Project #10 Translation Device
*There is something wrong with one of my algorithms. If it doesn't showup try refreshing until it does.*
Description
Scrutinizing the discrepencies between COVID-19 deaths of races and ethnicity and their population make up in the U.S.
Conception
I took a course in the summer about COVID-19 which alarmed me about the disproportionate impact on different ethnicity groups in the U.S. After research, the data does show siginificant differences. However, only looking at the numbers may be too underwhelming for a subject matter of this gravity. The design question here becomes: how to make the experience more impactful and inquisitive.
Sketches and Mechanisms
These sketches are made early on during the process of dataset finding, in which the representation included the development of the pandemic in the U.S. However, I believe this will interferre with focusing on the discrepencies. The usage of circles inspired me to produce the third sketch which ultimately was developed to form the final outcome.
Also inspired by scratch cards, spotlighting and magnifying glass, this
version puts emphasis on the user initiative to discover whats
'underneath' the surface - the very real deaths of Americans under the
hood of racial equality.
I deliberately did not specific which group was which in the belief that
aside from White Americans (which is obviously the biggest circle) the
rest of the races in the US all should be alarmed by this situation
regardless.
Using the data from CDC's COVID-19 dataset and US Census, the sketch produces results up to date. Upon retrieving the data, a few functions tally and set the radius of the circles by percentage of width/height. The location of each circles is randomized with algorithm in check for overlapse.
Top layer is draw of population ethnicity ratio.
Bottom layer is draw of COVID-19 death ratio of respective ethnicity.
A circle is draw in erase() mode to see through the top layer.
Finally a text description enboxing the sketch with transparent
background is draw on the very top.
Reflection
After actually drawing the populations by ratio I realized that some are really tiny, but I did think this is a good outcome in the way that it in some ways reflect the neglegence by the mainstream felt by minority groups.
Personally, the research process is more rewarding than the coding part. I realized many caveats and difficulties procuring suitable datasets and findout some ways around it. This is an extremely valuable experience for possible future projects working with datasets. The "invisible labor" behind datasets could not be more pronounced since I hardly saw any names attributed to any datasets. Or maybe this is for privacy?