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

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 base...

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Main Authors: Ann-Maree Vallence, Mark R Hinder, Hakuei Fujiyama
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2019-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0220481
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spelling doaj-63556335187f487f99ac118eebb21dae2021-03-03T19:52:12ZengPublic Library of Science (PLoS)PLoS ONE1932-62032019-01-01147e022048110.1371/journal.pone.0220481Data-driven selection of conference speakers based on scientific impact to achieve gender parity.Ann-Maree VallenceMark R HinderHakuei FujiyamaA 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.https://doi.org/10.1371/journal.pone.0220481
collection DOAJ
language English
format Article
sources DOAJ
author Ann-Maree Vallence
Mark R Hinder
Hakuei Fujiyama
spellingShingle Ann-Maree Vallence
Mark R Hinder
Hakuei Fujiyama
Data-driven selection of conference speakers based on scientific impact to achieve gender parity.
PLoS ONE
author_facet Ann-Maree Vallence
Mark R Hinder
Hakuei Fujiyama
author_sort Ann-Maree Vallence
title Data-driven selection of conference speakers based on scientific impact to achieve gender parity.
title_short Data-driven selection of conference speakers based on scientific impact to achieve gender parity.
title_full Data-driven selection of conference speakers based on scientific impact to achieve gender parity.
title_fullStr Data-driven selection of conference speakers based on scientific impact to achieve gender parity.
title_full_unstemmed Data-driven selection of conference speakers based on scientific impact to achieve gender parity.
title_sort data-driven selection of conference speakers based on scientific impact to achieve gender parity.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2019-01-01
description 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.
url https://doi.org/10.1371/journal.pone.0220481
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AT hakueifujiyama datadrivenselectionofconferencespeakersbasedonscientificimpacttoachievegenderparity
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