This book traces the theme of justice throughout the narrative of Exodus in order to explicate how yhwh’s reclamation of Israel for service-worship reveals a distinct theological ethic of justice grounded in yhwh’s character and Israel’s calling within yhwh’s creational agenda. Adopting a synchronic, text-immanent interpretive strategy that focuses on canonical and inner-biblical connections, Nathan Bills identifies two overlapping motifs that illuminate the theme of justice in Exodus. First, Bills considers the importance of Israel’s creation traditions for grounding Exodus’s theology of justice. Reading Exodus against the backdrop of creation theology and as a continuation of the plot of Genesis, Bills shows that the ethical disposition of justice imprinted on Israel in Exodus is an application of yhwh’s creational agenda of justice. Second, Bills identifies an educational agenda woven throughout the text. The narrative gives heightened attention to the way yhwh catechizes Israel in what it means to be the particular beneficiary and creational emissary of yhwh’s justice. These interpretative lenses of creation theology and pedagogy help to explain why Israel’s salvation and shaping embody a programmatic applicability of yhwh’s justice for the wider world. This volume will be of substantial interest to divinity students and religious professionals interested in the themes of exodus, exile, and return.
Todd is a banker obsessed solely with money. His life revolves around how many dollar bills he has in his possession. Then, after witnessing a poor old man gunned down before him, he realizes that there's more to life than just physical wealth.
Todd is a banker obsessed solely with money. His life revolves around how many dollar bills he has in his possession. Then, after witnessing a poor old man gunned down before him, he realizes that there's more to life than just physical wealth.
Senator Jim Jeffords left the Republican Party in May 2001 and became an independent. Because he agreed to vote with the Democrats on organizational votes, this gave that party a 51–49 majority in the Senate. Using the “Jeffords switch,” Chris Den Hartog and Nathan W. Monroe examine how power is shared and transferred in the Senate, as well as whether Democratic bills became more successful after the switch. They also use the data after the switch, when the Republican Party still held a majority on many Democratic Party-led committees, to examine the power of the committee chairs to influence decisions. While the authors find that the majority party does influence Senate decisions, Den Hartog and Monroe are more interested in exploring the method and limits of the majority party to achieve its goals.
Proposes a new theory of Senate agenda setting that reconciles a divide in literature between the conventional wisdom – in which party power is thought to be mostly undermined by Senate procedures and norms – and the apparent partisan bias in Senate decisions noted in recent empirical studies. Chris Den Hartog and Nathan W. Monroe's theory revolves around a 'costly consideration' framework for thinking about agenda setting, where moving proposals forward through the legislative process is seen as requiring scarce resources. To establish that the majority party pays lower agenda consideration costs through various procedural advantages, the book features a number of chapters examining partisan influence at several stages of the legislative process, including committee reports, filibusters and cloture, floor scheduling and floor amendments. Not only do the results support the book's theoretical assumption and key hypotheses, but they shed new light on virtually every major step in the Senate's legislative process.
This work is an autobiography that provides insight and inspiration for being a health advocate, and what that means on so many levels-from individual cases to individual leadership, from racial injustice to family lessons that help keep advocacy alive"--
How did the West--Europe, Canada, and the United States--escape from immemorial poverty into sustained economic growth and material well-being when other societies remained trapped in an endless cycle of birth, hunger, hardship, and death? In this elegant synthesis of economic history, two scholars argue that it is the political pluralism and the flexibility of the West's institutions--not corporate organization and mass production technology--that explain its unparalleled wealth.
In 1921 Austria became the first interwar European country to experience hyperinflation. The League of Nations, among other actors, stepped in to help reconstruct the economy, but a decade later Austria’s largest bank, Credit-Anstalt, collapsed. Historians have correlated these events with the banking and currency crisis that destabilized interwar Europe—a narrative that relies on the claim that Austria and the global monetary system were the victims of financial interlopers. In this corrective history, Nathan Marcus deemphasizes the destructive role of external players in Austria’s reconstruction and points to the greater impact of domestic malfeasance and predatory speculation on the nation’s financial and political decline. Consulting sources ranging from diplomatic dossiers to bank statements and financial analyses, Marcus shows how the League of Nations’ efforts to curb Austrian hyperinflation in 1922 were politically constrained. The League left Austria in 1926 but foreign interests intervened in 1931 to contain the fallout from the Credit-Anstalt collapse. Not until later, when problems in the German and British economies became acute, did Austrians and speculators exploit the country’s currency and compromise its value. Although some statesmen and historians have pinned Austria’s—and the world’s—economic implosion on financial colonialism, Marcus’s research offers a more accurate appraisal of early multilateral financial supervision and intervention. Illuminating new facets of the interwar political economy, Austrian Reconstruction and the Collapse of Global Finance reckons with the true consequences of international involvement in the Austrian economy during a key decade of renewal and crisis.
A Spiral Approach to Financial Mathematics lays a foundation of intuitive analysis of financial concepts early in the course, followed by a more detailed and nuanced treatment in later chapters. It introduces major financial concepts through real situations, integrates active learning, student focused explorations and examples with Excel spreadsheets and straightforward financial calculations. It is organized so sections can be read independently or through in-class guided-discovery activities and/or interactive lectures. Focusing on conceptual understanding to maximize comprehension and retention, using modern financial analysis tools and utilizing active learning, the book offers a modern approach that eliminates tedious and time-consuming calculations initially without underestimating the ability of readers. Covers FM Exam topics Includes Excel spreadsheets that enable the execution of financial transactions Presents a spiral, active learning pedagogical strategy that accentuates key concepts and reinforces intuitive learning
Mathematical demography is the centerpiece of quantitative social science. The founding works of this field from Roman times to the late Twentieth Century are collected here, in a new edition of a classic work by David R. Smith and Nathan Keyfitz. Commentaries by Smith and Keyfitz have been brought up to date and extended by Kenneth Wachter and Hervé Le Bras, giving a synoptic picture of the leading achievements in formal population studies. Like the original collection, this new edition constitutes an indispensable source for students and scientists alike, and illustrates the deep roots and continuing vitality of mathematical demography.
Create data mining algorithms About This Book Develop a strong strategy to solve predictive modeling problems using the most popular data mining algorithms Real-world case studies will take you from novice to intermediate to apply data mining techniques Deploy cutting-edge sentiment analysis techniques to real-world social media data using R Who This Book Is For This Learning Path is for R developers who are looking to making a career in data analysis or data mining. Those who come across data mining problems of different complexities from web, text, numerical, political, and social media domains will find all information in this single learning path. What You Will Learn Discover how to manipulate data in R Get to know top classification algorithms written in R Explore solutions written in R based on R Hadoop projects Apply data management skills in handling large data sets Acquire knowledge about neural network concepts and their applications in data mining Create predictive models for classification, prediction, and recommendation Use various libraries on R CRAN for data mining Discover more about data potential, the pitfalls, and inferencial gotchas Gain an insight into the concepts of supervised and unsupervised learning Delve into exploratory data analysis Understand the minute details of sentiment analysis In Detail Data mining is the first step to understanding data and making sense of heaps of data. Properly mined data forms the basis of all data analysis and computing performed on it. This learning path will take you from the very basics of data mining to advanced data mining techniques, and will end up with a specialized branch of data mining—social media mining. You will learn how to manipulate data with R using code snippets and how to mine frequent patterns, association, and correlation while working with R programs. You will discover how to write code for various predication models, stream data, and time-series data. You will also be introduced to solutions written in R based on R Hadoop projects. Now that you are comfortable with data mining with R, you will move on to implementing your knowledge with the help of end-to-end data mining projects. You will learn how to apply different mining concepts to various statistical and data applications in a wide range of fields. At this stage, you will be able to complete complex data mining cases and handle any issues you might encounter during projects. After this, you will gain hands-on experience of generating insights from social media data. You will get detailed instructions on how to obtain, process, and analyze a variety of socially-generated data while providing a theoretical background to accurately interpret your findings. You will be shown R code and examples of data that can be used as a springboard as you get the chance to undertake your own analyses of business, social, or political data. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Learning Data Mining with R by Bater Makhabel R Data Mining Blueprints by Pradeepta Mishra Social Media Mining with R by Nathan Danneman and Richard Heimann Style and approach A complete package with which will take you from the basics of data mining to advanced data mining techniques, and will end up with a specialized branch of data mining—social media mining.
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