Sarah was a very tough cut from the top awards in this very competitive region. She had a very nice statement. She incorporated a survey and a mission statement for her map, which is something we haven't seen before. Very creative! Her map scored well for competitivenss and compactness.
“If knowledge is power, knowing what we don’t know is wisdom.” ~ Adam Grant, PhD.
The act of making a map is tedious. It requires focus and commitment. Most importantly, the map-making process encompasses a series of value judgements. Conscious or otherwise, the choice to place one block in the first district and an adjacent block in the second district is rooted in a priority of the map-maker: aesthetics? Contiguity? Political partisanship?
These value judgements lie at the heart of what it means to draw the lines. But one question still remains: whose values are being reflected in our maps?
The answer, today, is a small group of political “experts.” These figures are undoubtedly rich in knowledge. But they also may be entrenched in their thinking.
The mission of this map is to reflect the values of my student community, whose opinions may be otherwise overlooked or subjugated by the barriers of unfamiliar political terminology. Through this experiment, I hoped to learn what my community understands about districting, and to explore the insights and ideas that may lurk in what we do not understand.
To start, I asked the students and faculty in my school to answer three fields:
1. Do you know how the districting process in Pennsylvania works?
2. If you are familiar with the process, please describe it. If you are not familiar with it, please make your best guess.
3. Regardless of whether you recalled the process or made a guess, do you think that your answer above is an effective way to draw the lines? Do you have any other ideas?
The data produced four values ranked in order of popularity: equal population, an ambiguous “fairness,” contiguity, and minimizing county splits. Based on these results, I created metrics to guide the map-making process that would preserve these values and their order. I prioritized population equivalence. In order to make sure that absolute population equivalence did not negate the latter values, I determined that a 5-citizen variant between districts was the maximum acceptable range. I interpreted “fairness” to mean equal compactness, that is, that each district is as compact as possible, but that more importantly, each district also falls within a fifteen percent range of compactness. Thus, each district is between 45 and 60% compact. The third and fourth values became integral to the aforementioned “value” judgements that come with the refinement of each map. When faced with the choice to place a 34 citizen block in district seven versus district eight, I turned to these values. Would one placement preserve contiguity? Could another placement help to preserve a county split?
The functionality of DistrictBuilder made this mathematical lens possible. Being able to simultaneously monitor the population, compactness, and, newly, racial and political demographic metrics allowed me to navigate the complexity of considering and pursuing multiple community values.
This map is imperfect. Had I surveyed a different number of people, targeted a group with different prior knowledge of the districting system, or defined some of the terms that characterize metrics of a map, the values, and the product, would surely have been different. But this map is an experimental first step to the question that moves me: how can we use the insights that mathematics and data hold to bring objectivity, democracy, and insight to the political structures of a deeply partisan nation?