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Coalmining was a notoriously dangerous industry and many of its workers experienced injury and disease. However, the experiences of the many disabled people within Britain's most dangerous industry have gone largely unrecognised by historians. This book examines the British coal industry through the lens of disability, using an interdisciplinary approach to examine the lives of disabled miners and their families.The book considers the coal industry at a time when it was one of Britain's most important industries, and follows it through a period of growth up to the First World War, through strikes, depression and wartime, and into an era of decline. During this time, the statutory provision for disabled people changed considerably, most notably with the first programme of state compensation for workplace injury. And yet disabled people remained a constant presence in the industry as many disabled miners continued their jobs or took up 'light work'. The burgeoning coalfields literature used images of disability on a frequent basis and disabled characters were used to represent the human toll of the industry.A diverse range of sources are used to examine the economic, social, political and cultural impact of disability in the coal industry, looking beyond formal coal company and union records to include autobiographies, novels and oral testimony. It argues that, far from being excluded entirely from British industry, disability and disabled people were central to its development. The book will appeal to students and academics interested in disability history, disability studies, social and cultural history, and representations of disability in literature.

"This book provides a forum for the cybernetics field in critical emerging technologies, including research into design, engineering, and technological aspects of cyborg creation and existence alongside humankind for issues in their potential acceptance, participation, policy, governance, and requisite socialization between individualization and corporate, global, networked, mechanized human and humanized machine experiences"--

Abstract
In this paper, I discuss some of the wider uses of adaptive and network sampling designs. Three uses of sampling designs are to select units from a population to make inferences about population values, to select units to use in an experiment, and to distribute interventions to benefit a population. The most useful approaches for inference from adaptively selected samples are design-based methods and Bayesian methods. Adaptive link-tracing network sampling methods are important for sampling populations that are otherwise hard to reach. Sampling in changing populations involves temporal network or spatial sampling design processes with units selected both into and out of the sample over time. Averaging or smoothing fast-moving versions of these designs provides simple estimates of network-related characteristics. The effectiveness of intervention programs to benefit populations depends a great deal on the sampling and assignment designs used in spreading the intervention.

Few industries are buffeted from as many strong forces as healthcare. The industry is highly regulated, thus dramatically increasing costs and sometimes even interfering with the ability to deliver healthcare. New drugs, treatments, and medical technologies are so common that keeping track of them can be overwhelming, and incorporating them into patient care or administration can be costly and complicated. On the social side, different groups have different opinions on any given topic and often the right thing to do depends on your point of view. Third party payers add another level of complexity, and competition adds yet another layer of difficulty as organizations seek to grow patient volume by positioning themselves as distinguished in terms of cost, quality, accessibility, and quality of patient experience.

"The Third Edition retains the general organization of the prior two editions, but it incorporates new material throughout the text. The book is organized into six parts: Part I covers basic sampling from simple random sampling to unequal probability sampling; Part II treats the use of auxiliary data with ratio and regression estimation and looks at the ideas of sufficient data, model, and design in practical sampling; Part III covers major useful designs such as stratified, cluster and systematic, multistage, and double and network sampling; Part IV examines detectability methods for elusive populations, and basic problems in detectability, visibility, and catchability are discussed; Part V concerns spatial sampling with the prediction methods of geostatistics, considerations of efficient spatial designs, and comparisons of different observational methods including plot shapes and detection aspects; and Part VI introduces adaptive sampling designs in which the sampling procedure depends on what is observed during the survey. For this new edition, the author has focused on thoroughly updating the book with a special emphasis on the first 14 chapters since these topics are invariably covered in basic sampling courses. The author has also implemented new approaches to explain the various techniques in the book, and as a result, new examples and explanations have been added throughout. In an effort to improve the presentation and visualization of the book, new figures as well as replacement figures for previously existing figures have been added. This book has continuously stood out from other sampling texts since the figures evoke the idea of each sampling design. The new figures will help readers to better visualize and understand the underlying concepts such as the different sampling strategies"--

The ability to collect and disseminate individually identifiable microdata is becoming increasingly important in a number of arenas. This is especially true in health care and national security, where this data is considered vital for a number of public health and safety initiatives. In some cases legislation has been used to establish some standards for limiting the collection of and access to such data. However, all such legislative efforts contain many provisions that allow for access to individually identifiable microdata without the consent of the data subject. Furthermore, although legislation is useful in that penalties are levied for violating the law, these penalties occur after an individual's privacy has been compromised. Such deterrent measures can only serve as disincentives and offer no true protection. This paper considers security issues involved in releasing microdata, including individual identifiers. The threats to the confidentiality of the data subjects come from the users possessing statistical information that relates the revealed microdata to suppressed confidential information. The general strategy is to recode the initial data, in which some subjects are "safe" and some are at risk, into a data set in which no subjects are at risk. We develop a technique that enables the release of individually identifiable microdata in a manner that maximizes the utility of the released data while providing preventive protection of confidential data. Extensive computational results show that the proposed method is practical and viable and that useful data can be released even when the level of risk in the data is high.

The classification of a financial instrument as "debt" or as "equity" is crucial in applying a wide range of income tax provisions. "Interest" expenses incurred on "debt," for example, are deductible in computing a firm's taxable income, whereas "dividends" paid on the firm's outstanding "equity" are not. "Interest" paid by a U.S. corporation to a foreign creditor is generally not subject to U.S. withholding taxes, whereas "dividends" paid on stock held by a foreign shareholder are typically subject to U.S. withholding taxes that range from 5% to 30% of the gross amount of the dividend paid. And the list goes on . . . . Not surprisingly, these disparities in tax treatment have inspired a plethora of schemes, many of them successful, designed to disguise equity investments as "debt." The urge to do so is perhaps nowhere more intense than in situations where the "debt" of a U.S. corporation is held by a foreign sister corporation located in a tax haven country. Interest paid or accrued on debt would be deductible in computing the U.S. corporation's U.S. taxable income, and would thereby permanently reduce the debtor's U.S. tax liability. The interest income earned by the foreign creditor would be exempt from both U.S. withholding taxes and income taxes in the foreign tax haven country. This interdisciplinary case was developed from the facts and circumstances before the U.S. Tax Court in litigation that resulted from the government's assertion that $975 million in "loans" made by a wholly owned Dutch subsidiary of Laidlaw Transit, Ltd. to several of Laidlaw's U.S. subsidiaries were in substance "equity." As in most debt-versus-equity cases, the stakes were high: Laidlaw's U.S. subsidiaries had deducted over $133 million of intercompany "payments" made to their Dutch sister corporation as "interest expense" and the IRS was suing to recover $52 million in back taxes (plus interest and penalties). This case integrates three disciplines – tax accounting, financial accounting, and finance -- in an easy-to-comprehend, yet rich setting appropriate for general management, finance, and accounting audiences. It invites students to thoroughly explore the substance-over-form doctrine as it applies to the debt-versus-equity issue, together with many of the tax, financial, accounting, and economic ramifications that flow from an instrument's classification. It also provides students with an opportunity to identify the ethical issues that attend the formulation and implementation of many tax minimization strategies and to identify factors that separate legal "tax avoidance" from criminal "tax evasion."