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The Oxford Handbook of Well-Being and Public Policy by Matthew D. Adler,Marc Fleurbaey Pdf
What are the methodologies for assessing and improving governmental policy in light of well-being? The Oxford Handbook of Well-Being and Public Policy provides a comprehensive, interdisciplinary treatment of this topic. The contributors draw from welfare economics, moral philosophy, and psychology and are leading scholars in these fields. The Handbook includes thirty chapters divided into four Parts. Part I covers the full range of methodologies for evaluating governmental policy and assessing societal condition-including both the leading approaches in current use by policymakers and academics (such as GDP, cost-benefit analysis, cost-effectiveness analysis, inequality and poverty metrics, and the concept of the "social welfare function"), and emerging techniques. Part II focuses on the nature of well-being. What, most fundamentally, determines whether an individual life is better or worse for the person living it? Her happiness? Her preference-satisfaction? Her attainment of various "objective goods"? Part III addresses the measurement of well-being and the thorny topic of interpersonal comparisons. How can we construct a meaningful scale of individual welfare, which allows for comparisons of well-being levels and differences, both within one individual's life, and across lives? Finally, Part IV reviews the major challenges to designing governmental policy around individual well-being.
This collection of six papers provides a valuable source of material on the real-world problem of allocating objects among competing claimants. The examples given show how mathematics, particularly the axiomatic method, can be applied to give insight into complex social problems. Originally presented as an AMS Short Course, these papers could serve as a suitable text for courses touching on game theory, decision sciences, economics, or quantitative political science. Most of the material is accessible to the mathematically mature undergraduate with a background in advanced calculus and algebra. Each article surveys the recent literature and includes statements and sketches of proofs, as well as unsolved problems which should excite student curiosity. The articles analyze the question of fair allocation via six examples: the apportionment of political representation, the measurement of income inequality, the allocation of joint costs, the levying of taxes, the design of voting laws, and the framing of auction procedures. In each of these examples fairness has a somewhat different significance, but common axiomatic threads reveal broad underlying principles. Each of the topics is concerned with norms of comparative equity for evaluating allocations or with standards of procedures for effecting them; it is this focus on normative properties which suggests that a mathematical analysis is appropriate. Though game theory provides a useful tool in many of these allocation problems, the emphasis here is on standards rather than strategy and equity rather than rationality, an approach which more accurately mirrors real-world social problems.
United States. Congress. House. Committee on the Judiciary. Subcommittee on Administrative Law and Governmental Relations
Author : United States. Congress. House. Committee on the Judiciary. Subcommittee on Administrative Law and Governmental Relations Publisher : Unknown Page : 124 pages File Size : 52,8 Mb Release : 1986 Category : Government liability ISBN : UCR:31210017817832
Fair Allocation of Government Fault Act by United States. Congress. House. Committee on the Judiciary. Subcommittee on Administrative Law and Governmental Relations Pdf
Handbook of Computational Social Choice by Felix Brandt,Vincent Conitzer,Ulle Endriss,Jérôme Lang,Ariel D. Procaccia Pdf
A comprehensive survey of computational aspects of collective decisions for graduate students, researchers, and professionals in computer science and economics.
Shows how mathematics, particularly the axiomatic method, can be applied to give insight into complex social problems. This collection provides material on the real-world problem of allocating objects among competing claimants. Each article surveys the literature and includes statements and sketches of proofs, as well as unsolved problems.
Marion Danis,Samia A. Hurst,Leonard M. Fleck,Reidun Førde,Anne Slowther
Author : Marion Danis,Samia A. Hurst,Leonard M. Fleck,Reidun Førde,Anne Slowther Publisher : Oxford University Press, USA Page : 481 pages File Size : 48,6 Mb Release : 2014-10-09 Category : Medical ISBN : 9780199989447
Fair Resource Allocation and Rationing at the Bedside by Marion Danis,Samia A. Hurst,Leonard M. Fleck,Reidun Førde,Anne Slowther Pdf
Health systems need to set priorities fairly. In one way or another, part of this important task will fall to physicians. How do they make judgments about resource stewardship, and how should they do so? How can they make such decisions in a manner that is compatible with their clinical duties to patients? In this book, philosophers, bioethicists, physicians, lawyers and health policy experts make the case that priority setting and rationing contribute significantly to the possibility of affordable and fair healthcare and that clinicians play an indispensable role in that process. The book depicts the results of a survey of European physicians about their experiences with rationing and other cost containment strategies, and their perception of scarcity and fairness in their health care systems. Responding to and complementing these findings, commentators discuss why resource allocation and bedside rationing is necessary and justifiable. The book explores how bedside rationing relates to clinical judgments about medical necessity and medical indications, marginal benefits, weak evidence based medicine, off-label use. The book highlights how comparative studies of health care systems can advance more effective and fair bedside rationing through learning from one another. From a practical standpoint, the book offers a number of strategies for health care systems and clinicians to work in tandem to allocate and ration resources as fairly as possible: how to foster more attention to fairness when rationing at the bedside, how to avoid exacerbating health disparities when allocating resources, how to teach about bedside rationing to students, how to discuss rationing more explicitly in the public arena and in the doctor's office.
Resource Allocation and Performance Optimization in Communication Networks and the Internet by Liansheng Tan Pdf
This book provides a comprehensive introduction to the underlying theory, design techniques and analytical results of wireless communication networks, focusing on the core principles of wireless network design. It elaborates the network utility maximization (NUM) theory with applications in resource allocation of wireless networks, with a central aim of design and the QoS guarantee. It presents and discusses state-of-the-art developments in resource allocation and performance optimization in wireless communication networks. It provides an overview of the general background including the basic wireless communication networks and the relevant protocols, architectures, methods and algorithms.
An Introduction to Allocation Rules by Jens Leth Hougaard Pdf
This book provides an overview of existing methods for allocating costs and benefits. It will help readers evaluate the pros and cons of various methods involved in terms of factors such as fairness, consistency, stability, monotonicity and manipulability.
Algorithmic aspects of resource allocation and multiwinner voting: theory and experiments by Kaczmarczyk, Andrzej Pdf
This thesis is concerned with investigating elements of computational social choice in the light of real-world applications. We contribute to a better understanding of the areas of fair allocation and multiwinner voting. For both areas, inspired by real-world scenarios, we propose several new notions and extensions of existing models. Then, we analyze the complexity of answering the computational questions raised by the introduced concepts. To this end, we look through the lens of parameterized complexity. We identify different parameters which describe natural features specific to the computational problems we investigate. Exploiting the parameters, we successfully develop efficient algorithms for spe- cific cases of the studied problems. We complement our analysis by showing which parameters presumably cannot be utilized for seeking efficient algorithms. Thereby, we provide comprehensive pictures of the computational complexity of the studied problems. Specifically, we concentrate on four topics that we present below, grouped by our two areas of interest. For all but one topic, we present experimental studies based on implementations of newly developed algorithms. We first focus on fair allocation of indivisible resources. In this setting, we consider a collection of indivisible resources and a group of agents. Each agent reports its utility evaluation of every resource and the task is to “fairly” allocate the resources such that each resource is allocated to at most one agent. We concentrate on the two following issues regarding this scenario. The social context in fair allocation of indivisible resources. In many fair allocation settings, it is unlikely that every agent knows all other agents. For example, consider a scenario where the agents represent employees of a large corporation. It is highly unlikely that every employee knows every other employee. Motivated by such settings, we come up with a new model of graph envy-freeness by adapting the classical envy-freeness notion to account for social relations of agents modeled as social networks. We show that if the given social network of agents is simple (for example, if it is a directed acyclic graph), then indeed we can sometimes find fair allocations efficiently. However, we contrast tractability results with showing NP-hardness for several cases, including those in which the given social network has a constant degree. Fair allocations among few agents with bounded rationality. Bounded rationality is the idea that humans, due to cognitive limitations, tend to simplify problems that they face. One of its emanations is that human agents usually tend to report simple utilities over the resources that they want to allocate; for example, agents may categorize the available resources only into two groups of desirable and undesirable ones. Applying techniques for solving integer linear programs, we show that exploiting bounded rationality leads to efficient algorithms for finding envy-free and Pareto-efficient allocations, assuming a small number of agents. Further, we demonstrate that our result actually forms a framework that can be applied to a number of different fairness concepts like envy-freeness up to one good or envy-freeness up to any good. This way, we obtain efficient algorithms for a number of fair allocation problems (assuming few agents with bounded rationality). We also empirically show that our technique is applicable in practice. Further, we study multiwinner voting, where we are given a collection of voters and their preferences over a set of candidates. The outcome of a multiwinner voting rule is a group (or a set of groups in case of ties) of candidates that reflect the voters’ preferences best according to some objective. In this context, we investigate the following themes. The robustness of election outcomes. We study how robust outcomes of multiwinner elections are against possible mistakes made by voters. Assuming that each voter casts a ballot in a form of a ranking of candidates, we represent a mistake by a swap of adjacent candidates in a ballot. We find that for rules such as SNTV, k-Approval, and k-Borda, it is computationally easy to find the minimum number of swaps resulting in a change of an outcome. This task is, however, NP-hard for STV and the Chamberlin-Courant rule. We conclude our study of robustness with experimentally studying the average number of random swaps leading to a change of an outcome for several rules. Strategic voting in multiwinner elections. We ask whether a given group of cooperating voters can manipulate an election outcome in a favorable way. We focus on the k-Approval voting rule and we show that the computational complexity of answering the posed question has a rich structure. We spot several cases for which our problem is polynomial-time solvable. However, we also identify NP-hard cases. For several of them, we show how to circumvent the hardness by fixed-parameter tractability. We also present experimental studies indicating that our algorithms are applicable in practice. Diese Arbeit befasst sich mit der Untersuchung von Themen des Forschungsgebiets Computational Social Choice im Lichte realer Anwendungen. Dabei trägt sie zu einem besseren Verständnis der Bereiche der fairen Zuordnung und der Mehrgewinnerwahlen bei. Für beide Konzepte schlagen wir – inspiriert von realen Anwendungen – verschiedene neue Begriffe und Erweiterungen bestehender Modelle vor. Anschließend analysieren wir die Komplexität der Beantwortung von Berechnungsfragen, die durch die eingeführten Konzepte aufgeworfen werden. Dabei fokussieren wir uns auf die parametrisierte Komplexität. Hierzu identifizieren wir verschiedene Parameter, welche natürliche Merkmale der von uns untersuchten Berechnungsprobleme beschreiben. Durch die Nutzung dieser Parameter entwickeln wir erfolgreich effiziente Algorithmen für Spezialfälle der untersuchten Probleme. Wir ergänzen unsere Analyse indem wir zeigen, welche Parameter vermutlich nicht verwendet werden können um effiziente Algorithmen zu finden. Dabei zeichnen wir ein umfassendes Bild der Berechnungskomplexität der untersuchten Probleme. Insbesondere konzentrieren wir uns auf vier Themen, die wir, gruppiert nach unseren beiden Schwerpunkten, unten vorstellen. Für alle Themen bis auf eines präsentieren wir Experimente, die auf Implementierungen der von uns neu entwickelten Algorithmen basieren. Wir konzentrieren uns zunächst auf die faire Zuordnung unteilbarer Ressourcen. Hier betrachten wir eine Menge unteilbarer Ressourcen und eine Gruppe von Agenten. Jeder Agent gibt eine Bewertung des Nutzens jeder Ressource ab und die Aufgabe besteht darin, eine "faire" Zuordnung der Ressourcen zu finden, wobei jede Ressource höchstens einem Agenten zugeordnet werden kann. Innerhalb dieses Bereiches konzentrieren wir uns auf die beiden folgenden Problemstellungen. Der soziale Kontext bei der fairen Zuordnung unteilbarer Ressourcen. In vielen Szenarien, in denen Ressourcen zugeordnet werden sollen, ist es unwahrscheinlich, dass jeder Agent alle anderen kennt. Vorstellbar ist beispielsweise ein Szenario, in dem die Agenten Mitarbeiter eines großen Unternehmens repräsentieren. Es ist höchst unwahrscheinlich, dass jeder Mitarbeiter jeden anderen Mitarbeiter kennt. Motiviert durch solche Szenarien entwickeln wir ein neues Modell der graph-basierten Neidfreiheit. Wir erweitern den klassischen Neidfreiheitsbegriff um die sozialen Beziehungen von Agenten, die durch soziale Netzwerke modelliert werden. Einerseits zeigen wir, dass wenn das soziale Netzwerk der Agenten einfach ist (zum Beispiel, wenn es sich um einen gerichteten azyklischen Graph handelt), in manchen Fällen faire Zuordnungen effizient gefunden werden können. Andererseits stellen wir diesen algorithmisch positiven Ergebnissen mehrere NP-schweren Fällen entgegen. Ein Beispiel für einen solchen Fall sind soziale Netzwerke mit einem konstanten Knotengrad. Faire Zuteilung an wenige Agenten mit begrenzter Rationalität. Begrenzte Rationalität beschreibt die Idee, dass Menschen aufgrund kognitiver Grenzen dazu neigen, Probleme, mit denen sie konfrontiert werden, zu vereinfachen. Eine mögliche Folge dieser Grenzen ist, dass menschliche Agenten in der Regel einfache Bewertungen der gewünschten Ressourcen abgeben; beispielsweise könnten Agenten die verfügbaren Ressourcen nur in zwei Gruppen, erwünschte und unerwünschte Ressourcen, kategorisieren. Durch Anwendung von Techniken zum Lösen von Ganzzahligen Linearen Programmen zeigen wir, dass unter der Annahme einer kleinen Anzahl von Agenten die Ausnutzung begrenzter Rationalität dabei hilft, effiziente Algorithmen zum Finden neidfreier und Pareto-effizienter Zuweisungen zu entwickeln. Weiterhin zeigen wir, dass unser Ergebnis ein allgemeines Verfahren liefert, welches auf eine Reihe verschiedener Fairnesskonzepte angewendet werden kann, wie zum Beispiel Neidfreiheit bis auf ein Gut oder Neidfreiheit bis auf irgendein Gut. Auf diese Weise gewinnen wir effiziente Algorithmen für eine Reihe fairer Zuordnungsprobleme (wenige Agenten mit begrenzter Rationalität vorausgesetzt). Darüber hinaus zeigen wir empirisch, dass unsere Technik in der Praxis anwendbar ist. Weiterhin untersuchen wir Mehrgewinnerwahlen, bei denen uns eine Menge von Wählern sowie ihre Präferenzen über eine Reihe von Kandidaten gegeben sind. Das Ergebnis eines Mehrgewinnerwahlverfahrens ist eine Gruppe (oder eine Menge von Gruppen im Falle eines Unentschiedens) von Kandidaten, welche die Präferenzen der Wähler am besten einem bestimmten Ziel folgend widerspiegeln. In diesem Kontext untersuchen wir die folgenden Themen. Die Robustheit von Wahlergebnissen. Wir untersuchen, wie robust die Ergebnisse von Mehrgewinnerwahlen gegenüber möglicher Fehler der Wähler sind. Unter der Annahme, dass jeder Wähler eine Stimme in Form einer Rangliste von Kandidaten abgibt, modellieren wir einen Fehler als einen Tausch benachbarter Kandidaten in der Rangliste. Wir zeigen, dass für Wahlregeln wie SNTV, k-Approval und k-Borda die minimale Anzahl an Vertauschungen, welche zu einer Ergebnisänderung führt, einfach zu berechnen ist. Für STV und die Chamberlin-Courant-Regel ist diese Aufgabe allerdings NP-schwer. Wir schließen unsere Untersuchung der Robustheit unterschiedlicher Wahlregeln ab mit einer experimentellen Evaluierung der durchschnittlichen Anzahl zufälliger Vertauschungen, die zu einer Änderung des Ergebnisses führen. Strategische Abstimmung bei Wahlen mit mehreren Gewinnern. Wir fragen, ob eine bestimmte Gruppe von kooperierenden Wählern ein Wahlergebnis zu ihren Gunsten manipulieren kann. Dabei konzentrieren wir uns auf die k-Approval-Wahlregel. Wir zeigen, dass die Berechnungskomplexität der besagten Manipulation eine reiche Struktur besitzt. Auf der einen Seite identifizieren wir mehrere Fälle in denen das Problem in Polynomzeit lösbar ist. Auf der anderen Seite identifizieren wir jedoch auch NP-schwere Fälle. Für einige von ihnen zeigen wir, wie die Berechnungsschwere durch parametrisierte Algorithmen umgangen werden kann. Wir präsentieren zudem experimentelle Untersuchungen, welche darauf hindeuten, dass unsere Algorithmen in der Praxis anwendbar sind.
A unique book that specifically addresses equitable resource allocation problems with applications in communication networks, manufacturing, emergency services, and more Resource allocation problems focus on assigning limited resources in an economically beneficial way among competing activities. Solutions to such problems affect people and everyday activities with significant impact on the private and public sectors and on society at large. Using diverse application areas as examples, Equitable Resource Allocation: Models, Algorithms, and Applications provides readers with great insight into a topic that is not widely known in the field. Starting with an overview of the topics covered, the book presents a large variety of resource allocation models with special mathematical structures and provides elegant, efficient algorithms that compute optimal solutions to these models. Authored by one of the leading researchers in the field, Equitable Resource Allocation: Is the only book that provides a comprehensive exposition of equitable resource allocation problems Presents a collection of resource allocation models with applications in communication networks, transportation, content distribution, manufacturing, emergency services, and more Exhibits practical algorithms for solving a variety of resource allocation models Uses real-world applications and examples to explain important concepts Includes end-of-chapter exercises Bringing together much of the equitable resource allocation research from the past thirty years, this book is a valuable reference for anyone interested in solving diverse optimization problems.
On the Fair and Efficient Allocation of Indivisible Commodities by Richard Engelbrecht-Wiggans Pdf
Auctions and fair division problems are situations in which commodities are to be allocated fairly and efficiently. While a variety of schemes exist for fairly allocating finely divisible homogeneous commodities, most schemes are not applicable to the problem of allocating indivisible items. This paper considers the problem of fairly allocation sets of indivisible objects. 'Dollars, ' a finely divisible, homogeneous, transferrable commodity, are used to evaluate individuals preferences and to transfer value among individuals. This introduction of dollars has several implications; the main result is that fair allocation problems may be viewed as two smaller problems. First auction the goods among the individuals and then divide the resulting revenue according to the chosen definition of fairness. Several existing fair allocation schemes are reviewed; examples illustrate some difficulties associated with their use. Kuhn's definitions of 'fairness' are presented and two extensions are considered for the case where individuals have different shares in the collection of goods.
Rationing and Resource Allocation in Healthcare by Ezekiel Emanuel,Harald Schmidt,Andrew Steinmetz Pdf
Budgets of governments and private insurances are limited. Not all drugs and services that appear beneficial to patients or physicians can be covered. Is there a core set of benefits that everyone should be entitled to? If so, how should this set be determined? Are fair decisions just impossible, if we know from the outset than not all needs can be met? While early work in bioethics has focused on clinical issues and a narrow set of principles, in recent years there has been a marked shift towards addressing broader population-level issues, requiring consideration of more demanding theories in philosophy, political science, and economics. At the heart of bioethics' new orientation is the goal of clarity on a complex set of questions in rationing and resource allocation. Rationing and Resource Allocation in Healthcare: Essential Readings provides key excerpts from seminal and pertinent texts and case studies about these topics, contextualized by original introductions. The volume is divided into three broad sections: Conceptual Distinctions and Ethical Theory; Rationing; and Resource Allocation. Containing the most important and classic articles surrounding the theoretical and practical issues related to rationing and how to allocate scare medical resources, this collection aims to assist and inform those who wish to be a part of bioethics' 21st century shift including practitioners and policy-makers, and students and scholars in the health sciences, philosophy, law, and medical ethics.
In theory and practice, the notion of fairness is far from simple. The principle is often elusive and subject to confusion, even in institutions of law, usage, and custom. In Fairness, Nicholas Rescher aims to liberate this concept from misunderstandings by showing how its definitive characteristics prevent it from being absorbed by such related conceptions as paternalistic benevolence, radical egalitarianism, and social harmonization. Rescher demonstrates that equality before the state is an instrument of justice, not of social utility or public welfare, and argues that the notion of fairness stops well short of a literal egalitarianism. Rescher disposes of the confusions arising from economists' penchant to focus on individual preferences, from decision theorists' concern for averting envy, and from political theorists' sympathy for egalitarianism. In their place he shows how the idea of distributive equity forms the core of the concept of fairness in matters of distributive justice. The coordination of shares with valid claims is the crux of the concept of fairness. In Rescher's view, this means that the pursuit of fairness requires objective rather than subjective evaluation of the goods being shared. This is something quite different from subjective equity based on the personal evaluation of goods by those laying claim to them. Insofar as subjective equity is a concern, the appropriate procedure for its realization is a process of maximum value distribution. Further, Rescher demonstrates that in matters of distributive justice, the distinction between new ownership and preexisting ownership is pivotal and calls for proceeding on very different principles depending on the case. How one should proceed depends on context, and what is adjudged fair is pragmatic, in that there are different requirements for effectiveness in achieving the aims and purposes of the sort of distribution that is intended. Rescher concludes that fairness is a fundamentally ethical concept. Its distinctive modus operandi contrasts sharply with the aims of paternalism, preference-maximizing, or economic advantage. Fairness will be of interest to philosophers, economists, and political scientists.
Resource Allocation and Cross-layer Control in Wireless Networks by Leonidas Georgiadis,Michael J. Neely,Leandros Tassiulas Pdf
Information flow in a telecommunication network is accomplished through the interaction of mechanisms at various design layers with the end goal of supporting the information exchange needs of the applications. In wireless networks in particular, the different layers interact in a nontrivial manner in order to support information transfer. In this text we will present abstract models that capture the cross-layer interaction from the physical to transport layer in wireless network architectures including cellular, ad-hoc and sensor networks as well as hybrid wireless-wireline. The model allows for arbitrary network topologies as well as traffic forwarding modes, including datagrams and virtual circuits. Furthermore the time varying nature of a wireless network, due either to fading channels or to changing connectivity due to mobility, is adequately captured in our model to allow for state dependent network control policies. Quantitative performance measures that capture the quality of service requirements in these systems depending on the supported applications are discussed, including throughput maximization, energy consumption minimization, rate utility function maximization as well as general performance functionals. Cross-layer control algorithms with optimal or suboptimal performance with respect to the above measures are presented and analyzed. A detailed exposition of the related analysis and design techniques is provided.
National Academies of Sciences, Engineering, and Medicine,Health and Medicine Division,Board on Population Health and Public Health Practice,Board on Health Sciences Policy,Committee on Equitable Allocation of Vaccine for the Novel Coronavirus
Author : National Academies of Sciences, Engineering, and Medicine,Health and Medicine Division,Board on Population Health and Public Health Practice,Board on Health Sciences Policy,Committee on Equitable Allocation of Vaccine for the Novel Coronavirus Publisher : National Academies Press Page : 273 pages File Size : 51,7 Mb Release : 2020-11-30 Category : Medical ISBN : 9780309682244
Framework for Equitable Allocation of COVID-19 Vaccine by National Academies of Sciences, Engineering, and Medicine,Health and Medicine Division,Board on Population Health and Public Health Practice,Board on Health Sciences Policy,Committee on Equitable Allocation of Vaccine for the Novel Coronavirus Pdf
In response to the coronavirus disease 2019 (COVID-19) pandemic and the societal disruption it has brought, national governments and the international community have invested billions of dollars and immense amounts of human resources to develop a safe and effective vaccine in an unprecedented time frame. Vaccination against this novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), offers the possibility of significantly reducing severe morbidity and mortality and transmission when deployed alongside other public health strategies and improved therapies. Health equity is intertwined with the impact of COVID-19 and there are certain populations that are at increased risk of severe illness or death from COVID-19. In the United States and worldwide, the pandemic is having a disproportionate impact on people who are already disadvantaged by virtue of their race and ethnicity, age, health status, residence, occupation, socioeconomic condition, or other contributing factors. Framework for Equitable Allocation of COVID-19 Vaccine offers an overarching framework for vaccine allocation to assist policy makers in the domestic and global health communities. Built on widely accepted foundational principles and recognizing the distinctive characteristics of COVID-19, this report's recommendations address the commitments needed to implement equitable allocation policies for COVID-19 vaccine.
