Social choice with infinite populations: construction of a rule and impossibility results

 We provide a simple construction of social choice rules for economies with infinite populations. The rules are continuous, Pareto and non-dictatorial; they are constructed as limits of individual preferences when the limit exists, and otherwise as adequate generalizations. This contrasts with the impossibility results of Arrow (1951) and Chichilnisky (1980), which are valid on economies with finitely many individuals. Our social choice rules are, however, limits of dictatorial rules. This paper was written in 1979. Received: 30 October 1994/Accepted: 22 April 1996     

Modifying a central composite design to model the process mean and variance when there are hard-to-change factors

Summary.  An important question within industrial statistics is how to find operating conditions that achieve some goal for the mean of a characteristic of interest while simultaneously minimizing the characteristic's process variance. Often, people refer to this kind of situation as the robust parameter design problem. The robust parameter design literature is rich with ways to create separate models for the mean and variance from this type of experiment. Many times time and/or cost constraints force certain factors of interest to be much more difficult to change than others. An appropriate approach to such an experiment restricts the randomization, which leads to a split-plot structure. The paper modifies the central composite design to allow the estimation of separate models for the characteristic's mean and variances under a split-plot structure. The paper goes on to discuss an appropriate analysis of the experimental results. It illustrates the methodology with an industrial experiment involving a chemical vapour deposition process for the manufacture of silicon wafers. The methodology was used to achieve a silicon layer thickness value of 485 Å while minimizing the process variation.     

The Role of Pre-collegiate Partnership Programs in Environments Ambivalent about Affirmative Action: Reflections and Outcomes from an Early Implementation

Preparing underrepresented students for college success though pre-collegiate partnership programs is one alternative to affirmative action programs. This article describes the Multicultural Excellence Program (MEP), a partnership program between an urban school district and 22 four-year higher education institutions. MEP, begun in 1987, targets 7th–12th-grade students from groups historically underrepresented in higher education. It helps them plan how to prepare themselves for continuing on to a four-year college. Analyses evaluating program effectiveness examined outcomes of over 4,000 secondary students and 243 college students. Despite substantial turnover, particularly at transition points, MEP has been very successful in enrolling its high school graduates immediately in four-year colleges. Although many MEP students have thrived in college, a smaller proportion has struggled.     

生态人类学与西藏草地研究

以往,关于西藏草地问题的研究中,缺乏一定的社会科学的研究方法和研究角度,使这一领域的研究存在某些缺憾.本文尝试应用生态人类学的一些基本理论和思考方式切入这一研究领域,从而使西藏的草地研究为西藏草业的发展模式提供更为广阔的视野和客观的建议.     

Pressures towards and against formalization: Regulation and informal employment in Mozambique

The informal economy accounts for the bulk of employment in many emerging economies. Regulation theory suggests that all economic activity is characterized by a complex combination of formal and informal regulation. Looking at the case of Mozambique, this article explores the pressures towards and against formalization, and the forms regulation can take, drawing on qualitative research based on in‐depth elite interviews and observation. The findings highlight how the State's role in promoting formalization of the informal economy is ambivalent; its approach incorporates both “progressive” elements, which focus on the modernization of regulations and institutions, and “conservative” elements, which inhibit this process of change.     

The Impact of Costliness,Competitive Importance,and Modularity of Investments on Outsourcing

This study is motivated by examples of outsourcing that are not readily explained by widely established economic theories. We extend recent literature that develops the idea that outsourcing can help firms avoid overinvestment by specifying more precisely the conditions under which this thesis is likely to apply. Our extension is realized through a two‐period game theoretic model in which the outsourcing and in‐house investments are driven by (1) the cost required to develop a product or process module, (2) competitive relevance, defined as the module's share in the production cost or the module's importance to the customer, and (3) modularity, defined as the extent to which generic investments in the module can approach firm‐specific investments in terms of the overall product/process performance. The analysis generates predictions about what types of insourcing, outsourcing, and non‐sourcing behaviors are likely to emerge in different parts of the parameter space. Outsourcing to a more concentrated industry upstream emerges at equilibrium when modularity is high, relevance low to medium, and development cost high enough that none or only a subset of focal firms wants to invest. While firms are forced to insource and overinvest due to a prisoner's dilemma when the development cost is sufficiently high relative to the module's relevance, we do not find outsourcing equilibria that solve this problem in a two‐period game with no commitment. This result implies that some form of tacit coordination in a multi‐period game may be necessary. We conclude the study with a discussion of empirical implications.     

Forecasting murder within a population of probationers and parolees: a high stakes application of statistical learning

Summary.  Forecasts of future dangerousness are often used to inform the sentencing decisions of convicted offenders. For individuals who are sentenced to probation or paroled to community supervision, such forecasts affect the conditions under which they are to be supervised. The statistical criterion for these forecasts is commonly called recidivism, which is defined as a charge or conviction for any new offence, no matter how minor. Only rarely do such forecasts make distinctions on the basis of the seriousness of offences. Yet seriousness may be central to public concerns, and judges are increasingly required by law and sentencing guidelines to make assessments of seriousness. At the very least, information about seriousness is essential for allocating scarce resources for community supervision of convicted offenders. The paper focuses only on murderous conduct by individuals on probation or parole. Using data on a population of over 60000 cases from Philadelphia's Adult Probation and Parole Department, we forecast whether each offender will be charged with a homicide or attempted homicide within 2 years of beginning community supervision. We use a statistical learning approach that makes no assumptions about how predictors are related to the outcome. We also build in the costs of false negative and false positive charges and use half of the data to build the forecasting model, and the other half of the data to evaluate the quality of the forecasts. Forecasts that are based on this approach offer the possibility of concentrating rehabilitation, treatment and surveillance resources on a small subset of convicted offenders who may be in greatest need, and who pose the greatest risk to society.     

A new model and class of designs for mixture experiments with process variables

Experiments that involve the blending of several components are known as mixture experiments. In some mixture experiments, the response depends not only on the proportion of the mixture components, but also on the processing conditions, A new combined model is proposed which is based on Taylor series approximation and is intended to be a compromise between standard mixture models and standard response surface models. Cost and/or time constraints often limit the size of industrial experiments. With this in mind, we present a new class of designs that will accommodate the fitting of the new combined model.