Much research in recent years for evidence evaluation in forensic science has focussed on methods for determining the likelihood ratio in various scenarios. One proposition concerning the evidence is put forward by the prosecution and another is put forward by the defence. The likelihood of each of these two propositions is calculated, given the evidence. The likelihood ratio, or value of the evidence, is then given by the ratio of the likelihoods associated with these two propositions. The aim of this research is twofold. Firstly, it is intended to provide methodology for the evaluation of the likelihood ratio for continuous autocorrelated data. The likelihood ratio is evaluated for two such scenarios. The first is when the evidence consists of data which are autocorrelated at lag one. The second, an extension to this, is when the observed evidential data are also believed to be driven by an underlying latent Markov chain. Two models have been developed to take these attributes into account, an autoregressive model of order one and a hidden Markov model, which does not assume independence of adjacent data points conditional on the hidden states. A nonparametric model which does not make a parametric assumption about the data and which accounts for lag one autocorrelation is also developed. The performance of these three models is compared to the performance of a model which assumes independence of the data. The second aim of the research is to develop models to evaluate evidence relating to traces of cocaine on banknotes, as measured by the log peak area of the ion count for cocaine product ion m/z 105, obtained using tandem mass spectrometry. Here, the prosecution proposition is that the banknotes are associated with a person who is involved with criminal activity relating to cocaine and the defence proposition is the converse, which is that the banknotes are associated with a person who is not involved with criminal activity relating to cocaine. Two data sets are available, one of banknotes seized in criminal investigations and associated with crime involving cocaine, and one of banknotes from general circulation. Previous methods for the evaluation of this evidence were concerned with the percentage of banknotes contaminated or assumed independence of measurements of quantities of cocaine on adjacent banknotes. It is known that nearly all banknotes have traces of cocaine on them and it was found that there was autocorrelation within samples of banknotes so thesemethods are not appropriate. The models developed for autocorrelated data are applied to evidence relating to traces of cocaine on banknotes; the results obtained for each of the models are compared using rates of misleading evidence, Tippett plots and scatter plots. It is found that the hiddenMarkov model is the best choice for themodelling of cocaine traces on banknotes because it has the lowest rate of misleading evidence and it also results in likelihood ratios which are large enough to give support to the prosecution proposition for some samples of banknotes seized from crime scenes. Comparison of the results obtained for models which take autocorrelation into account with the results obtained from the model which assumes independence indicate that not accounting for autocorrelation can result in the overstating of the likelihood ratio.

The discrepancy between what students are being taught within K-12 science classrooms and what they experience in the real world has been well documented. This study sought to explore the ways a high school biology curriculum, which integrates socioscientific issues, impacts students' emotive reasoning and their ability to evaluate evidence, make informed decisions on contemporary scientific dilemmas, and integrate scientific content knowledge in their reasoning on SSI. Both quantitative and qualitative methods were used to examine differences within and between an SSI treatment group and a comparison group as well as individual differences among students' responses over a semester of high school biology. Results indicated students used emotions largely to evaluate evidence and make decisions on contentious scientific dilemmas. In addition, the results showed students used newly gained scientific content knowledge to make logical predictions on contentious scientific issues. Statistical significance was found between groups of students in regard to their interest in the use of embryonic stem cell treatments to restore rats' vision, as well as students' abilities to evaluate evidence. Theoretical implications regarding the use of SSI in the classroom are presented.

There were several evidence evaluation systems in the history. Torture with fire, water, which was used as a proof in the Middle Ages, later transformed into a formal evidence system. After the bourgeois revolutions the system of formal evidence was changed into the principle of free evidence evaluation by internal conviction. The purpose of the evaluation of evidence is to check its admissibility, concern, certainty and sufficiency. Any material to be recognised as evidence must meet all the requirements. In the current Code of Criminal Procedure of the Republic of Lithuania (CCP) the range of subjects evaluating evidence was narrowed in comparison with the former CCP valid till 1 May 2003. According to the current CCP, evidence is evaluated by judges. Other participants of criminal procedings can also evaluate the collected material, but only judges can recognise the collected material as evidence. The evaluation of evidence by other participants of criminal proceedings cannot affect courts decisions. The guarantees of judicial independence ensure free formation of internal conviction. The CCP provides that the full analysis of all the circumstances and the rule of law base the internal conviction. Indeed, other factors also influence the formation of internal conviction: the level of legal consciousness, socio - historical, psychological aspects, the collegiality of criminal case hearing. Separate kinds of evidence have their own specific nature requiring different... [to full text]

No description available.