There is still a need to challenge the ‘add and stir’ model of diversity, a practice of sprinkling in more women, people of color, disabled folks and assuming that is enough to change current paradigms.
Moya Z. Bailey, All the Digital Humanists Are White, All the Nerds Are Men, but Some of Us Are Brave
This quote, through the vivid metaphor of “adding and stirring,” prompts us to reflect on diversity practices. As more diverse groups enter the academic and digital humanities fields, the contours of these domains are being redefined. However, symbolically allowing marginalized groups to enter the digital humanities field and continuing to adapt them to mainstream ways does not address the fundamental structural reasons causing the issues.
To truly achieve diversity, a deeper understanding and correction of underlying biases and discrimination are needed. This requires the creation of a friendly environment that leaves room for the comfort of those who may be marginalized within existing structures. Overly simplistic and tokenistic approaches cannot truly address the challenges in the digital humanities.
This quote’s critique of the “add and stir” resonates strongly with my past experiences. Some organizations implement diversity initiatives only superficially, to achieve a specific percentage of diversity in their statistics. Unfortunately, these initiatives often ignore the real experiences and feelings of these diverse groups and fail to provide them with real support and equal opportunities.
For example, I encountered this when I participated in an academic program that claimed to welcome people from diverse backgrounds, including those from areas with limited educational resources who may have lacked professional training. While the program did enroll some students from these backgrounds and met its numerical diversity goals, it did not adjust accordingly to effectively accommodate them. As a result, students who already lacked knowledge and skills remained under-trained. They are trying to grapple with the knowledge points, but slowly, causing communication and collaboration difficulties. Sadly, they continue to be marginalized in the program. As a result, diversity failed to produce any substantial value.
In this term, I hope to learn more tools in data visualization. My past knowledge of data visualization has been too simple and limited. So far, I have been introduced to a variety of methods such as maps, network analysis, and text analysis, and I find them to be very useful tools. I’m looking forward to learning more.
