Tools: Scrivener for Writing

There are few things that I encounter in real life where I think to myself, “Mother of God.  This is a game changer.”  The fact is, that I am an old dog and you know how we are with new tricks.


I recently joined the Mac cult and was introduced to Scrivener (there is also a PC version).  I don’t remember how it happened.  But I somehow came across it and did the free trial- thinking, “well, what is all this about?”  Long story short, Scrivener is for people who write (read: writers and academics).  It is pretty sweet- once you get used to it.  I admit, I am still working out all the things that it can do, and that I have only scratched the surface of its capabilities.

What I like most about it is that it takes a lot of the hassle of working with a traditional text editor (*side eyes MS Word*) like formatting and inability to move sections around easily out of the writing process.  It is easy to organize thoughts and parts of text.  It is possible to work on a section at a time in a large document, something that I believe is difficult in Word, particularly with very large sections and chapters.  In scrivener, these sections can be rearranged and dragged/dropped easily.

The thing I like most about it though, is that it keeps different components of a project together.  Because Scrivener has a “research” option, it is possible to keep your notes on a project with the actual project (as opposed to as comments in the body of a text).  Because we all know what happens when push comes to shove and MS Word’s formatting is giving you fits: deletions.  We delete those comments all in the name stopping some of the crazy auto-formatting that happens anytime you try to add a table or a figure or a page break or a section break to a word doc.  The problem is, that sometimes these thoughts and comments are substantive…. they belong to the thought structure of the paper.  In Scrivener, these thoughts can be kept alongside the sections where they occur.

There is a handy outlining feature in Scrivener, which if you ask me, is super useful for outlining academic papers.  As close to using index cards as you can get without actually using index cards.  There are templates that you can use- like Essays, Novels, and Non-Fiction, that each come front loaded with genre specific material.  It isn’t all crazy useful, but that content is easily deleted to customize your specific document.

This video is a great on-ramp to Scrivener, even if it is quite long (turn on while you eat lunch).  If you are thinking of parting ways with Word, or are trying to think of a way to work better, it might be worth your time to check out Scrivener.  To be fair, there is a steep learning curve in that it isn’t exactly intuitive to get up and running.  But it is definitely worth the free trial download!

Cheers and Happy Writing!

The Socially Vulnerable in Catastrophes and Disasters

If you consume any local media in Chicago, it would be hard to miss that last week was the 20th anniversary of the Great Chicago Heatwave of 1995.  Twenty years ago, temperatures in the city climbed to 106 degrees, with a heat index of 120.  Over 700 Chicagoans died as a result of the extreme temps: most of whom were the elderly poor.


What is remarkable, is that this happened in America, in the recent past.  This wasn’t some forgotten era, an ephemeral ghost haunting pages of history books.  In our lifetime, people died because they were poor and socially isolated.  Moreover, the destructiveness of the Chicago Heatwave was merely a sign of marginalizing neglect that is symptomatic of this new version of big American cities.  Eric Klinenberg (author of Heat Wave: A Social Autopsy of Disaster in Chicago) noted that examination of the disaster reveals “not simply the obvious relationship between poverty and suffering, but some of the institutional and social mechanisms upon which extreme forms of American insecurity are built” (1999).

In many ways, those that died during the Chicago Heat Wave illustrate how the socially vulnerable are at increased risk in natural disasters.  Some of those that died did so without working air conditions or even the economic resources to operate the ones they owned.  Many were disabled- unable to transport themselves out of their smothering apartments to cooling centers and public spaces where they could get cool.

It is no surprise that the some of the Chicago neighborhoods with the highest rates of heat related deaths were also those with the highest levels of violent crime in the year preceding the heat wave.  Neighborhoods that had slowly deteriorated over during the second half of the twentieth century presented a unique challenge to the socially vulnerable: escape to the cooling centers and public spaces outdoors, where they risked falling victim to the violent criminal activity in their neighborhoods or stay in their suffocating apartments.  Many “chose” to stay and many died.


Table 3 from page 85 of “Heat Wave: A Social Autopsy of Disaster in Chicago”.

Ten years following the Heat Wave, Hurricane Katrina devastated the Gulf Coast of Mexico in the Summer of 2005.  Unfortunately, the lessons learned in Chicago were ignored in the Gulf Coast and 1,100 residents of New Orleans and St. Bernard Parish died when levees broke.  Again, the socially vulnerable bore the brunt of the storm.  At the time, Louisiana was the second poorest state in the Union.  More than 90,000 people in Louisiana made less than $10,000 a year.  African-Americans made 40% less in the Gulf Coast than whites.


Twenty-three percent of the New Orleans residents were considered poor (which was 76% higher than the national average).  Moreover, one in four New Orleans residents didn’t have access to a car, which might have been useful for escaping Katrina.  Moreover, the poor in the Gulf Coast overwhelmingly live in substandard housing- which was problematic when levees broke, unleashing the high waters of the flooding Lake Pontchartrain and the Mississippi River.


Those unfamiliar with how poverty works often assume that in times of emergency, individuals use personal resources to avoid catastrophe.  The problem with this is the assumption that individuals have personal resources at their disposal to avoid catastrophe.  Many don’t; they just paid the rent; it’s a week until pay day.  Many of the poor are forced to weather such events in place. Most of the time, this isn’t about the personal responsibility of individuals who don’t evacuate or seek out cooling centers.


The Pressure and Release (PAR) Model of Vulnerability and Disaster by Blaikie et al (1994)

This is about poverty and inequality in America.  Inequality before, during and after emergent weather events predicts the harm and devastation experienced by individuals.  Increasing inequality in America means that we can expect not only greater vulnerability to these events, but also greater devastation among those who are least likely to survive it.

Useful Resources

Klinenberg, Eric. 1999.  Denaturalizing Disaster: A Social Autopsy of the 1995 Chicago Heat Wave.  Theory and Society 28: 239-295.

Klinenberg, Eric. 2002. Heat Wave: A Social Autopsy of Disaster in Chicago. Chicago: The University of Chicago Press.

Center for American Progress.  2005.  Who are Katrina’s Victims?

Berube, Alan and Bruce Katz.  2005.  Katrina’s Window: Confronting Concentrated Poverty Across America.  Brookings Institution.

Berube, Alan and Steven Raphael.  2005.  Access to Cars in New Orleans.  Brookings Institution.

Where are the Guns?

Top 25 countries with gun ownership

The U.S. has the highest gun ownership in the world and is the only country to have a rate of ownership greater than 60%.

In 2007, the most recent data available by the Small Arms Survey, showed 270 million civilian guns in circulation in the U.S. According to, during the same year, 3.9 million small arms were manufactured in the U.S. In the same year, the annual rate of all gun deaths per 100,000 people was 10.37, non-fatal gun injury was 23.19, and the percentage of homicides committed with a firearm was reported to be 59% in the U.S.

Although the proportion of homicides committed with a fire-arm increased only by one percentage point from 2007 to 2010 (59% to 60%), the reported annual number of small arms manufactured for the same 3-year period jumped from 3.9 million to 5.45 million.

The graph below ranks countries by the rate of gun ownership in 2007. GunOwnershipByCountry


Gun ownership in the U.S.

Based on the 2007 data from, cumulatively, the southern region had the highest gun ownership compared to any other region in the U.S. At least 40% of residents owned a gun in 11 of the 14 southern states.

The eastern U.S. had the lowest gun ownership, where a majority had gun ownership of 25% or less, with the exception of Maine (40.2%) and Vermont (42%).

Four southern states (Arkansas, Mississippi, Alabama and West Virginia), 4 Western states (Wyoming, Idaho, Montana, and Alaska) and 2 Midwestern states (the Dakotas) had more than half of the state’s total population owing a gun.

Hawaii’s gun ownership (6.7%) was the lowest while Wyoming (59.7%) had the highest percentage of gun owners in the entire U.S. Hawaii was the only state to report a rate less than 10%.



Who are most likely to own guns in the U.S.?

According to the 2007-2012 Gallup poll survey, the single most influential predictor of gun ownership was gender. Males were 5 times more likely to own a gun than females. The next strongest predictors were marital status and region. The Gallup study found that almost two-thirds of southern married men owned a gun.

The graph below shows the profile of gun owners based on demographic, socio-economic, behavioral and geographic characteristics.

  • Those most likely to own a gun are: sothern, rural, white, married, conservative, republican, male,  50-64 years old, income of $50-75K a year, Protestant or Christian and military service.
  • Those least likely to own a gun are: female, Hispanic, 18-29 years old, postgraduate educated, eastern, urban and politically liberal, independent.

Note: The highest value under each category has a color and texture



Learning How We Write with Sarah Read

During a research leave this past Spring Quarter, Assistant Professor Sarah Read of Writing, Rhetoric & Discourse (WRD) has been utilizing ATLAS.ti in the SSRC’s computer lab for her ethnographic project at the facility that operates the world’s fifth largest supercomputer.  With visiting privileges from Argonne National Laboratory as a guest faculty researcher, Sarah is analyzing the technical documentation and reporting processes of the Argonne Leadership Computing Center where the cutting-edge machine is housed. She is studying technical documentation and reporting processes with a focus on the daily activities of the “knowledge workers” who operate it. Her focus is on writing, traced through documentation related to and generated by the supercomputing center.


“I think it’s fascinating to create an account of what it takes to build and operate a world-class supercomputer,” Sarah said. Through her interviews with supercomputing center staff, Sarah has been delighted to discover that they “think like researchers” themselves, tackling uncharted terrain in what is “essentially a research project in supercomputing.” Every year the staff prepares a report on operations required by their sponsoring federal agency. In this report they demonstrate how the facility has met the metrics of availability, utilization and capability supported by data that staff must work out how to generate. “It’s a big machine. It’s not easy,” she notes. Nothing is pre-formed. Staff have no manual to consult when the machine fails, no button to press to spit out the right data. Figuring out how to “write down the machine” is a complex, research-based task itself.

A theory-driven researcher and ethnographer, Sarah describes herself as “fundamentally a rhetorician, but I study it in technical environments.” The project combines her competing interests and background in writing, science and the humanities. “I consider myself a collector of qualitative data, but I don’t consider myself really a social scientist. I’m kind of in a grey area epistemologically,” she explains. Her ethnographic approach, which interests her in “the theory-driven points of view,” permits her to admit to strong biases. “I think there’s value in creating descriptive accounts of phenomenon within new theoretical frameworks that make visible previously invisible aspects of that phenomenon” she said. “It makes the strange mundane and the mundane strange again.”

As a self-taught, new fan of ATLAS.ti, Sarah too is learning as she progresses, experimenting with how to make the application work within her methodologies. This spring she worked hard with the networking view tool and is now concentrating on coding. ATLAS is “very object-oriented,” she said, treating chunks of a transcript as a whole document. She’s impressed with its analytical power and its visual capabilities that helpfully reveal networked relationships among research artifacts. “It’s a tool for analysis, but network views can also be research products” she noted.

Currently Sarah is continuing to code interview data for an article about how gathering data for the operations report structures staff work activities at the supercomputing facility. She is also writing a proposal for a book about the infrastructural function of writing and documentation for technical organizations.

Sarah offers to share what she’s learned about ATLAS.ti with other DePaul researchers. She’s found that talking through the process is mutually beneficial. If you’re interested in learning more about the application, please contact the SSRC[] or Sarah [].

Useful Tools: Up and Running with Lynda and Public Data Sets

Are you in a research funk?

Are you at a place where you’re sick of the research you have been doing?  Maybe you’re not sick of your topic, you’ve just exhausted your data sources.  Lynda (which DePaul subscribes to) has a tutorial/video series that can help you find new data sources.  “Up and Running with Public Data Sets” by Curt Frye is a 2 hour long tutorial of videos that introduce you to some widely used datasets, including the Census and American Fact Finder, the Internal Revenue Service, the US Department of Education, the US Department of Labor Statistics.


Moreover, there a couple of sections on data tools, such as search engines (Quandl and INFORUM) and visualizing data.  As a 2 hour long introduction, “Up and Running” seems like it could be useful to many researchers without requiring a substantial buy-in in terms of resources or time.