In ENVS 220, we have explored the elements of interdisciplinary environmental analysis and research—data, methods, theories, and frameworks—with a focus on the former two throughout the course of our lab investigations and project . The data we have used for quantitative analysis has been both self-produced and provided by agencies such as the World Bank and the Yale Center for Environmental Law & Policy. We provided our own data for a social network analysis of citations between environmental classics with Gephi and for our studies of River View Natural Area, via GIS and a Google Tour. For the former, we combed through Google Scholar to find the most cited citations of the environmental classics, linked together through a shared spreadsheet; for the latter, we surveyed different sections of RVNA and uploaded the data to Fulcrum. The use of class-sourced data allowed us to rapidly gather a great deal of novel data. For several of the other labs, we used existing data from the World Bank and the Environmental Performance Index to fuel our investigations into the statistical and spatial relationships between national-level environmental variables. Both the global data and literature exploration and the global data statistical lab used information on per capita carbon dioxide emissions and other quantified variables from the World Bank to look at very coarse environmental trends, first by a simple ordering of the data, and then by using SPSS to discover correlations between CO2 per capita and infant mortality, gross capital formation (as % of GDP), and urbanization. We used the EPI to study spatial patterns in environmental variables in GIS, with our specific variables being improved water and sanitation access. For our qualitative analysis of ads supporting or opposing Measure 92, the data we looked at included the spokespeople in each ad, the talking points used, who the texts emphasized, the associations portrayed between talking points and actors, and the musical and visual components.
We have used a variety of methods to analyze data, including statistical and numerical analysis (via SPSS Statistics and Excel), spatial analysis (via GIS and Google Earth Tours), and social network analysis (via Gephi). For my team’s project, on the Portland Urban Growth Boundary and housing prices, we integrated several of these analyses within a single project, using GIS to map census tract data of housing prices, statistically analyzing this data with Excel, and then conducting a narrative analysis to assess perceptions of housing prices and the UGB. As you may notice, many of the methods are heavily computerized; while computer programs can be an enormous aid in interpreting data, it has been incredibly important to keep centered on the meaning of the numbers or figures they spit out. Moreover, while the theories and frameworks side of environmental analysis has not been explicitly examined as of yet, they have played a large role in my lab team’s discussion of results. The theory of ecological succession played in heavily in our analysis of spatial patterns of tree distribution in RVNA, and the ideological framework that anthropogenic carbon dioxide emissions are both bad and positively correlated with human development directed that exploration. The framework that ivy is bad directed much of our exploration of RVNA images, with that bias fully acknowledged and embraced during the making of the narration. In our qualitative narrative analysis, my prior awareness of existing frameworks of privileging consumers over producers played a large role in the identification of the common strains of consumerist focus in both the Yes and NO ad campaigns. Finally, frameworks played a significant role in our team projects, as we used the narrative analysis to understand how evaluative frameworks played out regarding descriptions and explanations of the UGB and housing prices.
In addition to the four levels of environmental analysis, we have also discussed the importance of questions to environmental research, differentiating between descriptive, explanatory, evaluative, and instrumental questions. I reflected on this side of environmental analysis in a couple of my synthesis posts, my lab team project and my concentration proposal. For the lab team project, we searched for evaluative and instrumental questions in existing scholarly literature, with this search culminating in our broad question: What are the effects of regional urban planning on housing equity? This is obviously unanswerable, but that was not the concern; rather, it was used to think about descriptions and explanations of a certain element (housing prices) of our object, the Urban Growth Boundary. This thus led to our focused question: What are perceptions and realities of housing prices in relation to the Portland Urban Growth Boundary?
For my concentration, I have posed several of each type of question to guide my investigation of transportation politics in gentrifying cities. I have attempted to add some scholarly creativity to my investigation of this popular and frequently ideologically-polarized field. I have tried to further the depth of my own thinking on the subject by both exposing myself to a variety of ideas on cities and transportation, and then examining my own aesthetic values and political biases. I think that a major portion of scholarly creativity involves critical examination of something which has not yet been deconstructed in such a way, and remains the purview of generalities or assumptions or “big words.” Over the course of the steady evolution of my concentration I have become increasingly concerned with interpreting the online debates on assorted transportation and urban planning blogs, that I’ve informally observed for several years, within a scholarly setting, and integrating it with existing academic literature, theories, and frameworks..The role that transit has played in shaping the landscape of gentrification has associated transit investment and advocacy with urban revitalization, gentrification, and dispossession. This fact then produces and foregrounds splits between progressive urbanist advocates, as comparative evaluative opinions of gentrification and transit can vary dramatically.