Guidance on interviewing child witnesses in Scotland

The guidance was commissioned from Dr Amina Memon and Lynn Hulse at Aberdeen University. Their work was overseen by a steering group with representatives from the Scottish Executive Justice Department, the Crown Office and Procurator Fiscal Service, NCH Scotland, the Association of Chief Police Officers in Scotland, the Association of Directors of Social Work, the Law Society for Scotland, the Scottish Association of Community Child Health and the Scottish Children’s Reporter Administration. A full list of those involved is given in the Appendix C. pt. 1. Guidance on interviewing child witnesses in Scotland -- pt. 2. Guidance on the questioning of children in court -- pt. 3. Lord Justice-General's memorandum on child witnesses: appendix to Guidance on the questioning of children in court -- pt. 4. Guidance on child witness court familiarisation visits -- pt. 5. Information about child, young and vulnerable adult witnesses to inform decision-making in the legal process: good practice guide -- pt. 6. Code of practice to facilitate the provision of therapeutic support to child witnesses in court proceedings -- pt. 7. Guidance on the conduct of identity parades with child witnesses.

[Book review] "Memory and Suggestibility in the Forensic Interview"

Book review of: Eisen, M.L., Quas, J.A. & Goodman, G.S. (Eds.) (2002). Memory and suggestibility in the forensic interview. Mahwah, NJ: Lawrence Erlbaum Associates. ISBN: 0-8058-3080-4/$55.00 Special Prepaid Price

Elemental analysis of soil samples for forensic purposes by inductively coupled plasma spectrometry - precision considerations

Major and trace elemental composition provides a powerful basis for forensic comparison of soils, sediments and rocks. However, it is important that the potential 'errors' associated with the procedures are fully understood and quantified, and that standard protocols are applied for sample preparation and analysis. This paper describes such a standard procedure and reports results both for instrumental measurement precision (repeatability) and overall 'method' precision (reproducibility). Results obtained both for certified reference materials and example soils show that the instrumental measurement precision (defined by the coefficient of variation, CV) for most elements is better than 2-3%. When different solutions were prepared from the same sample powder, and from different sub-sample powders prepared from the same parent sample, the CV increased to c. 5-6% for many elements. The largest variation was found in results for certified reference materials generated from 23 instrument runs over an 18 month period (mean CV=c. 11%). Some elements were more variable than others. W was found to be the most variable and the elements V, Cr, Co, Cu, Ni and Pb also showed higher than average variability. SiO2, CaO, Al2O3 and Fe2O3, Rb, Sr, La, Ce, Nd and Sm generally showed lower than average variability, and therefore provided the most reliable basis for inter-sample comparison. It is recommended that, whenever possible, samples relating to the same investigation should be analysed in the same sample run, or at least sequential runs.

The Jama legal narrative. Part II: A foray into concepts of improbability

In judicial decision making, the doctrine of chances takes explicitly into account the odds. There is more to forensic statistics, as well as various probabilistic approaches which taken together form the object of an enduring controversy in the scholarship of legal evidence. In this paper, we reconsider the circumstances of the Jama murder and inquiry (dealt with in Part I of this paper: "The Jama Model. On Legal Narratives and Interpretation Patterns"), to illustrate yet another kind of probability or improbability. What is improbable about the Jama story, is actually a given, which contributes in terms of dramatic underlining. In literary theory, concepts of narratives being probable or improbable date back from the eighteenth century, when both prescientific and scientific probability was infiltrating several domains, including law. An understanding of such a backdrop throughout the history of ideas is, I claim, necessary for AI researchers who may be tempted to apply statistical methods to legal evidence. The debate for or against probability (and especially bayesian probability) in accounts of evidence has been flouishing among legal scholars. Nowadays both the the Bayesians (e.g. Peter Tillers) and Bayesioskeptics (e.g. Ron Allen) among those legal scholars whoare involved in the controversy are willing to give AI researchers a chance to prove itself and strive towards models of plausibility that would go beyond probability as narrowly meant. This debate within law, in turn, has illustrious precedents: take Voltaire, he was critical of the application or probability even to litigation in civil cases; take Boole, he was a starry-eyed believer in probability applications to judicial decision making (Rosoni 1995). Not unlike Boole, the founding father of computing, nowadays computer scientists approaching the field may happen to do so without full awareness of the pitfalls. Hence, the usefulness of the conceptual landscape I sketch here.

The Jama legal narrative part II: A foray into concepts of improbability

In judicial decision making, the doctrine of chances takes explicitly into account the odds. There is more to forensic statistics, as well as various probabilistic approaches, which taken together form the object of an enduring controversy in the scholarship of legal evidence. In this paper, I reconsider the circumstances of the Jama murder and inquiry (dealt with in Part I of this paper: 'The JAMA Model and Narrative Interpretation Patterns'), to illustrate yet another kind of probability or improbability. What is improbable about the Jama story is actually a given, which contributes in terms of dramatic underlining. In literary theory, concepts of narratives being probable or improbable date back from the eighteenth century, when both prescientific and scientific probability were infiltrating several domains, including law. An understanding of such a backdrop throughout the history of ideas is, I claim, necessary for Artificial Intelligence (AI) researchers who may be tempted to apply statistical methods to legal evidence. The debate for or against probability (and especially Bayesian probability) in accounts of evidence has been flourishing among legal scholars; nowadays both the Bayesians (e.g. Peter Tillers) and the Bayesio-skeptics (e.g. Ron Allen), among those legal scholars who are involved in the controversy, are willing to give AI research a chance to prove itself and strive towards models of plausibility that would go beyond probability as narrowly meant. This debate within law, in turn, has illustrious precedents: take Voltaire, he was critical of the application of probability even to litigation in civil cases; take Boole, he was a starry-eyed believer in probability applications to judicial decision making. Not unlike Boole, the founding father of computing, nowadays computer scientists approaching the field may happen to do so without full awareness of the pitfalls. Hence, the usefulness of the conceptual landscape I sketch here.

The use of a mathematical multicriteria decision-making model for selecting the fire origin room

Over the last three decades, the fire safety codes have been changing from a prescriptive approach to a performance-based one. Some countries, such as the USA, Sweden, New Zealand, Australia and the UK, are in an advanced stage of development and implementation of the performance-based codes. However, there are some difficulties in this process. Most of them are due to the uncertainties associated with fire design. For instance, one of the questions that need to be answered is how to select the most probable fire origin room (FOR)? On the other hand, to know where the FOR is located is also an important aspect in terms of forensic issues. Given that, to address this question is an important step for the establishment of fire designs (i.e., pre-fire phases) and also for fire investigations (i.e., post-fire phases). This paper proposes a methodology for selecting the FOR through the use of a mathematical multicriteria decision-making model: the analytical hierarchy process (AHP). The proposed method is then applied to a hypothetical study case. The results are presented and discussed in this paper.