My work in the Critical Food Studies Lab has revolved around understanding food deserts in Central Indiana. A large part of my work is “tool-based”, meaning I apply many different Geographic Information Systems (GIS) techniques in order to discover and illuminate trends not easily appreciated within large datasets. Additionally, my work revolves around applying mathematical principles to the challenge of food deserts. Overall my work is data based, with large importance being placed on the interpretation and manipulation of data. Much of the work I performed this fall was concerned with data mining and database building. Geographically, my research location consists of a two-county ring surrounding Marion County, Indiana. In these counties, census tract data were collected concerning population sizes and each census tracts geographically weighted center. From the population data, a “W-Matrix” was built to address the population size of each census tract. From the centroid data, a “D-Matrix” was built to analyze the time it would take to drive from each centroid to every other centroid. In order to create the D-Matrix, I used a network analysis tool in ArcMap (the program I use to perform my GIS tasks). In ArcMap, there is a series of network analysis tools that perform a variety of functions. As the name suggests, each network analysis function is dependent on a “network” of sorts in order to perform each said analysis. For my work, I used a “network” of streets and centerlines consisting of every street and centerline in North America. For my analysis, I elected to use an OD cost matrix. This tool is ideal for the D-Matrix due to the values it accumulates. The OD cost matrix accumulates both time and distance values between two points. The OD cost matrix draws “lines” based on the network given accumulating data on the distance and time it would take to traverse these “lines”. The lines form a matrix but they are in actuality routes that carry data, very similar to the routes seen in Google Maps for example. In ArcMap, all constraints were lifted with the exception of what vehicle I would use. Each time was calculated using a single occupancy vehicle. And so through performing the OD cost matrix a network of lines was created. A line is produced traveling from each centroid to every other centroid. With a total of 530 census tracts, the OD cost matrix consisted of 280,900 lines. Now that’s a lot of lines! From those lines, I extracted all the time data and created a time database within Excel. From the time database, all the data is synthesized into the D-Matrix. The D-Matrix is rather large; keep in mind its 530 by 530 census tracts, a total of 280,900 data points. In order to synthesize the D-Matrix in a quick and easy manner, I used an OFFSET function within Excel. I also tried to build and use a macro for this but found the OFFSET function to be simpler and much more user-friendly. For those unfamiliar with Excel or the OFFSET function, it is a tool that moves columns or rows of data into a matrix. Rather than copying and pasting 530 columns of data, the OFFSET formula will do it quickly and easily. If you are having trouble moving columns of data into a matrix, much like I was, here is an example of the formula I ended up creating: =OFFSET(drv_tms!$F$2:$F$279842,COLUMN()-COLUMN($D$4)+((ROW()-ROW($D$4))*(ROWS(drv_tms!$F$2:$F$279842)/529)),0,1,1) From the D-Matrix I then created an “S-Matrix” which is concerned with various time limits or constraints The S-Matrix is a binary analysis of the D-Matrix. It analyzes the time it takes to travel from each centroid under certain time limits. The time limits I used for the S-Matrix were 5, 10, 15, 20, 25, 30, and 35 minutes. Again the S-Matrix is binary, meaning, for example, with the 5-minute time constraint, if the travel time was under 5 minutes a “1” was used to represent that line. If the travel time was over 5 minutes a 0 was used. Binary for this example is just true and false, 1 being true and 0 being false. From these three matrices, my next step is to create covering models and running said models through solver.
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by Hannah Gruber My work with the Critical Food Studies Lab has been working with the lab’s Co-director, Angela Babb, and her project with the Thrifty Food Plan. The Thrifty Food Plan (TFP) provides the basis for food stamp allotments given by the Supplemental Nutrition Assistance Program (SNAP). It uses an algorithm to determine market baskets containing sufficient nutrients for a healthy person based on age and sex. It has become increasingly clear that the allotments are not enough to cover the nutritious diet suggested by the TFP, especially for those who have specific diet restrictions such as allergies or intolerances. Previous members of the Lab made a new model based on George Stigler’s calculations, proving that it is not possible to achieve nutrient recommendations at a minimal cost. Unfortunately, the data from this model is outdated and from early 2000s data that the 2006 TFP uses. During my time in this lab, I’ve been working on recreating this model with updated nutrient profiles, food groups, and upper and lower limits for each nutrient. Some of this data comes from the USDA’s 2015-2020 Dietary Guidelines for Americans (DGAs) where they provide information beneficial for policymakers and health professionals to influence Americans’ diets. I hit a few bumps along the way, such as struggling to find data that fit the criteria needed for the new model. The USDA’s new DGAs reduced the food groups from 58 groups in the 2006 TFP model to just 19 food groups. An example of one of the updated food groups is Vegetables which includes subgroups Dark Green (broccoli), Red-orange (carrots), Beans and Peas, Starches (corn), and Other (cauliflower). The upper and lower limits given in the new DGAs are largely the same as the ones used in the 2006 TFP and reflect a range of data from the late 1990s through early 2000s. The limits give a range of safe levels of nutrients that can be consumed without negative health effects. Some of the nutrients don’t have any data on limits so we are assuming there are not substantial consequences from low or high intakes. I finally managed to combine all of this information into a new spreadsheet and will be moving on from here to something slightly new. This summer I plan to continue working with the TFP, but this time with the market baskets. I will go to all of the food outlets in Bloomington and attempt to purchase the market baskets within the amount allotted by the TFP. I’m looking forward to continuing my work with the TFP, but on a local level. I am hoping to find some interesting information on Bloomington’s grocery prices and whether or not any of the stores will be able to provide a (not so thrifty) food plan. Hopefully my work will contribute more proof that people using SNAP are not given enough to sustain a nutritious diet. by Vanessa Lopez
My work this past semester with the Critical Food Studies Lab has been focused mainly on food pantries throughout the state of Indiana. This work derives from my colleague, Hannah Wilson, who is taking a more comprehensive lens at food insecurity in Indiana. Other lab members and I have collected food pantry data via phone surveys in order to verify, update and improve a list started by Purdue Extension. The importance of this is to collect data on certain restrictions a food pantry may have, their hours of operation, what kind of items are provided to families, and if they have a choice as to what they receive. This data can also be interpreted to further investigate what kind of items are in high demand by clients and how pantries receive their food. An interesting issue that I learned when working on this project, was the lack of food banks for smaller food pantries throughout the state of Indiana. This came about when speaking to Ray Rodarte, leader of the Grant County Rescue Mission. When I spoke with Rodarte, he explained that a common problem food pantries face is a lack of access to food banks. This is particularly more difficult for smaller pantries that run out of church basements. Ray stated that this was the main reason they switched over from operating as a food pantry to a food bank in Grant County. This way they are able to help provide food donations for other pantries in the area. The reason why there is a lack of access to food banks is that food banks have not allowed for more food pantries to work with them according to Rodarte. Food banks such as Midwest and Gleaners have kept the same client list for a couple of years now. This issue is something that could help initiate a new movement that encourages new food banks to start up or for food banks to change their client list more often. In addition to working with Hannah, I have also begun to design a project of my own. With the help of Angela Babb, Co-Director of the Lab, I have commenced research on the relationship between migrant work and health. Poor health may be due to being exposed to pesticides over long periods of time. Having long exposure to these toxins causes diseases and even affects their children's health, in some cases leading to birth defects or delayed cognitive development. Currently, I am in the process of seeing what human rights organizations such as the Farmer Labor Organizing Committee and Agricultural Justice Project are doing in Indiana, to observe if they provide any help to migrant laborers and farmers that help them understand the chemicals they are exposed to. The end goal for this project is to help me collect all the data necessary that would allow me to present a research project proposal to a graduate program or organization that I could collaborate with after completing my undergraduate degree at Indiana University. by Hannah Davis My research with the Critical Food Studies Lab over the past year has primarily consisted of collecting and analyzing historical data on agriculture in Indiana. These data come from the USDA’s Census of Agriculture. Approximately every five years, the census collects information about farmland, farmer demographics, crop and livestock production, and the associated economic costs and gains. During the fall semester, I gathered data on the production of specialty crops, namely fruits, vegetables and nuts. I used these data in tandem with a list of all farmers’ markets in the state, collected by Kassandra Leuthart. My goal was to determine whether there exists a correlation between specialty crop production and the existence of farmers’ markets in Indiana at the county level. Through statistical analysis, I concluded that that relationship does not exist. What I found was simply that crop production has decreased overall in Indiana, while farmers markets continue to grow in popularity. This implies that the emergence of farmers’ markets does not rely on an increase in local specialty crop production. This semester I collected data on the age, sex and race of farm operators in Indiana. I am using this information to perform statistical and spatial analysis that will help food scholars understand the historic and geographic patterns that exist in these demographic data. So far, I have found an increase in the average age of farmers since the 1980s. I have also seen an increase in the number of female and racial minority farmers starting around the 1990s. These numbers reveal that farming in Indiana has become more diverse in the past few decades, albeit by a relatively small amount. Using mapping software in my analysis will allow me to look at patterns both temporal and spatial. The insights gleaned from this research will provide food scholars with a better picture of who manages farmland in Indiana, and where they are located. I am also currently working with Green Camino, a local compost collection company. Green Camino collects and composts household food waste, helping Bloomington residents divert their organic waste from traditional waste streams and reduce their carbon footprint. Work that Hannah Gruber and I performed using GIS helped the company match their existing customer addresses to their corresponding city sanitation route, which will allow the company to plan their future pickup routes in coordination with trash and recycling collection. It was rewarding to be able to use my spatial analysis skills to do work that aided a local business. I hope to continue to collaborate with Green Camino to do surveying and story mapping work that will help them expand their customer base. by Hannah Wilson My work in the Critical Food Studies Lab began in October 2017 when I became a Sustainability Scholar through the School of Public and Environmental Affairs. My project was originally assigned to me as short, preliminary work where I was able to look at the socioeconomic aspect behind food for the first time. Stemming from previous projects in the early days of the CFSL, my work focused on studying food poverty with a computational approach. I started with three "theoretical" families generated from previous analysis of food insecure individuals. Each of these families was moved around three locations in South-Central Indiana, and I analyzed how their situation changed based on where they lived. I calculated an end of the month (EOM) monetary remainder (either positive or negative) by balancing their assets with their liabilities. In the end, I found that the EOM changed for each family in each location. Whether it be that some areas differ in the number food pantries/ grocery stores, transportation means or costs of living, it was evident to me that location can make a large impact on whether or not a family goes hungry. One major factor in determining food poverty that I was not able to consider in my first project was time. People who are living on SNAP (food stamps) benefits are often forced to utilize emergency food aid like food pantries to supplement the amount of food they bring in to their home. In fact, many families will go hungry without these pantries. The problem is these pantries tend to have very specific hours, do not clearly communicate with the public and are concentrated only in urban areas/ larger cities. My current work seeks to apply this knowledge to the research I completed last year. Currently, I am working with both Christopher and Vanessa to create "time tables" that match six theoretical families' working hours with the working hours of surrounding pantries. In creating these tables, I have found that many pantries are rather inaccessible to the populations that they are seeking to help because many of them are open only one day a week or for only an hour or two at a time. These time tables have been more complicated than originally anticipated because my computations require me to generalize hundreds of pantries and personally make choices about how families in poverty would act in choosing which pantries to utilize. This has shown limitations in my work that can only be fixed with a detailed ethnographic work, but that was never the intention for this project. In the next few weeks, I will be working on the paper I am presenting at the American Association of Geographers (AAG) Conference in April. I think my paper will find a unique place in the conference because it incorporates the aspect of time into geographical studies. As was my hope with the preliminary work I did for this research, I hope to show the faults in the systems we've put in place to help the food insecure. Certainly, income makes a big difference in one's access to food, but many have not considered the effect that location and time can make. by Emma Freestone My project with the Critical Food Studies Lab is inspired by something I started working on last semester in my Food and Poverty class that focused on the cliff effects of poverty. Cliff effects describe the extreme loss of net worth once an individual is no longer eligible for benefits such as child care, Section 8 Housing, SNAP, etc. due to a marginal increase in income. For the research project we collaborated with Steve Thomas, director of Monroe County United Ministries (MCUM) and he became our mentor as he taught us about examples of cliff effects that he sees the patrons at MCUM struggle with daily. Our main goal of the project has been to research and compile a list of eligibility requirements for a variety of benefits including SNAP (food stamps), CCDF (child care voucher), Hoosier Healthcare, On My Way Pre-K, etc. in order to create a worksheet and spreadsheet for financial coaches to use as a tool to walk MCUM’s clients through and ensure that they can anticipate when they may be close to an eligibility cut off and prepare accordingly. Connected in an important way, is the research that Belén Rogers is doing with in-person, voluntary interviews at MCUM’s Client Choice pantry to listen to patron’s thoughts on how the pantry’s environments impact them, why they choose the foods they do, how they prepare the foods they choose, and if they choose the same food every visit. The overarching goal of this project is to compile the interviewee’s anecdotes in order to ascertain how to provide preferred food options in a more cost-effective and efficient way. I have been helping Belén conduct these interviews each week and we have received positive responses from individuals eager to participate and share their experiences. I also have started working on a project to research farmers in Monroe County and surrounding counties who have participated in gleaning. I plan to survey those who don’t glean to determine if they have interest but are disconnected and lacking support, discover to what extent food waste could be eliminated by gleaning, and see if a potential gleaning network could be mapped out between farms and food banks. Harriman Farms utilizes 225 acres spread out over several fields and the primary client that purchases his produce is Kroger, therefore if it doesn’t comply with a certain standard the food is not accepted. Ten thousand (100,000) pounds of produce was gleaned from Harriman Farms last season (Hoosier Hills Food Bank). I have been in contact with farms that are on the list of having participated in gleaning before with Hoosier Hills Food Bank and have been going through the list of vendors at the Bloomington Farmer’s Market. As I go, I have been gathering data on the locations of the farms so I will eventually be able to create an interactive map. My goals for this semester in the lab are to improve my GIS modeling skills and help analyze the research from the interviews at MCUM with Belén and write a paper with the findings. by Brian Healey So far, my year of research has been filled with copious amounts of spreadsheets, Facebook pages and Google street views, all in an effort to create an interactive database for farmers across the state of Indiana. This project consists of seven maps, each one filled with different layers of data points I have collected alongside Jodee Ellett, the head of this project. The areas that the maps cover range from Food Producers to Food Education, Technical Assistance and everything in between. We are mapping anything and everything an Indiana farmer could want or need all in one place. Collecting all of this data in one spot has never been done by the state before. The challenge of finding the information that I need is that it is scattered across different web pages and files buried deep within one of the hundreds of state websites and countless Facebook pages. This, is one of the problems Jodee and I have been hoping to solve with this project. Besides the monotony of looking at lists of different aspects of the food chain for hours on end, the work can be very interesting, and I am hoping that the final product will be widely used once it is up and running. Thankfully, the majority of the data collection work is behind me and the process of creating the maps has begun. As of writing this post, I have one of the maps fully completed with another nearing the same point. Seeing the endless flow of spreadsheets turn into a visible and usable map is an extremely rewarding experience. I got a sense of accomplishment when the first map was complete because despite only being 1/7th of the way through the project, I saw the light at the end of the tunnel. Recently, Jodee and I met with Eduardo Brondizio of the IU CASEL lab to discuss the process of getting our research out into the world. Eduardo and his team helped us visualize how our project will be presented. This meeting went great and lifted a weight off both of our shoulders as the destination of the maps was the last big unknown regarding the project. Now that the location of the final maps is taken care of, we can focus on the process of creating and refining the maps to the point that we are satisfied and hopefully to the point that the users are satisfied as well. One way we plan to maximize the ongoing accuracy and value of the project is our community initiative where we hope that members of each community the maps are presented to, help to provide feedback and information that would otherwise be unavailable. I hope that my work ends up being appreciated and used for years to come. I believe that farmers new and old will find this site helpful in furthering their livelihoods, whether that be by expanding their area of operation, getting routine assistance or finding new distributors. I think that this project has the potential to become a “go to” for Indiana’s farm community. by Belen Rogers Access to food does not mean access to choice of food. When “all our actions are carefully dictated to us” (Tirado18) as Linda Tirado, author of From Hand to Mouth says “you have no idea how strong the pull to feel worthwhile is. It’s more basic than food” (Tirado xviii). The act of choosing is valuable and acknowledges people’s worth. A pantry might be open at a certain time but people might only choose to go if they feel welcome and are able to choose the foods their household wants. But choices are often judged and restricted by policies. Assumptions of optimizations and weighted rational models that describe decision making are built into policy. These optimizations are almost consistently expected of a person: buying all necessary nutrients in a good-tasting but low expense diet is calculated into people’s Supplemental Nutrition Administration Program (SNAP) (food stamp) allocation. Taste preference for lobster, however, is not. I apply two different disciplines, geography and cognitive science, to studying behavior models of food choice. I study the impact of these choices that guide consumer supply and demand and affect the health and environment of ours and other current and future species. To do this, I focus on the decision making environments of a “client-choice” food pantry located in Bloomington. “Client-choice” pantries advertise a model that lets clients choose in order to avoid foods they are allergic to, that prevents food waste, and that recognizes dignity. Studying popular choices at food pantries can lead to insight into what foods people choose in an environment that is not financially restrictive. It can lead to insight into how order of food presented influences choice. I expect to learn about what foods people do not choose and why (e.g. people may not own the necessary appliances or because of the quality of food). I am particular about the method in which I approach my research. I talk and read about people and assume decisions of people of low income but I want to start listening to people. I seek voluntary contributions from pantry clients, responses that will hopefully reflect interviewees’ daily life. I will conduct interviews to learn about how the pantry’s environments impacts them, why clients choose what foods they choose, and if they choose the same food every visit. Nutritional information covers package labels; human, animal, and environmental ethics are considered in sourcing transparency, and social pressure is strong; decisions about food are loaded. I am interested in studying options, but I focus on choice and decision-making processes. Understanding cognitive decision mechanisms in the Critical Food Studies lab highlights predictive models of how geographical, social, political, and cultural environments shape habits. Decisions situationally correspond to those environments. It would be practical that these decisions were based on one factor considering human computational power and space and time restraints. Learning how choices are made will bring to light how restrictive some environments are, where decisions are implicitly and explicitly made for you because of your income. Tirado says, “junk food is a pleasure that we are allowed to have; why would we give that up?” (Tirado xv) while modern debates include the decision to ban soda on SNAP. This research will hopefully inform these debates and other policies. |
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