EASE Awards for the EASE Journal, European Science Editing in 2022/23

Best original research paper or review paper as voted by members
Winner – Impact of war on editors of science journals from Ukraine: Results of a survey
Authors: Maryna Zhenchenko, Iryna Izarova, Yulia Baklazhenko, Ukraine
Best reviewer voted by the Editorial Team
Winner - Roohi Ghosh, Ambassador, Researcher Outreach, Engagement, and Success, Cactus Communications (CACTUS), India
Best Original Research or Review paper awarded by the ESE Editorial Advisory Board
Winner – Needs of early-career professionals in STM: Findings from two surveys
Authors: Erin Foley, Rachel Moriarty, Kerys Martin
The panel thought this was a great study on workplace cultures that affect many EASE members and our extended network of colleagues. It contains many enlightening results, and prompts activities that the publishing industry (and our own committees at EASE!) might wish to address and get organisations thinking more about the needs of their early career employees and members.
Knowing how to support people at early stages of their careers, and being active in doing so is really important, and this is a valuable addition to the literature providing organisations take heed! We look forward to the third iteration of this project!
Best Viewpoint paper awarded by the ESE Editorial Advisory Board
Winner – Challenges of qualitative data sharing in social sciences
Author: Tanja Vuckovic Juros
The awards panel agreed this highlights a field where there is a growing amount of discussion (and ‘anecdata’) and, this paper captures some prominent issues well.
The social sciences and humanities are often a secondary consideration or overlooked entirely in much of the discussions around research and research practices. This viewpoint reflects on the implications of reward structures and cultural pressures towards transparency and open science practices that risk penalizing the social sciences, for its own best practices of ethical and integrity considerations for handling qualitative data.