Work

Data-driven selection of conference speakers based on scientific impact to achieve gender parity

Year: 2019

Type: article

Abstract: A lack of diversity limits progression of science. Thus, there is an urgent demand in science and the wider community for approaches that increase diversity, including gender diversity. We developed a novel, data-driven approach to conference speaker selection that identifies potential speakers based on scientific impact metrics that are frequently used by researchers, hiring committees, and funding bodies, to convincingly demonstrate parity in the quality of peer-reviewed science between men and women. The approach enables high quality conference programs without gender disparity, as well as generating a positive spiral for increased diversity more broadly in STEM.

Source: PLoS ONE

DOI: 10.1371/journal.pone.0220481

Authors: Ann-Maree Vallence, Mark R. Hinder, Hakuei Fujiyama

Institutions: Murdoch University, University of Tasmania

Language: English

Topic: scientometrics and bibliometrics research

Subfield: Statistics, Probability and Uncertainty

Field: Decision Sciences

Domain: Social Sciences

SDGs: Gender equality, Reduced inequalities

Open Access status: gold

Estimated APC paid: $1,595