The Chronicle ran a piece today called “The Long Odds of the Faculty Job Search.” Two narratives are told – a search for a creative writing position at Ohio and a search for a linguist at Florida.

Academic job search narratives – at least in the Humanities – are attractive for what they might reveal: the secrets for success. When I was a graduate student, I was very interested in these narratives; I believed that they would show me how to get a job. There really are no secrets, of course. One must prepare (build a CV), write a dissertation that is part of a larger conversation (so others will be interested), attend conferences as a grad student (start to build audience and show you are in the field) and meet people (network with those who might later know you when you apply).

This is the preparation. Many people don’t prepare. For the prepared, which we can assume includes a significant number of applicants described in the two Chronicle narratives, then comes the network. The network brings together the human (committee) and non-human (CV, letters of recommendation, previous experience, dissertation topic, school one applies to, etc) actors. When people say the job search is a “crap shoot” or “lottery,” I assume that they are talking about the network. The network is neither; it is merely the moment where actors come together and the result of this coming together is a job offer. The actors can come together, really like the candidate, and still not make an offer. Or the actors may come together, not make an offer because they weren’t satisfied with the network that formed, and the candidate can still be great. With the humans, it is extremely difficult to predict what will occur. In searches I’ve chaired or been a member of, we sometimes agree, we sometimes don’t. As a candidate, I was accepted or passed over by the humans for all kinds of reasons, some of which I still don’t understand today. We can’t really control the humans. We can’t control the non-humans either, but we can interact with them differently.

I offer my own brief narratives as example.

• 2001. I am graduating from the University of Florida. I have more interviews than anyone else from my program. I have publications. I have a textbook about to be published. I know people. I ran conferences as a graduate student. I also have a year left of funding if things don’t work out. I don’t get an offer until almost the end of the hiring season, as WPA at The University of Detroit Mercy. A small Jesuit liberal arts university is not my first choice. But it’s what I get. One non-human, my interviewing skills, has failed me. I obviously don’t interview well. The year of funding left is a non-human actor in this network that does not influence my return to graduate school. I take the job and its very low “take it or leave it” offer. The funding affects me in that I know I could return, but the poor performance after so many interviews has more effect in this network: Who is to say I will do better the following year? I also already know someone at UDM.
• 2003. Over an informal dinner, the chair of Wayne State asks me to apply to their opening. I don’t. I’m not sure I want to stay in Detroit, though I know I want to leave UDM at some point. When the job is not filled, and it is re-opened in the Spring, I do apply. As probably the only candidate, I get the job and its much higher salary. The actors – an unfilled job (a job unfilled, actually, after several tries) and already being in Detroit play a role as much as my background and CV. So does that dinner. It returns to the conversation during the campus visit.  I also already know someone at Wayne.
• 2007. When we can’t get spousal hires at Wayne State or Penn State, we go on the market, and I get an offer at the University of Missouri. Two actors – beyond my book about to come out and my CV – play a role (as far as I can tell). I’ve been a WPA previously (the position included being the WPA), and the first person the job is offered to turns it down. In the logic of the university, paying an extra few thousand in salary is not the same as hiring someone’s partner. That is, our hiring costs Missouri more than the extra few thousand the first person wanted, but our hiring does not affect salary compression. The WPA position at UDM is an actor here.  It plays a role. I also already know someone at Missouri.
• 2011. When we are asked to apply to The University of Kentucky (we are not on the market), one actor plays an important role (as far as I can tell) beyond my CV and books. When I was WPA of the composition program at Missouri, a talk on Turnitin.com was held by the IT educational group, ET@MO. I don’t care about Turnitin, and as composition director, would never allow it to be used program-wise. But, as composition director, I felt I should attend and hear what the group was saying. No one else attended. The Vice Provost showed up and saw me there, and he heard some comments I offered. When the Campus Writing Program position opened up at Missouri (a better paying position than composition director with much better amenities), he remembered me. That WAC position of a million dollar program, an actor in this network, played a role when we negotiated our acceptance at Kentucky.

I only touch upon a few actors here: people I knew, positions held and accepted, space (Detroit also was an actor), attending a talk no one else attended, a dinner. I gave a talk a couple months ago, and a graduate student picked me up to take me to the airport the next day. He apologized for not coming to the talk. “I had a lot of papers to grade.” The talk took about an hour and a half. That hour and a half could eventually be an actor in a network the graduate student may later enter. Or not. I feel comfortable, though, saying that the paper grading will not be a significant actor later.

Of course, one does not know. The one actor I always return to is that Turnitin talk. If I hadn’t gone, would I have been WAC director? Would I have received a level of ethos that would later have to be addressed in a future job negotiation where an endowed professor position was put on the table (would I, as only Associate Professor have received that offer)? I don’t know.

My advice regarding the job narrative is something like: gather all the actors into your network that you can.You have no idea how they will interact later on, but if you have no actors (no dinners, no conference discussions, no attending talks by people whose work is or is not in your field, no whatever), you likely have nothing. I watch a lot of graduate students (at Wayne, at Missouri, and even here at Kentucky in our brief, not totally involved time), have nothing. They go on the market without any networks to enter and be a part of, and are angry when the results are not positive. Grading papers as excuse to not interact with someone? Not a valuable actor later on. Driving someone to the airport? A good actor, but interacting in a more scholarly way by attending the talk (how do people give talks? how do they present themselves? what do they talk about? can I engage with that person afterward?), a better actor.

When I was a graduate student at our main conference, I asked a question at a fairly well known scholar’s talk on a textbook he was co-writing. My question was a critique – I wanted to know why something hadn’t been included. The scholar responded, and we talked afterward (I told him my name). A month or so later, I was asked to review the textbook for the publisher. The network provided me a little money for the review (good for a graduate student!). In 2001, I interviewed at the scholar’s university, and he was on the committee. We knew each other. I didn’t get the job, but I know that my question was an actor in this network. Even without the job, I still think the actor was important. Networks aren’t good or bad things. They don’t guarantee success or failure. They are our interactions. If we have no interactions, we don’t have much of a career and often, we don’t have a chance to start a career in this profession.

My wife, the composition director, and I were talking sections this morning. Much of this has to do with staffing in the composition program, staffing that includes 150 sections of courses: three levels of composition and business writing. With the business writing courses, they are running 25 sections of 25 students. A part time instructor (reduced to 3/3 without health benefits, based on the university’s response to Obamacare) means four PTIs could handle it mostly (we still have one leftover section). If funding for those PTIs is yanked, which seems to be the case, what do you do? I look back on my first WPA job and the advice of the former chair of the department: “Don’t fill the sections. Fuck ‘em.” He also had been fired, so I didn’t follow his advice.

How do you restructure, if at all? We discussed one large course – 100 students, with one breakout section staffed by one TA. Professor (or whoever) lectures two days a week and does not grade. TA handles all 100 students for grading.

In a 2/2 situation with sections capped at 27, the TA would grade and teach 54 students a semester. In this situation, the TA does not teach (much or at all) but grades 100 students.

With business writing, we have 625 students. We need six TAs (with leftover of 25 students) who will now handle about double the number of students than if they were teaching. We need six 100 student sections. We need three faculty, each teaching two sections (faculty are on a 2/2 load). I can’t imagine any faculty member wanting his/her teaching each semester to be two 100 student business writing courses. So, we need six faculty? That’s a lot. That pulls from  other important teaching the faculty member might do in the curriculum. And with only  nine tenure line faculty (five non-tenure line), it makes the program a business writing program. We are not a business writing program, even if we wanted to be one.

What if, then, we had one 625 student MOOC or course of some sort. And six TAs to grade? Those six TAs would normally teach 324 students. The difference is 301 students, who would, in a teaching situation,  be taught by another five to six TAs. We saved the cost of five to six TAs.

What does a TA cost? I think $12,000 without health benefits (I don’t know the cost of their health benefits to the university). But with a new model that counts tuition wavers as real money, the cost would be even higher. A PTI, I believe, makes about $2,800 or $3,200 a course without health benefits (I don’t remember the number I was told recently). Swap TA for PTI (thinking that a PTI would want this work which is only grading), and the cost is $16,800 for six PTIs ($2,800) or  $19,200 ($3,200) for one MOOC -like course. Pretty cheap. It’s a little bit more than what one PTI on a 4/4 load makes in a semester. For the price of one PTI teaching four courses (108 students), you get six PITs grading 625 students.

Now, my math skills are based on using Google calculator. If I’m wrong, so be it. No surprise. I have balanced budgets in my WPA past, but often not on the first try.

And I’m not advocating this scenario. I’m not advocating any option. I’m an outsider/bystander not privy to the delicate conversations going on behind closed doors. I’m merely thinking about the problem since I am not participating in its solution. There are, no doubt, other options available. One option, in all sincerity, is fuck it. Don’t fill the sections. If the sections make money – which they have to since a PTI’s salary is covered by four students in a 27 student capped course – then who would want the sections unfilled? 23 students at $900 each is $20,700 for one course; $20,700 x 25 is $517,500 (which might pay off a good chunk of the tenure line faculty salaries). If you don’t cover the sections, you lose substantial money. But the cost to staff seems so low to begin with. The MOOC like course, as we see, greatly reduces expense. What are the hidden costs to jamming 625 students in one course? We’d find out in time, I’m sure.

A few years ago, I gave a talk at the WPA conference on the narratives of cap size in first year courses. Going through WPA-L archives, one could see how the “argument” against raising caps was often situated as if such arguments had never occurred. That is, the archives revealed the same “Help, my dean wants to raise cap sizes, what should I do” threads going back years. None of the narratives of face to face attention or manageable size, of course, mattered. Yet, such arguments were repeated as evidence in such a struggle. The struggle is seldom won.

I was thinking this morning about a cap size shift form let’s say 25 students to 27 in a first year course. The savings from this shift would be about $900 per student over 25 (the cost of the course). We offer 87 sections of the first year course. 2 x 87 = 174. 174  x $900 = $156,600. The average instructor on a 4/4 load without health benefits, I believe, makes around $28,000 a year here at UK. That comes to 5.5 instructors who will not need to be hired. The money is significant, no doubt. To make an argument against raising the cap by two students, one would have to show that this savings of money is not as significant as it appears to be.

The average TA teaching the additional two students is also going to shift to a 2/2 load. 2/2 is not unreasonable for graduate students to teach and has become a norm nationwide. But 54 students a semester for someone

• Still taking coursework
• Writing a dissertation
• Learning how to teach and be a student

is a lot. I can teach 54 students a semester. I’m not a TA. What, then, would be the retention fallout from the assumed issues that will develop when a TA struggles to respond adequately to student work and do his/her own work in order to graduate on time and get a job? We have 174 new students in the raised cap sections. If retention rates see an 10% drop off (and I think the number is higher), how much money is lost? The average student at UK pays about $9,000 a year on tuition. 17 is 10% of the 174 number (almost). 17 x 9 = $153,000 lost each year over the next three years for each student who leaves UK. That comes to almost $1.4 million.

Of course, I cannot argue total causality over a first year writing course not providing enough attention to a student, and thus, that student leaves the university. But I also provide a fairly low drop off number. All kinds of factors lead to student success and retention.  But I cannot deny that any course in the first year experience is important to overall student success. My work in the Wired residential college shows this point. In a two year period (our only two year period to date), students who completed Wired have a 92% retention rate (they are still at UK). The university has, I believe, somewhere around 72% retention. That’s a lot of lost money.

I’m actually not against raising caps. I’m realistic. But I’m also realistic regarding who teaches the course. If I have to teach a course of 25 and the cap is raised to 27, I’m fine. I can handle the extra work. I question, though, whether brand new teachers (TAs in a four-six year period learning the profession) or part time instructors who have no health benefits and are likely teaching elsewhere since the pay here is not so great (and who, frankly, are doing this work because they did not get jobs elsewhere) have the same ability to balance work that I do. I also question the savings here. Is it worth the risk of greater loses than what I believe is a fairly conservative estimate? I see no savings. I have a $3,000 year potential saving, but a $1.4 millon loss over graduation period (and also, no alumni to draw from in later years).

My reason for this little breakdown? Local exigence, of course.

With the “free” or cheap availability of services online, we see a great deal of tension between the concepts of the disruptive and what we might call the useful.

• The disruptive = this will change the world
• The useful = this makes X easier to do

When the service vanishes or is bought out, the disruptive narrative becomes a narrative of anger and betrayal. Thus, Douglas Rushkioff makes a public announcement on CNN.com  that he is closing his Facebook account or Anil Dash wants to teach us what the Web really means (because supposedly we have lost that meaning). The recent Elsevier acquisition of Mendeley highlights this point. Prominent technology figures make clear that their usage of the service will end because a publishing conglomerate known for limited access will now own the free service. One doesn’t just stop using a service that until this point was free, cheap, or appeared disruptive;  one makes that cessation public. Public outcries often conflate usefulness with a greater ideological mission. In this narrative, the free or cheap is a the alternative with no motives other than improving the public good; the other thing is the big, bad, corporation that wants to destroy all that is good in life. No free or cheap service can be interested in financial gain, the narrative relates. Financial gain is the nature of big business.  Technology narratives often begin from this narrative and are disappointed when conditions become otherwise.

Part of this public outcry is a conflation of a belief with a usage. The belief is that technological innovations are for the greater good (“this will change the world”).  The service, though, may not be born out of such a disruption but may just be an idea (“wouldn’t it be cool to share scholarship the way we can share digital files otherwise”). Sometimes innovators have both positions in mind, but not always. Sometimes innovators do want their ideas to make them money. Or make them a lot of money. Users, on the other hand, want to approach a technological innovation as a moment of utopia or the greater good (“now we are all liberated”).  Facebook has been largely treated this way. The desire to show students at an Ivy League university who else is in their class has transformed into a billion dollar business. For some reason, adults who have used this service over the last few years have decided that the service is theirs and not Facebook’s (see boyd’s insistence on Facebook being a public utility a few years back), and that the millions of dollars it takes to run Facebook is of no consequence. Thus, if Facebook runs ads to pay for those servers and employees, and if those ads make usage of the information users eagerly yield to the application, users get angry. The same holds true for Gmail. A free cloud based app that gives you 10 GB of storage wants to push ads to you based on an algorithmic reading of information patterns so that the app makes money?  Disruption or business innovation? Maybe both. But disruptions do not need to be bound to purification narratives, as Latour might say. Users do not need to treat each innovation as a cultural rebirth or new era of hope. We might remember that one of the first websites created upon the innovation we call the Web was a company that sold hot sauces.

I, too, feel disappointment when a useful service vanishes. I used Del.icio.us regularly before it went under, and I depend on RSS for my web reading so much that Google’s decision to cancel its Reader can be summed up as “this sucks.” But neither service was ever presented to me as altruistic or world changing. Or: I never approached each service as such. This sucks can be the generic reaction to service cancellation. This sucks, however, need not be an ideological position.

Yesterday, as we drove north on Limestone, we noticed that a restaurant we visited once and thought was fine had closed. This sucks, I thought. But I did not feel the sense of betrayal or loss that often accompanies other business failures. Google Reader made my online reading easy and informative. This sucks, I thought when I read about its upcoming closure. My trust or lack of trust regarding Google likely resembles those feelings I have for other companies whose products I consume. There is an emotional connection obviously (it would suck if Founders stopped making beer, for instance). But that emotional connection is not such that I believe it is about me.  I don’t feel betrayed when something I liked is no longer available or no longer available in the way it once was. I merely feel: this sucks. Rushkoff making a public show of his emotions on CNN.com is an “about me” emotional moment. For some reason, Facebook is about him (or anyone else upset over its data mining practices). He feels betrayed. The disruption, it turns out, was about making money, not the emotional attachment he, or others, placed on Facebook (others might call this a fetish). If I trust or don’t trust Google (or Facebook), should I feel that way about any other producer of goods and services I use: the gas company, Founders, Apple, the taco truck, the yogurt I buy, local meat providers, Bikram Yoga, Whole Foods, Levi’s, the Miami Heat, and so on?

But for some reason, free online applications raise our emotional attachments in ways many of these other products don’t. We conflate disruption (“life will now be better than ever and we will all be equal and happy”) with service or business.Maybe the question isn’t if information wants to be free or not. Maybe the question is if users want to be free or not of emotional attachments? Maybe, after all the Luddite and techno-phobia narratives we also hear, technology is not as cold as we are told it is. Maybe technology is highly emotional; it captures passion and misapplied affection in ways that treat all innovation as a personal trust or belief.

My two and a half year old son won’t stop saying “fuck.” Whatever he thinks this word means, he – like many other two and a half year olds – knows it’s something that he’s not supposed to say. In order to divert him from saying fuck, but keeping with the spirit of saying “bad words,” I’ve been trying to convince him to replace fuck with “Burt Bacharach.” When he says fuck, I reply, “Oh no. You mean Burt Bacharach.” Then he will yell, “Burt Bacharach!” This works with modest success. He does say Burt Bacharach a good deal, and even greeted me that way this morning when I cam home from the gym. But he also still says fuck.

The idea of conditioning children to certain meanings is not new. When Morgan Spurlock writes of his plans to punch his kid every time they pass a McDonald’s so that his kid associates pain with fast food, he speaks of such conditioning. And of course, the idea that language is ambiguous is not new. We all know the story of words having arbitrary meanings – whether we say fuck or Burt Bacharach. When Anil Dash writes in a recent (to me) post entitled “The Web We Lost,” that “we’re going to face a big challenge with re-educating a billion people about what the web means,” he, too, seems to be caught in the ambiguity of language. What the web means? Does the web mean something? Dash seems to believe it does. In this narrative, the web means 1. users control everything 2. commerce (which gives the users what to control) controls nothing. 3. Companies should not pursue “their agendas instead of collaborating in a way that would serve users.” All of these positions, of course, are the result of conditioning too – a conditioning that blankets practices under the generic term “capitalism” (always used as a pejorative) and treats what is current as our inability to recognize what we’v lost. As Dash says,”we’ve abandoned core values” with current web practices. Substitute “core values” for “family values” and you have basic conservative thought. Indeed, this kind of technology narrative is highly conservative in its understanding of the present as it relates to a supposed past.

We might call this meaning romanticism. Or wishful thinking. Or naivety. Or utopian visions. Or gatekeeping.  Or even conservatism. What it does, though, is attribute a meaning to a period (let’s say early Facebook or pre-Facebook) that was not there to begin with. That is, it assumes that what we are calling “the web” was always meant to be an altruistic space of sharing and giving and user generated content and…..but where is the evidence to support this narrative, a narrative that David Weinberger, too, seems to support? Mostly in memory. Commerce was with the web early on – even if not at the scale we see it today. And there is nothing in any constitution or declaration or anything that maintained early on that all content must be user generated and profits should be controlled and market control not allowed.

It’s not uncommon to attribute to past moments, technologies, experiences to this type of rearview mirror thinking. The narrative typically is: everything we have now is ok….but damnit, it is nowhere near as great as what we once had. And as Jameson pointed out, this is how pastiche functions. It hides history (even as Dash makes a claim for historical reflection).

Like my Burt Bacharach experiment, this process succeeds and fails simultaneously. My kid knows that Burt Bacharach (whatever that is) is not fuck. Fuck is better than Burt Bacharach. Burt Bacharach, for him, is merely another word to yell. He seems to doubt it having the power fuck has. On the other hand, he says fuck a bit less than he used to, and he says Burt Bacharach a bit more than he used to (since he wasn’t saying it at all). The rearview mirror approach does draw attention to contemporary problems (good), though its romanticism hides the previous problems (bad). The problem, as McLuhan said, is when rearview mirror thinking is all the thinking we have; our garden of edens dominate our vision, we are stuck in blind fields, and we ignore the power of the contemporary and recent. I will take CMS over .html pages any day. Updates and tweets have re-formulated the necessity of brevity and quick response. And while I am not supporter of dominant market forces stifling competition, the spin-off economies often associated with dominant entities – everything from Grantland to Facebook’s innovative usage of advertising – is fascinating and complex (as well as a space for further innovation).

Mosaic as the browser to cherish over Chrome? Flickr tags over Instagram creativity? Technorati’s slowness and inability to crawl everything as opposed to a Google cache? Do we remember the same history here or just the pastiche?

The announcement that Google is canceling its Reader has hit me hard. I like news. I like following a variety of news sources. RSS allows me to follow news easily. The Reader consolidates the feeds into one space. Some of the topics (as I have arranged them) in my subscriptions:

• Beer
• City
• Food
• Israel
• Music
• Sports
• Tech
• Kentucky

And a whole bunch of things left without a category (friends’ feeds, political feeds, Grantland). Beer alone makes up a significant part of my subscriptions - numbering close to 1,000. With so much information circulating on a daily basis, how else can I keep track? RSS is vital. I spent some time tracking down alternatives that will allow import of Googles saved feed file.

• Old Reader – about 27,000 imports ahead of me in the que. It will be awhile.
• Feedly – nice interface. But it doesn’t default to showing the entire article. And it relies on my Google account.
• Rolio -still processing my Google file.

The beauty about the feed is that it minimizes Web reading to one site – a frame in a tabbed browser. Keep it open. News comes to you. We used to click on those endless “blogrolls” before RSS in order to keep up with each other’s thoughts and ideas. RSS aggregates. Aggregation is a key principle of new media writing and thinking.

Facebook, too, aggregates writing and thinking. But it is limited to “friends” and “pages” and not to the endless supply of topic driven writing occurring elsewhere.

There are other ways to aggregate, of course, I aggregate every MOOC piece I can find in Diigo. These collected sites inform my thinking and will play a role regarding how I write about MOOCs. But these links did not come to me. I went to them. I saved them. Now they are aggregated. I need, though, the links to come to me first.

Aggregation teaches. I can attribute a great deal of my beer knowledge to my RSS subscriptions. On a daily basis, I learn about releases, commentary, tastings, upcoming events, promotional materials, video releases, collaborations and so on.  This is how I spend some of my day. Learning by aggregation.

We spent last week in Las Vegas at our field’s main conference. I did not want to go. But an opportunity existed (more later) that I felt I had to follow up on. Walking along the Strip, one encounters the Sammy Hagar restaurant, Hard Rock Cafe, the M & M Store, Margaritaville, and a number of other chains (restaurants and stores). I know why I don’t like Vegas. But it’s too easy to offer up that critique of superficiality (it’s a commonplace aggregated in our collective critical knowledge). Instead, there is the question of why others like Las Vegas. Obviously, people like Vegas and these places. When I left at 3:30 am Saturday for an early flight, the Strip was still packed with people. Vegas visitors like this aggregation of the commonplace (similar, we can say, to how critics like their own aggregated commonplaces such as a typical critique of Vegas). You can go to a House of Blues in many cities; why come to Vegas to go to one? You can drink a Coors tall boy at 10 am anywhere. Why come to Vegas just to do it while walking down the street (and for more money, too)? There is an aggregation here that is meaningful to many people. They like this stream of familiar storefronts and headline acts (Faith Hill, The Blue Men, Roseanne Barr). The people, though, go to the aggregation. It’s assembled for them. Nice and neat.

I like my Reader aggregation. It’s neat, too, but only because of how I organize it. It’s not pre-organized for me. And its content changes daily (In Vegas, Grand Canyon tours will be there today, tomorrow, the next day….so, too, will be Eddie Griffin and his three shows a week act at some casino). What makes RSS special, then, if aggregation exists already in numerous spaces in a variety of forms (like the Vegas strip)? I could say “surprise” (look at what I got today!), or content (my feeds are more meaningful than the Hard Rock Cafe), or the juxtaposition of disparate material (as opposed to the same $8.50 beer draught price along the strip).

Or not. I simply like my own aggregation. Others choose Vegas’ aggregation. The difference, of course, is that of atoms and bits. Nobody’s canceling Vegas in July. It will still be doing its job then. Google Reader, on the other hand, will vanish as bits.  Atoms, too, can vanish. And bits can remain. Just not in this case.

It’s no secret that ours is a wold of pattern formation. I often introduced the concept of pattern formation when I was a WAC director (and later used it as exigence in “Networked Assessment”) by drawing attention to the infamous underwear bomber, a situation where pattern formation would have revealed his intent (instead of catching him while in the act).

The Digital Humanities, too, is interested in patterns. I’ve understood the literary/historical side of its work (even in the call to “build”) as the re-energized study of the novel. Either the novel itself or some variation of Google’s Ngram (the novel over time) will reveal new patterns previously unidentified in whatever kind of hermeneutical work done without algorithm. The 19th century, as our inside joke goes, is suddenly discovered to be all about transportation once such a pattern is identified over a novel or series of novels. Obviously, the work is important to people who study texts in order to produce interpretive meaning.

Big data is a sports issue as well. Henry Abbot on what is basically the Moneyball question asks how stats produce patterns which, in turn, can inform general managers about a player’s likelihood of contributing to a team’s success. Big data, here as well, is about interpreting. The payoff of that interpretation, though, is financial. Find the right pattern, and you may find the right mix of players for success.

Out of all the recent discussion of MOOCs, the one pattern I notice is the utopian/distopic dichotomy. This pattern attracts my attention for a number of reasons. One is it’s obvious (how many anti-MOOC pieces note the benefits of face to face education; how many pro-MOOC pieces note the open access issue). The second reason is that I am basically hearing the exigence I discovered for writing Digital Detroit: Detroit is in ruins/Detroit is on the verge of rejuvenation. It was not too difficult to see that no space (city or otherwise) could be reduced to such a simple binary. MOOCs, on the other hand, are treated as such a binary. We might call this interpretative gesture small data since it is concerned with only pro/con positions or the re-circulation of commonplaces.

Thus, there is one text to mine: the commonplace. We can have a library of commonplaces (and we always do: Middle East, Detroit, presidential campaign, gun control….). Big data, as the Digital Humanities like to call it, is really just building a library of texts so that they may be efficiently mined. And I’m not sure that Moneyball is the same thing. The Moneyball move involves the specific study of statistics (a library of texts) in order to predict future performance. The literary mining of big data is often a return to practices already in circulation, practices that can be simplistically reduced to “what happened back then?”

I prefer to look ahead. Examining data in order to better understand how an audience acts, an idea can be invented, a message will be delivered…..this seems to me the essence of locating and using big data. Part of that examination is understanding how individuals might act in terrorist situations. Part of that examination might involve persuasion (arguing for positions within the university, for instance, as I see my colleagues often do without data of any sort). Part of the examination might be getting students to take courses in a department that is not yet a department (our own dilemma in WRD) . Part of that examination might involve activity tracing (as assessment studies claims for itself, though typically with a pre-determined goal to declare relevance).

There are tales of big data. Moneyball is one such tale. In the film Moneyball, Peter Brand says:

It’s about getting things down to one number. Using the stats the way we read them, we’ll find value in players that no one else can see. People are overlooked for a variety of biased reasons and perceived flaws. Age, appearance, personality. Bill James and mathematics cut straight through that. Billy, of the 20,000 notable players for us to consider, I believe that there is a championship team of twenty-five people that we can afford, because everyone else in baseball undervalues them.

Value, of course, is a shifting concept. But think about this quote for a second. “We’ll find value in players that no one else can see.” What I want out of big data is what I and everyone else can’t yet see. I know that a committee of the most predictable computer people on campus will yield a very predictable response on MOOCs. I know it because the committee itself does not reflect big data (its value is based on a commonplace – circulated role in the university as the familiar, “ASK THAT PERSON”). I know that the search through a novel will produce endless issues of “what we thought was x is really y” because this is a commonplace among literary approaches to interpretative works. Big data, exemplified by Moneyball, is not about re-finding the commonplace. But we are good at mining commonplaces. Our politics, our university policies, our approaches to scholarship – so often we are back with a commonplace. And in this mining, we produce not what no one else can see, but what we already saw. Face to face education is superior. Of course. Or as NPR told me this morning while I was driving to yoga, Detroit is in ruins. Of course.  Are there tales of big data? Or is there just one tale, a commonplace mined again and again?

My email inbox has 1,593 messages in it. I say that knowing that the goal of many email users is to have zero messages in their inbox. A recent Lifehacker post narrates one such goal. “Inbox zero is a lofty and often unachievable dream for most,” the post states, “and for a long time I just assumed that piles of email would rule my life.”  I call the tellers of such email narratives the “1,000-0″ email users. They are typically individuals who have about 1,000 messages in their inbox, and they want zero. They tell the 1,000-0 narrative in order to share their major achievement of eliminating all that unwanted email taking up space in their virtual inbox. A Chicago Tribune writer tells this narrative. A ProBlogger post tells this narrative. 1,000-0 is the goal of the story’s outcome. 1,000-0 is the story of victory agains the odds.

I have 1,593 messages in my inbox. This number does not reflect all the email stored in my Thunderbird program, nor the messages saved on my other laptop, which also has a Thunderbird installation and which I spark up every now and then for a file not transferred to my new(er) laptop. My trash folder, on the other hand, has 5,476 messages in it, a number that makes my inbox look puny and insignificant. Even with 1,593 inbox messages, I have deleted 5,476 messages – messages that could easily return to my inbox without much notice. Why I deleted 5,476 messages and kept 1,593 messages is not entirely clear to me, but something indicated to me to allow many of my messages to be deleted, or at least moved to a folder called “trash.”

Unlike the stories associated with email glut,I  don’t fee that email rules my life. In fact, hours go by without a single email arriving in my inbox. Even though I do some administrative work (it’s over 20% of my DOE), I don’t get that much administrative email. Even though I’m editing a collection, writing a book, reviewing all the time for journals, and doing other academic work, I don’t get that much email. Even though I encourage (or beg) students to talk about their semester projects with me, only a few ever take me up on the offer – either in person or by email. I’m not on any listservs.My wife sends me Google chats, not email.  My parents don’t email me. My colleagues don’t email me – except to tell me not to discuss university business on email.

But I do have 1,593 messages in my inbox, a number that would bother most 1,000-0 email users. Because everything digital these days associated with academia is being called “Digital Humanities,” I wondered: is this a Digital Humanities problem? Email seems to be forgotten in Digital Humanities’ narratives, even as it is dominant in 1,000-0 narratives. Given the “big data” impulse of many Digital Humanities scholars, one might wonder why all this big data – 1,593 messages in my case – is not an object of study.

What are some of the important subject  headings of these 1,593 messages?

• “Re:”
• “Fw:”
• “Introduction”
• “Meeting Agenda”
• “Meeting Minutes”
• “Updates”
• “POT:  18th Floor”

Granted, these are not very exciting subject headings on their own. And granted, this is a small sample size mostly taken from the last few emails in my inbox.  But neither would be much of the material data mined by a typical Digital Humanities scholar running algorithmic searches through a typical online database of images or scanned text be exciting on its own.  Digital Humanities scholars love patterns in material, often more than the material itself. In fact, I’m sure these subject headings could tell a fascinating story if brought together at the point of pattern formation. That story might be “We’re going to have an agenda and minutes for the 18th floor” or “Hey, there are updates of the agenda on the 18th floor.” Fascinating stuff.

For this reason, I am sure, I do not care about having zero emails in my inbox. If I were to eliminate all of my email, what data would I have to mine? How could I make sense of “Re:” in light of the larger email conversation that might also include “POT: 18th Floor”?  Are Digital Humanists missing out on a big data by reducing their inboxes to zero? Are they denying themselves insights into the subject matter of contemporary media based education as it relates to email? MIght we learn what the big story of 21st email inboxes are by examining and studying this big data?

Oh look. A new message. Make that 1,594 now.