The Summer Studio Fellowship created an experience centered on exploration.  The combination of being introduced to new tools, campus resources, and being given time created a space with which to examine the role data plays in my scholarship and how I communicate my work. In studying the New Deal, agency reports start to tell part of the story of addressing the youth problem made worse by the Great Depression, but with the bureaucratic nature of the reports, they are not the most interesting things, especially for the general public. But therein lay the opportunity to create a resource that connects the public with history in a way that engages them. After discussing this with my advisors and museum partners, we decided that a map which showed the widespread nature of the New Deal programs like the Civilian Conservation Corps (CCC) and National Youth Administration (NYA) would best connect people to my work. Mapping allows for people to see how much their communities may have been changed and show them sites like lakes, schools, and campsites that were newly created in the New Deal. I was able to highlight communities that received disproportionate amounts of federal government support and am working on compiling period newspaper clippings to understand local Iowans experience of the Great Depression. Thus at the same time, visualizations are connecting the public to their history, they are advancing my own academic inquiry.

     The public focused nature of this project definitely developed throughout the summer. I used my time this summer to have the discussions about what a lasting project looks like and took time to lay the groundwork of a lasting project. I think this studio experience was a great opportunity to develop skills and confidence for undertaking digital projects in the future. I now have a much better understanding of what it takes to set up a project and how to go about initiating it. 

-Luke Borland  

               It has been a fascinating few weeks working on my digital project as well as attending the classes during the summer. A reminder of what I have been working on: I am developing a website/ web portfolio of my professional information, and my past and current research work. During summer, I was able to develop a website, under the kind guidance of Ethan from the Digital Studio. I am thoroughly enjoying the process, which is still ongoing, though sometimes it feels like the deeper I dig, the more there is to uncover. It does seem like I am slowly moving along.

               One of the functions of my website was to make scientific knowledge (my research in Audiology) accessible to lay people or people outside my field. I did get some input on how to do this from the Studio scholarship classes, especially from how presentations are done at the Jakobson Conference. As I was developing the website, I had some questions regarding how to present my research, which I am still trying to find answers to. For instance, should I translate all my research projects into layman terms? Much of my research so far has been basic research which will be useful for Audiologists or hearing aid manufacturers to implement changes; and I wondered if anyone (other than people working on this problem) would be interested in reading about this. Thinking about this reminded me of the idea of translational research.

Sheila T. Moodie who has been studying translational research and implementation science in Audiology for 20 years defined knowledge translation as “identifying and using the best possible strategies for conducting research, synthesizing results and translating results into clinical practice so that effective and efficient health services are delivered to patients in our care”.  Though I am interested in conducting research that can be incorporated in clinical care, I wondered how long it would take for my research to be translated into and be used in everyday Audiology practice. My research participants often asked me if the hearing aid we were testing currently would be soon available in the Market because they really liked it. However, it takes more than around 10 years for Audiology research to trickle down into clinic. I do not dishearten my research participants with this knowledge. However, getting back to my project, I can at least make it easier for them (my research participants and others) to read current research, which might be implemented by the time their children and grandchildren have (or maybe don’t have) age-related hearing loss.

View my video here:

Soumya Venkitakrishnan

Since my last post, I paused a little bit on the visualization of the networks on Meetup.com. Instead, I worked more on reading the literature on group dynamics, social networks, and organizational ecology and finalizing my research questions for my dissertation which this project is part of. The finalized core research question is: what makes a group more likely to be successful in constant competition against other groups for resources and members? In other words, how do groups secure their membership growth and retainment over time? I intend to answer this question by looking at the co-participation network structure both within and across the groups to investigate how the network characteristics and the change of them contribute to the growth and retainment of memberships over time.

After refining and clarifying the research questions, I was able to return to the visualization part of the project and continue making more graphs. With some data cleaning, merging, transformation, and conversion in Python, I was able to create the networks of interest in various time intervals. To share some progress I made during the second half of the fellowship, below are some snapshots on the evolution of the networks of groups in New York City in 2010, 2013, 2016, and 2019. In the graph, each node represents a meetup group. Each color of the node indicate the broad group category the group belongs to, such as tech, socializing etc. (I also have graphs with legends indicating which color represents which category. However, I have 33 categories in the graphs, so I needed to combine some categories before displaying the legend.) The links between the nodes indicate that the two linked nodes have shared group members. The width of the links indicates proportion of shared members relative to the combined membership size of the two groups. Of course, these graphs are far from perfect and I certainly need to work on finalizing them. However, with what I currently have, it is obvious that global network expanding in size and density. This suggests that members participate in multiple groups and that competition for member’s finite time is becoming more and more crucial for a group’s growth and survival. In the future, I will develop ways to visualize how competition in the network affect individual’s participation patterns which shapes group’s recruiting strategies which then impact the competition in the global network.

Below is my brief reflection of my experience at the Studio this summer. Hope you will enjoy watching it!

Qianyi

Hey blog, it’s Julianna again. In my previous post, I described the film I pitched… and how my life exploded this summer. (The too-long-didn’t-read: there was an accident, a week in STICU, and an aborted film shoot.) 

GIF: The Lawrence Livermore National Laboratory just digitized and archived 497 (mesmerizing, terrifying) films of early nuclear tests, which can be found on LLNL’s youtube channel.

I’ve spent the last few weeks figuring out what all of this means for my family, myself, and my film. It’s been a crash course in: how to be a more supportive sister and potential caretaker; how to approach the creative process when I don’t have everything I need; and how to make work that grapples with darkness when I too am in the dark.

All of this said: I don’t understand the big picture yet, so I’ll focus on details instead.

Thinking about America’s current relationship with petroleum led me to ask a question I ask a lot these days: How did we get here? This ultimately led me to the 1970s oil crisis. (TL;DR: Postwar America consumed more oil than it could produce, so it began importing oil from the Middle East; the Organization of Petroleum Exporting Countries (OPEC) declared an oil embargo in 1973; the price of oil sky-rocketed, leading to fuel shortages; America freaked out!)

Photos, L to R: Long lines at a New York City gas station; No fuel for sale at a Pennsylvania gas station. Credit: NPR, “The 1973 Arab Oil Embargo: The Old Rules No Longer Apply.”

Years after the initial embargo, on July 15, 1979, Jimmy Carter beamed into TV sets across America to deliver his landmark “Crisis of Confidence” speech. (Carter gets a bad rap but as a former ATLien, I’m partial.) To paraphrase, Carter says we’re the reason we’re in this mess, and… he isn’t wrong. In my opinion, this speech draws a clear parallel between then and now, but this stands out in particular:

“… Too many of us now tend to worship self-indulgence and consumption. Human identity is no longer defined by what one does, but by what one owns. But we’ve discovered that owning things and consuming things does not satisfy our longing for meaning. We’ve learned that piling up material goods cannot fill the emptiness of lives which have no confidence or purpose.”

Stills, L to R: Jimmy Carter is disappointed. Very disappointed. Credit: Miller Center, “July 15, 1979: ‘Crisis of Confidence’ Speech'”

After a lengthy but well-deserved reprimand, Carter lays out a plan for energy self-sufficiency. Among strict import quotas, incentives for developing alternate fuels, and the suggestion that “we must face the truth,” there’s this:

“We will protect our environment. But when this nation critically needs a refinery or a pipeline, we will build it.”

Cut to: the vast network of pipelines being built across America.

Before this gets too long, I’d like to thank Matt Butler, Stephanie Blalock, Leah Morlan, Tom Keegan, my fellow fellows, and the Digital Scholarship & Publishing Studio et al. This opportunity gave me the support and protected time to not only research and make work, but also deal with a major unexpected life change. I’m so grateful for it. 

In closing, here are a few selections from my work-in-progress film. Thanks for watching and reading!

– Julianna Villarosa

Since my last post, I settled upon collecting films with references to honeymoons and more broadly, to films that adhere to a romance narrative. Using IMDB’s keyword search, I researched films that contained words such as “newlyweds” and “honeymoon” in their plot description. I then ran a search for the films within UIowa’s media library and rented every DVD that was available. I entered these titles into a spreadsheet along with release date, genre, director and relevant themes. While I collected close to 50 titles, I managed to rent, download, transcode and sort through about 30 films. Creating a viable workflow for this task was a challenge. When I discussed my objectives with Matthew Butler, he suggested I use Trello to track my workflow.

As I came to realize that I would not collect the number of films that I had hoped to collect, I decided to at least collect films from a range of decades, so I would have the opportunity to track the phasing in and out of certain narratives over time.

In Consuming the Romantic Utopia, Eva Illouz chronicles the interrelationship between love and capitalism over the course of the 20th century. She writes that though, “mass culture did not create the ideal of romance,” it did “transform the old romantic ideal into a ‘visual utopia’ that combined elements of the American dream (of affluence and self-reliance) with romantic fantasy” (31). Illouz argues that film promoted identification with romantic heroes by rendering fantasies in the sharp focus of cinematic realism. From Illouz’s writing I borrowed conceptions of love that have coexisted, waxing and waning in popularity over the past century. Influenced by religious ideals as well as market forces, many of the narrative frameworks she discusses contradict one another. 

Some examples include:

Love as a redemptive force

Love as a “utopia of transgression”

Love as a consumerist leisure practice

Love as a democratizing force or “love is blind”

While I haven’t gotten very far in the editing process, I have begun organizing sequences by shots, scenarios and themes that recur across the films. In the video below, I’ve edited together some of these recurring images, tropes and characters.

-Samantha Kahrar

As my last post discussed, my project this summer deals with a series of monthly reports by public health nurses in 1930s Native American communities. Each report includes statistics and a narrative description of the nurse’s work. The narratives are often detailed and evocative, and sometimes represent indigenous voices—those of the handful of Native women who worked as public health nurses for the Office of Indian Affairs. However, the voices of Native patients are always filtered through the nurse’s perspective. I thought the statistical reports might offer a closer look at how patients, their families and their communities were actually responding to the federal government’s health program, and I have been working with the Studio this summer on cleaning and visualizing a large portion of that data.

For many reasons, rooted in both historical and personal experience, Native patients and families often refused treatment in hospitals and rejected public health nurses’ advice. Because of this resistance, field nurses kept track of who told them about new cases. One of the categories of reports was “By family.” This statistic is nowhere near a perfect measurement of Native families’ trust in public health nurses. For one thing, healthcare options in 1930s reservations were usually limited and health conditions dire, so reporting a problem to a field nurse could be a last resort. There’s also plenty of potential for inaccuracy and inconsistency in the numbers themselves, as I discussed in my previous post. However, these statistics do offer a different way to look at Native families’ actions and choices.

I used Excel visualizations to look at the patterns in the number and the percentage of new cases reported by families. Excel’s “slicer” feature allows me to quickly break down a chart based on a large dataset and see individual patterns.  I can compare a particular nurse’s statistics with her narratives and add depth to both sources. Here’s an example:

In March of 1934, field nurse Georgia Lyle, a white woman, was transferred from the Eastern Cherokee community in North Carolina to the Fort Berthold Reservation in North Dakota. In April, she noted that people said they had been waiting for a field nurse for seven years, and that the agency had “bought and worn out two field nurse’s cars without ever having a field nurse.” The claim that the community really wanted a public health nurse matches the statistics for Lyle’s first full month on the job, when families reported 94% of new cases. However, the following months show a striking change, with smaller and smaller percentages of the new cases reported by families.

And at the same time, the actual number of new cases per month stayed fairly consistent (with an unusually large number in October. It’s not completely clear why so many more cases were reported by “others” in this month, but Lyle’s narrative mentions at least one teacher who told her about a case.)

So, what happened? Why were families less and less inclined to report new cases to Lyle after her first month of work?

In June, Lyle wrote about her feelings of inadequacy and the difficulty of truly improving public health in the face of drought and pervasive poverty. In August, she wrote, “While it has been a pleasure to work with the Indians on this reservation I do not see how a field nurse can accomplish anything without the cooperation of the Agency physician.” The physician disapproved of public health nursing (a common attitude, since many physicians saw it as a threat to their authority) and blocked Lyle from performing several of her expected tasks. Beyond that, Lyle portrayed him as someone who resented his Native patients and saw them as obstacles to his own professional advancement. She reported that he said, “I do not need a field nurse but I do want another nurse in the hospital. If I had more help and could get these Indians to let me do two hundred (200) major operations I could get to be a fellow of the American College of Surgeons.”

This kind of attitude was common. A great deal has been written both about the exploitation of indigenous patients in general, and specifically about the Office of Indian Affairs’ issues with under-qualified and even abusive personnel. Native author Zitkála-Šá wrote in 1900 that Native American boarding schools were more of a charity for indifferent and incompetent employees than for their students, and she specifically mentioned a school doctor.  

So, it’s easy to understand why the Fort Berthold community might have been eager to see a new health worker and then disillusioned when the limits of her work became clear. If that’s the story behind the graph, it’s infuriating, but also illuminating. Many field nurses complained that Native patients were fatalistic about their health problems, but this combination of statistics and text shows patients’ families acting in pursuit of better health.

 I hope there’s more to this story; there certainly are other interpretations of this data, and I have several more years’ worth of statistics to analyze. It’s also one of many stories I hope to draw out of the source material with the help of the digital skills I’ve learned this summer.

–Laurel Sanders

During the last few weeks of the Digital Scholarship & Publishing Studio Fellowship, I am revising my methodology paper as I discussed with my committee in the last meeting. In the previous data set, the dates of the first cycle of chemotherapy, treatments, diagnoses, and deaths were inaccurate. Thus, I obtained updated dates for the chemotherapy of 209 cancer patients. During the last two weeks, I clustered patients with the accurate dates of chemotherapy using different time periods, according to the attached video.

Previously, I used five symptoms; pain, nausea, and mobility, activity, and nutrition according to the Braden scale. But the Braden scale is not closely related to symptom severity after chemotherapy. So, I added three more symptoms: oral health, appetite, and psychosocial status.

To decide which time window to choose, I referred to previous literature. Albusoul et al. (2017) focused on symptom cluster change over time in breast cancer patients at four times: baseline, which is two days before the first chemotherapy treatment, during cycles 3 and 4, and one month after finishing chemotherapy. Byar et al. (2006) investigated the impact of adjuvant breast cancer chemotherapy on fatigue, other symptoms, and quality of life at 30, 60, and 90 days after the last treatment, and one year after the first treatment. Tracy (2016) identified symptom clusters and trajectories of depression and anxiety in Latina breast cancer survivors at baseline, 2, and 4 months post enrollment. So, I changed the time period of clustering from one month in my previous analysis to 3 months in the current analysis to evaluate the pattern of symptom clusters in a more extended time window.

For the next step, I need to create a spreadsheet including patients’ demographic and clinical characteristics and symptom cluster memberships using R codes. I was helped by Matthew Butler in the Studio when I revised my previous codes. In the new data sets, Cancer NAACCA and Cancer Vital, there are some discrepancies in the list of patients I had before. So, I sometimes filled out this spreadsheet manually to get patients’ medical records numbers (MRNs) and dates of death from reviewing in EPIC chart.

To sum up, I ran the expectation-maximization (EM) to cluster patients using one spreadsheet. The clinical implication is weak yet, so I will cluster patients using all cycles of chemotherapy rather than just first cycle. I hope I can get the interesting results soon from reanalysis using all cycles of chemotherapy and publish and share the clinically meaningful results with a larger audience. Participating as a fellow of Digital Scholarship & Publishing Studio was a valuable experience to realize the huge potential for using real health data. I gratefully appreciate your continuing support and the opportunity to meet other fellows and staff members.

-Sena Chae