Descending from the Ivory Tower – Digital Humanities Beyond Academia

As I already stated in my very first blogpost, I am a first generation Digital Humanist. I started this masters program an academic year ago, in 2015. In a month or so from now, I hope to graduate for the third and final time. I will be thrown under the bus – I mean into the job market – by February. How nice it would be, to stay safely hidden in the Ivory Tower of academia, not having to face whether or not I am truly qualified for the real world. It reminds me of a comment one of my professors once made about the similarity between Italian and Belgian students, remaining under the care of their parents until graduation. I tested myself already, I am perfectly capable of living abroad and taking care of myself, that is, with financial aid and Skype nearby. Now is the time to let it go, to become truly independent. But will I be independent from academia as well?

Stéfan Sinclair puts my internal debate into words in his blogpost on Digital Craft and Humanistic Perspectives Beyond Academia:

Don’t count on an academic job as a reward for your travails (in other words, don’t consider me as a model) and don’t count on your studies to prepare you for easy access to non-academic jobs.
(Sinclair, 2013)

Where do we stand as future masters in Digital Humanities? Do we stick to the tricky search of finding a job as a humanist, albeit some extra capabilities, or do we use our newly found digital confidence to demand a job in the promising world of IT? Is there a middle ground? Is there someting inbetween academia and the outside?

Even for those who do get the change to work on a PhD, possibilities for their academic employment increasingly drop, since the number of tenure track jobs available rapidly decreases for humanities scholars. Another option, discussed by Katarina Rogers, is that of alternative academics, or AltAc:

People with advanced humanities degrees who find stimulating careers in and around the academy but outside the tenure track.
(Rogers, 2015)

Some of those jobs outside the academy can exist in libraries, museums, archives, humanities centres and labs, presses, and so on (Rogers, 2015). In order for students and academics alike to prepare for a job out of the ivory tower, existing programs need to prepare their students adequately for an ever changing job market and society. The Digital Humanities are setting a good example since many of its implicit skills such as “collaboration, project management, and technological fluency” gain importance both within the academy and outside (Rogers, 2015). It is not necessarily about the specific job or career, but

People that identify with the term [alternative academic] tend to see their work through the lens of academic training, and incorporate scholarly methods into the way that work is done.
(Rogers, 2015)

That, together with all the reasons for why the humanities matter, will guide me through the maze. Furthermore, I also believe that the digital in Digital Humanities, increases my opportunities in the current society. Hopefully others will see the importance of the humanities, along with the promising but ever critical digital humanities.

Bibliography

Sinclair, Stéphan. “Digital Craft and Humanistic Perspectives Beyond Academia.” 2013. http://stefansinclair.name/digital-craft-and-humanistic-perspectives-beyond-academia/.

Rogers, Katina. “Humanities Unbound: Supporting Careers and Scholarship Beyond the Tenure Track.” Digital Humanities Quarterly, 9(1), 2015. http://www.digitalhumanities.org/dhq/vol/9/1/000198/000198.html.

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LaTeX – The Ulyssis Workshop (part 2)

Last time I introduced the very basics of LaTeX after a workshop organised by Ulyssis, which you can find here. As I promised earlier, today I will talk you through the code to insert tables and figures into your text. For those of you who want to really impress their peers, I will also explain how you can format two figures next to each other (which required some serious googling skills on my behalf). But let’s get started with the basics first.

You can add your table within a \part{Title goes here}, \section{Subtitle goes here}, or \subsection{Subsubtitle goes here} of your \begin{document}, but before your \end{document}. There are several kinds of tables, the most basic one starts by \begin{tabular}{c c c} to specify that you want three columns, and for each row you add item & item & item \\ to fill in the three columns. After you added several rows, don’t forget to \end{tabular}.

For your fancy table you \begin{table}[h] right here, but you want it in the \begin{center} and then you can \begin{tabular}{c c c} with some columns, which you know how to fill in by now (item & item & item \\ for each row). After you \end{tabular}, you add a \caption{fancy table}, you \end{center} and finally, you \end{table}. Once you understand the basics, you can make your life easier by creating your tables in a tool such as http://www.tablesgenerator.com/.

Now in order to add figures to your document, you need to add a package in your preambula – the thing that comes right after \documentclass[11pt]{article} at the start of your document. You can \usepackage{graphicx} to insert some fancy figures. Of course you need to save your picture in the same folder as your .tex file, otherwise it might be hard to find. Now you’re ready to \begin{figure} and \includegraphcs[width=0.5\textwidth]{your figure}, where you define the width of your figure, in this case 50%, but you could also set [width=100mm] to include a figure of 10 cm wide. To center your figure you can use the \centering command, and adding a \caption{your figure} works the same as for tables. Again you need to \end{figure} before you start with the rest of your text.

If you want two figures side by side (or even three, but you can probably figure it out if you understand the mechanism), stackexchange comes to the rescue. Because you need a specific type of \caption, you need to add another package in your preambula called \usepackage{caption}. So again you \begin{figure} by \centering both your figures in the middle of the page. But you now split your figure into two \begin{minipage}{.5\textwidth} each taking up 50% of the width of your page. In order for each figure to look spot on, you should use \centering again, then \includegraphics[width=0.9\linewidth]{first image}. In this case the linewidth for each figure takes up only half of the page, so the 90% used here, actually means you have a 10% margin between this figure and the next. In this case, you need the \captionof{figure}{This figure} to add a caption to the first figure. If you want to refer to your figure in the text you can always add a \label{fig:figure1} and inside your text \ref{fig:figure1} so that the number of the figure is always correct, even if you add other figures. Now you need to \end{minipage} number one, and in order for the two minipages to appear next to each other, you need a % inbetween. Now you can repeat the \begin{minipage}{.5\textwidth} process to add one more figure, and after you \end{minipage}, also \end{figure}.

So there you go, the perfect tables and figures to impress any reader! Next time, I will explain how to add your citations and bibliographic references, BiBTeX style.

Social (Media) Data: a gold mine for Digital Humanities?

Lev Manovich identifies two types of data used in social and cultural studies during the twentieth century: “‘surface data’ about lots of people and ‘deep data’ about a few individuals or small groups” (Manovich, 2012). An intermediate method is used in statistics, where a researcher chooses a sample to represent an entire country for example. Comparing this aproach to Photoshop, Manovich goes on to say:

A “pixel” that originally represented one person comes to represent one thousand people who are all assumed to behave in exactly the same way. (Manovich, 2012)

This is exactly what happened in polls preceding the recent Presidential Elections in the United States of America, and predicting that Hillary Clinton would win. Nate Silver’s FiveThirtyEight 2016 general election forecast predicted Donald Trump would only have a 28.2% chance of winning, although they estimated a 10% chance that Clinton would win the popular vote and lose the electoral college vote. Their model containing three versions needs quite a lengthy user guide, their polls-plus version of the model combining polls with an economic index and each version following four major steps:

  1. Collect, weight and average polls. – based on Pollster ratings.
  2. Adjust polls.
  3. Combine polls with demographic and (in the case of the polls-plus) economic data.
  4. Account for uncertainty and simulate the election thousands of times.

Nate Silver later defended his model in Why FiveThirtyEight Gave Trump A Better Chance Than Almost Anyone Else saying that:

People mistake having a large volume of polling data for eliminating uncertainty. […] the polls sometimes suffer from systematic error: Almost all of them are off in the same direction. (Silver, 2016)

The four objections Manovich states with regard to the rise of social media and new computational tools that can process massive amounts of data (Manovich, 2012) can help explain why The Polls Missed Trump.

The first objection Manovich describes, is the lack of availablity of data outside of the social media companies, specifically for transactional data (Manovich, 2012). In the case of the election polls, one of the recurrent errors is the nonresponse bias, or “failing to get supporters of one candidate to respond with the same enthusiasm as supporters of his opponent” as Carl Balik and Harry Enten stated in their article asking Pollsters Why.

The second objection Manovich formulates, is the lack of authenticity, since communications over social media and digital footprints are often carefully curated and systematically managed (Manovich, 2012). However, “several pollsters rejected the idea that Trump voters were too shy to tells [sic] pollsters whom they were supporting” (Balik and Enten, 2016). However, automated-dialer calls which used a recorded voice registered more Trump voters as opposed to live-interviews (Balik and Enten, 2016).

Manovich also raises a third objection, referring to the size versus depth issue since different data leads to different questions, patterns, and insights (Manovich, 2012). In the aftermath of the elections, many explinations for why the polls were off took the stage in several articles. Even on the FiveThirtyEight website, I found at least three articles offering a different point of view, even contradicting each other: Jed Kolko explaining Trump Was Stronger Where The Economy Is Weaker, Carl Bialik stating that Voter Turnout Fell, Especially In States That Clinton Won, but also claiming No, Voter Turnout Wasn’t Way Down From 2012, whereas Clare Malone blamed the outcome on the sentiment of Americans Don’t Trust Their Institutions Anymore. The differing approaches even amonst the same redaction team shows how some refer to individuals’ emotions, while others state voter turnout or a weak economy.

Finally Manovich’s fourth objection points out the need for specialized expertise especially in computer science, statistics and data mining, needed to work on large data sets and especially combining the data as Nate Silver did for his general election forecast. Even though he clearly has a well-defined method, adding several factors and ranking pollsters based on historical data on their accuracy, polling needs to “get more comfortable with uncertainty” (Balik and Enten, 2016). One of the people they interviewed even went as far as to state that “the incentives now favor offering a single number that looks similar to otheer polls instead of really trying to report on the many possible campaign elements that could affect the outcome. Certainty is rewarded, it seems” (Balik and Enten, 2016).

If Digital Humanists want to make sure that:

The rise of social media, along with new computational tools that can process massive amounts of data, makes possible a fundamentally new approach to the study of human beings and society. (Manovich, 2012)

We need to change how students in humanities are being educated, something the Advanced Master in Digital Humanities of the KU Leuven is certainly trying to achieve.

Bibliography

Manovich, Lev. “Trending: The Promises and the Challenges of Big Social Data.” Debates in the Digital Humanities. Minneapolis, MN: University of Minnesota Press, 2012.

Silver, Nate. “2016 Election Forecast.” FiveThirtyEight, November 8, 2016. https://projects.fivethirtyeight.com/2016-election-forecast/#plus.

Balik, Carl, and Enten, Harry. “The Polls Missed Trump. We Asked Pollsters Why.” FiveThirtyEight, November 9, 2016.  http://fivethirtyeight.com/features/the-polls-missed-trump-we-asked-pollsters-why/.

LaTeX – The Ulyssis Workshop (part 1)

Because I wanted to try a different approach to learning LaTeX, I went to a workshop organised by Ulyssis, a group of KU Leuven students offering workshops to other students. They explained the basics of LaTeX in about two hours, creating a template for a paper in the first hour and explaining BibTex in the second hour of the workshop. During the workshop they helped install an easy LaTeX editor and a team of students was at hand all the time to answer individual questions. So in this blogpost, I would like to share my newly acquired knowledge!

The structure of a LaTeX document always has the same basic elements, opening the document with the preambula, containing all metadata (the hidden specifics of the document itself). First, we specified the \documentclass adding the size of our font [11pt] and the type of document, namely {article}. If we need to import packages to do the fancy stuff dreams are made of, we need to \usepackage{awesomeness} to add some more functionalities and funky features -for your information, there is no package awesomeness for all I know, but please feel free to make one. Of course you can add the \title{Anything you like}, as well as the \author{me!} and the \date{\today} or any other day you like. No one needs to know you started your paper the day of the deadline.

Alright, we have our metadata, now we can \begin{document} by \maketitle and starting a \newpage for your magical automatically created \tableofcontents on a \newpage. Most papers contain an \abstract, but since LaTeX needs some help understanding what you want exactly, you should still \begin{abstract} and after writing your brilliant summary of everything you are about to write, you need to \end{abstract} for LaTeX to know you are done.

Now you need to start providing your table of contents some content. In an article you can divide your text into \part{one, two, three} and add \section{one, two, three} which can exist of \subsection{one, two, three}. You can add \paragraph{With a lot of witty, smart, funny, intelligent text} and even \textbf{bold text} and \textit{italics}. Furthermore you can also create different types of lists, starting with a bullet list by \begin{itemize} containing several \item items untill you decide to \end{itemize}. Sometimes you need to specify the order of your list \begin{enumerate} again containing \item one and ending your \end{enumerate}. Finally, if you want to provide descriptions to your awesome concepts, you \begin{description} adding \item[awesome concept] with your clear explination before adding another \item[greatness] adding your own brilliant definition and bringing an \end{description} to your awesomeness.

Before you go, don’t forget to \end{document} and feel like a professional programmer while you let LaTeX do the work (press run!), typesetting the best paper you ever wrote. Catch up next time for some more on tables and figures sprucing up your text!

Genderizing Digital Humanities

During our class on Digital Humanities, Politics and Gender we discussed diversity related issues. I would like to start by quoting the definition of diversity:

The condition or quality of being diverse, different, or varied; difference, unlikeness.
(Oxford English Dictionary)

However, diversity can be better understood in terms of intersectionality, which has moved beyond the race-class-gender relationship as described by legal scholar Kimberlé Crenshaw (Crenshaw, 1991), now also including what Roopika Risam specifies as “additional axes of difference including sexuality and ability”. Risam also adds that “as a lens for scholarship [in the digital humanities], intersectionality resists binary logic, encourages complex analysis, and foregrounds difference” (Risam, 2015).

Since I am mostly interested in the gender equity problem, without ignoring the other aspects of intersectionality, I would like to go into detail on society’s ever persistent binary logic when it comes to gender. First, let’s take a look at the psychological and sociological use of the term gender I am referring to, which originated in the United States.

The state of being male or female as expressed by social or cultural distinctions and differences, rather than biological ones; the collective attributes of traits associated with a particular sex; or determined as a result of one’s sex. Also: a (male or female) group characterized in this way.
(Oxford English Dictionary)

Even within this very considerate definition, the binary persists. According to the Oxford English Dictionary it is either male or female, not even including “other” and still very much linked to an individuals biological sex, which (just so you know) can also differ from male or female. As a psychologist, Rose Marie Hoffman moves away from this definition of gender as collective attributes, instead discussing Gender Self-Definition and Gender Self-Acceptance (Hoffman, 2006).

Hoffman describes the stages of the Feminist Identity Model (Downing and Roush, 1985) based on Cross’s Black Identity Development Model (Cross Jr, 1971) as:

(a) unawareness of inequity and discrimination through
(b) experience of crises that force one to confront such inequities to
(c) an immersion and identification with one’s own group that provide opportunities for
reflection and exploration to
(d) integration of one’s experiences around the area of
oppression and a concomitant achievement of balance (i.e., able to evaluate people
as individuals instead of only as group members) and, finally, to
(e) a commitment to meaningful action toward eliminating the ism involved.
(Hoffman, 2006).

This Feminist Identity Development also shows some similarities with the sex role transcendence theory by Rebecca et al., which falls into three phases: a lack of awareness of gender roles, a polarization stage, and the transcendence of gender role stereotypes (Rebecca et al., 1976). The womanist position differs from the feminist position in that it
recognizes “poverty, racism, and ethnocentrism as equal concerns with sexism” (Henley
et al., 1998).

Where does Digital Humanities come in, you might ask yourself. I would like to refer to Nickoal Eichmann, Jeana Jorgensen, and Scott B. Weingarts’ study of fifteen years of DH conferences (2000-2015). They did so

(1) to call out the biases and lack of diversity at ADHO conferences in the earnest hope it will help improve future years’ conferences, and (2) to show that simplistic, reductive quantitative methods can be applied critically, and need not feed into techno-utopic fantasies or an unwavering acceptance of proxies as a direct line to Truth.
(Eichmann et al., 2016)

However, in order to study the lack of diversity, in the name of data quality, they acknowledge “the gross and problematic simplifications involved in this process of gendering authors without their consent or input” (Eichmann et al., 2016). In their own defense they state that “with regards to gender bias, showing whether reviewers are less likely to accept papers from authors who appear to be women can reveal entrenched biases, whether or not the author actually identifies as a women” (Eichmann et al., 2016). I can, to a certain extent, agree that gender bias stems from the perception of a person’s gender, rather than the gender they identify with. The question remains however, whether you can assume others to identify authors as male, female, or unknown/other.

There are several tools to test your own bias, such as https://implicit.harvard.edu/implicit/takeatest.html, and http://www.lookdifferent.org/what-can-i-do/implicit-association-test. Fortunately, and probably after working on my master thesis considering the gender balance in both Computer Science and Digital Humanities for a year, my result suggests “little to no association between female and male and science and liberal arts”. This test again demonstrates a binary definition of gender, confirming my main concern.

Bibliography

Kimberle Crenshaw. Mapping the margins: Intersectionality, identity politics, and violence
against women of color. Stanford Law Review, 43(6):1241–1299, 1991. ISSN
00389765. URL http://www.jstor.org/stable/1229039.

Roopika Risam. Beyond the margins: Intersectionality and the digital humanities. DHQ:
Digital Humanities Quarterly, Volume 9, Number 2, 2015.

Rose M. Hoffman. Gender self-definition and gender self-acceptance in women: Intersections
with feminist, womanist, and ethnic identities. Journal of Counseling and
Development : JCD, 84(3):358–372, Summer 2006. URL http://search.proquest. com/docview/219028098?accountid=17215.

Nancy E. Downing and Kristin L. Roush. From passive acceptance to active commitment:
A model of feminist identity development for women. The Counseling
Psychologist, 13(4):695–709, 1985. doi: 10.1177/0011000085134013. URL http: //tcp.sagepub.com/content/13/4/695.abstract.

William E Cross Jr. The negro-to-black conversion experience. Black world, 20(9):
13–27, 1971.

Meda Rebecca, Robert Hefner, and Barbara Oleshansky. A model of sex-role transcendence.
Journal of Social Issues, 32(3):197–206, 1976.

Nancy M Henley, Karen Meng, Delores O’Brien, William J McCarthy, and Robert J
Sockloskie. Developing a scale to measure the diversity of feminist attitudes. Psychology
of Women Quarterly, 22(3):317–348, 1998.

Nickoal Eichmann-Kalwara, Jeana Jorgensen, and Scott Weingart. Representation at
Digital Humanities Conferences (2000-2015). prepublished, 3 2016. URL 10.6084/ m9.figshare.3120610.v1.

LaTeX vs. MS Word – The Battle

Most master students of KU Leuven need to write their thesis sooner or later. However, finding your template might cause nervous breakdowns before you even start writing. Once you do find the page containing the specific template for your masters program, KU Leuven often doens’t offer any choice: you have to use MS Word.

In order to assert whether this situation only occurs in certain faculties, I created this list:

MS Word 9 – 4 LaTeX.

Even though I couldn’t find all faculty templates, this list shows me exactly what I was expecting – with one exception. LaTeX is mostly used in Science, Technology, Engineering, and Mathematics or STEM-programs only, with the notable exception of Economics and Business. Luckily, you don’t have to take my word for it.

In the article Don’t Format Manuscripts by Brischoux and Legagneux, they discuss a frequent occuring issue in academia. If an academic paper got rejected by a journal, resubmitting an improved version usually requires the researcher to reformat the text to the journals standard which can be very time consuming. Only LaTeX users can save time on reformatting if the journal offers an automatic template. Mathematics, Statistics and Probability and Physics show the highest rates of LaTeX users for submitted papers (ranging from 96,9% to 74%), followed by Computer Sciences (45,8%) (Brischoux and Legagneux, 2009).

But does this mean LaTeX is better than Word? José Luis Blanco discusses a scientific experiment determining which typesetting tool is more productive. Turns out that Word is unbeatable – when it comes to long blocks of continuous text and creating tables. However, LaTeX  beats Word on all levels when it comes to texts full of equations. In their usability questionnaire, the researchers on Experimental Psychology from the University of Giessen (Germany) also found that:

LaTeX users significantly more often reported to enjoy their work with their respective software than Word users […]. (Knauff, Nejasmic, 2014)

Even though the ease of use might convince you to never look outside the comfort of the Word-box, here are some of my personal opinions on the advantages of LaTeX:

  1. It is Open Source software, need I say more?
  2. The focus during writing is on content, not markup.
  3. It saves you time adapting to other templates.
  4. It doesn’t crash when you have more than 100 pages – personal experience.
  5. It looks more professional.
  6. Implementing citations, footnotes and bibliography is easy using extensions like BiBTeX.

Maybe some of you are still wondering, what is LaTeX? Well, the the LaTeX Project gives this definition:

LaTeX, which is pronounced «Lah-tech» or «Lay-tech» (to rhyme with «blech» or «Bertolt Brecht»), is a document preparation system for high-quality typesetting.

You could compare it to the Hyper Text Markup Language or HTML, with the important difference that LaTeX is used for documents instead of webpages.

So if you are taking the Online Publishing course, and are already learning how to use HTML, why not push yourself further out of your comfort zone? I used LaTeX for an essay I wrote last year for another course, and taught myself while working on the essay for three days using the Five minute guide to LaTeX.

Bibliography

Knauff, M., & Nejasmic, J. (2014). An Efficiency Comparison of Document Preparation Systems Used in Academic Research and Development. PloS one, 9(12), e115069.

Brischoux, F., & Legagneux, P. (2009). Don’t Format Manuscripts. The Scientist, 23(7), 24.

So you think you know Digital Humanities?

Although I have been enrolled in the Master of Digital Humanities (MDH) for a year by now, the discussion on “What is digital humanities?” remains relevant as there is no single answer to this simple question. In fact, there are several interesting definitions of digital humanities (DH) on the http://whatisdigitalhumanities.com/ website. Every time you refresh their website you get a different point of view, another attempt at defining DH.

In my opinion, DH comes down to two essential and complementary elements: employing digital tools to study the Humanities and Social Sciences, and criticizing the limits and biases those tools may cause. Unfortunately defining DH brings a whole new set of problems to the table. As Lisa Spiro clarifies in “This Is Why We Fight”: Defining the Values of the Digital Humanities:

Even as the digital humanities (DH) is being hailed as the “next big thing”, members of the DH community have been debating what counts as digital humanities and what does not, who is in and who is out, and whether DH is about making or theorizing, computation or communication, practice or politics (Spiro, 2012).

The same people that try to define DH and therefore select the “chosen ones”, dwell on how wonderfull and revolutionary the community of DH is in comparison to other more traditional academics. Matthew Kirschenbaum noticed this (self)praise of Digital Humanities in his article on What is Digital Humanities and What’s It Doing in English Departments? after the discussion on Croxall’s paper at the 2009 Modern Language Association (MLA).

Many seemed to feel that the connection to wider academic issues was not incidental or accidental and that digital humanities, with a culture that values collaboration, openness, nonhierarchical relations, and agility, might be an instrument for real resistance or reform (Kirschenbaum, 2012).

This brings me to my next topic: “What are the core values of digital humanities?”. Before I discuss these values, I would like to point out that the simple act of defining values, usually means these values do not (yet) exist in reality.

The first value Lisa Spiro discusses in her article is openness on two levels, both in the exchange of ideas, and in the strive for open content and software as well as transparancy (Zorich, 2008). I believe several issues arise from this strive for openness. The first issue regarding the exchange of ideas, will be discussed together with the second value. Secondly, open content and transparancy in humanities research, can violate the privacy of the participants. Once there are clear guidelines, I do believe openness stands at the core of Digital Humanities. You can find DH project guidelines here: Digital_Humanities (Burdick et al., 2012, 122-135).

Spiro goes on to the second value of collaboration, which does not only improve productivity, but also encourages new approaches. However, in the humanities identifying the author is key, since the author should get the credit. Articles from the natural sciences often contain an entire list of authors, contributors, and so on, that are ordered according to their contribution. The first author for example is the person that wrote the article, while the last author oversees the project. Therefore I feel DH needs a clear order of contributors with meaning attached to every position so that every person that collaborated gets the correct recognition for their work. As Bethany Nowviskie already states in het blogpost on monopolies of invention:

The biggest question for you may be how you’ll open potentially awkward conversations about status in a way that strengthens your team, creates – rather than limits – opportunity, and permits the kind of fluidity and professional growth we all want to foster over the course of long-term, collaborative initiatives. (Nowviskie, 2009).

This statement also connects to Lisa Spiro’s third value of collegiality and connectedness. I truly hope that the positive atmosphere from the MDH generation 1.0, will transfer to the generation 2.0. In our program I do feel there isn’t such a competitive spirit as in my previous field of study, and the feedback and encouragement of fellow students is really nice. Whether this atmosphere applies to the broader DH community, I do not know.

The final two values will probably recur extensively in my next blogposts, so I will not discuss diversity and experimentation in this blogpost. However, in the context of experimentation I would like to add that no result, is still a result and should definitely not be hidden. When a certain project fails, describing the steps in the process can actually help other researchers, as well as open the discussion on why it didn’t work and how it could work with another method/tool/dataset.

Bibliography

Spiro, Lisa. ““This Is Why We Fight”: Defining the Values of the Digital Humanities.” Debates in the Digital Humanities. Minneapolis, MN: University of Minnesota Press, 2012.
http://dhdebates.gc.cuny.edu/debates/text/13.

Kirschenbaum, Matthew. “What Is Digital Humanities and What’s It Doing in English Departments?”. Debates in the Digital Humanities. Minneapolis, MN: University of Minnesota Press, 2012.
http://dhdebates.gc.cuny.edu/debates/text/38.

Zorich, Diane. A Survey of Digital Humanities Centers in the United States. Washington, DC: Council on Library and Information Resources, 2008.
https://www.clir.org/pubs/reports/pub143/pub143.pdf.

Burdick, Anne, Drucker, Johanna, Lunenfeld, Peter, Presner, Todd, and Schnapp, Jeffrey. Digital_Humanities. Cambridge, MA: MIT Press, 2012.
https://mitpress.mit.edu/sites/default/files/titles/content/9780262018470_Open_Access_Edition.pdf.

Nowviskie, Bethany. “Monopolies of Invention.” Bethany Nowviskie. December 30, 2009.
http://nowviskie.org/2009/monopolies-of-invention/.