Modeling gender differences in the job promotion process: Replication and extension of Martell et al. (1996).

Differences in employee evaluations due to gender bias may be small in any given rating cycle, but they may accumulate to produce large disparities in the number of women and men promoted to the top of an organization. A highly cited simulation by Martell et al. (1996) demonstrates this cumulative advantage process in a multilevel organization. We replicated this simulation to uncover important details about its operating assumptions, and we extended the simulation to examine a range of variables that may impact the cumulative effects of gender bias. The replication revealed that the male cumulative advantage in the Martell et al. simulation requires (a) decades of typical promotion cycles to produce, (b) constant mean differences in the performance ratings of women and men but equal within-group variances, and (c) attrition that occurs randomly at a low and constant rate. Our extended simulation demonstrates that (a) cumulative effects of gender bias are higher when the attrition rate is lower, (b) gender biases are mitigated when attrition is more strongly associated with good or poor performance, and (c) the cumulative effects of mean gender differences in performance ratings can often be smaller than the cumulative effects of variance differences between gender subgroups. Results suggest that talent development and recognition of high performers might have a greater positive impact on female representation at top levels of a firm than programs aimed at reducing bias in employee evaluations. We encourage additional simulation work that further explores the dynamics of cumulative advantage in employment settings. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Designing microbial consortia with defined social interactions.

Designer microbial consortia are an emerging frontier in synthetic biology that enable versatile microbiome engineering. However, the utilization of such consortia is hindered by our limited capacity in rapidly creating ecosystems with desired dynamics. Here we present the development of synthetic communities through social interaction engineering that combines modular pathway reconfiguration with model creation. Specifically, we created six two-strain consortia, each possessing a unique mode of interaction, including commensalism, amensalism, neutralism, cooperation, competition and predation. These consortia follow distinct population dynamics with characteristics determined by the underlying interaction modes. We showed that models derived from two-strain consortia can be used to design three- and four-strain ecosystems with predictable behaviors and further extended to provide insights into community dynamics in space. This work sheds light on the organization of interacting microbial species and provides a systematic framework-social interaction programming-to guide the development of synthetic ecosystems for diverse purposes.