2018
DOI: 10.1002/jls.21566
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Unconscious Gender Bias: Implications for Women's Leadership Development

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Cited by 76 publications
(92 citation statements)
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“…Overall, these issues strengthen the importance of evidence‐based research to further understand the extent and nature of bias, including the underlying beliefs and determinants and how best to address these at individual and organisational and systems levels to support equity for all (as noted by Keane) . As we outlined in our original article, the Athena SWAN (Scientific Women's Academic Network) charter has shown that organisational and systems level change, along with measurement and transparent reporting, is necessary for progress towards equity in academia.…”
mentioning
confidence: 77%
See 1 more Smart Citation
“…Overall, these issues strengthen the importance of evidence‐based research to further understand the extent and nature of bias, including the underlying beliefs and determinants and how best to address these at individual and organisational and systems levels to support equity for all (as noted by Keane) . As we outlined in our original article, the Athena SWAN (Scientific Women's Academic Network) charter has shown that organisational and systems level change, along with measurement and transparent reporting, is necessary for progress towards equity in academia.…”
mentioning
confidence: 77%
“…Unconscious or implicit bias is proposed as a contributor to inequity in health care leadership. While we acknowledge Keane's comments on the lack of formal evidence regarding implicit bias, based on research, personal and shared experiences of hundreds of women through our leadership programs and from cross‐sector reports, unconscious or implicit bias appears to permeate the lived experiences of women in many fields including medicine. Here, we firmly agree and indeed propose that more research is needed to understand the extent, nature and impact of this bias …”
mentioning
confidence: 96%
“…A stream of work has shown that such biases are particularly powerful in the domain of people ' s perception. For example, studies have shown that people often hold negative implicit attitudes based on gender or group memberships that leads to prejudiced judgments (Madsen & Andrade, 2018 ).…”
Section: Unconscious Biasmentioning
confidence: 99%
“…As outlined by recent Big Data Analytics studies considering decades of scientific careers (Huang et al, 2020;Odic and Wojcik, 2019;Chavatzia, 2017), gender disparities in science cannot be explained by intrinsic differences in attitudes to science between genders but rather have to be traced in the establishment of implicit gender biases promoted by news media and by social media representations of science (Shapiro and Williams, 2012;Moss-Racusin et al, 2012;Madsen and Andrade, 2018;Steinke, 2017). In this way, the reconstruction of mindsets vehiculated by information systems becomes a key point for understanding, acting upon and closing the gender gap in science.…”
Section: Towards a Cognitive Approach To Information Processingmentioning
confidence: 99%