Biblio

This project addresses a classic employment law question in Canada and elsewhere using machine learning approach: how do we know whether a worker is an employee or an independent contractor? This is a central issue for self-represented litigants insofar as these two legal categories entail very different rights and employment protections. In this interdisciplinary research study, we collaborated with the Conflict Analytics Lab to develop machine learning models aimed at determining whether a worker is an employee or an independent contractor. We present a number of supervised learning models including a neural network model that we implemented using data labeled by law researchers and compared the accuracy of the models. Our neural network model achieved an accuracy rate of 91.5%. A critical discussion follows to identify the key features in the data that influence the accuracy of our models and provide insights about the case outcomes.

Digitalization of production and management as the imperatives of Industry 4.0 stipulated the requirements of state regulators for informing and training personnel of a significant object of critical information infrastructure. However, the attention of industrial enterprises to this problem is assessed as insufficient. This determines the relevance and purpose of this article - to develop a methodology and tool for raising the awareness of workers of an industrial enterprise about information security (IS) of significant objects of critical information infrastructure. The article reveals the features of training at industrial enterprises associated with a high level of development of safety and labor protection systems. Traditional and innovative methods and means of training personnel at the workplace within the framework of these systems and their opportunities for training in the field of information security are shown. The specificity of the content and forms of training employees on the security of critical information infrastructure has been substantiated. The scientific novelty of the study consists in the development of methods and software applications that can perform the functions of identifying personal qualities of employees; testing the input level of their knowledge in the field of IS; testing for knowledge of IS rules (by the example of a response to socio-engineering attacks); planning an individual thematic plan for employee training; automatic creation of a modular program and its content; automatic notification of the employee about the training schedule at the workplace; organization of training according to the schedule; control self-testing and testing the level of knowledge of the employee after training; organizing a survey to determine satisfaction with employee training. The practical significance of the work lies in the possibility of implementing the developed software application in industrial enterprises, which is confirmed by the successful results of its testing.