The tales we tell : exploring the legal stories of Queensland women who kill

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.

Fiduciary Duty and the Atmospheric Trust

This book explores the application of concepts of fiduciary duty or public trust in responding to the policy and governance challenges posed by policy problems that extend over multiple terms of government or even, as in the case of climate change, human generations. The volume brings together a range of perspectives including leading international thinkers on questions of fiduciary duty and public trust, Australia's most prominent judicial advocate for the application of fiduciary duty, top law scholars from several major universities, expert commentary from an influential climate policy think-tank and the views of long-serving highly respected past and present parliamentarians. The book presents a detailed examination of the nature and extent of fiduciary duty, looking at the example of Australia and having regard to developments in comparable jurisdictions. It identifies principles that could improve the accountability of political actors for their responses to major problems that may extend over multiple electoral cycles.

Data preprocessing for anomaly based network intrusion detection : a review

Data preprocessing is widely recognized as an important stage in anomaly detection. This paper reviews the data preprocessing techniques used by anomaly-based network intrusion detection systems (NIDS), concentrating on which aspects of the network traffic are analyzed, and what feature construction and selection methods have been used. Motivation for the paper comes from the large impact data preprocessing has on the accuracy and capability of anomaly-based NIDS. The review finds that many NIDS limit their view of network traffic to the TCP/IP packet headers. Time-based statistics can be derived from these headers to detect network scans, network worm behavior, and denial of service attacks. A number of other NIDS perform deeper inspection of request packets to detect attacks against network services and network applications. More recent approaches analyze full service responses to detect attacks targeting clients. The review covers a wide range of NIDS, highlighting which classes of attack are detectable by each of these approaches. Data preprocessing is found to predominantly rely on expert domain knowledge for identifying the most relevant parts of network traffic and for constructing the initial candidate set of traffic features. On the other hand, automated methods have been widely used for feature extraction to reduce data dimensionality, and feature selection to find the most relevant subset of features from this candidate set. The review shows a trend toward deeper packet inspection to construct more relevant features through targeted content parsing. These context sensitive features are required to detect current attacks.