"The strength of this book . . . encompasses a broad view of history from the bottom up and deals not only with biographical background of the nonelite in labor but with insights into black, immigrant, and grassroots working-class history as well."--Choice Originally published in 1981. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.
Some colleges will do anything to improve their national ranking. That can be bad for their students—and for higher education. Since U.S. News & World Report first published a college ranking in 1983, the rankings industry has become a self-appointed judge, declaring winners and losers among America's colleges and universities. In this revealing account, Colin Diver shows how popular rankings have induced college applicants to focus solely on pedigree and prestige, while tempting educators to sacrifice academic integrity for short-term competitive advantage. By forcing colleges into standardized "best-college" hierarchies, he argues, rankings have threatened the institutional diversity, intellectual rigor, and social mobility that is the genius of American higher education. As a former university administrator who refused to play the game, Diver leads his readers on an engaging journey through the mysteries of college rankings, admissions, financial aid, spending policies, and academic practices. He explains how most dominant college rankings perpetuate views of higher education as a purely consumer good susceptible to unidimensional measures of brand value and prestige. Many rankings, he asserts, also undermine the moral authority of higher education by encouraging various forms of distorted behavior, misrepresentation, and outright cheating by ranked institutions. The recent Varsity Blues admissions scandal, for example, happened in part because affluent parents wanted to get their children into elite schools by any means necessary. Explaining what is most useful and important in evaluating colleges, Diver offers both college applicants and educators a guide to pursuing their highest academic goals, freed from the siren song of the "best-college" illusion. Ultimately, he reveals how to break ranks with a rankings industry that misleads its consumers, undermines academic values, and perpetuates social inequality.
A disrobing acrobat, a female Hamlet, and a tuba-playing labor activist--all these women come to life in Rank Ladies. In this comprehensive study of women in vaudeville, Alison Kibler reveals how female performers, patrons, and workers shaped the rise and fall of the most popular live entertainment at the turn of the century. Kibler focuses on the role of gender in struggles over whether high or low culture would reign in vaudeville, examining women's performances and careers in vaudeville, their status in the expanding vaudeville audience, and their activity in the vaudevillians' labor union. Respectable women were a key to vaudeville's success, she says, as entrepreneurs drew women into audiences that had previously been dominated by working-class men and recruited female artists as performers. But although theater managers publicly celebrated the cultural uplift of vaudeville and its popularity among women, in reality their houses were often hostile both to female performers and to female patrons and home to women who challenged conventional understandings of respectable behavior. Once a sign of vaudeville's refinement, Kibler says, women became associated with the decay of vaudeville and were implicated in broader attacks on mass culture as well.
Is The Wire better than Breaking Bad? Is Cheers better than Seinfeld? What's the best high school show ever made? Why did Moonlighting really fall apart? Was the Arrested Development Netflix season brilliant or terrible? For twenty years-since they shared a TV column at Tony Soprano's hometown newspaper-critics Alan Sepinwall and Matt Zoller Seitz have been debating these questions and many more, but it all ultimately boils down to this: What's the greatest TV show ever? That debate reaches an epic conclusion in TV (THE BOOK). Sepinwall and Seitz have identified and ranked the 100 greatest scripted shows in American TV history. Using a complex, obsessively all-encompassing scoring system, they've created a Pantheon of top TV shows, each accompanied by essays delving into what made these shows great. From vintage classics like The Twilight Zone and I Love Lucy to modern masterpieces like Mad Men and Friday Night Lights, from huge hits like All in the Family and ER to short-lived favorites like Firefly and Freaks and Geeks, TV (THE BOOK) will bring the triumphs of the small screen together in one amazing compendium. Sepinwall and Seitz's argument has ended. Now it's time for yours to begin!
Much has changed for workers in the years since Staughton and Alice Lynd's classic Rank and File: Personal Histories by Working-Class Organizers was first published in 1973. The New Rank and File presents interviews with working-class organizers of the 1970s, 1980s, and 1990s who face the challenges of a new economy with the same determination and creativity shown by those profiled in the earlier book. Reflecting the increasing globalization of labor practices—and problems—The New Rank and File contains oral histories of workers in Guatemala, Palestine, Nicaragua, Mexico, and Canada, as well as the United States.In their narratives, rank-and-file workers from many different industries and workplaces reveal the specific incidents and pervasive injustices that triggered their activism. They discuss the frustrations they faced in attempting to effect change through traditional means, and the ways in which they have learned to advocate through innovation. In an incisive introduction, the Lynds set forth their distinctive perspective on the labor movement, with a focus on "solidarity unionism": making decisions on the assumption that we all may be leaders at one time or another rather than relying on static hierarchies. Their insights, along with true stories told in the organizers' own words, contain much to inspire a new generation of workers and activists.Jim BrophyTony BudakAndrea CarneyChinese Staff and Workers' AssociationCoalition of University EmployeesBill DiPietroKay EisenhowerRich FeldmanThe Frente Autentico del TrabajoMarshall GanzMia GiuntaMartin GlabermanMayra GuillenThe Hebron Union of Workers and General Service PersonnelHugo HernandezMargaret KeithElly LearyEd MannCharlie McCollesterVirginia RomanVicky StarrGary StevensonMike StoutManuela Aju TambrizJames TrevathanTriState Conference on SteelMauricio VallejosWorkers for Ford in Mexico
The former chief of the Seattle Police Force offers a hard-hitting, candid assessment of law enforcement, discussing issues of gun control, prostitution, narcotics, and race in the process.
Due to the fast growth of the Web and the difficulties in finding desired information, efficient and effective information retrieval systems have become more important than ever, and the search engine has become an essential tool for many people. The ranker, a central component in every search engine, is responsible for the matching between processed queries and indexed documents. Because of its central role, great attention has been paid to the research and development of ranking technologies. In addition, ranking is also pivotal for many other information retrieval applications, such as collaborative filtering, definition ranking, question answering, multimedia retrieval, text summarization, and online advertisement. Leveraging machine learning technologies in the ranking process has led to innovative and more effective ranking models, and eventually to a completely new research area called “learning to rank”. Liu first gives a comprehensive review of the major approaches to learning to rank. For each approach he presents the basic framework, with example algorithms, and he discusses its advantages and disadvantages. He continues with some recent advances in learning to rank that cannot be simply categorized into the three major approaches – these include relational ranking, query-dependent ranking, transfer ranking, and semisupervised ranking. His presentation is completed by several examples that apply these technologies to solve real information retrieval problems, and by theoretical discussions on guarantees for ranking performance. This book is written for researchers and graduate students in both information retrieval and machine learning. They will find here the only comprehensive description of the state of the art in a field that has driven the recent advances in search engine development.
In June of 1990, a conference was held on Probablity Models and Statisti cal Analyses for Ranking Data, under the joint auspices of the American Mathematical Society, the Institute for Mathematical Statistics, and the Society of Industrial and Applied Mathematicians. The conference took place at the University of Massachusetts, Amherst, and was attended by 36 participants, including statisticians, mathematicians, psychologists and sociologists from the United States, Canada, Israel, Italy, and The Nether lands. There were 18 presentations on a wide variety of topics involving ranking data. This volume is a collection of 14 of these presentations, as well as 5 miscellaneous papers that were contributed by conference participants. We would like to thank Carole Kohanski, summer program coordinator for the American Mathematical Society, for her assistance in arranging the conference; M. Steigerwald for preparing the manuscripts for publication; Martin Gilchrist at Springer-Verlag for editorial advice; and Persi Diaconis for contributing the Foreword. Special thanks go to the anonymous referees for their careful readings and constructive comments. Finally, we thank the National Science Foundation for their sponsorship of the AMS-IMS-SIAM Joint Summer Programs. Contents Preface vii Conference Participants xiii Foreword xvii 1 Ranking Models with Item Covariates 1 D. E. Critchlow and M. A. Fligner 1. 1 Introduction. . . . . . . . . . . . . . . 1 1. 2 Basic Ranking Models and Their Parameters 2 1. 3 Ranking Models with Covariates 8 1. 4 Estimation 9 1. 5 Example. 11 1. 6 Discussion. 14 1. 7 Appendix . 15 1. 8 References.
