Bias Amplification in Gender, Gender Identity, and Geographical Affiliation.
Journal
Journal of chemical information and modeling
ISSN: 1549-960X
Titre abrégé: J Chem Inf Model
Pays: United States
ID NLM: 101230060
Informations de publication
Date de publication:
26 12 2022
26 12 2022
Historique:
pubmed:
20
5
2022
medline:
28
12
2022
entrez:
19
5
2022
Statut:
ppublish
Résumé
In the quest for greater equity in science, individual attitudes and institutional policies should also embrace greater diversity and inclusion of minority groups. This viewpoint calls for a broader definition of gender bias in STEM to include gender identity and for increased attention to the issue of bias amplification due to geographic affiliation in the field of computational chemistry and chemoinformatics. It briefly discusses some active interventions to tackle bias on gender, gender identity, and geographic affiliation in STEM.
Identifiants
pubmed: 35587272
doi: 10.1021/acs.jcim.2c00533
pmc: PMC9795548
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
6297-6301Références
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