The increased interest in analyzing and explaining gender inequalities in tech, media, and academia highlights the need for accurate inference methods to predict a person's gender from their name. Several such services exist that provide access to large databases of names, often enriched with information from social media profiles, culture-specific rules, and insights from sociolinguistics. We compare and benchmark five nameto-gender inference services by applying them to the classification of a test data set consisting of 7,076 manually labeled names. The compiled names are analyzed and characterized according to their geographical and cultural origin. We define a series of performance metrics to quantify various types of classification errors, and define a parameter tuning procedure to search for optimal values of the services' free parameters. Finally, we perform benchmarks of all services under study regarding several scenarios where a particular metric is to be optimized.

Despite the increasing number of women graduating in mathematics, a systemic gender imbalance persists and is signified by a pronounced gender gap in the distribution of active researchers and professors. Especially at the level of university faculty, women mathematicians continue being drastically underrepresented, decades after the first affirmative action measures have been put into place. A solid publication record is of paramount importance for securing permanent positions. Thus, the question arises whether the publication patterns of men and women mathematicians differ in a significant way. Making use of the zbMATH database, one of the most comprehensive metadata sources on mathematical publications, we analyze the scholarly output of ∼150,000 mathematicians from the past four decades whose gender we algorithmically inferred. We focus on development over time, collaboration through coautorships, presumed journal quality and distribution of research topics—factors known to have a strong impact on job perspectives. We report significant differences between genders which may put women at a disadvantage when pursuing an academic career in mathematics.

Abstract. Let f : C → C be a transcendental entire map that is subhyperbolic, i.e., the intersection of the Fatou set F (f ) and the postsingular set P (f ) is compact and the intersection of the Julia set J (f ) and P (f ) is finite. Assume that no asymptotic value of f belongs to J (f ) and that the local degree of f at all points in J (f ) is bounded by some finite constant. We prove that there is a hyperbolic map g ∈ {z → f (λz) : λ ∈ C} with connected Fatou set such that f and g are semiconjugate on their Julia sets. Furthermore, we show that this semiconjugacy is a conjugacy when restricted to the escaping set I(g) of g. In the case where f can be written as a finite composition of maps of finite order, our theorem, together with recent results on Julia sets of hyperbolic maps, implies that J (f ) is a pinched Cantor bouquet, consisting of dynamic rays and their endpoints. Our result also seems to give the first complete description of topological dynamics of an entire transcendental map whose Julia set is the whole complex plane.

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.

For a polynomial p with a repelling fixed point z 0 , we consider Poincaré functions of p at z 0 , i.e. entire functions L which satisfy L(0) = z 0 and p(L(z)) = L(p ′ (z 0 ) · z) for all z ∈ C. We show that if the component of the Julia set of p that contains z 0 equals {z 0 }, then the (fast) escaping set of L is a spider's web; in particular it is connected. More precisely, we classify all linearizers of polynomials with regards to the spider's web structure of the set of all points which escape faster than the iterates of the maximum modulus function at a sufficiently large point R.