The 9th Atlanta Conference on Science and Innovation Policy (ATLC 2023) was held between May 24th – 26th at the Georgia Institute of Technology. Our research group took part in it by presenting «Informetric methods for studying the diversity of the scientific workforce: towards a state-of-the-art» authored by Nicolás Robinson-García, Carmen Corona-Sobrino, Zaida Chinchilla-Rodríguez, Daniel Torres-Salinas and Rodrigo Costas. The work dealt with the following:
«Background and rationale Evaluative processes struggle with the notion of diversity of a scientific workforce (Walsh et al., 2019). Despite overwhelming evidence on the need for diverse teams in terms of division of labor (Robinson-Garcia et al., 2020), ethnic mix (Freeman & Huang, 2015) or gender (Díaz-García et al., 2013; Maddi & Gingras, 2021) among others, bibliometric methods have traditionally been focused on the development of impact and productivity indicators. Recently, the development of machine learning algorithms, new data sources and strong calls for action favoring an open and diverse scientific ecosystem, have given room to a stream of studies focused on studying different aspects of career trajectories, diversity of profiles or biases in science. In this paper we attempt at reviewing recent advances in the development of novel informetric approaches and methods to study diversity in science. Specifically, we focus on those related to the scientific workforce.»
Take a look at the presentation delivered by Nicolás. You can also access the full program and abstracts book.