201 resultados para Expert Testimony.

em Queensland University of Technology - ePrints Archive


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Within coronial investigations, pathologists are called upon to given evidence as to cause of death. This evidence is given great weight by the coroners; after all, scientific ‘truth’ is widely deemed to be far more reliable than legal ‘opinion’. The purpose of this paper is to examine the ontological and epistemological status of that evidence, from the perspectives of both the pathologists and the coroners. As part of an Australian Research Council Linkage Grant, interviews were conducted with seven pathologists and 10 coroners from within the Queensland coronial system. Contrary to expectations, and the work of philosophers of science, such as Feyerabend (1975), pathologists did not present their findings in terms of unequivocal facts or objective truths relating to causes of death. Rather, their evidence was largely presented as ‘educated opinion’ based upon ‘the weight of evidence’. It was actually the coroners who translated that opinion into ‘medical fact’ within the proceedings of their death investigations, arguably as a consequence of the administrative necessity to reach a clear-cut finding as to cause of death, and on the basis of their own understanding of the ontology of medical knowledge. These findings support Latour’s (2010) claim that law requires a fundamentally different epistemology to science, and that science is not entirely to blame for the extravagant truth-claims made on its behalf

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The bulk of the homicide research to date has focused on male offending, with little consideration given to women's offending and in particular, their constructions within the courtroom following a homicide-related charge. This thesis examines, in detail, nineteen homicide cases finalised in the Queensland Supreme Courts between 01/01/1997 and 31/12/2002, in order to document and discuss the various legal stories available to women who kill. Predominantly, two “stock stories” are available within the court. The first, presented by the defence, offers the accused woman a victimised position to occupy. Evidence of victimisation is made available through previous abuse, expert testimony from psychologists and psychiatrists, challenges to her mental health, or appeals to her emotional nature. The second stock story, presented by the prosecution, positions the accused woman as angry, full of revenge, calculating and self serving. Such a script is usually supported by witnesses, police evidence, and family members. This thesis examines these competing and contradictory scripts using thematic discourse analysis to examine the court transcripts in detail. It argues that the "truth" of the fatal incident is based on one of these two prevailing scripts. This research destabilises the dominant script of violent female offending in the feminist literature. Most research to date has focussed on explaining the circumstances in which women kill, concentrating attention on the victimisation of the violent offending woman and negating or de-prioritising any volition on her part. By analysing all transcripts of women whose trials were held within the specified period, this research is able to demonstrate the stories used to describe their complex offending, and draw attention to the anger and intent that can occur alongside the victimisation.

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Allegations of child sexual abuse in Family Court cases have gained increasing attention. The study investigates factors involved in Family Court cases involving allegations of child sexual abuse. A qualitative methodology was employed to examine Records of Judgement and Psychiatric Reports for 20 cases distilled from the data corpus of 102 cases. A seven-stage methodology was developed utilising a thematic analysis process informed by principles of grounded theory and phenomenology. The explication of eight thematic clusters was undertaken. The findings point to complex issues and dynamics in which child sexual abuse allegations have been raised. The alleging parent’s allegations of sexual abuse against their ex-partner may be: the expression of unconscious deep fears for their children’s welfare, or an action to meet their needs for personal affirmation in the context of the painful upheaval of a relationship break-up. Implications of the findings are discussed.

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1. Species' distribution modelling relies on adequate data sets to build reliable statistical models with high predictive ability. However, the money spent collecting empirical data might be better spent on management. A less expensive source of species' distribution information is expert opinion. This study evaluates expert knowledge and its source. In particular, we determine whether models built on expert knowledge apply over multiple regions or only within the region where the knowledge was derived. 2. The case study focuses on the distribution of the brush-tailed rock-wallaby Petrogale penicillata in eastern Australia. We brought together from two biogeographically different regions substantial and well-designed field data and knowledge from nine experts. We used a novel elicitation tool within a geographical information system to systematically collect expert opinions. The tool utilized an indirect approach to elicitation, asking experts simpler questions about observable rather than abstract quantities, with measures in place to identify uncertainty and offer feedback. Bayesian analysis was used to combine field data and expert knowledge in each region to determine: (i) how expert opinion affected models based on field data and (ii) how similar expert-informed models were within regions and across regions. 3. The elicitation tool effectively captured the experts' opinions and their uncertainties. Experts were comfortable with the map-based elicitation approach used, especially with graphical feedback. Experts tended to predict lower values of species occurrence compared with field data. 4. Across experts, consensus on effect sizes occurred for several habitat variables. Expert opinion generally influenced predictions from field data. However, south-east Queensland and north-east New South Wales experts had different opinions on the influence of elevation and geology, with these differences attributable to geological differences between these regions. 5. Synthesis and applications. When formulated as priors in Bayesian analysis, expert opinion is useful for modifying or strengthening patterns exhibited by empirical data sets that are limited in size or scope. Nevertheless, the ability of an expert to extrapolate beyond their region of knowledge may be poor. Hence there is significant merit in obtaining information from local experts when compiling species' distribution models across several regions.

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Expert elicitation is the process of retrieving and quantifying expert knowledge in a particular domain. Such information is of particular value when the empirical data is expensive, limited, or unreliable. This paper describes a new software tool, called Elicitator, which assists in quantifying expert knowledge in a form suitable for use as a prior model in Bayesian regression. Potential environmental domains for applying this elicitation tool include habitat modeling, assessing detectability or eradication, ecological condition assessments, risk analysis, and quantifying inputs to complex models of ecological processes. The tool has been developed to be user-friendly, extensible, and facilitate consistent and repeatable elicitation of expert knowledge across these various domains. We demonstrate its application to elicitation for logistic regression in a geographically based ecological context. The underlying statistical methodology is also novel, utilizing an indirect elicitation approach to target expert knowledge on a case-by-case basis. For several elicitation sites (or cases), experts are asked simply to quantify their estimated ecological response (e.g. probability of presence), and its range of plausible values, after inspecting (habitat) covariates via GIS.

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Numerous expert elicitation methods have been suggested for generalised linear models (GLMs). This paper compares three relatively new approaches to eliciting expert knowledge in a form suitable for Bayesian logistic regression. These methods were trialled on two experts in order to model the habitat suitability of the threatened Australian brush-tailed rock-wallaby (Petrogale penicillata). The first elicitation approach is a geographically assisted indirect predictive method with a geographic information system (GIS) interface. The second approach is a predictive indirect method which uses an interactive graphical tool. The third method uses a questionnaire to elicit expert knowledge directly about the impact of a habitat variable on the response. Two variables (slope and aspect) are used to examine prior and posterior distributions of the three methods. The results indicate that there are some similarities and dissimilarities between the expert informed priors of the two experts formulated from the different approaches. The choice of elicitation method depends on the statistical knowledge of the expert, their mapping skills, time constraints, accessibility to experts and funding available. This trial reveals that expert knowledge can be important when modelling rare event data, such as threatened species, because experts can provide additional information that may not be represented in the dataset. However care must be taken with the way in which this information is elicited and formulated.

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Research on expertise, talent identification and development has tended to be mono-disciplinary, typically adopting adopting neurogenetic deterministic or environmentalist positions, with an over-riding focus on operational issues. In this paper the validity of dualist positions on sport expertise is evaluated. It is argued that, to advance understanding of expertise and talent development, a shift towards a multi-disciplinary and integrative science focus is necessary, along with the development of a comprehensive multi-disciplinary theoretical rationale. Here we elucidate dynamical systems theory as a multi-disciplinary theoretical rationale for capturing how multiple interacting constraints can shape the development of expert performers. This approach suggests that talent development programmes should eschew the notion of common optimal performance models, emphasise the individual nature of pathways to expertise, and identify the range of interacting constraints that impinge on performance potential of individual athletes, rather than evaluating current performance on physical tests referenced to group norms.

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Theory predicts that efficiency prevails on credence goods markets if customers are able to verify which quality they receive from an expert seller. In a series of experiments with endogenous prices we observe that verifiability fails to result in efficient provision behaviour and leads to very similar results as a setting without verifiability. Some sellers always provide appropriate treatment even if own money maximization calls for over- or undertreatment. Overall our endogenous-price-results suggests that both inequality aversion and a taste for efficiency play an important role for experts’ provision behaviour. We contrast the implications of those two motivations theoretically and discriminate between them empirically using a fixed-price design. We then classify experimental experts according to their provision behaviour.

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Experts in injection molding often refer to previous solutions to find a mold design similar to the current mold and use previous successful molding process parameters with intuitive adjustment and modification as a start for the new molding application. This approach saves a substantial amount of time and cost in experimental based corrective actions which are required in order to reach optimum molding conditions. A Case-Based Reasoning (CBR) System can perform the same task by retrieving a similar case which is applied to the new case from the case library and uses the modification rules to adapt a solution to the new case. Therefore, a CBR System can simulate human e~pertise in injection molding process design. This research is aimed at developing an interactive Hybrid Expert System to reduce expert dependency needed on the production floor. The Hybrid Expert System (HES) is comprised of CBR, flow analysis, post-processor and trouble shooting systems. The HES can provide the first set of operating parameters in order to achieve moldability condition and producing moldings free of stress cracks and warpage. In this work C++ programming language is used to implement the expert system. The Case-Based Reasoning sub-system is constructed to derive the optimum magnitude of process parameters in the cavity. Toward this end the Flow Analysis sub-system is employed to calculate the pressure drop and temperature difference in the feed system to determine the required magnitude of parameters at the nozzle. The Post-Processor is implemented to convert the molding parameters to machine setting parameters. The parameters designed by HES are implemented using the injection molding machine. In the presence of any molding defect, a trouble shooting subsystem can determine which combination of process parameters must be changed iii during the process to deal with possible variations. Constraints in relation to the application of this HES are as follows. - flow length (L) constraint: 40 mm < L < I 00 mm, - flow thickness (Th) constraint: -flow type: - material types: I mm < Th < 4 mm, unidirectional flow, High Impact Polystyrene (HIPS) and Acrylic. In order to test the HES, experiments were conducted and satisfactory results were obtained.