Our audience consists of the Reno City Council, Reno Housing Authority, Reno residents, particularly seniors and college students, Local Non-profit organizations, Developers/Contractors, and Mayor Hillary Shieve. Our audience cares about the fair representation of residents in the election process of Reno City Council Members, which requires them to take action to build inclusionary housing for college students and nursing facilities throughout Reno. The benefits of acting include oversight in the development of district maps, housing for the largest demographic groups, and equitable representation throughout the city. If no action is taken, the legislative body would determine districts without regard to communities of interest, potential gerrymandering, minority group voter suppression, discredit to the government institution, and perpetuate the housing crisis. Building strategic inclusionary housing for the two largest demographic groups in Reno will equalize voter representation throughout the city.
The following is a summarized list of the dimensions and measures from the dataset used on this project:
A more detailed presentation of dimensions and measures can be found in the Data Dictionary for this dataset located in the Appendix. The Fact Table of the data set used on this project consists of the following table:
The above Fact Table has a grain that gives us the amount of population by race, sex, housing type, housing unit status, Income, and density. The Dimensions Table of the data set used on this project consists of the following: Zip Code, Race, Age range, Age range by Sex, and Housing Type.
Our research started with the Reno City Council wards and ended in Reno housing types per zip code. Beginning with the city wards, the group attempted to find the correct demographic data for each ward in an effort to answer the beginning research question; what are the demographic shifts from the 2010 census data to the 2020 census data used to calculate the Reno City Council electoral ward map? (Appendix 3) Unfortunately, the data needed for this specified question was unable to be found in the census data. The city wards’ demographics were obtainable, but the geographic data needed to understand the mapping and potential redistricting was out of reach.
With the discovery of the ward and census data being inaccessible, we shifted to Reno zip code demographic data. Thus, changing the research question to, what are the communities of interest in Reno based on zip codes? (Appendix 5) The new research question created the need for exploration into the communities of interest found in the Reno zip code demographic data. The communities of interest were race, age, housing type, employment status, education, and household income. Each community was thoroughly examined to find inequalities or patterns throughout the zip codes (Appendix 5).
The race was found to be equally dispersed in each zip code, meaning that the populations of each race were similar enough in each zip code to be considered evenly represented. Even with the abundance of one race over the others, the overall trend is even. The trend of the white population being so much higher than the others is the same from total population to individual zip code population, as seen in Figure 1 and Figure 2.
Age and employment status were two communities that didn’t show significant trends. They instead became sub-categories for other communities in showing why other communities of interest were showing the inequalities or patterns presented. We concluded that these two communities did not require further exploration beyond its surface.
Education and household income showed connected patterns. The zip codes with lower incomes had high populations in the education of High School degrees and lower, while the higher income zip codes had high populations in the education of High School degrees and higher. We examined this as an income divide among the city, however since every city and state handles income divides differently, this was merely noted as a potential need for action.
Housing types were where we found our demand for action. There are four zip codes that hold the only populations for nursing facilities and college student housing. With the average age range of college students being 15-30 and nursing facilities attendants age being 65+, these communities of interest are not equally represented in the city.
The communities of interest found in nursing facilities and college student housing create the majority of the population in the city. With this identification, we investigated the two housing types' age ranges throughout each zip code to discover if the need for further development in those areas is needed. Figure 3 visualizes the population discovery while also showing the four zip codes the housing types are concentrated in.
Further investigation into nursing facilities showed four zip codes that contained the housing type. With an age range of 65+ we showed that due to limited options of location for this housing type the city created higher populations of the older community to be concentrated in the four zip codes over the others. Figure 4 highlights the four zip codes in question and shows the population and 65+ age range. This is followed by Figure 5 which examines the 65+ age range throughout the city, thus showing the concentrations within the four zip codes.
Our college student housing investigation was done similarly to that of the nursing facilities with similar outcomes. College student housing was found to be in two zip codes, one of which is shared by the nursing facilities. Utilizing the analysis of age range again, we re-defined the age range to 15-30 throughout the city. Again, we see the concentration of the newly defined age range concentrated in the two zip codes discovered to obtain college student housing. Figure 6 shows the highlighting of the two zip codes and Figure 7 examines the college age range throughout the city.
It is the hope of our group that this project is able to prompt a broader discussion regarding communities of interest and inclusionary housing. Reno is a diverse place with many communities of interest making up the fabric of the community. It is impossible to know what makes up a community without study of its components. Research such as ours only begins to scratch the surface of identifying communities of interest and directing action for the equitable benefit of all. It is of our opinion that further research is required to allow entities such as the Reno City Council, Local Non-profit Organizations, and elected officials to fully understand and act toward the benefit of the communities they serve. Our group identified communities of Race, Income, and Age as possible communities of research that could be more equitably represented by the stakeholders previously mentioned. Our limited analysis should encourage others to further uncover communities of interest and work toward equalized representation.
As presented in the data and findings, fair representation of residents in the election process of Reno City Council Members is paramount. This requires the City Council to take action to build inclusionary housing for college students and nursing facility residents throughout Reno. The benefits of acting include oversight in the development of district maps, housing for the largest demographic groups, and equitable representation throughout the city. If no action is taken, the city council would determine districts without regard to communities of interest, potential gerrymandering could occur, and vulnerable voter groups will be suppressed bringing discredit to the government institution and perpetuating the housing crisis. Building strategic inclusionary housing for the two largest demographic groups in Reno will equalize voter representation throughout the City.