In October, Robin Burke (of CDM) and John Shanahan (of English) stopped by the SSRC’s Mess Hall to discuss their venture, Reading Chicago Reading. The project, which was recently funded by the National Endowment for the Humanities, is an empirical examination into who reads what kinds of books. The digital humanities project started by examining the One Book, One Chicago (OBOC) program, operated by the Chicago Public Library. Essentially, Burke and Shanahan (as well as their research team, which also includes SSRC Staff Members Nandhini Gulasingam and Jessi Bishop-Royse), are using OBOC data from CPL to examine various aspects of the well-known reading program.
The Reading Chicago Reading project is innovative in that the team is combining data from texts, community demographics, circulation records, and social media to yield book-level predictions on who is interested in a particular item. Combining CPL checkout data with other data, such as Census data, the Reading Chicago Reading research team is hoping to determine how the characteristics of branch libraries influence OBOC participation. Burke and Shanahan are hoping to use these various data sources to predict community interest in various titles CPL might consider for future iterations of OBOC.
For more information on their recent projects, please check out the results page of the Reading Chicago Reading website.
There is a crack in everything,
That’s how the light gets in.
Anthem, Leonard Cohen
In Sleep’s Dark Kingdom, by DePaul faculty member Steve Harp, is an artist’s book created in response to the SSRC’s call for proposals to celebrate the UNESCO designated International Year of Light.
My approach takes as its starting point the notion that conceptions of light are meaningless without framing notions of darkness. Light only enters the realm of perception out of a darkness.
In “The Hollow Men,” (1925) T. S. Eliot writes of “death’s dream kingdom,” a place of disguises, with “eyes I dare not meet.” It is a kind of limbo, a twilight kingdom – a place between. The dream kingdom is also, of course, the place of sleep – itself a liminal zone between the clear consciousness of the light of day and the obscure darkness of unconsciousness. If light is a metaphor for clarity or understanding, sleep has its own light emerging from darkness: the cold, crystalline clarity Freud posits residing in the dream continually hidden by layers of resistances obscuring it in metaphor, symbol, displacement. Yet centrally, what Freud suggests is that the light of the dream (the latent content) can only become visible emerging from a darkness (the manifest content – always only known through its telling or representation, never through direct access to the dream “itself” – a kind of double cloaking or darkness).
My project touches on or suggests four “realms” or kingdoms of darkness, terrestrial and extraterrestrial, conscious and unconscious, in which light’s emergence from darkness and obscurity is to be celebrated all the more for its rarity and brevity. What I have attempted to do in this project – itself obscurely explained thus far – is to suggest darkness as an opportunity for light, darkness as the necessary frame allowing glimmers of light – of clarity, of understanding, of meaning, of hope – to break through and become manifest themselves.
I started thinking about it the other day and realized that I have been using Stata for over ten years. OVER TEN YEARS!! Seriously, where has the time even gone?
I realized that we might be due for a nifty resource list for learning Stata. There is a lot out there, and it can be difficult to wade through what is there when you have different types of questions and problems. Sometimes I just need a quick reminder on the exact formatting of the code/syntax for a particular command. Sometimes I am trying to help novice users get their feet wet. The former needs a solution at the 3 foot level, the latter needs a 30,000 foot view.
Below, I have categorized some of the Stata Resources that I use often. As I find more and more items, I will come back and add to this list.
A Gentle Introduction to Stata– Last published this year, this text is in the 5th edition and is good for learning the specifics of data management, exploratory statistics, and analyses. Princeton Website– A step by step tutorial for working in Stata. Also covers a lot more of the “why”.
UNC Pop Center Website-Has commands sorted by function for ease. If you are looking for help on combining data files, you’d find five examples commands you could use.
IDRE UCLA Website– This is a wonderful resource for interpreting Stata output.
edX Channel on Getting Started with Stat
David Braudt Introductory Stata workshop
Stata PDF Manuals- these are pdf files that are accessible from the Help menu of Stata. The manuals are organized according to type of analysis, like there is a document for Time Series Analysis and one for Structural Equation Modeling.
The Workflow of Data Analysis Using Stata– Despite the fact that this edition was published in 2008, there is a lot of extremely valuable information here on how to organize Stata data and do files, as well as version control.
Last week DePaul’s MPH Program and the Center for Community Health Equity co-hosted the Health Disparities and Social Justice Conference at the Loop Campus in conjunction with DePaul’s MPH program. The day was full of fantastic events regarding health disparities and social justice issues in Chicago and beyond. The opening keynote was delivered by Patricia O’Campo of the Centre for Urban Health Solutions at St. Michael’s Hospital in Ontario, Toronto.
Friends of the center Noam Ostrander and Fernando de Maio participated in a panel discussion of the Chicago Health Equity Reader, a year long project whose ultimate aim is to produce a reader of the essential readings on Chicago Health.
SSRC Director and Sociology Faculty member Greg Scott was on hand with the Safe Shape exhibit as well as two collaborative film projects (Everywhere but Safe and Making a Place Called Safe) he has produced with VOCAL-NY and the San Francisco Drug Users Union. Noam Ostrander presented his collaborative project with SSRC Senior Research Methodologist Jessica Bishop-Royse on seasonal patterns in homicide mortality in the US.
The event brought together a wide variety of public health professionals, students, researchers, public officials, and community stakeholders, who were afforded the opportunity to engage with presenters and provide feedback and comments.
This summer I discovered a sweet mapping tool. For a lot of researchers and writers, it can be tricky to get places plotted on a map. Don’t get me wrong, I adore Google Maps, but it gets fairly tedious manually adding cities to the map.
Map Customizer allows you to enter a list of locations manually (by typing) or copying and pasting a list from a text editor or spreadsheet. It uses Google Maps for mapping.
Once you’ve created your survey, you can save it and point back to your map’s address.
I think it is super helpful if you have a lot of addresses, cities, or locations to enter and would really just like to do so with a copy and pasted list.
The joint collaboration between DePaul University and Rush University, the Center for Community Health Equity, is hosting the Health Disparities and Social Justice Conference on Friday August 12, 2016. The conference will take place in the DePaul Center, at the 8th Floor of 1 East Jackson Blvd from 830am-4pm. Registration is free and the program is posted online HERE.
DePaul SSRC Director Greg Scott will have his project Safe Shape on exhibition. Senior Research Methodologist Jessica Bishop-Royse will be presenting collaborative work on seasonal patterns in homicide mortality in the US with DePaul MSW faculty member Noam Ostrander.
This is probably old hat to everyone- but I recently discovered Google’s NGram Viewer, which can compile a line graph of specific words published in books on a timeline.
You could graph specific words against each other, like comparing medicine, public health, and demography against each other. Even cooler is that you can specify specific datapoints, say 1800-2016. Or, 1800-1900.
It is a pretty elegant feature, it can show how our understand of subject areas have changed over time.
It’s simplicity could be useful for people wanting to generate simple and elegant figures for presentations and classes, etc.