<p> The goal of this quantitative non-experimental, correlational research study was to examine what individual characteristics correlated with the decision-making processes of students pursuing an undergraduate degree in criminal justice. The sample was drawn from students at several traditional (brick and mortar) degree programs, and once institutional review boards approval were gained, data collection commenced. The Congruent and Incongruent Moral Dilemma&rsquo;s test of dual-process, developed by Conway and Gawronski (2013), was used to collect data concerning ethical decision-making. The survey was collected through Survey Monkey and the data were analyzed using IBM SPSS 24 software. Of the 313 responses collected, 138 were usable. The participants were asked to choose between what was an acceptable (congruent dilemmas showing utilitarianism) or unacceptable harm (incongruent dilemmas showing deontology) in a series of ethical decision-making scenarios. The differences between the two dilemmas were found to have significance. The results indicated that age and education (criminal justice versus other majors) were significant, but not as predictors of ethical decision-making; with criminal justice majors having a higher selection of deontology than non-majors. Gender was the significant predictor of ethical decision-making. Women, having higher levels of deontology than men. Results found that with increased religious attendance, and those without military experience had higher levels of deontology but were not significant predictors of ethical decision-making. Furthermore, as individuals increased their socio-economic status there was a decrease in deontological inclinations. Finally, the results of traditional on-campus program and non-traditional program students was not a significant predictor of ethical decision-making. These findings are evidence that individual characteristics influence deontological and utilitarian inclinations and help resolve some of the theoretical ambiguities in prior research. This research can help inform academic institutions, criminal justice organizations, and students preparing for a career in public safety to be better prepared to make quick and ethical decisions in the field and help focus training and educational programs to assist with this process.</p><p>

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The development of predictive biomarkers in neuroscience is increasingly enabling bioprediction of adverse behavioural events, from psychosis to impulsive violent reaction. Because many brain-based disorders can be thought of as end-states of a long development, bioprediction carries immense therapeutic potential. In this thesis, I analyse issues raised by the development of bioprediction of brain-based disorder. I argue that ethical analysis of probabilities and risk information bioprediction provides is confounded by philosophical and social structures that have, until recently, functioned nominally well by assuming categorical (binary) concepts of disorder, especially regarding brain-disorder. Through an analysis of the philosophical concept of disorder, I argue that we can and ought to reorient disorder around probability of future harm and stratify disorder based on the magnitude of risk. Rejection of binary concepts in favour of this non-binary (probability-based) one enables synergy with bioprediction and circumnavigation of ethical concerns raised about proposed disorders of risk in psychiatry and neurology; I specifically consider psychosis and dementia risk. I then show how probabilistic thinking enables consideration of the implications of bioprediction for two areas salient in mental health: moral responsibility and justice. Using the example of epilepsy and driving as a model of obligations to protect others against risk of harm, I discuss how the development of bioprediction is poised to enhance moral responsibility. I then engage with legal cases and science surrounding a predictive biomarker of impulsive violent reaction to propose that bioprediction can sometimes rightly diminish responsibility. Finally, I show the relevance of bioprediction to theories of distributive justice that assign priority to the worse off. Because bioprediction enables the identification of those who are worse off in a way of which we have previously been ignorant, a commitment to assign priority to the worse off requires development of and equal access to biopredictive technologies.