How new techniques of quantification shaped the New Deal and American democracy.
When the Great Depression struck, the US government lacked tools to assess the situation; there was no reliable way to gauge the unemployment rate, the number of unemployed, or how many families had abandoned their farms to become migrants. In America by the Numbers, Emmanuel Didier examines the development in the 1930s of one such tool: representative sampling. Didier describes and analyzes the work of New Deal agricultural economists and statisticians who traveled from farm to farm, in search of information that would be useful for planning by farmers and government agencies. Didier shows that their methods were not just simple enumeration; these new techniques of quantification shaped the New Deal and American democracy even as the New Deal shaped the evolution of statistical surveys.
Didier explains how statisticians had to become detectives and anthropologists, searching for elements that would help them portray America as a whole. Representative surveys were one of the most effective instruments for their task. He examines pre-Depression survey techniques; the invention of the random sampling method and the development of the Master Sample; and the application of random sampling by employment experts to develop the "Trial Census of Unemployment."
Автор: Nishisato Shizuhiko Название: Optimal Quantification and Symmetry ISBN: 981169169X ISBN-13(EAN): 9789811691690 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book offers a unique new look at the familiar quantification theory from the point of view of mathematical symmetry and spatial symmetry.
Описание: PART 1: Sociology of Quantification: Alain Desrosiиres's contributions Chapter 1. Introduction to the work of Alain Desrosiиres: the history and sociology of quantification; Michel Armatte.- Chapter 2. Alain Desrosiиres's reflexive numbers Luc Boltanski.- Chapter 3. Alain Desrosiиres's spectacles: one lens realist, the other constructivist; Emmanuel Didier.- Chapter 4. From statistics to international quantification: a dialogue with Alain Desrosiиres; Roser Cussу.- Chapter 5. Learning from the history of the probabilistic revolution: the French school of Alain Desrosiиres; Fabrice Bardet PART 2. THE STATISTICAL ARGUMENT IN THE NEOLIBERAL ERA CHAPTER 6. Quantifying the effects of public action on the unemployed: disputes between experts and the rethinking of labour market policies in France (1980‐2000); Etienne Penissat.- CHAPTER 7. Counting the homeless in Europe: 'compare before harmonising'; Cйcile Brousse.- CHAPTER 8. The statistical backbone of the new European economic governance: the Macroeconomic Imbalance Procedure Scoreboard; Gilles Raveaud.- CHAPTER 9. Evaluating public policies or measuring the performance of public services?; Florence Jany‐Catrice PART 3: USES OF QUANTIFICATION: POWER AND RESISTANCE CHAPTER 10. Private accounting, statistics and national accounting in France: a unique relationship (1920‐1960s); Bйatrice Touchelay.- CHAPTER 11: Figures for what purposes? The issues at stake in the struggles to define and control the uses of statistics; Marion Gilles.- CHAPTER 12: The uses of quantification: power and resistance. The example of unemployment statistics.- Chapter 13: Statistical argument: construction, uses and controversies Prices and purchasing power; Alain Gйly.- CHAPTER 14: The quantification of the social sciences: an historical comparison; Alain Desrosiиres.
Описание: An Accelerated Course with Applications in Computational Sciences and Engineering
Автор: Sullivan, T.j. Название: Introduction to uncertainty quantification ISBN: 3319794787 ISBN-13(EAN): 9783319794785 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This text provides a framework in which the main objectives of the field of uncertainty quantification (UQ) are defined and an overview of the range of mathematical methods by which they can be achieved.
Описание: This textbook teaches the essential background and skills for understanding and quantifying uncertainties in a computational simulation, and for predicting the behavior of a system under those uncertainties.
Описание: New Practices of Comparison, Quantification and Expertise in Education discusses contemporary trends and activities related to comparisons and quantifications. It aims to help scholars to conduct empirically based research on how comparisons and quantifications are instituted in practice at different levels in the educational system.
Автор: Miranda Olff; Guido Godaert; Holger Ursin Название: Quantification of Human Defence Mechanisms ISBN: 3540538216 ISBN-13(EAN): 9783540538219 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Provides a comprehensive review of questionnaire methods and laboratory methods for evaluating human defence mechanisms. The subject is treated in theoretical papers as well as papers regarding the state of the art, with particular emphasis on the consensus that exists within Europe.
Автор: Jadamba Название: Uncertainty Quantification In Varia ISBN: 1138626325 ISBN-13(EAN): 9781138626324 Издательство: Taylor&Francis Рейтинг: Цена: 16843.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The primary objective of this book is to present a comprehensive treatment of uncertainty quantification in variational inequalities and some of its generalizations emerging from various network, economic, and engineering models. Some of the developed techniques also apply to machine learning, neural networks, and related fields.
Автор: Bruno Название: The Social Sciences of Quantification ISBN: 3319439995 ISBN-13(EAN): 9783319439990 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This book details how quantification can serve both as evidence and as an instrument of government, whether when dealing with statistics on employment, occupational health and economic governance, or when developing public management or target-driven policies. In the process, it presents a thought-provoking homage to Alain Desrosi?res, who pioneered ways to study large numbers and the politics underlying them.
It opens with a summary of Desrosi?res's contributions to the field in which several generations of researchers detail how this statistician and historian profoundly influenced them. This tribute, based on personal testimonies, bears witness to the vitality of the school of thought and analytical framework Desrosi?res initiated. Next, a collection of essays explores the statistical argument in the neoliberal era, examining issues such as counting the homeless in Europe, measuring the performance of public services, and quantifying the effects of public action on the unemployed in France.
The third part details the uses of quantification. It reveals that although statistics are frequently used to the advantage of those in power, they can also play a vital role in challenging and resisting both the conventions underlying the measurements as well as the measurements themselves.
Featuring the work of economists, historians, political scientists, sociologists, and statisticians, this title provides readers with a thoughtful look at an influential figure in the history of statistics. It also shows how statistics are used to direct public policy, the degree of conflict that is possible in their production, and the disputes that can develop around their uses.
Автор: Souza De Cursi Eduardo Название: Uncertainty Quantification and Stochastic Modelling with Excel ISBN: 3030777561 ISBN-13(EAN): 9783030777562 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents techniques for determining uncertainties in numerical solutions with applications in the fields of business administration, civil engineering, and economics, using Excel as a computational tool.
Описание: This book offers a new look at well-established quantification theory for categorical data, referred to by such names as correspondence analysis, dual scaling, optimal scaling, and homogeneity analysis.
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