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1 to 4 of 4 Results
Jun 26, 2023
Lokanan, Mark, 2023, "The Morality and Tax Avoidance: A Sentiment and Position Taking Analysis", https://doi.org/10.5683/SP3/6ITXEI, Borealis, V1, UNF:6:PcCTl842dS5P1OtsLHgqYA== [fileUNF]
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 avo...
Oct 5, 2022
Lokanan, Mark, 2022, "Fraud Exploitation", https://doi.org/10.5683/SP3/UMZH4V, Borealis, V1
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...
Sep 28, 2022
Lokanan, Mark, 2022, "Determinants of Investment Fraud", https://doi.org/10.5683/SP3/Q3K08Q, Borealis, V1
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 c...
Mar 4, 2021
Hodson, Jaigris; Veletsianos, George, 2021, "Inoculating against an infodemic: microlearning interventions to address CoV misinformation", https://doi.org/10.5683/SP2/DJNPQV, Borealis, V1
The dataset was created as part of the CIHR-funded project, 'Inoculating against an infodemic: Microlearning interventions to address CoV misinformation'. This research examines digital misinformation flows pertaining to the 2020 COVID-19 pandemic for the purpose of developing ed...
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