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Current Selection
Status : Active
Scheme : Discovery Projects
Research Topic : MENTAL RETARDATION
Australian State/Territory : ACT
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  • Active Funded Activity

    Discovery Projects - Grant ID: DP240100108

    Funder
    Australian Research Council
    Funding Amount
    $765,745.00
    Summary
    Thwarted Identity: The Missing Link Between Psychopathology and Prejudice. Prejudice and the extremist violence that arises from it are typically explained either by the psychopathology of individual perpetrators, or by their membership of extremist groups. This project will seek to reconcile these competing explanations and resolve this impasse that has obstructed progress in combating prejudice. This project develops a new framework specifying causal and reciprocal links between the novel conc .... Thwarted Identity: The Missing Link Between Psychopathology and Prejudice. Prejudice and the extremist violence that arises from it are typically explained either by the psychopathology of individual perpetrators, or by their membership of extremist groups. This project will seek to reconcile these competing explanations and resolve this impasse that has obstructed progress in combating prejudice. This project develops a new framework specifying causal and reciprocal links between the novel concept of thwarted identity, psychopathology, ideology, and prejudice. Expected outcomes are new policy solutions and novel targets for interventions to reduce prejudice and extremist violence, which will deliver significant benefit by addressing these pernicious social problems.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP200100219

    Funder
    Australian Research Council
    Funding Amount
    $428,350.00
    Summary
    Emotions and Employee Turnover: New Methods for Complex Dynamic Systems. This project aims to vastly improve the data-analytic capabilities of social and health researchers, while increasing knowledge about emotion dynamics and their link to employee turnover. By drawing on and advancing methods from ecology and applied physics, this project plans to investigate the role that individual emotions play in employee turnover with new quantitative methods for characterising and testing causality in c .... Emotions and Employee Turnover: New Methods for Complex Dynamic Systems. This project aims to vastly improve the data-analytic capabilities of social and health researchers, while increasing knowledge about emotion dynamics and their link to employee turnover. By drawing on and advancing methods from ecology and applied physics, this project plans to investigate the role that individual emotions play in employee turnover with new quantitative methods for characterising and testing causality in complex dynamic systems. The expected outcomes include an improved capacity for researchers, managers, and policy makers to understand complex organisational, economic, and health systems. This will provide immediate societal benefits by informing the development and deployment of targeted interventions in such systems.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP190101294

    Funder
    Australian Research Council
    Funding Amount
    $380,000.00
    Summary
    Improving the specificity of affective computing via multimodal analysis. This project aims to develop multimodal affective sensing techniques that can sense very subtle expressions in human moods and emotions. Much research in affective computing has investigated ways to improve the sensitivity of affect sensing approaches, resulting in more accurate estimates of affective states such as emotions or mood. What remains unsolved so far is the issue of specificity. This project will address this i .... Improving the specificity of affective computing via multimodal analysis. This project aims to develop multimodal affective sensing techniques that can sense very subtle expressions in human moods and emotions. Much research in affective computing has investigated ways to improve the sensitivity of affect sensing approaches, resulting in more accurate estimates of affective states such as emotions or mood. What remains unsolved so far is the issue of specificity. This project will address this issue through novel analyses of very subtle cues in facial and vocal expressions of affect embedded in a multimodal deep learning framework. Current approaches can successfully assist in binary classification tasks. This project will tackle the much more difficult problem of developing advanced affective sensing technology to simultaneously handle homogeneous and heterogeneous affect classes as well as continuous range estimates of affect intensity.
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