TY  - GEN
A1  - Steuer-Dankert, Linda
A1  - Berg-Postweiler, Julia
A1  - Leicht-Scholten, Carmen
T1  - One does not fit all: applying anti-bias trainings in academia
T2  - Twenty-third international conference on diversity in organizations, communities & nations June 22 - 23, 2023 Toronto Metropolitan University, Rogers Communication Centre Toronto, Canada
N2  - Anti-bias trainings are increasingly demanded and practiced in academia and industry to increase employees’ sensitivity to discrimination, racism, and diversity. Under the heading of “Diversity Management”, anti-bias trainings are mainly offered as one-off workshops intending to raise awareness of unconscious biases, create a diversity-affirming corporate culture, awake awareness of the potential of diversity, and ultimately enable the reflection of diversity in development processes. However, coming from childhood education, research and scientific articles on the sustainable effectiveness of anti-bias in adulthood, especially in academia, are very scarce. In order to fill this research gap, the paper explores how sustainable the effects of individual anti-bias trainings on the behavior of participants are. In order to investigate this, participant observation in a qualitative pre-post setting was conducted, analyzing anti-bias trainings in an academic context. Two observers actively participated in the training sessions and documented the activities and reflection processes of the participants. Overall, the results question the effectiveness of single anti-bias trainings and show that a target-group adaptive approach is mandatory due to the background of the approach in early childhood education. Therefore, it can be concluded that anti-bias work needs to be adapted to the target group’s needs and reality of life. Furthermore, the study reveals that single anti-bias trainings must be embedded in a holistic diversity management approach to stimulate sustainable reflection processes among the target group. This paper is one of the first to scientifically evaluate anti-bias training effectiveness, especially in engineering sciences and the university context.
KW  - Academia
KW  - Engineering Habitus
KW  - Organizational Culture
KW  - Diversity Management
KW  - Anti-Bias
Y1  - 2023
ER  -