Letter to the editor: Commentary on “Strategic choice in linear sequential unmasking,Roger Koppl,Science & Justice,https://doi.org/10.1016/j.scijus.2018.10.010”

This letter to the Editor comments on the paper ‘Strategic choice in linear sequential unmasking’ by Roger Koppl (Science & Justice, https://doi.org/10.1016/j.scijus.2018.10.010).     

Agarose gel electrophoresis of human erythrocyte glutamic-pyruvic transaminase (GPT EC 2.6.1.2)

The method of choice to determine erythrocyte glutamate-pyruvic transaminase (GPT) including rare variants was starch gel electrophoresis. Methods using agarose as gel medium were not reported to our knowledge. We present an adapted method using the Tris/maleate buffer system and an agarose of low endosmosis. The common as well as rare variant types of GPT were quickly and reliably separated. In addition, a method for the consecutive determination of esterase D (ESD) and GPT on the same gel using the malic acid buffer system is described.     

The use of the likelihood ratio for evaluative and investigative purposes in comparative forensic handwriting examination

This paper extends previous research and discussion on the use of multivariate continuous data, which are about to become more prevalent in forensic science. As an illustrative example, attention is drawn here on the area of comparative handwriting examinations. Multivariate continuous data can be obtained in this field by analysing the contour shape of loop characters through Fourier analysis. This methodology, based on existing research in this area, allows one describe in detail the morphology of character contours throughout a set of variables. This paper uses data collected from female and male writers to conduct a comparative analysis of likelihood ratio based evidence assessment procedures in both, evaluative and investigative proceedings. While the use of likelihood ratios in the former situation is now rather well established (typically, in order to discriminate between propositions of authorship of a given individual versus another, unknown individual), focus on the investigative setting still remains rather beyond considerations in practice. This paper seeks to highlight that investigative settings, too, can represent an area of application for which the likelihood ratio can offer a logical support. As an example, the inference of gender of the writer of an incriminated handwritten text is forwarded, analysed and discussed in this paper. The more general viewpoint according to which likelihood ratio analyses can be helpful for investigative proceedings is supported here through various simulations. These offer a characterisation of the robustness of the proposed likelihood ratio methodology.     

Forensic drug intelligence: an important tool in law enforcement

Organised criminality is a great concern for national/international security. The demonstration of complex crimes is increasingly dependant on knowledge distributed within law-enforcement agencies and scientific disciplines. This separation of knowledge creates difficulties in reconstructing and prosecuting such crimes. Basic interdisciplinary research in drug intelligence combined with crime analysis, forensic intelligence, and traditional law enforcement investigation is leading to important advances in crime investigation support. Laboratory results constitute one highly dependable source of information that is both reliable and testable. Their operational use can support investigation and even provide undetected connections or organisation of structure. The foremost difficulties encountered by drug analysts are not principally of a chemical or analytical nature, but methodologies to extract parameters or features that are deemed to be crucial for handling and contextualising drug profiling data. An organised memory has been developed in order to provide accurate, timely, useful and meaningful information for linking spatially and temporally distinct events on a national and international level (including cross-border phenomena). Literature has already pointed out that forensic case data are amenable for use in an intelligence perspective if data and knowledge of specialised actors are appropriately organised, shared and processed. As a particular form of forensic case data, the authors' research focuses on parameters obtained through the systematic physical and chemical profiling of samples of illicit drugs. The procedure is used to infer and characterise links between samples that originate from the same and different seizures. The discussion will not, however, focus on how samples are actually analysed and compared as substantial literature on this topic already exists. Rather, attention is primarily drawn to an active and close collaboration between magistrates, forensic scientists, law enforcement investigators and crime analysts from different institutions with the aim of generating, using and validating relevant profiling case data as integral part of investigative and crime analysis processes. Original advances are highlighted through experiences from criminal investigations of offences related to the unlawful importation, exportation, supply and possession of illicit drugs.     

The significance of offending behavior for predicting sexual recidivism among sex offenders of various age groups

Based on a sample of 682 male sex offenders, this study investigated variables of the offending behavior for predicting sexual recidivism in different age groups. The sex offenders were allocated into four age groups. For each group, those characteristics of offending behavior showing a significant bivariate correlation with sexual recidivism were extracted. Using logistic regression, we then analyzed their incremental validity above and beyond a previously developed Crime Scene Behavior Risk (CBR)-Score, which measures the risk of sexual recidivism without taking into account the offenders' age (Dahle, Biedermann, Gallasch-Nemitz, & Janka, 2010). Age-specific offending behavior variables with incremental validity were combined with the general CBR-Score into age-specific scores and examined for their predictive accuracy. We also analyzed the extent in which these age-specific scores showed incremental validity above and beyond the Static-99 (Hanson & Thornton, 1999). For three of the four age groups, age-specific Crime Scene Behavior Risk-Scores could be determined which were incrementally valid above and beyond the Static-99. Predictive accuracy varied between AUC=.74 and AUC=.90 (r=.28 to r=.49) depending on age group. The results are discussed within context of recent findings on the latent dimensions of actuarial risk assessment variables.     

The evaluation of evidence in the forensic investigation of fire incidents (Part I): an approach using Bayesian networks

The forensic investigation of the origin and cause of a fire incident is a particularly demanding area of expertise. As the available evidence is often incomplete or vague, uncertainty is a key element. The present study is an attempt to approach this through the use of Bayesian networks, which have been found useful in assisting human reasoning in a variety of disciplines in which uncertainty plays a central role. The present paper describes the construction of a Bayesian network (BN) and its use for drawing inferences about propositions of interest, based upon a single, possibly non replicable item of evidence: detected residual quantities of a flammable liquid in fire debris.     

Decision theoretic properties of forensic identification: underlying logic and argumentative implications

The field of forensic science has profited from recent advances in the elicitation of various kinds probabilistic data. These provide the basis for implementing probabilistic inference procedures (e.g., in terms of likelihood ratios) that address the task of discriminating among competing target propositions. There is ongoing discussion, however, whether forensic identification, that is, a conclusion that associates a potential source (such as an individual or object) with a given item of scientific evidence (e.g., a biological stain or a tool mark), can, if ever, be based on purely probabilistic argument. With regard to this issue, the present paper proposes to analyze the process of forensic identification from a decision theoretic point of view. Existing probabilistic inference procedures are used therein as an integral part. The idea underlying the proposed analyses is that inference and decision are connected in the sense that the former is the point of departure for the latter. As such the approach forms a coordinated whole, that is a framework also known in the context as 'full Bayesian (decision) approach'. This study points out that, as a logical extension to purely probabilistic reasoning, a decision theoretic conceptualization of forensic identification allows the content and structure of arguments to be examined from a reasonably distinct perspective and common fallacious interpretations to be avoided.     

A general approach to Bayesian networks for the interpretation of evidence

Bayesian networks (BNs) are mathematically and statistically rigorous techniques for handling uncertainty. The field of forensic science has recently attributed increased attention to the many advantages of this graphical method for assisting the evaluation of scientific evidence. However, the majority of contributions that relate to this topic restrict themselves to the presentation of already "constructed" BNs, and often, only a few explanations are given as to how one obtains a specific BN structure for a given problem. Based on several examples, the present paper will therefore attempt to explain in more detail some guiding considerations that might be helpful for the elicitation of appropriate structures for BNs.