Repetitions and reflections in Chronicle of a Death Foretold

Gabriel Garcia Marquez' Chronicle of ~ Death Foretold is a spiralling search for satisfying explanations of why events occur as they do. The first sentences prefigure the book's concern with the nature of memory and our perception of reality as describable in words. The narrator's declared intention of reassembling "the broken mirror of memory" allows the scrutiny of many kinds of reflections: dream images, recollections and retrospective insights, repetitions and contradictions. Memory is both individual and collective; separate voices are joined in a town history. The story of a small town murder becomes a chronicle of a universal need to understand the purpose of life. The fallibility of memory and of words is expanded into the impossibility of recovering the past objectively. We are able to perceive repeated patterns of behavior but the meaning of history eludes us. Interwoven throughout the cycling narrative fabric of repetitions, mockeries and fragmented insights are affirmations of the creativity and strength of human imagination, and Chronicle is ultimately a celebration of the power of words, despite the inadequacy of language to mirror objective reality

Of Cherries, Fudge, and Onions: Science and Its Courtroom Perversion

The thesis of this article is that the Supreme Court decision in Daubert v. Merrell Dow Pharmaceuticals, Inc.\u27s focus on the scientific method, however rigorously applied, invites certain classes of abuses. There are instances in which evidence can be made to look more scientific by a process that in fact and substance makes is utterly unscientific

Farrell G. Forsberg and Vicki A. Forsberg v. Burningham and Kimball, a Utah general partnership, Christensen and Kimball, a Utah general partnership as partner of Burningham and Kimball; Victor M. Kimball, individually and as general partner of Christensen and Kimball: Brief of Appellee

Brief of Appellee APPEAL FROM A FINAL JUDGMENT ISSUED BY THE THIRD JUDICIAL DISTRICT COURT FOR SALT LAKE COUNTY HONORABLE MICHAEL R. MURPH

The Adjudication of Minor Offenses in New York City

American criminal justice is founded on overcriminalization and discretion. Our legislatures have long criminalized much more conduct than can be effectively sanctioned. American police and prosecutors have been granted virtually unreviewable authority (discretion) to allocate investigative and prosecutorial resources. Minor crimes absorb the bulk of our ordinary, local enforcement efforts and there is an endless supply of minor crime, which may be pursued. With minor offenses, discretion is critical at all phases. This article argues that criminal courts, where ninety percent of all cases are heard, could benefit from reform. The author argues for the development of the record so that these offenses are adjudicated on the merits, rather than merely processed

Finding Associations and Computing Similarity via Biased Pair Sampling

This version is ***superseded*** by a full version that can be found at http://www.itu.dk/people/pagh/papers/mining-jour.pdf, which contains stronger theoretical results and fixes a mistake in the reporting of experiments. Abstract: Sampling-based methods have previously been proposed for the problem of finding interesting associations in data, even for low-support items. While these methods do not guarantee precise results, they can be vastly more efficient than approaches that rely on exact counting. However, for many similarity measures no such methods have been known. In this paper we show how a wide variety of measures can be supported by a simple biased sampling method. The method also extends to find high-confidence association rules. We demonstrate theoretically that our method is superior to exact methods when the threshold for "interesting similarity/confidence" is above the average pairwise similarity/confidence, and the average support is not too low. Our method is particularly good when transactions contain many items. We confirm in experiments on standard association mining benchmarks that this gives a significant speedup on real data sets (sometimes much larger than the theoretical guarantees). Reductions in computation time of over an order of magnitude, and significant savings in space, are observed.Comment: This is an extended version of a paper that appeared at the IEEE International Conference on Data Mining, 2009. The conference version is (c) 2009 IEE