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Lokanan, Mark 2023-06-26 This dataset consists of textual transcript analysis from the Parliamentary Commission on Banking Standards on tax avoidance in the U.K. The data is used to examines the moral and legal underpinnings of corporate tax avoidance. Cast in terms of a totemic symbol that brand tax avoidance as within the purview of the law, the paper invokes the attributional frames of the new sociology of morality to examine the position of both the moral advocates and the amoral critics of aggressive tax avoidance.
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Lokanan, Mark 2022-09-28 This research aims to examine investment fraud cases in Canada by coding cases retrieved from the Investment Industry Regulatory Organization of Canada's website. The dataset consists of features related to enforcement, offenders, and victims and consists of numeric, float, and categorical variables. This research will contribute to understanding investment fraud in Canada and provide information that can be used to prevent and detect investment fraud.
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Lokanan, Mark 2022-10-05 The purpose of this dataset is to build machine learning classifiers to predict exploitation of securities fraud victims in Canada. The dataset consists of numeric, float, and categorical variables. The dataset also consist of features related to victims’ demographics, financial profile, and investments. This work was done with funding from a SSHRC Insight Development Grant

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