Self-interest,distributive justice,and the income distribution: A theoretical fragment based on St. Anselm's postulate

The Mertonian starting idea for this paper is St. Anselm's idea that the will has two inclinations: an affection for what is to the person's own advantage and an affection for justice. We show that in decision-making situations, where the individual must choose a course of action from among a set of alternatives, the individual, subject to the two inclinations and thus guided by the twin considerations of own good and the common good as he/she forms the preference orderings for the alternatives, is in one of three states: (i) the state of Harmony, defined by perfect coincidence of the orderings induced by the two criteria; (ii) the state of Conflict, defined by perfect reversal of the orderings; and (iii) the state of Ambiguity, defined by ordering-pairs which are neither identical nor exactly opposite. The most general result states that if the number of alternatives is two, then the individual is in either Harmony or Conflict; if, however, the number of alternatives exceeds two, then Ambiguity is also a possible outcome. We then apply the framework to the case of choosing an income distribution, letting the own-good and common-good criteria dictate orderings based on personal outcomes (such as own income or own income rank) and social outcomes (such as mean income or income inequality), respectively, and examining the relation between the two orderings in five families of probability distributions. In the special case where own good is an increasing function of own income and the common good is a decreasing function of income inequality, our results show that each society has a group in Harmony (the poorest group) and one additional group, either in Conflict or in Ambiguity. Finally, we speculate about the behavioral and social implications of the three states and their configurations in the population.     

Identification and quantitation by 1H-NMR of metabolites in animal organs and tissues. An application of NMR spectroscopy in forensic science

1H-nuclear magnetic resonance (NMR) was applied to the study of metabolites in rat organs and tissues. From 1H-NMR spectra of D2O extracts of various organs and tissues, lactate, pyruvate, and some other substances were simultaneously identified and quantitated. On the basis of the results, the use of 1H-NMR for estimating post-mortem time was suggested.     

证明标准建构的虚幻与现实——从考察两大法系国家的证明标准历史出发

民事诉讼证明标准是衡量法官形成内心确信的尺度.本文通过对证明标准在两大法系国家的统一和分离历史的考察,探讨不同法系确立不同的民事诉讼证明标准的原因,进而在借鉴国外经验的基础上构建我国的民事诉讼证明标准.     

英美法系民事诉讼证明标准理论基础研究

英美法系民事诉讼证明标准有盖然性权衡的证明、灵活证明标准、预先的盖然性方法、主观确信的理论等。其理论基础在于预期效用性理论。即由民主的方式决定裁决的效用性计算并在同类案件同等适用,就可以克服灵活多样的证明标准所引起的不确定性。其适用就是公正合理的。     

论期待可能性理论在我国的借鉴

期待可能性理论因其立足人性,符合刑法谦抑原则等而具有相应的合理性。结合我国全面构建和谐社会、大力贯彻宽严相济刑事政策的新形势,借鉴其"合理内核"对我国当前的刑事司法具有特别意义和积极作用。     

混合STR分型分析方法研究进展

混合STR分型的解释及分析一直是国际上法医物证领域研究的热点和难点。随着DNA检验技术的发展,案件中检出的混合STR分型呈现出模板量降低以及混合组分数增加的趋势,其解释变得愈加复杂,传统的人工分析方法已难以满足现实要求。近几年国外基于统计算法模型的自动化软件解析方法渐趋成为混合STR分型分析的主要方法。本文综述了混合STR分型分析方法的相关研究进展,包括人工为主的定性分析方法以及基于统计模型的基因型概率分析方法;讨论了混合STR分型分析方法的未来发展趋势以及人工智能技术的应用前景。     

The Development and Application of Random Match Probabilities to Firearm and Toolmark Identification

The field of firearms and toolmark analysis has encountered deep scrutiny of late, stemming from a handful of voices, primarily in the law and statistical communities. While strong scrutiny is a healthy and necessary part of any scientific endeavor, much of the current criticism leveled at firearm and toolmark analysis is, at best, misinformed and, at worst, punditry. One of the most persistent criticisms stems from the view that as the field lacks quantified random match probability data (or at least a firm statistical model) with which to calculate the probability of a false match, all expert testimony concerning firearm and toolmark identification or source attribution is unreliable and should be ruled inadmissible. However, this critique does not stem from the hard work of actually obtaining data and performing the scientific research required to support or reject current findings in the literature. Although there are sound reasons (described herein) why there is currently no unifying probabilistic model for the comparison of striated and impressed toolmarks as there is in the field of forensic DNA profiling, much statistical research has been, and continues to be, done to aid the criminal justice system. This research has thus far shown that error rate estimates for the field are very low, especially when compared to other forms of judicial error. The first purpose of this paper is to point out the logical fallacies in the arguments of a small group of pundits, who advocate a particular viewpoint but cloak it as fact and research. The second purpose is to give a balanced review of the literature regarding random match probability models and statistical applications that have been carried out in forensic firearm and toolmark analysis.     

Estimating the probability of allelic drop-out of STR alleles in forensic genetics

In crime cases with available DNA evidence, the amount of DNA is often sparse due to the setting of the crime. In such cases, allelic drop-out of one or more true alleles in STR typing is possible. We present a statistical model for estimating the per locus and overall probability of allelic drop-out using the results of all STR loci in the case sample as reference. The methodology of logistic regression is appropriate for this analysis, and we demonstrate how to incorporate this in a forensic genetic framework.     

亲子鉴定中HLA分型母子对排除概率的简易计算法

为了解决用ＨＬＡ分型作亲权鉴定时计算母子对排除概率的困难，本文提出ＨＬＡ分型母子时排除概率Ｘｉ的简易计算法，可计算出１５对常用ＨＬＡ分型Ｘｉ值，比有关文献介绍的计算法简便，且适用范围广，可推广应用。     

False-negative probability in the SEM/EDS automated discovery of iGSR particles: A Bayesian approach

The automated search software integrated with a scanning electron microscope (SEM/EDS) has been the standard tool for detecting inorganic gunshot residues (iGSR) for several decades. The detection of these particles depends on various factors such as collection, preservation, contamination with organic matter, and the method for sample analysis. This article focuses on the influence of equipment resolution setup on the backscattered electron images of the sample. The pixel size of these images plays a crucial role in determining the detectability of iGSR particles, especially those with sizes close to the pixel size. In this study, we calculated the probability of missing all characteristic iGSR particles in a sample using an SEM/EDS automated search and how it depends on the image pixel resolution setup. We developed and validated an iGSR particle detection model that links particle size with equipment registers and applied it to 320 samples analyzed by a forensic science laboratory. Our results show that the probability of missing all characteristic iGSR particles due to their size is below 5% for pixel sizes below 0.32 μm². These findings indicate that pixel sizes as large as twice the one commonly used in laboratory casework, that is, 0.16 μm², are effective for initial sample scanning, yielding good detection rates of characteristic particles that could exponentially reduce laboratory workload.