Within analytics, demographic information (e.g., race and gender) is often used carelessly, with a surface level analysis being the end all be all for discussions around issues of disparities and injustice. Such surface level approaches, lacking historical or contextual realities, are insufficient to combat the dark history of demographic data being used to “prove” deficiencies of entire groups.
During this workshop we will highlight the importance of constructing the “why” behind using demographic data in analyses. In addition, we will discuss the limitations and consequences that are inherent in focusing on such data exclusively.
Finally, using open data on math test results as well as the NYC school directory, we will explore how other factors aside from demographic data explain variation in student math ability
