Merge Left

From the acclaimed author of Dog Whistle Politics, an essential road map to neutralizing the role of racism as a divide-and-conquer political weapon and to building a broad multiracial progressive future "Ian Haney López has broken the code on the racial politics of the last fifty years."—Bill Moyers In 2014, Ian Haney López in Dog Whistle Politics named and explained the coded racial appeals exploited by right-wing politicians over the last half century—and thereby anticipated the 2016 presidential election. Now the country is heading into what will surely be one of the most consequential elections ever, with the Right gearing up to exploit racial fear-mongering to divide and distract, and the Left splintered over the next step forward. Some want to focus on racial justice head-on; others insist that a race-silent focus on class avoids alienating white voters. Can either approach—race-forward or colorblind—build the progressive supermajorities necessary to break political gridlock and fundamentally change the country's direction? For the past two years, Haney López has been collaborating with a research team of union activists, racial justice leaders, communications specialists, and pollsters. Based on conversations, interviews, and surveys with thousands of people all over the country, the team found a way forward. By merging the fights for racial justice and for shared economic prosperity, they were able to build greater enthusiasm for both goals—and for the cross-racial solidarity needed to win elections. What does this mean? It means that neutralizing the Right's political strategy of racial division is possible, today. And that's the key to everything progressives want to achieve. A work of deep research, nuanced argument, and urgent insight, Merge Left: Fusing Race and Class, Winning Elections, and Saving America is an indispensable tool for the upcoming political season and in the larger fight to build racial justice and shared economic prosperity for all of us.

Programming Languages: Concepts and Implementation teaches language concepts from two complementary perspectives: implementation and paradigms. It covers the implementation of concepts through the incremental construction of a progressive series of interpreters in Python, and Racket Scheme, for purposes of its combined simplicity and power, and assessing the differences in the resulting languages.

Discovering Computer Science: Interdisciplinary Problems, Principles, and Python Programming introduces computational problem solving as a vehicle of discovery in a wide variety of disciplines. With a principles-oriented introduction to computational thinking, the text provides a broader and deeper introduction to computer science than typical introductory programming books. Organized around interdisciplinary problem domains, rather than programming language features, each chapter guides students through increasingly sophisticated algorithmic and programming techniques. The author uses a spiral approach to introduce Python language features in increasingly complex contexts as the book progresses. The text places programming in the context of fundamental computer science principles, such as abstraction, efficiency, and algorithmic techniques, and offers overviews of fundamental topics that are traditionally put off until later courses. The book includes thirty well-developed independent projects that encourage students to explore questions across disciplinary boundaries. Each is motivated by a problem that students can investigate by developing algorithms and implementing them as Python programs. The book's accompanying website — http://discoverCS.denison.edu — includes sample code and data files, pointers for further exploration, errata, and links to Python language references. Containing over 600 homework exercises and over 300 integrated reflection questions, this textbook is appropriate for a first computer science course for computer science majors, an introductory scientific computing course or, at a slower pace, any introductory computer science course.

Automated and semi-automated manipulation of so-called labelled transition systems has become an important means in discovering flaws in software and hardware systems. Process algebra has been developed to express such labelled transition systems algebraically, which enhances the ways of manipulation by means of equational logic and term rewriting. The theory of process algebra has developed rapidly over the last twenty years, and verification tools have been developed on the basis of process algebra, often in cooperation with techniques related to model checking. This textbook gives a thorough introduction into the basics of process algebra and its applications.

Baseball is not the only sport to use "moneyball." American football fans, teams, and gamblers are increasingly using data to gain an edge against the competition. Professional and college teams use data to help select players and identify team needs. Fans use data to guide fantasy team picks and strategies. Sports bettors and fantasy football players are using data to help inform decision making. This concise book provides a clear introduction to using statistical models to analyze football data. Whether your goal is to produce a winning team, dominate your fantasy football league, qualify for an entry-level football analyst position, or simply learn R and Python using fun example cases, this book is your starting place. You'll learn how to: Apply basic statistical concepts to football datasets Describe football data with quantitative methods Create efficient workflows that offer reproducible results Use data science skills such as web scraping, manipulating data, and plotting data Implement statistical models for football data Link data summaries and model outputs to create reports or presentations using tools such as R Markdown and R Shiny And more

This collection explicates one of the core ideas underpinning Minimalist theory – explanation via simplification – and its role in shaping some of the latest developments within this framework, specifically the simplest Merge hypothesis and the reduction of syntactic phenomena to third factor considerations. Bringing together recent papers on the topic by Epstein, Kitahara, and Seely, with one by Epstein, Seely and Obata, and one by Kitahara, the book begins with an introduction which situates the papers in a cohesive overview of some of the latest research on Minimalism, as facilitated by current theoretical developments. The volume integrates a historical overview of evolutions in Merge, starting with Chomsky’s (pre-Merge) Aspects model up to current theoretical models, including a primer of Chomsky’s most recent theory of Merge based on the concept of Workspace. The Minimalist notions of "perfection" and "simplification" are also outlined, providing clearly explicated coverage of key technical concepts within the framework as applied to grammatical phenomena. Taken as a whole, the collection both introduces and advances Minimalist theory for students and scholars in linguistics and related sub-disciplines of psychology, philosophy, and cognitive science, as well as offering new directions for future research for researchers in these fields.