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Sociologists have not neglected the study of relationships, but there remains no central definition of what a relationship is. This study offers a definition of relationships that supports a conceptual tool and visualization technique for analyzing relational processes that are otherwise difficult to model using standard ethnographic methods and social network analysis techniques. Grounded in the work of social psychologists and relational sociologists, the premise of this proposition is that relationships are both remembered and imagined. I maintain that relationships are molded by a flow of changing circumstances and dynamic cognitive processes, a characteristic that I refer to as disjointed fluidity. With data from my ethnographic study of doctoral student mentorship, I use this perspective to detail the mechanisms by which relationships are created, maintained, and dissolved. I go on to introduce a new computational ethnographic technique that visualizes relationship properties and characteristics of relational processes using cognitive–temporal depictions called pixels and flows. This book contributes to the efforts in relational sociology to build a universal conceptualization of relationships. It differs from existing literature in its focus on the elements of relationships and their function in social construction.

We examine and compare current practices in teaching preparation in U.S. accounting, finance, management, and economics doctoral programs.

We conduct an anonymous online survey of the pedagogical training practices experienced by Ph.D. students in accounting, finance, management, and economics programs in the United States.

Results indicate that accounting, finance, and management perform similarly with respect to providing doctoral students with first-hand teaching experience and requiring for-credit courses in teacher training. Accounting and management appear to utilize doctoral students as teaching assistants less than the other disciplines. A lower proportion of accounting doctoral students indicate that their program requires proof of English proficiency prior to teaching, and pedagogical mentoring is rare across disciplines. Accounting and management doctoral students feel more prepared to teach undergraduate courses compared to finance and economics students. However, all disciplines indicate a relative lack of perceived preparation to teach graduate courses.

This study provides empirical evidence of the current practices in pedagogical training of accounting, finance, management, and economics doctoral students.

The results highlight several areas where accounting could possibly improve with regard to pedagogical training in doctoral programs. In particular we suggest (1) changes in the teaching evaluation process, (2) development of teaching mentorships, (3) implementing a teaching portfolio requirement, and (4) incorporation of additional methods of assisting non-native English speakers for teaching duties.

The study fills a gap in the literature regarding the pedagogical training in accounting doctoral programs.

Recent educational initiatives by the Obama Administration have highlighted the need for more racial and ethnic diversity in Science, Technology, Engineering, and Mathematics (STEM) fields (The White House, 2011). While African Americans are underrepresented in faculty positions nationally, accounting for only 5.2% of all academic faculty across all disciplines (Harvey, W. B., & Anderson, E. L. (2005). Minorities in higher education: Twenty-first annual status report. Washington, DC: American Council on Education), the underrepresentation of African Americans in STEM fields such as computing science is even more severe. According to a recent Computing Research Association (CRA) Taulbee Survey, African Americans represent just 1.3% of all computing sciences faculty (CRA, 2006).

This paper examines the benefits of one program that specifically seeks to fulfill the Obama Administration’s initiatives by addressing this disparity in higher education.

The program helps prepare doctoral students for the academic job search process in an effort to increase the ranks of African American faculty in computing sciences.

Though STEM-related jobs have become a critical sector in the United States economy, there remains a severe employment shortage of eligible workers in these fields (Beyer, Rynes, Perrault, Hay, & Haller, 2003; National Science Foundation, 2009). The shortage of workers who possess the necessary skills to fulfill this growing sector of the economy are at a level last reached the middle of the 20th century (ACT, 2006; Jackson et al., in press). Even so, approximately 1.6 million supplementary workers with degrees in the computing sciences will be required to satisfy workforce demands according to the U. S. Department of Labor (Beyer et al., 2003; Hecker, 2001). Social misfortunes have played a significant role in the disproportioned participation rates of ethnic minorities in STEM fields. Although it could be argued that the field of computing sciences has moved to the forefront of STEM within this information-based global economy, very few African Americans productively contribute to the field (Carver, 1994; Gilbert, Jackson, George, Charleston, & Daniels, 2007).

There is currently a great deal of attention in psychometric and statistical methods on ensuring measurement invariance when examining measures across time or populations. When measurement invariance is established, changes in scores over time or across groups can be attributed to changes in the construct rather than changes in reaction to or interpretation of the measurement instrument. When measurement in not invariant, it is possible that measured differences are due to the measurement instrument itself and not to the underlying phenomenon of interest. This chapter discusses the importance of establishing measurement invariance specifically in postsecondary settings, where it is anticipated that individuals' perspectives will change over time as a function of their higher education experiences. Using examples from several measures commonly used in higher education research, the concepts and processes underlying tests of measurement invariance are explained and analyses are interpreted using data from a US-based longitudinal study on bioscience PhD students. These measures include sense of belonging over time and across groups, mental well-being over time, and perceived mentorship quality over time. The chapter ends with a discussion about the implications of longitudinal and group measurement invariance as an important conceptual property for moving forward equitable, reproducible, and generalizable quantitative research in higher education. Invariance methods may further be relevant for addressing criticisms about quantitative analyses being biased toward majority populations that have been discussed by critical theorists engaging quantitative research strategies.

This chapter shares the experiences of two graduate students as they navigated higher education during the pandemic. Engaging in graduate study during the pandemic shaped their socialisation experiences, challenged their understanding of themselves as scholars and impacted their relationships with mentors. This chapter shares personal reflections of their experiences and explores their sense of professional identity and aspirations for the future.