Task specialization across research careers

bioRxiv (Cold Spring Harbor Laboratory)

Abstract

Abstract Scientific careers are conceived as one unique pathway which scientists must follow to succeed. We report the diversity of profiles scientists exhibit based on their contributorship and look into biases in their career trajectory. We use Bayesian networks to train a prediction model based on a dataset of 70,694 publications from PLoS journals representing 347,136 distinct authors and their associated contribution statements. This model is used to predict the contributions of 222,925 authors in 6,236,239 publications, and apply a robust archetypal analysis to profile scientists by career stage. We divide scientific careers into four stages: junior, early-career, mid-career and late-career. Three scientific archetypes are found throughout the four career stages: leader, specialized, and supporting. All three archetypes are encountered for the early- and mid-career stages, whereas for junior and late-career stages only two archetypes are found. Scientists assigned to the leader and specialized archetypes tend to have longer careers than researchers who belong to the supporting archetype. There is consistent gender bias at all stages: the majority of male scientists belong to the leader archetype, while the larger proportion of women belong to the specialized archetype, especially for early and mid-career researchers.

Authors 5

1. Nicolás Robinson‐García corresponding

   Delft University of Technology

   Affiliation as printed

   Delft Institute of Applied Mathematics (DIAM)

   Delft Institute of Applied Mathematics (DIAM), TU Delft, 2628 XE, Delft, The Netherlands

2. Rodrigo Costas Aachen Centre for Science and Technology Studies

   Leiden University · Stellenbosch University

   Affiliation as printed

   Centre for Research on Evaluation, Science and Technology (CREST), Stellenbosch University

   Centre for Science and Technology Studies (CWTS)

   Centre for Research on Evaluation, Science and Technology (CREST), Stellenbosch University, Stellenbosch, South Africa

   Centre for Science and Technology Studies (CWTS), Leiden University, 333 AL, Leiden, The Netherlands

3. Cassidy R. Sugimoto

   Indiana University Bloomington · Indiana University

   Affiliation as printed

   School of Informatics, Computing, and Engineering, Indiana University Bloomington

   School of Informatics, Computing, and Engineering, Indiana University Bloomington, IN 708,Bloomington, U.S.A

4. Vincent Larivière

   Université de Montréal

   Affiliation as printed

   École de bibliothéconomie et des sciences de l’information, Université de Montréal

   École de bibliothéconomie et des sciences de l'information, Université de Montréal, H3T 1N8, Montreal, Canada

5. Gabriela F. Nane

   Delft University of Technology

   Affiliation as printed

   Delft Institute of Applied Mathematics (DIAM)

   Delft Institute of Applied Mathematics (DIAM), TU Delft, 2628 XE, Delft, The Netherlands