The biomedical sciences have a problem retaining white women and underrepresented minorities in academia. Despite increases in the representation of these groups in faculty candidate pools, they are still underrepresented at the faculty level, particularly at the Full Professor level. The lack of diverse individuals at the Full Professor level contributes to the attrition of women and under-represented minorities, as it confirms unconscious biases. The presence of unconscious biases contribute to feelings of not belonging by trainees and are amplified by visual representation of who is presented as the “top scientist in their field”. Top scientists are not only defined by the attainment of Full Professorships, but also through invited seminar series. Invitations for faculty to present their research at other university departments is highly valued offer that provides an opportunity for collaborations and networking. However, if invited speakers do not represent the demographics of current trainees, these visual representations of successful scientists may contribute to decreased attitudes of self-identification as a scientist, ultimately resulting in trainees leaving the field or the academy. In this study, we compare invited-speaker demographics to the current trainee demographics in one microbiology and immunology department and find that trainees are not proportionally represented by speakers invited to the department. Our investigation prompted changes in policy for how invited speakers are selected in the future to invite a more diverse group of scientists. To facilitate this process, we developed a set of tips and a web-based resource that allows scientists, committees, and moderators to identify members of under-served groups. These resources can be easily adapted by other fields or sub-fields to promote inclusion and diversity at seminar series’, conferences, and colloquia.
Hagan_SpeakerDiversity_JMBE_2019
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|- README.md # the top level description of content (this doc)
|- MI_invited_speaker_present.pdf # pdf version of data presented to the Department of Microbiology & Immunology at UM in Spring 2019
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|- data # deidentified compiliation of raw data
| |- speaker_dataset_14-19.csv # speaker and host demographics
| |- trainee_data_19.csv # graduate student and postdoc demographics
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|- code/ # any programmatic code
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|- figures/ # output from the original (Spring 2019) analysis
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|- submission/ # files needed to execute the study Rmarkdown