Update on Project Activities
This week was mainly devoted to delving into our small group projects. We each gathered data from the census and other reliable sources and began some analytical work. We plan to bring a summary of each of our sub-projects to Sunday’s video conference with the Hartnell team and our other community partners so we can better see how each project is fitting together/overlapping and work through issues as a group. For clarity, we plan to give a brief summary of each sub-project in these weekly reflections: * Segregation: Hannah compiled data tables and shapefiles from the 1980-2010 censuses through SimplyAnalytics, which has proven to be a really useful tool for quick, customizable visualizations. She found that race/ethnicity data is actually available at the block group level as well as the tract level, so she plans to use the block group data to get a more granular picture of residential distributions in Salinas. Next, she joined these data tables and shapefiles in ArcGIS and began segregation index calculations by generating deviational ellipses for each racial/ethnic group in each year. * Transportation: TBA * Crime: Jasmin and Jose started combing through crime statistics from 1993-2013 that were gathered from an online resource. We prepared questions and sent emails to both the police chief and east side commander to try to set up meetings with them about collecting more qualitative and quantitative police department data. * Public Health: TBA What We Observed and Learned Getting into the nitty-gritty details of data analysis led some of us to reconsider even the variables and categorizations we chose. For instance, the segregation sub-project divides the Salinas population into white non-Latinos, Latinos, Asian Americans, and African Americans. Those categorizations initially seemed perfectly logical, but they failed to account for mixed race people and Latinos of Asian and African descent. Based on preliminary research into the demographics of Salinas, it seems like these mixed populations have historically been very small, but it is still troubling (especially to the mixed-race sub-project lead) that these groups are often re-categorized or left out of demographic analyses. As we take a detailed look at our data, we are also finding new opportunities. One group member attended a geocoding workshop with Stace Maples and found that it may be possible to build an address locator for the 1930 census enumerator logs. Also, one of our colleagues at Hartnell, Jose, found detailed monthly crime statistics from the Salinas Police Department that we can use to create infographics. We have realized that there are many useful tools and data sources hidden amidst more conventional resources, and we will keep our eyes open for more of these great finds as we continue our research. Critical Analysis As we become more deeply involved in our respective sub-projects, it will become easy to succumb to a sort of tunnel vision. Although our topics are linked together by policy, history, and (of course) place, they each have their own specialized terminology, documentation, and data sources. Therefore, regular cross-group communication is essential now more than ever. Despite understanding this, we are still struggling to meet and communicate in a timely manner. We did not meet in-person at all this week, and it seems that illness, class/work schedules, and misunderstandings led us to cancel two planned meetings. To get back on track, we would like to meet on Sunday morning, before the video conference, and discuss communication norms, goals, and work schedules. Hopefully, this discussion will get all of us back on the same page and help us move forward with minimal stress so we can create the best deliverables possible. To that end, we are also getting a better idea of how our deliverables will look. Many of the steps in our analysis process are interesting, but they may not be the most illustrative or accessible parts of the project to display. We need to turn deviational ellipses, monthly crime reports, and acronym-riddled transportation plans into understandable, cohesive visuals. On the cartographic front, it will be important to limit both the number of maps and map layers so viewers are not overwhelmed by data. Bringing in written summaries and graphs through Esri StoryMaps or Carto could be an effective way to guide viewers through our analyses while still allowing them opportunities to explore based on their own interests. We want our deliverables to provoke curiosity and help people see their hometown in a new way. Comments are closed.
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