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This paper introduces a method by which researchers can assess the strength of their status manipulations in experimental research by comparing them against Monte Carlo simulated distributions that use aggregate Status Characteristics Theory (SCT) data.

This paper uses Monte Carlo methods to simulate the m and q parameter distributions and the proportion of stay (P(s)) score distributions for four commonly used status situations. It also presents findings from an experiment that highlight the processes by which researchers can utilize these simulated distributions in their assessment of novel status manipulations.

Findings indicate that implicitly relevant status manipulations have considerably more overlapping P(s) scores in the simulated distributions of high and low states of a status characteristic than explicitly relevant status manipulations. Findings also show that a novel status manipulation, the handedness manipulation, sufficiently creates high- and low-status differences in P(s) scores.

Future researchers can use these simulated distributions to plot the mean P(s) scores of each of their experimental conditions on the overlapping distribution for the corresponding status manipulation. Manipulations that produce scores that fall outside of the range of overlapping values are also likely to create status differences between conditions in other settings or populations.

We detail the evolution of open interaction coding schemes that have long been used to capture behavioral indicators of the power and prestige order in status characteristics research. Although the theoretical variables ostensibly measured with these methods are few and explicit, the implementation of open interaction coding is not standardized and different projects have keyed on different specific behaviors. We argue that open interaction coding could benefit from the utilization of a more refined and standardized coding scheme. We offer precise operational definitions and some illustrations from our own recent projects in hopes of fostering more transparency in future research.

Advances in Group Processes publishes theoretical analyses, reviews, and theory-based empirical chapters on group phenomena. The series adopts a broad conception of “group processes.” This includes work on groups ranging from the very small to the very large, and on classic and contemporary topics such as status, power, trust, justice, influence, decision-making, intergroup relations, and social networks. Previous contributors have included scholars from diverse fields including sociology, psychology, political science, business, philosophy, computer science, mathematics, and organizational behavior.