Threshold Decisions in Determining Whether to Prosecute Child Sexual Abuse. The objective of this project is new knowledge about the way police and prosecutors make decisions about the prosecution of child sexual assault that could be used to influence policy and practice. Few cases of child sexual abuse reported to the police ever go to court but recent research in New South Wales for the Royal Commission indicates that the proportion has declined sharply over the last decade or so. This projec ....Threshold Decisions in Determining Whether to Prosecute Child Sexual Abuse. The objective of this project is new knowledge about the way police and prosecutors make decisions about the prosecution of child sexual assault that could be used to influence policy and practice. Few cases of child sexual abuse reported to the police ever go to court but recent research in New South Wales for the Royal Commission indicates that the proportion has declined sharply over the last decade or so. This project aims to examine how police and prosecutors decide which cases proceed and why, and how they confer with each other as well as when and how they consult with complainants and their families. This project plans to also develop and test practice tools and principles for police and prosecutors with expected benefits for both them and the families involved.Read moreRead less
Statistical methods for quantifying variation in spatiotemporal areal data. This project aims to develop new statistical methods for extracting insights into spatial and temporal variation in areal data. These tools will extend the Australian Cancer Atlas which provides small area estimates for 20 cancers across Australia. The project is significant because it will allow government and other organisations to reap dividends from investment in collecting spatial information and it will enable mode ....Statistical methods for quantifying variation in spatiotemporal areal data. This project aims to develop new statistical methods for extracting insights into spatial and temporal variation in areal data. These tools will extend the Australian Cancer Atlas which provides small area estimates for 20 cancers across Australia. The project is significant because it will allow government and other organisations to reap dividends from investment in collecting spatial information and it will enable modelled small-area estimates to be released without compromising confidentiality. The expected outcomes include new statistical knowledge and new insights into cancer. The results will benefit the many disciplines, managers and policy makers that make decisions based on geographic data mapped over space and time. Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE240100109
Funder
Australian Research Council
Funding Amount
$460,157.00
Summary
Sexual offence interviewing: Towards victim-survivor well-being and justice. This project aims to improve the way victim-survivors are interviewed in sexual offence cases by examining their experiences and perceptions of investigative interview techniques. It expects to generate new knowledge about interview techniques that can promote victim well-being and the disclosure of sensitive information during investigative interviews. Expected outcomes include new theoretical frameworks in the field o ....Sexual offence interviewing: Towards victim-survivor well-being and justice. This project aims to improve the way victim-survivors are interviewed in sexual offence cases by examining their experiences and perceptions of investigative interview techniques. It expects to generate new knowledge about interview techniques that can promote victim well-being and the disclosure of sensitive information during investigative interviews. Expected outcomes include new theoretical frameworks in the field of investigative interviewing and an innovative toolkit of victim-centred training resources to directly inform investigative interview policies and practices in sexual offence cases. Anticipated benefits include better victim experiences of investigative interviews and enhanced justice responses to sexual violence.Read moreRead less
In for the count: Maximising trust and reliability in Australian elections. This project aims to develop innovative approaches to identifying, measuring, and evaluating errors and purposeful intervention in the uniquely complex elections at the basis of Australian democracy. Such methods can underpin a world-class election auditing system, which contends with the risks that are emerging at the intersection of election digitisation, cybersecurity and foreign interference. The project’s expected o ....In for the count: Maximising trust and reliability in Australian elections. This project aims to develop innovative approaches to identifying, measuring, and evaluating errors and purposeful intervention in the uniquely complex elections at the basis of Australian democracy. Such methods can underpin a world-class election auditing system, which contends with the risks that are emerging at the intersection of election digitisation, cybersecurity and foreign interference. The project’s expected outcomes are new auditing methods, tested on real Australian election data, with their benefits quantified against global best practice. The research outputs should help reinforce the community’s trust in Australian elections, which are a foundation for our security, social cohesion, and political resilience.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200101253
Funder
Australian Research Council
Funding Amount
$349,586.00
Summary
Making Machine Learning Fair(er). This project aims to develop and implement statistical methods to fight against algorithm bias. In doing so, this project expects to generate new knowledge in the mathematical sciences by employing innovative and interdisciplinary approaches to the development of fairness constraints on machine learning algorithms. Fairness will be seen through the lens of invariance, allowing the developed conceptual framework to find broad applications. Expected outcomes of t ....Making Machine Learning Fair(er). This project aims to develop and implement statistical methods to fight against algorithm bias. In doing so, this project expects to generate new knowledge in the mathematical sciences by employing innovative and interdisciplinary approaches to the development of fairness constraints on machine learning algorithms. Fairness will be seen through the lens of invariance, allowing the developed conceptual framework to find broad applications. Expected outcomes of this project include improved techniques for imposing invariance on deep learning algorithms. This should provide significant benefits to the general public by contributing to the advancement of socially responsible and conscientious machine learning.Read moreRead less
Creating perceptual experts in Australia's policing and security agencies. This project aims to create the next generation of experts in Australia’s policing and national security agencies, by improving crime scene evidence interpretation. Agencies are under pressure to develop more rigorous training practices that go beyond mere intuition and tradition. This project will use a novel approach that directs learning toward the most diagnostic perceptual cues. Expected outcomes include a solid empi ....Creating perceptual experts in Australia's policing and security agencies. This project aims to create the next generation of experts in Australia’s policing and national security agencies, by improving crime scene evidence interpretation. Agencies are under pressure to develop more rigorous training practices that go beyond mere intuition and tradition. This project will use a novel approach that directs learning toward the most diagnostic perceptual cues. Expected outcomes include a solid empirical basis for national training programs designed to create experts that are accurate, reliable, and continuously improving. Improving the training of experts will ensure the integrity of forensics as evidentiary tools available to police, lead to more reliable courtroom convictions and help safeguard Australia from terrorism and crime.Read moreRead less
Understanding the drivers and motivators of extremist violence. Despite intense interest in the issue, our understanding of and ability to respond to extremist violence is limited. This innovative program of research is designed to establish an empirical foundation for understanding and responding to extremist violence in Australia. It aims to examine risk and protective factors for such violence, the needs of those susceptible to committing such acts, and the effectiveness of intervention. Find ....Understanding the drivers and motivators of extremist violence. Despite intense interest in the issue, our understanding of and ability to respond to extremist violence is limited. This innovative program of research is designed to establish an empirical foundation for understanding and responding to extremist violence in Australia. It aims to examine risk and protective factors for such violence, the needs of those susceptible to committing such acts, and the effectiveness of intervention. Findings are expected to inform health, national security, social welfare, and justice agencies in their pursuit to identify those at risk of offending, address their clinical needs and manage the risk of harm they pose to society and to themselves.Read moreRead less
Early Career Industry Fellowships - Grant ID: IE230100380
Funder
Australian Research Council
Funding Amount
$390,574.00
Summary
Enhancing comprehension of forensic science in the justice system. Failures to effectively communicate the accuracy and reliability of forensic evidence to courts can lead to unreliable convictions and miscarriages of justice. This project aims to understand how best to distil complex information about error and uncertainty in forensic expert opinion evidence for enhanced comprehension of forensic science in the justice system. Outcomes include evidence-based strategies for communicating error a ....Enhancing comprehension of forensic science in the justice system. Failures to effectively communicate the accuracy and reliability of forensic evidence to courts can lead to unreliable convictions and miscarriages of justice. This project aims to understand how best to distil complex information about error and uncertainty in forensic expert opinion evidence for enhanced comprehension of forensic science in the justice system. Outcomes include evidence-based strategies for communicating error and uncertainty in forensic science and an accessible online dashboard for visualising known error rates in forensic disciplines. The knowledge gained from the project will help forensic experts to calibrate how they present their conclusions to courts for improved comprehension and evaluation of forensic evidence.Read moreRead less
The cost of keeping gruesome images from the world. This project aims to investigate one of society’s most invisible ‘frontline’ trauma workforces—the online content moderators responsible for limiting the public’s exposure to distressing and sensitive content on social media. Using a series of rigorous experiments, and cutting-edge psychological and physiological assessment techniques, the research will advance our understanding of the impact of indirect trauma on mental health. Expected outcom ....The cost of keeping gruesome images from the world. This project aims to investigate one of society’s most invisible ‘frontline’ trauma workforces—the online content moderators responsible for limiting the public’s exposure to distressing and sensitive content on social media. Using a series of rigorous experiments, and cutting-edge psychological and physiological assessment techniques, the research will advance our understanding of the impact of indirect trauma on mental health. Expected outcomes include novel empirical evidence for preventative strategies that will predict, monitor and reduce negative mental health outcomes. This will provide significant global benefits to people with indirect trauma experiences, such as defence and forensic personnel.Read moreRead less
Stochastic majorization--minimization algorithms for data science. The changing nature of acquisition and storage data has made the process of drawing inference infeasible with traditional statistical and machine learning methods. Modern data are often acquired in real time, in an incremental nature, and are often available in too large a volume to process on conventional machinery. The project proposes to study the family of stochastic majorisation-minimisation algorithms for computation of inf ....Stochastic majorization--minimization algorithms for data science. The changing nature of acquisition and storage data has made the process of drawing inference infeasible with traditional statistical and machine learning methods. Modern data are often acquired in real time, in an incremental nature, and are often available in too large a volume to process on conventional machinery. The project proposes to study the family of stochastic majorisation-minimisation algorithms for computation of inferential quantities in an incremental manner. The proposed stochastic algorithms encompass and extend upon a wide variety of current algorithmic frameworks for fitting statistical and machine learning models, and can be used to produce feasible and practical algorithms for complex models, both current and future.
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