DNA commission of the International society for forensic genetics: Assessing the value of forensic biological evidence - Guidelines highlighting the importance of propositions. Part II: Evaluation of biological traces considering activity level propositions.
Gill PDepartment of Forensic Sciences, Oslo University Hospital, Oslo, Norway; Institute of Clinical Medicine, University of Oslo, Oslo, Norway. Electronic address: peterd.gill@gmail.com.
Hicks TFaculty of Law, Criminal Justice and Public Administration, School of Criminal Justice, University of Lausanne, Lausanne, Switzerland; Fondation pour la formation continue universitaire lausannoise (UNIL-EPFL), 1015, Dorigny, Switzerland.
Butler JMNational Institute of Standards and Technology, Special Programs Office, Gaithersburg, MD, USA.
Gusmão LState University of Rio de Janeiro (UERJ), Rio de Janeiro, Brazil; IPATIMUP, Institute of Molecular Pathology and Immunology of the University of Porto, Portugal; Instituto de Investigação e Inovação em Saúde, University of Porto, Portugal.
Kokshoorn BNetherlands Forensic Institute, Division Biological Traces, P.O. Box 24044, 2490 AA, The Hague, the Netherlands.
Morling NSection of Forensic Genetics, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark.
van Oorschot RAHOffice of the Chief Forensic Scientist, Victoria Police Forensic Service Centre, Macleod, VIC, 3085, Australia; School of Molecular Sciences, La Trobe University, Bundoora, VIC, 3086, Australia.
Parson WInstitute of Legal Medicine, Medical University of Innsbruck, Innsbruck, Austria; Forensic Science Program, The Pennsylvania State University, PA, USA.
Prinz MJohn Jay College of Criminal Justice, New York, USA.
Schneider PMInstitute of Legal Medicine, Faculty of Medicine and University Clinic, University of Cologne, Germany.
Sijen TNetherlands Forensic Institute, Division Biological Traces, P.O. Box 24044, 2490 AA, The Hague, the Netherlands.
Taylor DForensic Science SA, GPO box 2790, Adelaide, 5001, South Australia, Australia; School of Biological Sciences, Flinders University, GPO Box 2100, 5001, Adelaide, SA, Australia.
English
The value of the evidence depends critically on propositions. In the second of two papers intended to provide advice to the community on difficult aspects of evaluation and the formulation of propositions, we focus primarily on activity level propositions. This helps the court address the question of "How did an individual's cell material get there?". In order to do this, we expand the framework outlined in the first companion paper. First, it is important not to conflate results and propositions. Statements given activity level propositions aim to help address issues of indirect vs direct transfer, and the time of the activity, but it is important to avoid use of the word 'transfer' in propositions. This is because propositions are assessed by the Court, but DNA transfer is a factor that scientists need to take into account for the interpretation of their results. Suitable activity level propositions are ideally set before knowledge of the results and address issues like: X stabbed Y vs. an unknown person stabbed Y but X met Y the day before. The scientist assigns the probability of the evidence, if each of the alternate propositions is true, to derive a likelihood ratio. To do this, the scientist asks: a) "what are the expectations if each of the propositions is true?" b) "What data are available to assist in the evaluation of the results given the propositions?" When presenting evidence, scientists work within the hierarchy of propositions framework. The value of evidence calculated for a DNA profile cannot be carried over to higher levels in the hierarchy - the calculations given sub-source, source and activity level propositions are all separate. A number of examples are provided to illustrate the principles espoused, and the criteria that such assessments should meet. Ideally in order to assign probabilities, the analyst should have/collect data that are relevant to the case in question. These data must be relevant to the case at hand and we encourage further research and collection of data to form knowledge bases. Bayesian Networks are extremely useful to help us think about a problem, because they force us to consider all relevant possibilities in a logical way. An example is provided.