I unfortunately missed class last week due to a cold, so I can only draw on information presented in the readings. Across all of the readings, I found the idea of equality as a performative measure to be most intriguing. In a political landscape in which equality is becoming more and more emphasized, it seems that there has been a trend towards focusing on the broad category of “women,” as opposed to focusing on the inherent stratified nature of equality within the gender (i.e. if more women are advancing into positions of political power, yet aren’t using that political power to advocate for the interests of other women, especially those possessing less privilege, is it really a step forward for gender equality?). I was unfamiliar with the statistical complexities of measuring gender inequality (particularly the motivations behind using one measure over another); however, coming from a data-intensive background, I was not surprised that these statistical measures can be heavily affected by data that misrepresents the actual composition of a region. It seems that if people were viewed less as mathematical objects and more as humans, the data might not ignore large sectors of the population in favor of presenting a region as more equal than others.

Although I had suspected that organizations purporting to advocate for equality only really advocate for the advancement of a select few, it was interesting to look at the economic, social, and political factors that influence not just the discussion around gender inequality, but also the policies that are put in place to increase measured equality. Overall, it might be better if organizations understood more of the complexities that the discussion surrounding gender entails and lessened their use of equality as a buzzword that makes them only appear as allies to women, while further acting as perpetrators of inequality through their data and policy curation practices.