I’m a long-time fan of games – card games, board games, and video games. I suppose this is an increasingly common thing as we live in a golden age for indie games. This is as true for board and card games as it is for video games. Recently, I began working on a game concept and design to simulate the ways human groups of differing social complexity might interact in time and space. Thus, Social Complexity: The Game was born.
It’s sort of a mash-up between Catan and the World Game. I am certainly not unique in this type of work; a good summary of similar (and more advanced) experiments with games and anthropological pedagogy can be found in the following blog posts by Krista Harper (Post 1 and Post 2).
Update: Scroll to bottom of page for interactive map of election results.
The 2016 presidential election was truly an historic event. While Clinton’s popular vote lead continues to rise (more than 2 million as I write this), Trump currently has the Electoral College lead. One result of this election is it’s polarization of American politics and society. Numerous reports of hate crimes and violence towards marginalized groups have been reported since election night. I count myself among those who are concerned over this rise, and I continue to look at various ways to support my local community during these difficult times. It is my hope that some of the following analysis will help folks identify like-minded neighbors.
One way I and others can help is through the use of counter-mapping to make sense of this election in our local vicinity. Counter-mapping refers to the use mapping technologies for non-elite purposes, and is increasingly acknowledged as a primary tool for subverting establishment politics and corporate interests. The first step in accomplishing this is to acquire data. In this case that means information on voting precinct boundaries and election results. Fortunately, the Alachua County Supervisor of Elections has a Google map of precincts and has posted the election results. It is a relatively straightforward process to take the Google-based KML data and convert it to a shapefile for use with GIS software (e.g., ArcGIS, QGIS). Similarly, converting data between PDF and Excel is pretty straightforward.
This post concerns the visualization of property values. I am working on this for an upcoming project on the African American experience in Asbury Park, New Jersey, and particularly the 1970 riot. Part of this research focuses on the socioeconomic experiences (e.g., access to property ownership, property values) of various groups ithroughout the 20th century. Property ownership remains part of the “American Dream” and lured African Americans to many northern locations, places promising a more equitable society. A promised often denied.
One goal for this project explores geovisualization. Geovisualization, short for geographic visualization, is the visual representation of geospatial analyses. This increasingly involves the creation of interactive displays to share location-specific data. This post is not a nuts-and-bults how to, but it does outline the general steps and process for producing some interesting images of property values.