographical mobility of the population, increasingly pose challenges to census practice and data quality. More recently, even the need for a census has been questioned on grounds of financial austerity and widespread availability of alternative population information sources. This article reviews how the modern census originated and how it evolved to confront these challenges, driven by indicators of quality and needs of users, and provides reflections on the future of the census within the national statistical infrastructure. To illustrate our discussions, we use case studies from a diverse range of national contexts. We demonstrate the implications that a country's needs, circumstances and experiences have on the census approach and practice while identifying the fundamental demographic assumptions