Mapping Bodies in Public Space

Our bodies turn into data post-incident, but what would it look like to collect it before? Spaces of Avoidance looks at the common routes taken and avoided in public spaces as a way to explore the ways we protect our own bodies everyday.

The recent wave of #metoo has led me on an exploration of sexual harassment and how it’s viewed in our country. After a body mapping exercise I conducted in 2017 among my classmates, it was very clear that every woman in my life has their own story. Some shared, some unique, but they had them. Going into this semester, I had the initial intent to map sexual harassment, but the data just wasn’t there. I’ve come across a handful of organizations like Hollaback who work toward lifting the veil, by mapping people’s experiences of harassment. But, I find it frustrating that these answers to data collection still rely on the victim, and not on proactive data. Needing a place (and data) to start, I decided to map my own experiences of sexual harassment for the month of October, 2018.

I tracked the amount of time I spent in public and if I experienced harassment that day. If I did, I divided my experiences into three categories: non-verbal, verbal and physical. In addition, I tracked the time of day it occurred and the location (in a more generic sense, ie. street, train, park). I turned this data into a GIF to help visualize my experience.

The GIF was a good technical exercise, but I didn’t feel like it properly conveyed my experiences. The goal in collecting this data was less spatial, and more reflexive. In an effort to bring these dots to life and put more emotion behind my experiences, I found inspiration in breath. The more uncomfortable a situation is, the tighter your breath, the faster your heart beats. Similar to a heart monitor, or sound waves as they get louder, I wanted to create an image that reflected the affect these moments had on me. The following images use the scale of intensity (non-verbal, verbal, physical) as a guide for the height of the waves, and the 31 days of October as a baseline.

About halfway through collecting this data, it occured to me that in the year I’ve been in NYC, I have already started in engrain tools to preemptively avoid these encounters. I am almost always “plugged-in” to my headphones, causing me to undoubtedly not even register some verbal encounters, but I also have specific paths I take and ones I avoid. Curious how other people move through public space, I asked eleven of my classmates and friends to participate in an avoidance mapping exercise. In total, I recorded data from fourteen maps (including my own three maps).

I provided a basemap with a central address of each participant’s choosing and asked them to use a blue pencil to draw the routes they most commonly take. I asked them to be as specific as possible, even paying attention to which side of the the street they would typically walk on. Then, with the red pencil, I asked them to draw the routes and areas they avoided. The reasons vary, from noisey streets and lots of dog poop, to corners where “men make kissy noises”. With one participant who biked, we ended up introducing a new color (green), because, despite poor road conditions or construction sites that guarantee getting a cat-call, one doesn’t have many options for their bike route. I took all these maps and plotted the points and comments into CARTO.

Because this project is less about pointing out a street or an area that’s “unsafe”, I decided to forego the basemap. The point of this exercise was for the participants to reflect on the agency they have over their own body, and what they do everyday to protect it. While I’m still in this discovery phase, I am experimenting with NYC Open Data that could correlate with points on this map. I have yet to draw any major conclusions, but I also am hesitant to perpetuate the Broken Windows theory. I plan on continue adding more and more maps to this project as I go into my final semester, but for now, the outcome is uncertain.

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