Author Blogs

Earlier this week, Kathleen Fitzpatrick presented a statement to the National Academy of Sciences on the MLA’s position on public access to scholarly work. I was particularly interested in this line:

we may in coming years operate under a model in which, rather than joining in order to receive the society’s journal, one instead joins a society in order to get one’s own work out to the world, surrounded by and associated with the other work done by experts in the field.

This statement led me to wonder what motivates people to join MLA. Are they really joining in order to receive the society’s journal? I found that a surprising claim. That has never been my motive for joining. I would be interested in some marketing/survey data that supported that argument. I would imagine that a significant part of MLA membership is driven by the organization’s gatekeeping function over employment opportunities in the profession. One has to be a member to access the MLA job list (or belong to a department that has membership and that is willing to share that access with you) and one has to pay MLA to attend the conference where most of the interviews are held (and join MLA to present at the conference). The other significant reason for being a member is that membership has become a kind of professional habit; it’s part of a professorial identity for certain fields. I’ve never felt that way myself. In fact, I’ve never really seen MLA as representing my interests. I have been an off and on member over the years, strictly in terms of whether I was on the job market and/or presenting at the conference. My membership in NCTE/CCCC has a similar track record. And I also wouldn’t join that organization for the purpose of receiving CCC .

I realize that’s a lot of digital ink for one aside in this position statement, but I imagine that, in trying to articulate new reasons for joining MLA, understanding the old motives would be important. Additionally, I think it would be important to consider the motives underlying publication by MLA members and prospective members.

The statement suggests that “the locus of a society’s value in the process of knowledge creation may be moving from providing closed access to certain research products to instead facilitating the broadest possible distribution of the work done by its members.” Now I might be interested in this, but it makes me wonder if MLA is going into the search engine optimization business. Will MLA drive traffic to my website or improve my Google Rank? I’m fairly certain this isn’t what is meant here. Instead, as indicated in the second half of that passage quoted above, “broadest possible distribution” probably means something like a humanities version of arXiv with a more social media feel or maybe an MLA-approved version of academia.edu. I think this perhaps what MLA Commons seeks to become.

In the comments following the statement, David Golumbia points to the variety of motives the underlie publishing done by MLA members. He argues “the number of MLA members who routinely publish in paying public venues from which they earn significant revenue is much larger than one might imagine off the top of one’s head. Doing anything to discourage or prohibit MLA members from publishing in these venues and earning income from their work can only have seriously negative effects on the profession.” I don’t know what significant or routinely means here, but I am sure there are MLA members who fit this category. To this first group of money-making authors, I would add a large number of MLA members for whom the primary motive to publication is getting tenure or a better job. That is a second group of motives. Finally, I would say that a large majority of MLA members publish work with virtually no concern for audience beyond getting their articles through the review process. All the really matters is journal reputation which is measured more by acceptance rate than by anything else. My point is that just as it may be a mistake to imagine that people join MLA to be able to read the journal, it may be a mistake to imagine that a MLA members, as a general rule, produce scholarship with the goal of it being read.

Part of this is the problem of hyper-specialization. Of course research is going to be specialized to some degree, to quite a high degree in fact. MLA has 30,000 members. There are more students in some MOOCs than there are members in MLA, so even writing something to the entirety of MLA is a comparatively small audience. Then if you think about the numbers in a particular part of the field, say “19th century American Literature,” one is imagining a number in the 1000s, probably low thousands. But, we aren’t done there. Then we are going to focus on a specific author (e.g. Melville) or period/region (e.g. antebellum Southern). Now we are in a community of 100s. That’s a small “broadest possible distribution”! However, it’s a lot of authors. There could be 100+ articles in the field every year, written primarily to this audience. Sure, the work might be of interest to a larger community, say the 1000s in 19th-century American literature, but those folks are all also generating publications. And not because there is a demand for the work by the reading audience, but because…. um, because… err.

Maybe because the authors want to be published. Maybe. We certainly want the professional rewards that accompany publication. We want to do the research. I would describe my own research interests as wide-ranging and often esoteric. People will come up to me and say they enjoy my blog but don’t read the OOO stuff. I get that. It can be dense, and the audience may be limited for it. However I am interested in OOO, and I am also tacitly pressured by my profession to be “theoretical.” I always feel my challenge as an author is to take these theoretical concerns and make them valuable for a larger audience or at least a different audience.

In short, as the MLA thinks about changing the way it approaches scholarly communication, I think it needs to explore more fully the motives that drive this work. More importantly, the shift toward digital publication will alter those motives I think (I hope). I would like to think that in my writing (both here and in more formal venues) that I am addressing concerns that have more kairotic purchase than they are just topics that I and a couple hundred other folks happen to study. I know that my move toward thinking of my work in these terms comes out of writing on this blog and thinking more about audience. I am guessing that if/when more scholars move toward more open venues, it might shift the tenor of their work as they strive to address those audiences. I’m sure this potential shift would signal a concern for many. And I wouldn’t say that it is a universal good; things will be lost and gained in the shift from one genre to another. Instead it is a matter for us to investigate.

After ten years, I’ve moved from typepad to wordpress. I won’t bore you with the story, but I’m still working on migrating my disqus-based comments. Hopefully that will all be worked out this weekend.

In The New Yorker, Joshua Rothman continues the discussion about the relative wisdom of entering graduate school in the humanities. In my mind, it comes down to this: getting a phd in the humanities (9.3 years on average) takes so damn long that it is almost impossible to measure the cost and benefit of it. I could give you my personal story, but as Rothman points out, personal stories aren't worth much in trying to make these decisions. All I'll say is that I didn't have a good reason to go to grad school, but once I was in, I became very strategic in relation to the job market. In our department, it seems like many people finish in 7 years, but they may have come from an MA that took them 1.5 years to finish, which would put us around the national average of 8.9 years from the start of grad school. The average age of a Phd recepient in English is 33.7, which happens to be about the time that I learned I had been tenured (which only points to the limited value of personal stories).

The challenge of making a purposive decision in entering a humanities doctoral program and the near-decade it takes to get the degree are symptomatic of a general decision-making problem across the disciplines. The problem is that doctoral education pretends to be about professionalization, but never really gets there. Instead, the humanities confuse hyper-specialization with professionalization. I've written about the woes of hyper-specialization before many times here. If we could avoid hyper-specialization, I think it would be conceivable to finish in five years rather than nearly nine. What that would mean is that those first three years of coursework and qualifying exam preparation would need to be much more purposeful in terms of the dissertation to be written. One would be introduced to the research methods and theories that would be taken up in the dissertating phase, and one would get a clear sense of the field. Most importantly, one would need to be taught how to write a dissertation (it isn't magic). In an English phd program, one would probably read the equivalent of 150 books in those 3 years and about half of those during preparation for exams that should be specifically tailored to one's research project. After having spent 3 years reading, discussing, and writing about this large corpus of texts, you then have two years to write that dissertation. Now the danger is that after having done all that work, one is tempted to embark on an entirely new project that requires reading another 100 books (or so). I think this temptation stems from the fact that people enter the humanities because they are interested in reading and research but not in communicating or composing knowledge.

There is also some strange notion at work about what knowledge is and how it is made. In my view, it is a perfectly acceptable heurstic to say, "I have read 150 books. Now I am going to write my dissertation based on the 3 years of research I have done. As such, I am going to limit my works cited to those books, plus a maximum of 25 more." Then one goes about organizing chapters based around those texts.  The sense of cohesion and mastery that a book or dissertation displays is always a rhetorical trick. It seems to me that this is what I learned when writing my dissertation: to take things I'd already written and make them appear as though they went together. And of course they did go together, in the way that a line can be drawn between any two points. I guess it was a trick I had learned on a smaller scale writing seminar papers, where I would take a few quotes from the course texts and stitch them together with my own writing.

But somehow it doesn't happen that way for most dissertation writers and I'm not entirely sure why, except to say that I think it has something to do with the general purposelessness of the humanities. Without a purpose, research can continue interminably. There is always more to read, other questions to ask, and so on. It is as though one becomes beguiled by one's own rhetorical trick into believing that there is something more, some deep hidden secret, some inspired master idea, that drives the text. Sure, we feel these things from time to time, those flashes of insight when everything seems to come together in our minds. But that's just a trick of the light; the mind doing what the mind does. I mean, I trust those intuitions inasmuch as I find they are reliable in predicting my ability to put certain ideas together, to compose knowledge, but I don't believe they are in the text. It makes more sense to say that knowledge is composed rather than discovered.

I think that if one approaches these matters purposively and pragmatically they remain a fair amount of hard work but they cease to be these quixotic journeys. So why don't we do it that way? Why does it take years rather than months to write a dissertation? I would guess it has to do with the value placed upon experience rather than results. This is what Rothman is expressing: one cannot get a good handle on the value of a humanities doctoral degree because one can't get a handle on the experience. I think that's completely the wrong way to look at it though, it does explain why it takes people so long. There's no ineffable expereince in writing a disseration; what you're feeling is the product of sensory deprivation as a result of not seeing the sun for weeks on end. The problem is, I fear, that graduate programs are structured to reinforce this notion rather than to dispel it.

In The New Yorker, Joshua Rothman continues the discussion about the relative wisdom of entering graduate school in the humanities. In my mind, it comes down to this: getting a phd in the humanities (9.3 years on average) takes so damn long that it is almost impossible to measure the cost and benefit of it. I could give you my personal story, but as Rothman points out, personal stories aren't worth much in trying to make these decisions. All I'll say is that I didn't have a good reason to go to grad school, but once I was in, I became very strategic in relation to the job market. In our department, it seems like many people finish in 7 years, but they may have come from an MA that took them 1.5 years to finish, which would put us around the national average of 8.9 years from the start of grad school. The average age of a Phd recepient in English is 33.7, which happens to be about the time that I learned I had been tenured (which only points to the limited value of personal stories).

The challenge of making a purposive decision in entering a humanities doctoral program and the near-decade it takes to get the degree are symptomatic of a general decision-making problem across the disciplines. The problem is that doctoral education pretends to be about professionalization, but never really gets there. Instead, the humanities confuse hyper-specialization with professionalization. I've written about the woes of hyper-specialization before many times here. If we could avoid hyper-specialization, I think it would be conceivable to finish in five years rather than nearly nine. What that would mean is that those first three years of coursework and qualifying exam preparation would need to be much more purposeful in terms of the dissertation to be written. One would be introduced to the research methods and theories that would be taken up in the dissertating phase, and one would get a clear sense of the field. Most importantly, one would need to be taught how to write a dissertation (it isn't magic). In an English phd program, one would probably read the equivalent of 150 books in those 3 years and about half of those during preparation for exams that should be specifically tailored to one's research project. After having spent 3 years reading, discussing, and writing about this large corpus of texts, you then have two years to write that dissertation. Now the danger is that after having done all that work, one is tempted to embark on an entirely new project that requires reading another 100 books (or so). I think this temptation stems from the fact that people enter the humanities because they are interested in reading and research but not in communicating or composing knowledge.

There is also some strange notion at work about what knowledge is and how it is made. In my view, it is a perfectly acceptable heurstic to say, "I have read 150 books. Now I am going to write my dissertation based on the 3 years of research I have done. As such, I am going to limit my works cited to those books, plus a maximum of 25 more." Then one goes about organizing chapters based around those texts.  The sense of cohesion and mastery that a book or dissertation displays is always a rhetorical trick. It seems to me that this is what I learned when writing my dissertation: to take things I'd already written and make them appear as though they went together. And of course they did go together, in the way that a line can be drawn between any two points. I guess it was a trick I had learned on a smaller scale writing seminar papers, where I would take a few quotes from the course texts and stitch them together with my own writing.

But somehow it doesn't happen that way for most dissertation writers and I'm not entirely sure why, except to say that I think it has something to do with the general purposelessness of the humanities. Without a purpose, research can continue interminably. There is always more to read, other questions to ask, and so on. It is as though one becomes beguiled by one's own rhetorical trick into believing that there is something more, some deep hidden secret, some inspired master idea, that drives the text. Sure, we feel these things from time to time, those flashes of insight when everything seems to come together in our minds. But that's just a trick of the light; the mind doing what the mind does. I mean, I trust those intuitions inasmuch as I find they are reliable in predicting my ability to put certain ideas together, to compose knowledge, but I don't believe they are in the text. It makes more sense to say that knowledge is composed rather than discovered.

I think that if one approaches these matters purposively and pragmatically they remain a fair amount of hard work but they cease to be these quixotic journeys. So why don't we do it that way? Why does it take years rather than months to write a dissertation? I would guess it has to do with the value placed upon experience rather than results. This is what Rothman is expressing: one cannot get a good handle on the value of a humanities doctoral degree because one can't get a handle on the experience. I think that's completely the wrong way to look at it though, it does explain why it takes people so long. There's no ineffable expereince in writing a disseration; what you're feeling is the product of sensory deprivation as a result of not seeing the sun for weeks on end. The problem is, I fear, that graduate programs are structured to reinforce this notion rather than to dispel it.

From the Chronicle, William Germano writes on the staid nature of monographs, particularly first books.

The academic book—especially that first academic book—is often conceived of as a snow globe. It's carefully constructed to be a perfect little world, its main purpose to be admired. There's a glass wall that separates the contents from the reader. That construction is not accident.

Within the realm of the snow globe, every authority on the subject has been cited or pacified. Look inside and find a perfect, tidy, improbable world where no questions are asked, or invited. Scholarly books, especially first ones, are a paranoid genre—their structure assumes that someone is always watching, eager to find fault. And they take every precaution against criticism.

Germano proposes the book as machine: "The book-as-machine should trouble or excite or inspire or even confuse. (Sowing confusion is, within a limited compass, a reasonable goal for a writer, just as long as it isn't the only goal.) The book-as-machine requires that the scholarly writer imagine a problem or concern that will engage the reader, making the investment of reading time worthwhile."

While Germano doesn't really raise dissertations in this context, in my view the problem begins there. Certainly one could say the problem lies with the conservative nature of the humanities. Or with the uncomfortable fact Ian Bogost observes in Alien Phenomenology: academics, on the whole, aren't good writers. Writing that doesn't follow the pedantic plodding of convention is treated as suspect (unless, of course, one is speaking about French theorists who are permitted to be wholly inscrutable). Graduate students acquire this view early on in their careers. In some ways I think it insulates academics from the expectation that their writing really have an audience. It is as if academic freedom should protect one from the requirement that others find one's work valuable. 

But here's the most interesting thing to me about Germano's comparison: snow globes. 

This is probably the most famous snow globe scene. 1941, the year of Citizen Kane, was around the time when snow globes (an invention of the 19th century) were reaching their height of popularity. Certainly by the late sixties interest in snow globes had waned and now they are really only of interest to the collector. Perhaps they are much like monographs in that respect: a curiosity from another time. In other words, the snow globe is not just an overwrought confection; they are an antiquated one as well.

I like Germano's idea of the book-as-machine, though I might want to take that more literally than he and imagine a different kind of technology than the print book. But in this post, I'm going to set aside the technology question and point to the preparation of academics to publish their research. The insanity of this whole business, as everyone knows, is that graduate students, on average, take more than 9 years to get doctorates in the humanities. This means they are spending more than five years writing dissertations: book-length texts that are, almost by definition, unpublishable. And if we follow Germano, after writing that unpublishable dissertation, we follow that with an unreadable monograph, which clearly one would only be prepared to write after spending five years writing unpublishable prose. After all, one doesn't learn to produce unreadable prose over night. 

So how about a dissertation project that can be completed in less time and results in a text that at least attempts to be readable and publishable, that looks to excite or inspire readers. Why should book length texts be written for narrow audiences of specialists, a maximum of a couple hundred readers? We don't have to jump to a "general readership." We can find plenty of middle ground there: the thousands in one's general field or the tens of thousands in one's discipline. Sure that's a challenge, but at least it's one worth taking up, a challenge that, if met, would mean having some impact. Maybe one doesn't pull this off in a dissertation, but the attempt lays the groundwork for moving forward in this vein. By the way, this task doesn't need to take five years either.

From the Chronicle, William Germano writes on the staid nature of monographs, particularly first books.

The academic book—especially that first academic book—is often conceived of as a snow globe. It’s carefully constructed to be a perfect little world, its main purpose to be admired. There’s a glass wall that separates the contents from the reader. That construction is not accident.

Within the realm of the snow globe, every authority on the subject has been cited or pacified. Look inside and find a perfect, tidy, improbable world where no questions are asked, or invited. Scholarly books, especially first ones, are a paranoid genre—their structure assumes that someone is always watching, eager to find fault. And they take every precaution against criticism.

Germano proposes the book as machine: “The book-as-machine should trouble or excite or inspire or even confuse. (Sowing confusion is, within a limited compass, a reasonable goal for a writer, just as long as it isn’t the only goal.) The book-as-machine requires that the scholarly writer imagine a problem or concern that will engage the reader, making the investment of reading time worthwhile.”

While Germano doesn’t really raise dissertations in this context, in my view the problem begins there. Certainly one could say the problem lies with the conservative nature of the humanities. Or with the uncomfortable fact Ian Bogost observes in Alien Phenomenology: academics, on the whole, aren’t good writers. Writing that doesn’t follow the pedantic plodding of convention is treated as suspect (unless, of course, one is speaking about French theorists who are permitted to be wholly inscrutable). Graduate students acquire this view early on in their careers. In some ways I think it insulates academics from the expectation that their writing really have an audience. It is as if academic freedom should protect one from the requirement that others find one’s work valuable.

But here’s the most interesting thing to me about Germano’s comparison: snow globes.

This is probably the most famous snow globe scene. 1941, the year of Citizen Kane, was around the time when snow globes (an invention of the 19th century) were reaching their height of popularity. Certainly by the late sixties interest in snow globes had waned and now they are really only of interest to the collector. Perhaps they are much like monographs in that respect: a curiosity from another time. In other words, the snow globe is not just an overwrought confection; they are an antiquated one as well.

I like Germano’s idea of the book-as-machine, though I might want to take that more literally than he and imagine a different kind of technology than the print book. But in this post, I’m going to set aside the technology question and point to the preparation of academics to publish their research. The insanity of this whole business, as everyone knows, is that graduate students, on average, take more than 9 years to get doctorates in the humanities. This means they are spending more than five years writing dissertations: book-length texts that are, almost by definition, unpublishable. And if we follow Germano, after writing that unpublishable dissertation, we follow that with an unreadable monograph, which clearly one would only be prepared to write after spending five years writing unpublishable prose. After all, one doesn’t learn to produce unreadable prose over night.

So how about a dissertation project that can be completed in less time and results in a text that at least attempts to be readable and publishable, that looks to excite or inspire readers. Why should book length texts be written for narrow audiences of specialists, a maximum of a couple hundred readers? We don’t have to jump to a “general readership.” We can find plenty of middle ground there: the thousands in one’s general field or the tens of thousands in one’s discipline. Sure that’s a challenge, but at least it’s one worth taking up, a challenge that, if met, would mean having some impact. Maybe one doesn’t pull this off in a dissertation, but the attempt lays the groundwork for moving forward in this vein. By the way, this task doesn’t need to take five years either.

On e-Literate, Elijah Mayfield has a good post addressing some of the myths (his term) going on around the subject of machine grading, particularly in response to the NY Times article that provocatively suggested that "Essay Grading Software Offers Professors a Break." I've been re-reading Manuel DeLanda's Philosophy and Simulation for my speculative realism class, which has me thinking about this is from some different angles I suppose. From Mayfield's perspective, as someone invested in machine learning and developing these kinds of applications, machine grading isn't about replacing professors (or giving them a break) but rather providing a different kind of feedback to authors. It really isn't grading at all. As Mayfield writes "If I were to ask whether a computer can grade an essay, many readers will compulsively respond that of course it can’t. If I asked whether that same computer could compile a list of every word, phrase, and element of syntax that shows up in a text, I think many people would nod along happily, and few would be signing petitions denouncing the practice as immoral and impossible."

This would be the point, right? The computer isn't "reading," so it clearly isn't "grading," if grading requires reading in the first place and means establishing relative quality (e.g. this essay is better than this other one). 

Mayfield doesn't want to think about machine grading as replacing teaching but rather as a supplement, helping students: "What if, instead of thinking about how this technology makes education cheaper, we think about how it can make education better? What if we lived in a world where students could get scaffolded, detailed feedback to every sentence that they write, as they’re writing it, and it doesn’t require any additional time from a teacher or a TA?" Perhaps it is pollyanna to imagine this outcome, but I am interested in different questions here.

First, let's dispense with the grading aspect. The problem with the grading process is that it is always underlying the lamest possible writing activity: one where 100s of students are asked to write essentially the same response to a single, fairly narrow prompt. There is no real purpose of communication with another human. No one wants to write the texts, and no one wants to read them. As I understand this, the machine can sort responses only because the answers are so uniform and predictable. Mayfield, at one point, uses the example of sorting between photos of ducks and photos of houses. And the reality is that this kind of essay writing is equivalent to asking students to go, take a photo of a duck, and submit it for a grade. As a result the computer can tell whether the student has taken a duck photo or not. But if the assignment was to take an "interesting" photo. Well, let's just say that don't yet have to worry about a computer making that judgment for us. 

On the other hand, I think part of the problem (and resistance) to machine grading lies in a serious misunderstanding of what humans do when they grade. To appropriate William Carlos Williams, a text is a machine made out of words. A text is a machine. For a Deleuzian like DeLanda, a human might be a machine as well. That is, humans reading texts are already machines processing other machines. In machine-to-machine relations, we are talking about capacities, not just the properties of a given text, which are finite, but the interaction of those properties with any possible reader in any given situation, which creates infinite capacities to affect. We already know all the things we do to norm readers to create predictable responses. In other words, grading is always about creating a situation that is unlike reading elsewhere, not only in a large standardized test, but in typical composition classroom grading as well. By regularizing one end of the equation, we hope to get better measurments of the other end (i.e. the student). As a grader I do not and cannot care about what the author says. To care is to invalidate the evaluative mechanism. It doesn't matter if I agree with your politics or not. All I am looking for is to see if the text has certain objective criteria. Have you ever watched a movie and started focusing on things like directorial or acting decisions (e.g. that's an interesting camera angle or that was a curious facial expression to match that line of dialog)? It's almost impossible to become affectively invested in the film. That's what grading is like.

That said, when one responds to student writing, one has to offer up real engagement with the text, because writing for the purpose of a grade is even more depressing than reading for the purpose of a grade. You have to generate some real, genuine human response to the subject matter. But this stops being about evaluation of the student then because we open up the Pandora's box of capacities; we become a chain of machinic interactions. And here the computer is already a welcome participant. Human feedback is valuable, but the network can analyze our text and offer thousands of interesting and useful responses. Today we use the network to uncover plagiarism, but tomorrow we could use it to link our students to 100s or 1000s of other writers and texts that share their interests. Think of a kind of reverse Google: your text is composed of these search terms. 

Whether the machine is a human or a computer, the mass grading process is a statistical procedure that says that a writer who produces a text with certain measurable qualities is likely to be an "A," "B," or whatever, which in turn means they are statistically likely to "know" the content on which they are being tested. On the other hand, when a text is read, by a human or a computer, the reader establishes links between the text and a larger network of data, which generates a response. Do I mean to equate humans and computers? Not really. I suppose my point is that the issue here is with the practice of grading, not the machine doing it.

On e-Literate, Elijah Mayfield has a good post addressing some of the myths (his term) going on around the subject of machine grading, particularly in response to the NY Times article that provocatively suggested that "Essay Grading Software Offers Professors a Break." I've been re-reading Manuel DeLanda's Philosophy and Simulation for my speculative realism class, which has me thinking about this is from some different angles I suppose. From Mayfield's perspective, as someone invested in machine learning and developing these kinds of applications, machine grading isn't about replacing professors (or giving them a break) but rather providing a different kind of feedback to authors. It really isn't grading at all. As Mayfield writes "If I were to ask whether a computer can grade an essay, many readers will compulsively respond that of course it can’t. If I asked whether that same computer could compile a list of every word, phrase, and element of syntax that shows up in a text, I think many people would nod along happily, and few would be signing petitions denouncing the practice as immoral and impossible."

This would be the point, right? The computer isn't "reading," so it clearly isn't "grading," if grading requires reading in the first place and means establishing relative quality (e.g. this essay is better than this other one). 

Mayfield doesn't want to think about machine grading as replacing teaching but rather as a supplement, helping students: "What if, instead of thinking about how this technology makes education cheaper, we think about how it can make education better? What if we lived in a world where students could get scaffolded, detailed feedback to every sentence that they write, as they’re writing it, and it doesn’t require any additional time from a teacher or a TA?" Perhaps it is pollyanna to imagine this outcome, but I am interested in different questions here.

First, let's dispense with the grading aspect. The problem with the grading process is that it is always underlying the lamest possible writing activity: one where 100s of students are asked to write essentially the same response to a single, fairly narrow prompt. There is no real purpose of communication with another human. No one wants to write the texts, and no one wants to read them. As I understand this, the machine can sort responses only because the answers are so uniform and predictable. Mayfield, at one point, uses the example of sorting between photos of ducks and photos of houses. And the reality is that this kind of essay writing is equivalent to asking students to go, take a photo of a duck, and submit it for a grade. As a result the computer can tell whether the student has taken a duck photo or not. But if the assignment was to take an "interesting" photo. Well, let's just say that don't yet have to worry about a computer making that judgment for us. 

On the other hand, I think part of the problem (and resistance) to machine grading lies in a serious misunderstanding of what humans do when they grade. To appropriate William Carlos Williams, a text is a machine made out of words. A text is a machine. For a Deleuzian like DeLanda, a human might be a machine as well. That is, humans reading texts are already machines processing other machines. In machine-to-machine relations, we are talking about capacities, not just the properties of a given text, which are finite, but the interaction of those properties with any possible reader in any given situation, which creates infinite capacities to affect. We already know all the things we do to norm readers to create predictable responses. In other words, grading is always about creating a situation that is unlike reading elsewhere, not only in a large standardized test, but in typical composition classroom grading as well. By regularizing one end of the equation, we hope to get better measurments of the other end (i.e. the student). As a grader I do not and cannot care about what the author says. To care is to invalidate the evaluative mechanism. It doesn't matter if I agree with your politics or not. All I am looking for is to see if the text has certain objective criteria. Have you ever watched a movie and started focusing on things like directorial or acting decisions (e.g. that's an interesting camera angle or that was a curious facial expression to match that line of dialog)? It's almost impossible to become affectively invested in the film. That's what grading is like.

That said, when one responds to student writing, one has to offer up real engagement with the text, because writing for the purpose of a grade is even more depressing than reading for the purpose of a grade. You have to generate some real, genuine human response to the subject matter. But this stops being about evaluation of the student then because we open up the Pandora's box of capacities; we become a chain of machinic interactions. And here the computer is already a welcome participant. Human feedback is valuable, but the network can analyze our text and offer thousands of interesting and useful responses. Today we use the network to uncover plagiarism, but tomorrow we could use it to link our students to 100s or 1000s of other writers and texts that share their interests. Think of a kind of reverse Google: your text is composed of these search terms. 

Whether the machine is a human or a computer, the mass grading process is a statistical procedure that says that a writer who produces a text with certain measurable qualities is likely to be an "A," "B," or whatever, which in turn means they are statistically likely to "know" the content on which they are being tested. On the other hand, when a text is read, by a human or a computer, the reader establishes links between the text and a larger network of data, which generates a response. Do I mean to equate humans and computers? Not really. I suppose my point is that the issue here is with the practice of grading, not the machine doing it.

Collin Brooke has a recent post revisiting an old CCCC presentation (I was there and posted about it back then. Collin updates his thinking in response to Anil Dash's talk on "The Web We Lost" and here. Jeff Rice also writes about Dash. All three offer views on what we've lost or gained as culture or discipline in the ongoing churn of digital media networks. Collin in particular talks about fields and streams--the disciplinary field in relation to the social media stream of middle-state publishing (Twitter, FB, blogging, etc.)--and thinks about what his graduate students need from him in balancing the more traditional content of the field with tendencies toward the stream. 3 years ago perhaps there was a greater need to recognize the stream; today maybe the stream has become a flood. 

I like this ecological trope and want to play it out. It's easy enough to say that our media ecology has experienced its own kind of climate change. The streams have moved, and the fields that once flourished have begun to dry up. But there's new life elsewhere. Fields and streams are part of a larger climate system. To incorporate Dash into this metaphor, we need to add the concept of cultivation, and, by extension, property. 10-15 years ago, the web operated by a far more open architecture than it does today. The corporate spaces of Facebook and Instagram have pushed out the more open blogging and Flickr. As Jeff points out, we can experience nostalgia about the early days of web 2.0 or web 1.0 or even the days before the web, when our discipline's research and pedagogical paradigms still made sense. Of course it's just as easy to have a romantic view of the future. For Jeff this begins with recognizing that the web does have an integral set of values toward being "open" or "closed." Open and closed systems are part of the same ecology though. All interaction requires a degree of openness, an openness to affect and be affected. Developing strategies for closing and redirecting streams might be understood as means for survival and reproduction (to stay with an ecological theme). Dash argues that we have lost something in moving from open to closed systems, even while we have maybe also gained something in the production of better, though closed, applications. Collin also wonders about what is gained or lost in the shifts from field to stream and back. For Jeff I think the question of what is gained or lost is not the right question, even though clearly we must all make decisions based upon values. Collin needs to decide about the curriculum for his graduate course. Elsewhere, we need to have conversations about the values that drive web practices. 

The danger with the ecological trope is to mistake this as naturalizing a situation that we should insist on viewing as cultural or social. However, given my Latourian view, I am not inclined to accept the natural-social distinction. Instead, I am trying to get at a sense of the actor-network operating here. What is it that the closed system of Facebook makes us do? (To use Latour's phrase,"makes" meaning not compels us but rather composes us; this is not about determinism in a zero-sum game where either the individual or society wins.) 

From my perspective, the interesting question is what is it that our students need to know or be able to do? Or in Latourian terms, what do they need to be made to do? We can start this question with graduate students, as Collin does, and ask what do students today, graduating in 2020, need? But we might as easily begin with undergraduate education, since today's grads are tomorrow's professors (hopefully): what will undergrads need to be made to do? Or perhaps one wants to think of this in terms of the citizens or professionals those students are and will become? However one phrases this, part of the answer has to be an ability to understand how these digital media networks function, what they do and do not do, and what the consequences of these choices might be. We might think of this as the procedural rhetoric of digital media. The informational-communicational world is far more complex today than 15-20 years ago. Figuring out how to learn to live in it... that's a task for the humanities. Not that humanists should tell people how to live (oops, too late), but rather that the humanities investigates this question and the ways we answer it.

Collin Brooke has a recent post revisiting an old CCCC presentation (I was there and posted about it back then. Collin updates his thinking in response to Anil Dash's talk on "The Web We Lost" and here. Jeff Rice also writes about Dash. All three offer views on what we've lost or gained as culture or discipline in the ongoing churn of digital media networks. Collin in particular talks about fields and streams–the disciplinary field in relation to the social media stream of middle-state publishing (Twitter, FB, blogging, etc.)–and thinks about what his graduate students need from him in balancing the more traditional content of the field with tendencies toward the stream. 3 years ago perhaps there was a greater need to recognize the stream; today maybe the stream has become a flood. 

I like this ecological trope and want to play it out. It's easy enough to say that our media ecology has experienced its own kind of climate change. The streams have moved, and the fields that once flourished have begun to dry up. But there's new life elsewhere. Fields and streams are part of a larger climate system. To incorporate Dash into this metaphor, we need to add the concept of cultivation, and, by extension, property. 10-15 years ago, the web operated by a far more open architecture than it does today. The corporate spaces of Facebook and Instagram have pushed out the more open blogging and Flickr. As Jeff points out, we can experience nostalgia about the early days of web 2.0 or web 1.0 or even the days before the web, when our discipline's research and pedagogical paradigms still made sense. Of course it's just as easy to have a romantic view of the future. For Jeff this begins with recognizing that the web does have an integral set of values toward being "open" or "closed." Open and closed systems are part of the same ecology though. All interaction requires a degree of openness, an openness to affect and be affected. Developing strategies for closing and redirecting streams might be understood as means for survival and reproduction (to stay with an ecological theme). Dash argues that we have lost something in moving from open to closed systems, even while we have maybe also gained something in the production of better, though closed, applications. Collin also wonders about what is gained or lost in the shifts from field to stream and back. For Jeff I think the question of what is gained or lost is not the right question, even though clearly we must all make decisions based upon values. Collin needs to decide about the curriculum for his graduate course. Elsewhere, we need to have conversations about the values that drive web practices. 

The danger with the ecological trope is to mistake this as naturalizing a situation that we should insist on viewing as cultural or social. However, given my Latourian view, I am not inclined to accept the natural-social distinction. Instead, I am trying to get at a sense of the actor-network operating here. What is it that the closed system of Facebook makes us do? (To use Latour's phrase,"makes" meaning not compels us but rather composes us; this is not about determinism in a zero-sum game where either the individual or society wins.) 

From my perspective, the interesting question is what is it that our students need to know or be able to do? Or in Latourian terms, what do they need to be made to do? We can start this question with graduate students, as Collin does, and ask what do students today, graduating in 2020, need? But we might as easily begin with undergraduate education, since today's grads are tomorrow's professors (hopefully): what will undergrads need to be made to do? Or perhaps one wants to think of this in terms of the citizens or professionals those students are and will become? However one phrases this, part of the answer has to be an ability to understand how these digital media networks function, what they do and do not do, and what the consequences of these choices might be. We might think of this as the procedural rhetoric of digital media. The informational-communicational world is far more complex today than 15-20 years ago. Figuring out how to learn to live in it… that's a task for the humanities. Not that humanists should tell people how to live (oops, too late), but rather that the humanities investigates this question and the ways we answer it.

The SUNY Council of Writing's annual conference was held yesterday in Buffalo. There were a number of interesting panels. Richard Miller and Kelly Kinney gave excellent plenary talks. Here I want to think about some of these conversations in relation to what we are doing at UB and my own vision for composition's future. 

Kelly is the director of the Writing Initiative at SUNY Binghamton, which recently won an NCTE CCCC award as a program of excellence. What are some of the program's defining features?

• Autonomy from the English department: this means independent space, budget, and hiring decisions, including deciding which TAs to admit as teachers.
• Class capped at 16. Binghamton has other courses students can take to meet their writing requirement, so the FYC class is limited to 1st year students only. Still 70-80% of first-year students take the course.
• 7 full-time faculty: some are traditional ladder faculty housed in the English department (including Kelly) and some are "clinical" faculty (non-research). I think they are at the instructor rank.
• Adjuncts make $4500 per course, which in part seems doable as I believe she only has two adjuncts.
• Common syllabus, which includes a portfolio worth 70% of the grade that is evaluated by at least two instructors.
• Portfolio instructor groups that meet on a weekly (bi-weekly?) basis, which is a great opportunity for professional development.

If there is one area the program is lacking it might be in moving toward digital composing, which is something that Kelly mentioned.  Digital composing was a central issue in Richard Miller's talk yesterday. It was a wide-ranging and well-received talk, and I will only settle on a few salient points. Miller discussed the struggles that students have with the directive to "be interested" in something that leads them to write. He observed that the superabundance of information and media stimulation is a significant factor in our students' (and, let's face it, our own) capacity to sustain a focused interest on a subject. We are all familiar with this argument, I think. We are, I think, equally aware of the countervailing argument that our always connected context facilitates opportunities to do incredible things with our "cognitive surplus." Miller also discussed this. Most importantly, he outlined the ways in which our traditional practices, hinged on the precepts that information is scarce (you have to go to the library and there's only one copy of the book) and mastery means content expertise, no longer applies. Instead, in a condition of information superabundance, mastery comes in the form of "resourcefulness:" having the skills to find the information and put it together for a digital community. For readers here, this message is familiar, but it was very well pitched to the audience yesterday (and still a message that the bulk of my discipline, to say nothing of the rest of the humanities, has failed to hear or understand).

One notable quality of Richard's pedagogy is his emphasis on helping students discover their passions and facilitating their exploration of those passions in a wide range of media and genre. It's a pedagogy that requires flexibility and improvisation from the instructor, which in turn requires a high level of expertise in rhetoric and composition. It also demands a specific pedagogical focus which puts the emphasis on the student where the connection to rhetoric and compositional processes arrives organically. You can check out some of Richard's students' work here. True, these are not FYC students. My point is not to say "look how well the students write." This isn't a heroic pedagogy narrative. Instead, my point is that the kind of appraoch that Richard takes would be difficult to accomplish in Kelly's program.

Or at least so we might think: that there is a tension between a standardized program and a classroom that faciliates this kind of open experimentation and pursuit of student interests. 

I've been thinking about these issues in our own program as we move to adopt a common textbook for our 101 writing course. The convention in the humanities (and elsewhere in the academy) is that professors choose the topics and readings for their courses. This is based, first, on the principle that professors teach a subject rather than teach students, and second, that professors are masters of the subject content. As such, the depiction of FYC as an experimental zone focused on student interests, while not uncommon in the field (at least once upon a time), is quite atypical otherwise.  FYC has become more disciplinary as the field has become more professionalized over the last 20 years (e.g. with the expansion of PhD programs in rhetoric and composition).

However I don't see these different emphases as necessarily opposition; they do require some tuning though. Without expertise in rhet/comp and commitment to its principles, the open FYC class becomes a free-for-all zone where the "content-less" nature of the course links with the conventional humanities impetus of the professor teaching according to her own content mastery to produce a curriculum where students are asked to write on whatever subject interests the instructor. With less experienced instructors it is very hard to get around this situation on some level, even if we attempt to negotiate some middle point where the writing topics represent some hoped for overlap between instructor and student interest/expertise. This is what we typically see with the "readers" publishers produce for FYC. 

We have adopted a common 101 textbook, Mike Palmquist's Joining the Conversation, which is a "rhetoric" (i.e. it offers instruction on rhetorical/compositional practices). The text does little, in my view, to limit the capacity of students to pursue their own interests as writers. As a "purpose-driven" rhetoric, it does introduce students to different purposes student-writers might identify in relation to their interests: evaluating, reporting, proposing, etc.  As such, students in a class might be asked "to evaluate," which might take the form of different genres--all different kinds of reviews (movies, books, performances, restaurants, a product etc.), an op-ed evaluation of a politician or law, an evaluation of a piece of research, a progress evaluation, a self-assessment, and so on. We can then make these genres more varied by intersecting them with different media (a slidecast, a blog post, a letter or memo, an internal report, a classroom essay). In theory, beyond the dictate "to evaluate" a student in a class using this text might choose among many genres depending on what suited her interest, purpose, and audience. In practice, an instructor might require all students to write movie reviews (for example). And in a way this might be understandable, especially for the novice instructor, as handling a wide range of topics and genres is challenging. This is particularly the case when an instructor adds topical readings (to extend my example: sample movie reviews and maybe some more academic/intellectual essay on film). At least in this example, we can hope that most FYC students can stir up some personal interest and expertise in movies. I have made this same choice in desiging the common syllabus taught by our incoming TAs: identifying specific topics in which I hope students and TAs will have some interest/experience--education, creativity, social media, etc. I have also narrowed the genre of a given assignment to make the task more manageable. 

Now I am wondering though if this is really the best decision. I would like to see a curriculum that opened up more opportunities for student interest and experiment, especially across media, while still introducing students to basic rhetorical concepts like purpose, audience, and genre and helping students identify and develop their compositional practices. I am sure the fear would be that chaos would ensue, but my experience is that when FYC students open a word processor they have a hard time writing anything that isn't basically essayistic (i.e. like what they wrote in high school). That's why the digital assignments are so interesting, because they push students into a different compositional network where they can't just replicate what they once did. We would still want students to write essays and draw on academic sources as part of the course. However I think part of the task would be to demonstrate how students can explore their interests and achieve purposes with audiences they seek to address by writing academic essays.

And part of the way I see that happening is in my vision of the future of composition. While I remain skeptical of much of the MOOC bizniz, I am interested in the largely untapped potential of creating real audiences and communities for/of student writers. Skip the 50K random MOOC participants and think for a moment of the 2500 UB FYC students in a given semester. Can we create a digital community that would allow them to share their work with other intersted students (and perhaps a larger web public)? Would there be value (for example) in 1000 students writing reviews of current movies, books, products, local hangouts, bands, events, etc? I think there could be. What if the proposing assignment led 500 students to write proposals to improve some aspect of local university life? What if another 50 wrote proposals to improve a neighborhood? Could something actually emerge from that? Maybe one student in a class wants to analyze fracking and no one else in her class does, but there are 15 other students similarly interested across the program. Could they form a research group together? Give feedback on each other's work? Maybe they could end up producing a collaborative website with academic reports and a multimedia presentation. 

This what I think about when I think about "cognitive surplus." Not untapped brain power necessarily but the way a network creates opportunities for thinking and creating that are not otherwise possible. A common textbook and curriculum would faciliate these kinds of activities, encouraging and empowering experimentation rather than operating in opposition to it. It's an approach that would recognize, as Richard Miller pointed out in his talk, that composing is no longer a cloistered activity.

The SUNY Council of Writing's annual conference was held yesterday in Buffalo. There were a number of interesting panels. Richard Miller and Kelly Kinney gave excellent plenary talks. Here I want to think about some of these conversations in relation to what we are doing at UB and my own vision for composition's future. 

Kelly is the director of the Writing Initiative at SUNY Binghamton, which recently won an NCTE CCCC award as a program of excellence. What are some of the program's defining features?

• Autonomy from the English department: this means independent space, budget, and hiring decisions, including deciding which TAs to admit as teachers.
• Class capped at 16. Binghamton has other courses students can take to meet their writing requirement, so the FYC class is limited to 1st year students only. Still 70-80% of first-year students take the course.
• 7 full-time faculty: some are traditional ladder faculty housed in the English department (including Kelly) and some are "clinical" faculty (non-research). I think they are at the instructor rank.
• Adjuncts make $4500 per course, which in part seems doable as I believe she only has two adjuncts.
• Common syllabus, which includes a portfolio worth 70% of the grade that is evaluated by at least two instructors.
• Portfolio instructor groups that meet on a weekly (bi-weekly?) basis, which is a great opportunity for professional development.

If there is one area the program is lacking it might be in moving toward digital composing, which is something that Kelly mentioned.  Digital composing was a central issue in Richard Miller's talk yesterday. It was a wide-ranging and well-received talk, and I will only settle on a few salient points. Miller discussed the struggles that students have with the directive to "be interested" in something that leads them to write. He observed that the superabundance of information and media stimulation is a significant factor in our students' (and, let's face it, our own) capacity to sustain a focused interest on a subject. We are all familiar with this argument, I think. We are, I think, equally aware of the countervailing argument that our always connected context facilitates opportunities to do incredible things with our "cognitive surplus." Miller also discussed this. Most importantly, he outlined the ways in which our traditional practices, hinged on the precepts that information is scarce (you have to go to the library and there's only one copy of the book) and mastery means content expertise, no longer applies. Instead, in a condition of information superabundance, mastery comes in the form of "resourcefulness:" having the skills to find the information and put it together for a digital community. For readers here, this message is familiar, but it was very well pitched to the audience yesterday (and still a message that the bulk of my discipline, to say nothing of the rest of the humanities, has failed to hear or understand).

One notable quality of Richard's pedagogy is his emphasis on helping students discover their passions and facilitating their exploration of those passions in a wide range of media and genre. It's a pedagogy that requires flexibility and improvisation from the instructor, which in turn requires a high level of expertise in rhetoric and composition. It also demands a specific pedagogical focus which puts the emphasis on the student where the connection to rhetoric and compositional processes arrives organically. You can check out some of Richard's students' work here. True, these are not FYC students. My point is not to say "look how well the students write." This isn't a heroic pedagogy narrative. Instead, my point is that the kind of appraoch that Richard takes would be difficult to accomplish in Kelly's program.

Or at least so we might think: that there is a tension between a standardized program and a classroom that faciliates this kind of open experimentation and pursuit of student interests. 

I've been thinking about these issues in our own program as we move to adopt a common textbook for our 101 writing course. The convention in the humanities (and elsewhere in the academy) is that professors choose the topics and readings for their courses. This is based, first, on the principle that professors teach a subject rather than teach students, and second, that professors are masters of the subject content. As such, the depiction of FYC as an experimental zone focused on student interests, while not uncommon in the field (at least once upon a time), is quite atypical otherwise.  FYC has become more disciplinary as the field has become more professionalized over the last 20 years (e.g. with the expansion of PhD programs in rhetoric and composition).

However I don't see these different emphases as necessarily opposition; they do require some tuning though. Without expertise in rhet/comp and commitment to its principles, the open FYC class becomes a free-for-all zone where the "content-less" nature of the course links with the conventional humanities impetus of the professor teaching according to her own content mastery to produce a curriculum where students are asked to write on whatever subject interests the instructor. With less experienced instructors it is very hard to get around this situation on some level, even if we attempt to negotiate some middle point where the writing topics represent some hoped for overlap between instructor and student interest/expertise. This is what we typically see with the "readers" publishers produce for FYC. 

We have adopted a common 101 textbook, Mike Palmquist's Joining the Conversation, which is a "rhetoric" (i.e. it offers instruction on rhetorical/compositional practices). The text does little, in my view, to limit the capacity of students to pursue their own interests as writers. As a "purpose-driven" rhetoric, it does introduce students to different purposes student-writers might identify in relation to their interests: evaluating, reporting, proposing, etc.  As such, students in a class might be asked "to evaluate," which might take the form of different genres–all different kinds of reviews (movies, books, performances, restaurants, a product etc.), an op-ed evaluation of a politician or law, an evaluation of a piece of research, a progress evaluation, a self-assessment, and so on. We can then make these genres more varied by intersecting them with different media (a slidecast, a blog post, a letter or memo, an internal report, a classroom essay). In theory, beyond the dictate "to evaluate" a student in a class using this text might choose among many genres depending on what suited her interest, purpose, and audience. In practice, an instructor might require all students to write movie reviews (for example). And in a way this might be understandable, especially for the novice instructor, as handling a wide range of topics and genres is challenging. This is particularly the case when an instructor adds topical readings (to extend my example: sample movie reviews and maybe some more academic/intellectual essay on film). At least in this example, we can hope that most FYC students can stir up some personal interest and expertise in movies. I have made this same choice in desiging the common syllabus taught by our incoming TAs: identifying specific topics in which I hope students and TAs will have some interest/experience–education, creativity, social media, etc. I have also narrowed the genre of a given assignment to make the task more manageable. 

Now I am wondering though if this is really the best decision. I would like to see a curriculum that opened up more opportunities for student interest and experiment, especially across media, while still introducing students to basic rhetorical concepts like purpose, audience, and genre and helping students identify and develop their compositional practices. I am sure the fear would be that chaos would ensue, but my experience is that when FYC students open a word processor they have a hard time writing anything that isn't basically essayistic (i.e. like what they wrote in high school). That's why the digital assignments are so interesting, because they push students into a different compositional network where they can't just replicate what they once did. We would still want students to write essays and draw on academic sources as part of the course. However I think part of the task would be to demonstrate how students can explore their interests and achieve purposes with audiences they seek to address by writing academic essays.

And part of the way I see that happening is in my vision of the future of composition. While I remain skeptical of much of the MOOC bizniz, I am interested in the largely untapped potential of creating real audiences and communities for/of student writers. Skip the 50K random MOOC participants and think for a moment of the 2500 UB FYC students in a given semester. Can we create a digital community that would allow them to share their work with other intersted students (and perhaps a larger web public)? Would there be value (for example) in 1000 students writing reviews of current movies, books, products, local hangouts, bands, events, etc? I think there could be. What if the proposing assignment led 500 students to write proposals to improve some aspect of local university life? What if another 50 wrote proposals to improve a neighborhood? Could something actually emerge from that? Maybe one student in a class wants to analyze fracking and no one else in her class does, but there are 15 other students similarly interested across the program. Could they form a research group together? Give feedback on each other's work? Maybe they could end up producing a collaborative website with academic reports and a multimedia presentation. 

This what I think about when I think about "cognitive surplus." Not untapped brain power necessarily but the way a network creates opportunities for thinking and creating that are not otherwise possible. A common textbook and curriculum would faciliate these kinds of activities, encouraging and empowering experimentation rather than operating in opposition to it. It's an approach that would recognize, as Richard Miller pointed out in his talk, that composing is no longer a cloistered activity.

Earlier this month, Levi had a post discussing his reservations regarding the term correlationism. His concern, as I understand it, is that we have reached a point where, at least in some circles, the declaration that somthing is "correlationist" has become a move to dismiss it out of hand. Levi, on the other hand, wants to be able to hold onto to the claim that different entities perceive differently (as a correlationist would). He takes up the example of different entities observing electro-magnetic waves and writes:

If the term “realism” is problematic, then this is because it suggests that the project isepistemological or one of deciding which form of access to the world is the true way the world is. It doesn’t make a whole lot of sense to me to decide whether the mantis shrimp, my best friend’s father, or the cat have truer access to the world.  They have different access to the world.  Nonetheless, the term “realism” is still indispensable for two reasons.  First, it is necessary to retain a realism of observers or monads.  The mantis shrimp can’t be reduced to my access to the mantis shrimp, but is an observer that exists in its own right.  The mantis shrimp is irreducible to what it is for me or anyone else.  Second, and this is really the same point, electro-magnetic waves are irreducible to how various beings have access to them.  

I was thinking about this point while discussing Morton's Realist Magic in class yesterday. We had read the introduction to the book (along with a couple of Tim's other essays), and we were discussing his central claim that "the aesthetic dimenstion is the causal dimension." In class, there was some uncertainty over the meaning of aesthetic and some wondering if this claim didn't end up as something much like weak correlationism. This uncertainty arose, I think, from thinking of aesthetics as a product of symbolic behavior. However, I see aesthetics differently, as I think Morton does, as a sensation or feeling. 

In any case, I was working through this with the students in the class, something struck me about correlationism in relation to Latour's critique of modernity. Specifcally, the correlationist argument, while refuting the "native realist" position it imagines as its opponent, holds on an important premise in naive realism: that a real world exists in something like the way realism describes, though we cannot have access to it. Now there are some extreme idealist positions that might not agree to this, but generally speaking correlationism is about an epistemological limit: what we can know about a real world that is out there. It strikes me that that "real world" is still largely understood in modern terms. 

Harman's object-oriented move is to contend that all objects, not just humans, encounter this epistemological limit: all objects only know the world in their own terms. As such, it's not that objects are out there being "real" in the conventional sense but we can't access their "realness." Objects are real, but reality is something different, weirder as the OOO folks like to say. Morton takes up quantum physics to argue objects can occupy contradictory positions, which means that they are ontologically unknowable; objects are real but they cannot be known, not because of our limits, but because of the way objects exist. Another way I might think about this is in terms of the end of the universe. According to at least one theory, the universe will end cold. It will continue to expand until it reaches a state of entropy. At that point, there will be zero information left. No knowledge. As we might take from cybernetics, information requires energy; information is energetic. To know something about the world is to do work: burn calories, drain laptop batteries, etc. Once we do away with the modernist's real world, the modernist-correlationist concern of not being able to access it doesn't make much sense. Instead, "knowing" becomes a way of doing work, of building alliances (to use Latour's terms). What we know is "real" in much the same way as anything else might be real. Knowing is as real as running. Inasmuch as any activity is real, the act of knowing is something. Knowledge as some kind of transmission or storage is also real. These are real objects unto themselves, built from other objects (as all objects are). As Latour suggests in his compositionist manifesto, some compositions are better than others. As Bryant suggests in the post mentioned above, some theories are better than others: "the Vikings thought that lightning occurred when the god Odin struck his hammer– and our theories of lightning might turn out to be mistaken as well –but lightning can’t be reduced to whatever some group of people happen to say about it.  There is a reality to lightning and some theories of lightning will be true and others false."

Once you can move into this position, you no longer face the prospect of trying to circumvent correlationism to get at the real world or the prospect of reconciling yourself to the fact that you will never really know anything about the world (i.e. the everything is text/representation). Instead, knowing becomes building real relations with real objects. Even though those objects do not exist in a way that would allow for the Truth as we have fantasized it, they are real enough to do work. The challenge then becomes one not of finding out the truth but of discovering the possibilities for composing.

Earlier this month, Levi had a post discussing his reservations regarding the term correlationism. His concern, as I understand it, is that we have reached a point where, at least in some circles, the declaration that somthing is "correlationist" has become a move to dismiss it out of hand. Levi, on the other hand, wants to be able to hold onto to the claim that different entities perceive differently (as a correlationist would). He takes up the example of different entities observing electro-magnetic waves and writes:

If the term “realism” is problematic, then this is because it suggests that the project isepistemological or one of deciding which form of access to the world is the true way the world is. It doesn’t make a whole lot of sense to me to decide whether the mantis shrimp, my best friend’s father, or the cat have truer access to the world.  They have different access to the world.  Nonetheless, the term “realism” is still indispensable for two reasons.  First, it is necessary to retain a realism of observers or monads.  The mantis shrimp can’t be reduced to my access to the mantis shrimp, but is an observer that exists in its own right.  The mantis shrimp is irreducible to what it is for me or anyone else.  Second, and this is really the same point, electro-magnetic waves are irreducible to how various beings have access to them.  

I was thinking about this point while discussing Morton's Realist Magic in class yesterday. We had read the introduction to the book (along with a couple of Tim's other essays), and we were discussing his central claim that "the aesthetic dimenstion is the causal dimension." In class, there was some uncertainty over the meaning of aesthetic and some wondering if this claim didn't end up as something much like weak correlationism. This uncertainty arose, I think, from thinking of aesthetics as a product of symbolic behavior. However, I see aesthetics differently, as I think Morton does, as a sensation or feeling. 

In any case, I was working through this with the students in the class, something struck me about correlationism in relation to Latour's critique of modernity. Specifcally, the correlationist argument, while refuting the "native realist" position it imagines as its opponent, holds on an important premise in naive realism: that a real world exists in something like the way realism describes, though we cannot have access to it. Now there are some extreme idealist positions that might not agree to this, but generally speaking correlationism is about an epistemological limit: what we can know about a real world that is out there. It strikes me that that "real world" is still largely understood in modern terms. 

Harman's object-oriented move is to contend that all objects, not just humans, encounter this epistemological limit: all objects only know the world in their own terms. As such, it's not that objects are out there being "real" in the conventional sense but we can't access their "realness." Objects are real, but reality is something different, weirder as the OOO folks like to say. Morton takes up quantum physics to argue objects can occupy contradictory positions, which means that they are ontologically unknowable; objects are real but they cannot be known, not because of our limits, but because of the way objects exist. Another way I might think about this is in terms of the end of the universe. According to at least one theory, the universe will end cold. It will continue to expand until it reaches a state of entropy. At that point, there will be zero information left. No knowledge. As we might take from cybernetics, information requires energy; information is energetic. To know something about the world is to do work: burn calories, drain laptop batteries, etc. Once we do away with the modernist's real world, the modernist-correlationist concern of not being able to access it doesn't make much sense. Instead, "knowing" becomes a way of doing work, of building alliances (to use Latour's terms). What we know is "real" in much the same way as anything else might be real. Knowing is as real as running. Inasmuch as any activity is real, the act of knowing is something. Knowledge as some kind of transmission or storage is also real. These are real objects unto themselves, built from other objects (as all objects are). As Latour suggests in his compositionist manifesto, some compositions are better than others. As Bryant suggests in the post mentioned above, some theories are better than others: "the Vikings thought that lightning occurred when the god Odin struck his hammer– and our theories of lightning might turn out to be mistaken as well –but lightning can’t be reduced to whatever some group of people happen to say about it.  There is a reality to lightning and some theories of lightning will be true and others false."

Once you can move into this position, you no longer face the prospect of trying to circumvent correlationism to get at the real world or the prospect of reconciling yourself to the fact that you will never really know anything about the world (i.e. the everything is text/representation). Instead, knowing becomes building real relations with real objects. Even though those objects do not exist in a way that would allow for the Truth as we have fantasized it, they are real enough to do work. The challenge then becomes one not of finding out the truth but of discovering the possibilities for composing.

Iternation has an interview with Victor Vitanza where he discusses the idea of "big rhetoric" (see below). Big rhetoric is a concept that has been around for a few decades. It remarks on the move by which all forms of symbolic communication come to be seen as rhetorical. It is arguably part of the larger "linguistic turn" of postmodernity and is juxtaposed to a narrower, more traditionally disciplinary rhetoric that might focus upon public address. 

Vitanza goes an interesting direction with this though in referencing George Kennedy's "A Hoot in the Dark: The Evolution of General Rhetoric," which looks beyond symbolic behaviors to animals (and even plants) to speculate on nonsymbolic, nonhuman rhetoric. Kennedy's point is that rhetoric is connected to communication and necessariy precedes symoblic behaviors since it is clear that animals communicate without a symbolic language. For me, Kennedy's most interesting thesis is one he says the least about: "Rhetoric is prior to intentionality or to any belief on the part of a speaker about the meaning of a sign or its effect on others." In my own work, I separate rhetoric from communication in following Deleuze and Guattari's argument that "Language is neither informational nor communica-tional. It is not the communication of information but something quite different: the transmission of order-words, either from one statement to another or within each statement, insofar as each statement accomplishes an act and the act is accomplished in the statement" (ATP, 79). This connects with their concept of incorporeal transformations. However, I take this further than Deleuze and Guattari do here to think about rhetoric in terms of expressions that cannot enact incorporeal transformations without recourse to language; expressions that are autonomous and auto-objective, or, as Kennedy puts it here, "prior to intentionality or to any belief on the part of the speaker." The bird's song expresses itself prior to expressing some bird's intentionality. As Vitanza puts it in responding to a question about the future of rhetoric, rhetoric is going wherever it wants, that it does not know where it is going, that it is just "rhetoricking." This is what Deleuze and Guattari would mean by autonomous as well, not "free-willed," but subject to its own internal goverance and laws, laws which are never fully knowlable by the self.

Big Ideas: Victor Vitanza with Jimmy Butts from Itineration on Vimeo.

Iternation has an interview with Victor Vitanza where he discusses the idea of "big rhetoric" (see below). Big rhetoric is a concept that has been around for a few decades. It remarks on the move by which all forms of symbolic communication come to be seen as rhetorical. It is arguably part of the larger "linguistic turn" of postmodernity and is juxtaposed to a narrower, more traditionally disciplinary rhetoric that might focus upon public address. 

Vitanza goes an interesting direction with this though in referencing George Kennedy's "A Hoot in the Dark: The Evolution of General Rhetoric," which looks beyond symbolic behaviors to animals (and even plants) to speculate on nonsymbolic, nonhuman rhetoric. Kennedy's point is that rhetoric is connected to communication and necessariy precedes symoblic behaviors since it is clear that animals communicate without a symbolic language. For me, Kennedy's most interesting thesis is one he says the least about: "Rhetoric is prior to intentionality or to any belief
on the part of a speaker about the meaning of a sign or its effect
on others." In my own work, I separate rhetoric from communication in following Deleuze and Guattari's argument that "Language is neither informational nor communica-tional. It is not the communication of information but something quite different: the transmission of order-words, either from one statement to another or within each statement, insofar as each statement accomplishes an act and the act is accomplished in the statement" (ATP, 79). This connects with their concept of incorporeal transformations. However, I take this further than Deleuze and Guattari do here to think about rhetoric in terms of expressions that cannot enact incorporeal transformations without recourse to language; expressions that are autonomous and auto-objective, or, as Kennedy puts it here, "prior to intentionality or to any belief on the part of the speaker." The bird's song expresses itself prior to expressing some bird's intentionality. As Vitanza puts it in responding to a question about the future of rhetoric, rhetoric is going wherever it wants, that it does not know where it is going, that it is just "rhetoricking." This is what Deleuze and Guattari would mean by autonomous as well, not "free-willed," but subject to its own internal goverance and laws, laws which are never fully knowlable by the self.

Big Ideas: Victor Vitanza with Jimmy Butts from Itineration on Vimeo.

As Steve Krause has noted and has been discussed a fair amount recently on the WPA-list, there is reason to be concerned with the growing role of grading writing by machines. There is a new site and petition (humanreaders.org), and I have added my name to that petition. So it should be clear that fundamentally I share the concerns raised there because I have confidence in the research beyond this position. Essentially the point is that current versions of machine grading software are not capable of "reading." What does that mean? It means that machines do not respond to texts in the way that humans do. It is possible to compose a text that humans would identify as nonsensical and receive a high score from a machine. Machines can be trained to look for certain features of texts that tend to correlate with "good writing" from a human perspective but those features can be easily produced without producing "good writing." The upshot, given the high stakes nature of many of these texts, is that students will not be taught to produce "good writing" but rather writing that scores well. The horrors of teaching to the test are a commonplace in our culture, so there's no need to take the argument further. 

And yet, of course, you would not be reading this if your computer (or phone) didn't read it first. If you have arrived at this page via Google, then there have been several levels of machine reading that brought you here. If it seems that Google and other search engines do a fairly good job of finding reliable texts on the subject in which you are interested, then it is because, by some means, they are good readers. No doubt, part of Google's system is reliant upon human evaluators who link and visit pages, including perhaps your own preferences. The same might be said of human readers. How did we figure out what "good writing" was? Do we not rely upon social networks for this insight? In its crudest form (and closer to assessment), don't we "norm" scorers of writing for assessment purposes?

Anyone who has ever done search engine optimizing has written explicitly for machines. One of the things that makes SEO trickly though is the secret, proprietary nature of Google's search algorithm. Unlike these machine grading mechanisms, it is not easy to game Google's search rank. Perhaps what is required for machine grading is a more complex, harder to predict, mechanism. In other words, while machines do not need to read in the same way as humans do, they might need to simulate the subjective, unreliable responses of human readers in order to serve our purposes. That last sentence encapsulates two potential errors we encounter in our discussions of machine grading.

1. Because machines don't read the way humans do, they don't understand the meaning of the text. Critics complain that machines can't recognize when a text is nonsense or counterfactual. (One might say the same of humans anyway.) On what basis do we claim that humans are the arbiters of sense? Only on the basis that we only care what humans think, or from a correlationist perspective, that we can only understand texts in terms of ourselves anyway. We don't understand why machines grade texts the way they do sometimes, but we don't say that machines are subjective, which is what we say when human readers disagree. Instead, we say that machines produce error. I say that machines are readers too. Maybe they aren't the readers we want to score our tests, but then we wouldn't want a room full of kindergarteners either. So being human is no guarantee of reliable scoring. 

2. Good machines would simulate human readers. This is our basic premise, right? That a machine would give the same score as a human to a given text. That is, we recognize that machines and humans will never read the same way but we need them to provide the same output in terms of scores. This would be like a calculator. A calculator doesn't do math like I do, but it gets the same answer. To make this happen we black box both the human and the calculator: the process is irrelevant; only the answer counts. But that's not really a good analogy for the scoring of human writing. 

Unlike calculable equations, there is not right score for a text. What human scoring processes demonstrate is that reading takes place within the context of a complex network of actors that serve to create "interrater reliability" and so on. We begin with the preimse that humans typically will not agree on the score for a text, even when you take a fairly similar group of readers (e.g. composition instructors teaching in same department) and writers (e.g. students in their classes). They already are conditioned to a high degree, but then we add on specific conditioning through the norming process and the common conditions in which they are reading. Add into that various social pressures such as recognizing the seriousness of the scoring and the pressure to grade like other readers so as to reduce the amount of work (discrepancies in scoring lead to additional readings and scorings). 

Scoring is not an objective, rational process. Once one abandons the flawed concept of intersubjectivity-- the consensual hallucination that we share thoughts when we agree--one has to come up with another explanation for why two readers give an essay the same score and that explanation, in my view, would involve an investigation of the actor/objects and network-assemblages that operate to produce results. We can complain that machines don't recognize meaning, but that's only because meaning isn't in the text. This has always been the flaw in any form of grading. We evaluate students based upon what their texts do to us as readers. The only reason students have any power to predict what our experience will be is because they participate in a shared network of activity: a network over which they have little control. 

So to go back to the original problem of machine grading, I would say that we need to ask what it is that we are trying to determine when we are grading these exams. Do we want to know if students can produce texts that have certain definable features in a testing situation? Do we want to know if students will get good grades on writing assignments in college? Or do we want to know, more nebulously, if students are "good writers"? I think we have proceeded as if these are the same questions. That is, good writers get good grades in college because they can produce texts with certain definable features. But that's not how it works at all, and I think we know that. 

In case we don't, just briefly... Good texts don't have certain definable features because the experience of "good" isn't inhered in the texts we read. This doesn't make the process subjective in the sense of one's reading practice being unpredictable or purely internal. It just makes reading relational. One way of defining rhetorical skill is having the ability to investigate the networks at work and produce texts that respond to those networks. We object to the notion of training students to compose texts that will produce positve responses from machines, but we also object to the notion of training students to compose texts that produce positive responses from normed human scorers. 

The real problem though is starting with the pedagogical premise that teaching writing means teaching students to reproduce definable textual features without understanding the rhetorical and networked operations underneath. Beacuse what we discover from machine readers is that we can compose texts that have those textual features but are ineffective from our perspective. This is a discovery we have already made a million times though as we have all seen many students who diligently replicate the requirements of an assignment and still manage to produce unsatisfactory results. Why? Because they have produced those features without understanding the rhetoricity behind them.

Machines are perfectly good readers. That's not where the problem is. The problem is that we don't understand reading.

As Steve Krause has noted and has been discussed a fair amount recently on the WPA-list, there is reason to be concerned with the growing role of grading writing by machines. There is a new site and petition (humanreaders.org), and I have added my name to that petition. So it should be clear that fundamentally I share the concerns raised there because I have confidence in the research beyond this position. Essentially the point is that current versions of machine grading software are not capable of "reading." What does that mean? It means that machines do not respond to texts in the way that humans do. It is possible to compose a text that humans would identify as nonsensical and receive a high score from a machine. Machines can be trained to look for certain features of texts that tend to correlate with "good writing" from a human perspective but those features can be easily produced without producing "good writing." The upshot, given the high stakes nature of many of these texts, is that students will not be taught to produce "good writing" but rather writing that scores well. The horrors of teaching to the test are a commonplace in our culture, so there's no need to take the argument further. 

And yet, of course, you would not be reading this if your computer (or phone) didn't read it first. If you have arrived at this page via Google, then there have been several levels of machine reading that brought you here. If it seems that Google and other search engines do a fairly good job of finding reliable texts on the subject in which you are interested, then it is because, by some means, they are good readers. No doubt, part of Google's system is reliant upon human evaluators who link and visit pages, including perhaps your own preferences. The same might be said of human readers. How did we figure out what "good writing" was? Do we not rely upon social networks for this insight? In its crudest form (and closer to assessment), don't we "norm" scorers of writing for assessment purposes?

Anyone who has ever done search engine optimizing has written explicitly for machines. One of the things that makes SEO trickly though is the secret, proprietary nature of Google's search algorithm. Unlike these machine grading mechanisms, it is not easy to game Google's search rank. Perhaps what is required for machine grading is a more complex, harder to predict, mechanism. In other words, while machines do not need to read in the same way as humans do, they might need to simulate the subjective, unreliable responses of human readers in order to serve our purposes. That last sentence encapsulates two potential errors we encounter in our discussions of machine grading.

1. Because machines don't read the way humans do, they don't understand the meaning of the text. Critics complain that machines can't recognize when a text is nonsense or counterfactual. (One might say the same of humans anyway.) On what basis do we claim that humans are the arbiters of sense? Only on the basis that we only care what humans think, or from a correlationist perspective, that we can only understand texts in terms of ourselves anyway. We don't understand why machines grade texts the way they do sometimes, but we don't say that machines are subjective, which is what we say when human readers disagree. Instead, we say that machines produce error. I say that machines are readers too. Maybe they aren't the readers we want to score our tests, but then we wouldn't want a room full of kindergarteners either. So being human is no guarantee of reliable scoring. 

2. Good machines would simulate human readers. This is our basic premise, right? That a machine would give the same score as a human to a given text. That is, we recognize that machines and humans will never read the same way but we need them to provide the same output in terms of scores. This would be like a calculator. A calculator doesn't do math like I do, but it gets the same answer. To make this happen we black box both the human and the calculator: the process is irrelevant; only the answer counts. But that's not really a good analogy for the scoring of human writing. 

Unlike calculable equations, there is not right score for a text. What human scoring processes demonstrate is that reading takes place within the context of a complex network of actors that serve to create "interrater reliability" and so on. We begin with the preimse that humans typically will not agree on the score for a text, even when you take a fairly similar group of readers (e.g. composition instructors teaching in same department) and writers (e.g. students in their classes). They already are conditioned to a high degree, but then we add on specific conditioning through the norming process and the common conditions in which they are reading. Add into that various social pressures such as recognizing the seriousness of the scoring and the pressure to grade like other readers so as to reduce the amount of work (discrepancies in scoring lead to additional readings and scorings). 

Scoring is not an objective, rational process. Once one abandons the flawed concept of intersubjectivity– the consensual hallucination that we share thoughts when we agree–one has to come up with another explanation for why two readers give an essay the same score and that explanation, in my view, would involve an investigation of the actor/objects and network-assemblages that operate to produce results. We can complain that machines don't recognize meaning, but that's only because meaning isn't in the text. This has always been the flaw in any form of grading. We evaluate students based upon what their texts do to us as readers. The only reason students have any power to predict what our experience will be is because they participate in a shared network of activity: a network over which they have little control. 

So to go back to the original problem of machine grading, I would say that we need to ask what it is that we are trying to determine when we are grading these exams. Do we want to know if students can produce texts that have certain definable features in a testing situation? Do we want to know if students will get good grades on writing assignments in college? Or do we want to know, more nebulously, if students are "good writers"? I think we have proceeded as if these are the same questions. That is, good writers get good grades in college because they can produce texts with certain definable features. But that's not how it works at all, and I think we know that. 

In case we don't, just briefly… Good texts don't have certain definable features because the experience of "good" isn't inhered in the texts we read. This doesn't make the process subjective in the sense of one's reading practice being unpredictable or purely internal. It just makes reading relational. One way of defining rhetorical skill is having the ability to investigate the networks at work and produce texts that respond to those networks. We object to the notion of training students to compose texts that will produce positve responses from machines, but we also object to the notion of training students to compose texts that produce positive responses from normed human scorers. 

The real problem though is starting with the pedagogical premise that teaching writing means teaching students to reproduce definable textual features without understanding the rhetorical and networked operations underneath. Beacuse what we discover from machine readers is that we can compose texts that have those textual features but are ineffective from our perspective. This is a discovery we have already made a million times though as we have all seen many students who diligently replicate the requirements of an assignment and still manage to produce unsatisfactory results. Why? Because they have produced those features without understanding the rhetoricity behind them.

Machines are perfectly good readers. That's not where the problem is. The problem is that we don't understand reading.