Helen Meskhidze

There has been significant interest in addressing the underrepresentation of various demographic groups in philosophy. Indeed, many have proposed remedies at the disciplinary level. However, underrepresentation is an issue that varies by subfield in philosophy. Women, for example, are especially underrepresented in subfields considered formal (e.g., logic). As has already been argued in the existing literature, addressing underrepresentation, even within subfields, is not as simple as recruiting more students from underserved populations. Instead, we advocate for a student-centered approach, promoting inclusive pedagogy. In this paper, we share a case study in which we implemented feminist and trauma-informed interventions in two undergraduate formal logic courses and investigated their impact with respect to elements of structural injustice. We found that our interventions successfully eliminated existing gender-based differences in perceptions of self-efficacy and largely diminished students’ perceptions of the objectivity of logic, but were unsuccessful at changing students’ impressions of the broader applicability of logic. By sharing our interventions, we hope to provide educators with practical tools and ideas for implementing similar approaches in their classrooms. By sharing our results, we invite educators to reflect on the potential impact of similar approaches in formal philosophy courses and on tools for measuring that impact.

There has been much interest in the recent philosophical literature on increasing the reliability and trustworthiness of computer simulations. One method used to investigate the reliability of computer simulations is code comparison. Gueguen, however, has offered a convincing critique of code comparisons, arguing that they face a critical tension between the diversity of codes required for an informative comparison and the similarity required for the codes to be comparable. Here, I reflect on her critique in light of a recent code comparison investigating self-interacting dark matter in two computer simulation codes. I argue that the informativeness of this particular code comparison was due to its targeted approach and narrow focus. Its targeted approach (i.e., only the dark matter modules) allowed for simulation outputs that were diverse enough for an informative comparison and yet still comparable. Understanding the comparison as an instance of eliminative reasoning narrowed the focus: we could investigate whether code-specific differences in implementation contributed significantly to the results of self-interacting dark matter simulations. Based on this case study, I argue that code comparisons can be conducted in such a way that they serve as a method for increasing our confidence in computer simulations being, as Parker defines, adequate-for-purpose.