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This paper aims to analyse two large-scale business case studies for the benefits of using AI, computer science and machine learning to assess, recruit and retain staff.

The authors interrogate two large-scale case studies, including metrics on the success of AI in relation to user experience, compatibility, psychometric benchmarking.

The authors conclude that AI removes bias from assessment, recruitment and training processes and can save businesses significant time and resources as well as improve the cultural fit and diversity of their recruits. There is a balance to be struck, though, as the systems used are only as good as the science supporting the selection – and humans must ultimately retain the role of decision makers.

These business case studies are examined in detail for the first time in this paper.

This inquiry is a theoretical analysis that attempts to identify the features of school structure that efficiently promote positive outcomes of organization, while limiting negative consequences that are often associated with bureaucratic structures. To that end, the concepts of enabling structures and mindful organizations are developed, contrasted, and synthesized. Then, the research and practical implications of enabling and mindful school structures are proposed and discussed.

The pupil control ideology (PCI) studies originated at The Pennsylvania State University under the direction of Professor Donald J. Willower. Describes the beginning and evolution of the PCI studies and the role of theory in their development. PCI inquiry is now in its fourth decade and the concept of pupil control ideology and its measure (PCI form) continue to be useful to researchers as they analyze behavior in school organizations.