Cyber attacks continue to increase in frequency and variety, making cyber malfeasance a rising area of study and a major policy issue. Categorizing cyber attackers aids targeted organizations in efficiently directing resources to enhance security. However, extant hacker typologies do not fully account for the multifaceted nature of cyber malfeasance, including the rise in socially and ideologically motivated hacking (e.g. crowdsourcing, hacktivism). I clarify the current state of field by uniting recent case studies on hackers with existing categorization techniques. Previous researchers have employed circumplex models-visualizations which depict relationships and boundaries between groups-as a way to visually organize hacker types. I propose an updated model-a weighted arc circumplex model-that is designed to represent the multidimensional nature of contemporary hacker types by offering a means of visually representing multiple motivations simultaneously. Finally, I demonstrate how archetypical circumplex models can be wed with sociograms to depict social and technical relationships between hacker groups.

We examine how an assistant coach's race and the race of his supervisor (the head coach) interact to affect future job quality. While past research argues that homophily is beneficial to job mobility, we find differential effects based on the race. OLS and OLR regression analyses on the quality of one's first head coaching job in NCAA men's basketball indicate that black assistant coaches working under black head coaches (black homophily) are significantly disadvantaged compared to all other racial combinations: white assistants with white supervisors (white homophily), white assistants with black supervisors (white heterophily), and black assistants with white supervisors (black heterophily). In contrast, there is no significant difference in job quality among the latter three groups: white homophily, white heterophily, and black heterophily. This indicates that while homophily is neither advantageous nor disadvantageous for whites, it is disadvantageous for black job candidates. This racially based disadvantage makes it difficult for minority job candidates to break through the glass ceiling and has real-world financial implications.

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We examine how race affects the employment status of subordinates following a job change by their immediate supervisors. We test whether racial homophily between a subordinate and a supervisor affects the odds of being let go. We also consider whether a racial match between an incoming head coach and assistant affects whether assistants retain their assistant coaching position. Data for these analyses come from a unique data set that explores what happens to 704 NCAA Division I college basketball assistant coaches after the head coach leaves the school. Logistic regression analyses confirm the benefit of working for a white head coach as this decreases the likelihood of being let go, compared to more positive outcomes such as following the coach to a new school, being internally promoted or retained after the head coach's departure. Furthermore, racial homophily with incoming head coaches insulates subordinates from having to search for new employment by increasing the likelihood of assistants being retained.

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