Product partition latent variable model for multiple change-point detection in multivariate data

The product partition model (PPM) is a well-established efficient statistical method for detecting multiple change points in time-evolving univariate data. In this article, we refine the PPM for the purpose of detecting multiple change points in correlated multivariate time-evolving data. Our model detects distributional changes in both the mean and covariance structures of multivariate Gaussian data by exploiting a smaller dimensional representation of correlated multiple time series. The utility of the proposed method is demonstrated through experiments on simulated and real datasets.     

The reality of net capital gains and annual profit on NZ primary producing businesses: data from a recent survey of all farm types

ABSTRACT

Annual net cash returns and net capital gains provide farmers with their actual and potential monetary rewards, respectively. This article reports on a national farm survey showing both actual and potential returns, on average, are not as high as might be imagined. This is supported by the findings of earlier studies and has implications for rural societies and their associated economies. Data on income, expenses and profit is presented as is data on farm value changes over the life of each farm. The information is adjusted for inflation to provide ‘real’ data. The profit and net capital gain figures are divided into groupings based on a range of criteria such as total farm capital, and labour compliment as a reflection of farm size. Statistically significant differences occur for some groupings such as farm type and farm size.     

The Ethical Challenges of Socially Responsible Science

Social responsibility is an essential part of the responsible conduct of research that presents difficult ethical questions for scientists. Recognizing one’s social responsibilities as a scientist is an important first step toward exercising social responsibility, but it is only the beginning, since scientists may confront difficult value questions when deciding how to act responsibly. Ethical dilemmas related to socially responsible science fall into at least three basic categories: 1) dilemmas related to problem selection, 2) dilemmas related to publication and data sharing, and 3) dilemmas related to engaging society. In responding to these dilemmas, scientists must decide how to balance their social responsibilities against other professional commitments and how to avoid compromising their objectivity. In this article, we will examine the philosophical and ethical basis of social responsibility in science, discuss some of the ethical dilemmas related to exercising social responsibility, and make five recommendations to help scientists deal with these issues.     

Policy Legitimacy,Rhetorical Politics,and the Evaluation of City‐Street Video Surveillance Monitoring Programs in Canada

This article examines the evaluation and legitimization of city‐street video surveillance in Ontario, Canada. We demonstrate how monitoring programs are promoted, designed, and justified based on rhetorical claims about their efficacy. Although program evaluation data do not commonly corroborate or support program objectives, we show how the rhetorical politics of video surveillance evaluation research finds legitimacy by adhering to the Ontario privacy commissioner's best practices guidelines—guidelines that are formulated to minimize rhetoric in system design. The findings raise questions about how city‐street video surveillance remains a viable policy option given the lack of evidence pertaining to its usefulness.