Christian Steinfeldt’s research while affiliated with HTW Berlin - University of Applied Sciences and other places

Collaboration practices have been shown to be crucial determinants of scientific careers. We examine the effect of gender on coauthorship-based collaboration in mathematics, a discipline in which women continue to be underrepresented, especially in higher academic positions. We focus on two key aspects of scientific collaboration—the number of different coauthors and the number of single authorships. A higher number of coauthors has a positive effect on, e.g., the number of citations and productivity, while single authorships, for example, serve as evidence of scientific maturity and help to send a clear signal of one's proficiency to the community. Using machine learning-based methods, we show that collaboration networks of female mathematicians are slightly larger than those of their male colleagues when potential confounders such as seniority or total number of publications are controlled, while they author significantly fewer papers on their own. This confirms previous descriptive explorations and provides more precise models for the role of gender in collaboration in mathematics.

The interplay between an academic's gender and their scholarly output is a riveting topic at the intersection of scientometrics, data science, gender studies, and sociology. Its effects can be studied to analyze the role of gender in research productivity, tenure and promotion standards, collaboration and networks, or scientific impact, among others. The typical methodology in this field of research is based on a number of assumptions that are customarily not discussed in detail in the relevant literature, but undoubtedly merit a critical examination. Presumably the most confronting aspect is the categorization of gender. An author's gender is typically inferred from their name, further reduced to a binary feature by an algorithmic procedure. This and subsequent data processing steps introduce biases whose effects are hard to estimate. In this report we describe said problems and discuss the reception and interplay of this line of research within the field. We also outline the effect of obstacles, such as non-availability of data and code for transparent communication. Building on our research on gender effects on scientific publications, we challenge the prevailing methodology in the field and offer a critical reflection on some of its flaws and pitfalls. Our observations are meant to open up the discussion around the need and feasibility of more elaborated approaches to tackle gender in conjunction with analyses of bibliographic sources.