Task specialization across research careers

  1. Nicolas Robinson-Garcia  Is a corresponding author
  2. Rodrigo Costas
  3. Cassidy R Sugimoto
  4. Vincent Larivière
  5. Gabriela F Nane
  1. Delft University of Technology, Netherlands
  2. Leiden University, Netherlands
  3. Indiana University Bloomington, United States
  4. Université de Montréal, Canada

Abstract

Research careers are typically envisioned as a single path in which researchers start being one of a large number of researchers working under the guidance of one or more experienced scientists and, if they are successful, end with the individual leading their own research group and training future generations of scientists. Here we study the author contribution statements of published research papers in order to explore possible biases and disparities in career trajectories in science. We used Bayesian networks to train a prediction model based on a dataset of 70,694 publications from PLoS journals, which included 347,136 distinct authors and their associated contribution statements. This model was used to predict the contributions of 222,925 authors in 6,236,239 publications, and to apply a robust archetypal analysis to profile scientists across four career stages: junior, early-career, mid-career and late-career. All three of the archetypes we found - leader, specialized, and supporting - were encountered for early-career and mid-career researchers. Junior researchers displayed only two archetypes (specialized, and supporting), as did late-career researchers (leader and supporting). Scientists assigned to the leader and specialized archetypes tended to have longer careers than those assigned to the supporting archetype. We also observed consistent gender bias at all stages: the majority of male scientists belonged to the leader archetype, while the larger proportion of women belonged to the specialized archetype, especially for early-career and mid-career researchers.

Data availability

All data is openly accessible at http://doi.org/10.5281/zenodo.3891055

The following data sets were generated

Article and author information

Author details

  1. Nicolas Robinson-Garcia

    Delft Institute of Applied Mathematics, Delft University of Technology, Delft, Netherlands
    For correspondence
    elrobinster@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0585-7359
  2. Rodrigo Costas

    Centre for Science and Technology Studies, Leiden University, Leiden, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7465-6462
  3. Cassidy R Sugimoto

    School of Informatics and Computing, Indiana University Bloomington, Bloomington, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Vincent Larivière

    École de bibliothéconomie et des sciences de l'information, Université de Montréal, Montreal, Canada
    Competing interests
    The authors declare that no competing interests exist.
  5. Gabriela F Nane

    Delft Institute of Applied Mathematics, Delft University of Technology, Delft, Netherlands
    Competing interests
    The authors declare that no competing interests exist.

Funding

European Commission (707404)

  • Nicolas Robinson-Garcia

South African DST-NRF Centre for Excellence in Scientometrics and Science, Technology and Innovation Policy

  • Rodrigo Costas

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2020, Robinson-Garcia et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 2,290
    views
  • 258
    downloads
  • 23
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Nicolas Robinson-Garcia
  2. Rodrigo Costas
  3. Cassidy R Sugimoto
  4. Vincent Larivière
  5. Gabriela F Nane
(2020)
Task specialization across research careers
eLife 9:e60586.
https://doi.org/10.7554/eLife.60586
  1. Further reading

Further reading

    1. Biochemistry and Chemical Biology
    2. Microbiology and Infectious Disease
    Ana Patrícia Graça, Vadim Nikitushkin ... Gerald Lackner
    Research Article

    Mycofactocin is a redox cofactor essential for the alcohol metabolism of mycobacteria. While the biosynthesis of mycofactocin is well established, the gene mftG, which encodes an oxidoreductase of the glucose-methanol-choline superfamily, remained functionally uncharacterized. Here, we show that MftG enzymes are almost exclusively found in genomes containing mycofactocin biosynthetic genes and are present in 75% of organisms harboring these genes. Gene deletion experiments in Mycolicibacterium smegmatis demonstrated a growth defect of the ∆mftG mutant on ethanol as a carbon source, accompanied by an arrest of cell division reminiscent of mild starvation. Investigation of carbon and cofactor metabolism implied a defect in mycofactocin reoxidation. Cell-free enzyme assays and respirometry using isolated cell membranes indicated that MftG acts as a mycofactocin dehydrogenase shuttling electrons toward the respiratory chain. Transcriptomics studies also indicated remodeling of redox metabolism to compensate for a shortage of redox equivalents. In conclusion, this work closes an important knowledge gap concerning the mycofactocin system and adds a new pathway to the intricate web of redox reactions governing the metabolism of mycobacteria.

    1. Biochemistry and Chemical Biology
    2. Cell Biology
    Santi Mestre-Fos, Lucas Ferguson ... Jamie HD Cate
    Research Article

    Stem cell differentiation involves a global increase in protein synthesis to meet the demands of specialized cell types. However, the molecular mechanisms underlying this translational burst and the involvement of initiation factors remains largely unknown. Here, we investigate the role of eukaryotic initiation factor 3 (eIF3) in early differentiation of human pluripotent stem cell (hPSC)-derived neural progenitor cells (NPCs). Using Quick-irCLIP and alternative polyadenylation (APA) Seq, we show eIF3 crosslinks predominantly with 3’ untranslated region (3’-UTR) termini of multiple mRNA isoforms, adjacent to the poly(A) tail. Furthermore, we find that eIF3 engagement at 3’-UTR ends is dependent on polyadenylation. High eIF3 crosslinking at 3’-UTR termini of mRNAs correlates with high translational activity, as determined by ribosome profiling, but not with translational efficiency. The results presented here show that eIF3 engages with 3’-UTR termini of highly translated mRNAs, likely reflecting a general rather than specific regulatory function of eIF3, and supporting a role of mRNA circularization in the mechanisms governing mRNA translation.