A Pandemic Is Good Discipline

"All I must do now was stay sound and good in my head
until morning when I would start to work again."
--Ernest Hemingway

This must have been in 1924. In Our Time had not yet been published, Hemingway had quit his job at the Toronto Star, and all his manuscripts had been lost in a suitcase at the Gare de Lyon. He wasn’t making very much money from his writing and was skipping meals, lying to his wife that he was eating out, so she would have more for herself and the boy. “It is necessary to handle yourself better when you have to cut down on food so you will not get too much hunger-thinking. Hunger is good discipline and you learn from it. And as long as they do not understand it you are ahead of them.” He was talking about his readers. “Oh sure,” he thought, “I’m so far ahead of them now that I can’t afford to eat regularly. It would not be bad if they caught up a little.” There’s a bad moment when he finds himself complaining to Sylvia Beach at Shakespeare and Company about money. He catches himself and apologizes. “Forgive you for what?” she says. “Don’t you know that all writers ever talk about is their troubles?”

I’ve been reading A Moveable Feast and it’s pretty good company. I had forgotten his passing mention, in “Hunger Was Good Discipline,” of what was then his “new theory”, or what we now called “the iceberg method”: “you could omit anything if you knew that you omitted, and the omitted part would strengthen the story and make people feel something more than they understood.” He connected this idea both to his hunger and to his lost manuscripts. There was a whole novel in that suitcase that, he suspected, demonstrated “the lyric facility of boyhood that was a perishable and as deceptive as youth was.” Writing now, he would have to do without it, and he decided this was “probably a good thing”. But he wasn’t ready to write a new novel yet: “it seemed an impossible thing to do when I had been trying with great difficulty to write paragraphs that would be the distillation of what made a novel.” That’s the difficulty I want to address in the coming weeks.

Of course, I’m not a novelist, and neither, I expect, are you. You’re probably trying to write a paper or a dissertation. Maybe you’re trying to write a book. But, like Hemingway, we’re writing prose, and the “distillation” of prose is the paragraph. It’s the “unit” of academic writing. It makes a statement and supports, elaborates or defends it, and any longer text is just a series of statements that have been variously supported, elaborated, and defended. Scholarly writing is the process of composing and arranging paragraphs that state what you know. These days, our process has been interrupted, but we must not complain about our troubles. Not too much. Every morning we get up and work on our paragraphs, our little disciplines. We decide what to put in and what to leave out and our iceberg gains a little of its dignity. Hemingway lived like that for almost two years. Then his readers finally caught up with him.

Homework in a Time of Quarantine

“Eighty percent of life,” said Woody Allen, “is showing up.” Fortunately at times like these, eighty percent of school is homework. As most of my readers are aware, the Danish university campuses are closed for the next two weeks in an attempt to control the spread of the coronavirus. But this does not mean that school is out for the students. Classes are still formally in session and we have been asked to develop online alternatives to on-site instruction. While I don’t want to disparage those who have poured a lot of energy and creativity into holding their classes online (see Andrew’s post, for example), I have decided to keep things as simple as possible, for both myself and my students. In this post, I want to say a few things about what I’ve decided to do, and why.

The basic principle is the one I stated at the outset. Closing the campus affects only about 20% of the activities that a university education provides. Most of the time, students should be reading and writing at home. The most important thing, therefore, is to make sure that these activities keep happening, and continue to be meaningful for the students. In principle, the students should be fine for two weeks just following the existing course syllabus in their reading, supplemented with some questions to answer in writing. But it’s a minimal solution and it can be vastly improved with very little effort.

I say that the students ought to be fine with individual homework “in principle”. In practice, of course, that may a bit optimistic. Will the students read if they’re not preparing for a class? Will they write the suggested essays? Will they understand the readings and the questions well enough to get something out of it? This will vary from student to student, and some students will no doubt find the individual exercises meaningless.

While I think this tells us something important about how dependent higher education has become on instruction, and how dependent students have become on their teachers, I don’t want to “politicize” the crisis. Later on, when we start talking about how to make institutions resilient to pandemics and other disasters, I’m sure I’ll want to return to it. Too much in academic life has become subject to external deadlines and “extrinsic motivation”, which, I believe, has made both research and teaching much more vulnerable than it should be.

But this, like I say, is no time to solve that problem. I bring it up now in order to think about all the things we can do keep students on track and motivated.

Since I want to keeps things simple, let’s start with some old-fashioned technologies. Most of our classes will be using some form of Learning Management System, to which the students already have ready access. (If not, email can be used for everything I’m about to suggest.) This will allow you to post instructions from day one. While you can begin to think about video lectures, I recommend you start with some clearly written advice and guidance for how the students should spend their time at home.

Basically, you will be using your LMS as a kind of blog (or you may just set up a blog, or use the one you have), where you regularly suggest readings and exercises for the students to be doing at home. I also recommend you set up a forum, where students can ask questions if they get stuck. (Alternatively, a comment field will do.) The tasks should be so simple that they know they’re stuck simply if they don’t know what to do. “Read Act II of Hamlet,” is perhaps easier said than done, but there’s no question about what they should be doing. Even better: “Read Act II of Hamlet out loud.” That way there can be no doubt in their minds whether they’re doing the assignment!

By a similar token, ask them to write paragraphs in well-defined writing moments. Have them work on their discipline. As much as possible, let them decide what to write about (or at least what to say) themselves. Ask them to make a plan to write at least six sentences and at most two-hundred words in 18 or 27 minutes the next day. Have them think seriously about who they’re talking to and how to say it. Again, after reading your instructions, it should be easy for them to know whether or not they’re doing what you’ve asked them to, irrespective of whether they think they’re doing it well or right. Have them do the assignments and similar assignments again, i.e., get them to repeat them. Tell them they are practicing. Like all practice, the task should be become easier with time and repetition. That’s how they know they’re learning.

Finally, a word about feedback. (I’ll say more about all these things in the days to come.) It is possible to facilitate feedback online by having students exchange their texts with each other. Here, too, keep the task simple and limited in time, so they can do it or not do it without any ambiguity about whether it’s one or the other. My “unfiltered feedback” exercise can easily be done by Skype (or even just phone). And most of it can be done in writing. If you want, you can pick one or more examples from a class set of submissions and do it as a short, 9-minute video. (I’ll demonstrate this in the coming days, too.)

I hope that is helpful to all those who are trying to cross these new social distances. Remember, academic writing is not “the loneliness that is the truth of things”. It’s a conversation among knowledgeable peers, and that conversation has always been mostly virtual. Eighty percent of school is homework.

Basis, Aim, and Structure

“A poem is a machine made of words.” (William Carlos Williams)

Think of a machine as a structure that is “geared” for action, an arrangement of parts that does something once it has been set in motion. Indeed, Williams thought of a poem as a “field of action”, just as Hemingway sought a “dignity of movement” in his prose. Good writing is effective writing — writing that has a series of intended effects on the reader. A paragraph is a little machine that makes a claim easier to believe, understand or agree with. An essay is constructed by arranging paragraphs in a series, one effect after another. In my weekly Wednesday talk this afternoon I’m going to try to leverage, if you will, these metaphors in thinking about the structure of a research paper. I want to help you distinguish the paragraphs in each section of a paper in terms of their means and ends, their causes (in Aristotle’s “material” sense) and their effects, or, as I have been calling them in my previous talks, their bases and their aims. The trick is to bring them all together for an overarching purpose, to get them working.

What, then, is your research paper based on? The obvious answer is that it is based on your research, but we can be much more specific about this when we consider each section in isolation from the others. The background section, for example, is based on publicly available sources of information, i.e., newspapers, books, company reports, government whitepapers, official statistics, and so forth; the theory section, by contrast, is based on the scientific literature, which you explored when doing the literature review. The crucial difference here is that your reader needs no special qualifications to access and understand your background sources, while your theory section is really only going to make sense to a trained specialist with access to the relevant journals. Your analysis is, of course, based on your data, to which you have privileged access as a writer. (No matter how open you are about your data, you should write about it as though the reader hasn’t seen it.) Your methods and discussion use sources of a different kind: experience and reason, respectively — your doing and your thinking. Think of your basis in each case as what qualifies or author-izes you to write it. Your introduction and conclusion, for example, are based on what is in the rest of the paper, which makes you, the author, the ideal writer of these sections.

As you can see, we can easily distinguish the sections of your paper on the basis of their sources. But we can also look at their aims — what each section is trying to accomplish. The introduction is, obviously, going to introduce your paper, which is to say, it’s going to open a dialogue with a knowledgeable peer about a subject that interests you. Your background section will inform the reader about facts you won’t presume the reader knows. The theory section will activate a set of expectations of your object in your reader. Since the analysis is going to try to bring about an “artful disappointment” of those expectations, your methods section will build trust in your data, so that your reader won’t just dismiss your results. The discussion section will then identify the implications of whatever tension exists between the theory you have used and the practice you have studied. Finally, the conclusion will (just as obviously as the introduction introduces) conclude the paper, bringing the conversation to a close, and bidding the reader farewell.

This smooth sequence of aims, with one task leading to another after it has been accomplished, should remind us that reading is a linear experience that moves forward in time. We have constructed a series of one-minute (i.e., one-paragraph) experiences that will ideally (though not always really) be lived by the reader from beginning to end, lasting about forty minutes altogether. Reading, like writing, is a process. But don’t forget that, at the end of the day, a paper is also a structure; it remains “standing” after the reading is done. Or, at least, it should remain standing. We might say you’ve walked the reader through a building that you have constructed and you don’t want them to come away with the feeling that it’s about to come down (that you intend to demolish it tomorrow). The discussion section should feel like it was “set up” by the background and theory sections. The analysis should challenge the theory but not overwhelm it. The methods section should establish limits that your conclusion respects. And your introduction should promise no more and no less than what your paper delivers. When the reader puts down your paper, there should be a clear image in their mind of a place they could (and hopefully will) revisit.

Williams’s friend, Ezra Pound, encouraged us to remember that not all images are still. There are moving images, imaginary films. Likewise, we must remember that not all structures are static. To say that something has structure is not to say that it doesn’t move, only that it moves, when it does, in a particular way. Even wholly imaginary dragons are constricted in their movements by their imaginary skeletons. A machine is a structure that repeats a series of motions over and over, belaboring a set of materials to produce an effect, a product, and even post-structuralists have this kind of structure. As I said a couple of years ago, 1968 marks a kind of “epochal shift” in our thinking about society, a movement, we might say, from “structure” to “machine”. It can be found in the famous opening lines of Deleuze and Guattari’s Anti-Oedipus:

It is at work everywhere, functioning smoothly at times, at other times in fits and starts. It breathes, it heats, it eats. It shits and fucks. … Everywhere it is machines — real ones, not figurative ones: machines driving other machines, machines being driven by other machines, with all the necessary couplings and connections.

These “desiring-machines” may just be the “poetic” counterpart of the “cognitive frames” of our prose. I tend to agree with Deleuze and Guattari that these tensions are not merely metaphorical, but I’m less inclined than some to abandon the prose of the world. And let’s watch our language, friends; let’s keep it clean out there!

Or don’t. Fu…

Observation, Interpretation, and Analysis

“Thus your data shimmers.” (Lisa Robertson)

I’m really enjoying preparing our weekly Wednesday talks. I’ve now had a chance to cover the theory and methods sections in some detail. This week I’ll be talking about writing the analysis. Because I’m trying to keep these talks applicable to the different levels that students are working at, as well as the full range of CBS degree programs, I’ve found myself occasionally waxing philosophical. I think this week’s talk will be a little more practical, but still general enough, I hope, to be of use to everyone. The overarching theme will be that of using your data to support factual claims about the object you have studied. That is, in our analysis we’re always moving from our direct observation of reality to our interpretation of that reality. It will be useful to think of each paragraph as including both an interpretation, which will be expressed in the key sentence, and some observations, which will support the factual claim it makes. That is, each paragraph in your analysis will assert a fact on the basis of your data.

Let’s begin with the data, which we have talked about before. It consists of what you have directly observed. In ethnography, it’s your record of what what people have done and said. In survey research, it consists of how they filled out your questionnaire. In financial market analysis, it consists of the stock prices you have exported from a relevant financial database. In discourse analysis, it’s the archive of documents you have collected. However you have gathered it, you deploy it in your analysis section by quoting (words or figures) as they appear in your data set or summarizing aggregates. Your statements about your data are true or false in a highly objective and unambiguous way. People either said what you quote them for or they didn’t. A certain number answered “yes” to a question and another just as certain number answered “no”. You just have to count them. The documents either invoke the codes you’re looking for or they don’t.

But an analysis is not just a summary of your data. You have collected the data in order to represent the facts as they are, independent of your data and your analysis, and making your data represent facts always requires an interpretation. The amount of days employees are off on sick leave in a particular company is a data point. Whether the company has a stressful working environment is a fact to be determined by your analysis. You gathered the data in order to determine the fact but, interestingly, if your readers want to observe the same fact, they don’t have to use the same data. Facts are not made of data, we might say, they just “give off” data. Like an astronomer gathers the light from a star, you design your instruments to be sensitive to data about the people you study. To borrow Lisa Robertson’s image, data is a “shimmer” on the surface of your facts. The data are ultimately ephemeral (which is why you have to keep a good record of them); the facts are made of sterner stuff.

Again, your analysis doesn’t just describe your data; it doesn’t just make claims about your sample. It makes claims about the world in which we live out of interpretations of your data. It tells us what your data has shown you, what it has taught you about your object. As I have said before on this blog, this lets you think of each paragraph in your analysis as repeating a simple pattern: the key sentence tells us what you mean and the rest of the paragraph tells us how you know. The key sentence may tell us what the people you have studied believe or desire, but the rest of the paragraph will tell us what they said or what they did to make you think so. Present your interpretation in the key sentence and build the rest of your paragraph around your observations. Obviously, you should make sure your observations support your interpretations.

It is tempting to see the analysis as a “write up” of your data. If we’re working with qualitative data, we’ll often start with memorable quotes from our interviews or striking observations from the fieldwork. Quantitative researchers might start with the “significant” results in their contingency tables. Either way, the writer thinks of their prose as a way tying these data point together, connecting the dots. But it is much better to organize your analysis around a set of claims about the world — statements of actual, ordinary fact. You will ultimately be composing a finite series of paragraphs, each of which says one thing, and supports that claim with your data. So plan out your analysis section as a series of claims that you are able to support, not just a number of themes inspired by your data. After all, your readers don’t just want to know about your data; they want to know what your data shows us about the world in which we live. They want your observations and your interpretations of them.

Method, Data, and Ethics

“No one can say what a ‘result’ is in the ‘human sciences’.” (Roland Barthes)

If your theory section is about the reader’s expectations, your methods section is about your competence to address them. Indeed, you have to present yourself as someone who is qualified to challenge your reader’s expectations of your research object. This will be the main point of my talk this afternoon in the Craft of Research Series (or “Weekly Wednesdays” as we’re starting to call them internally). The talks are directed at students who are working on their year-end research projects and I’m rather encouraged by the turnout. It gives me a chance to talk about things that I normally pass over rather quickly in my “How to Write” and “How to Structure a Research Paper” lectures. Today, for example, I get a chance to go into some depth about the difference between “methods” and “methodology” as well as “experience” and “empirical data”. I’ll also get a chance to discuss the ethical implications and limitations of your methodological choices. As ever, you decide how to write by considering who you’re writing for: a serious, engaged and intelligent peer.

Think of your method as what you do to learn about the world, and think of methodology as a way of holding you accountable. “Method” comes from the Greek word hodos for “way or manner” and, more literally, “path”. The suffix “-logy” indicates some sort of “discourse” about (or “account” of) why you did things the way you did (a methodology is a “doctrine of method”). Where exactly did you go to look for answers to your research question? What did you look at? When and how long did you observe? How many people did you talk to? Did you survey them or interview them? What questions did you ask them? Or did you draw on census, polling, or financial data? How did you decide which data to include and which to exclude? Notice that all these are questions of “method” and are answered straightforwardly and factually. At the end of the day, you just have to be honest about what you did. The methodological question is: why did you do it that way? And here you will be invoking the methods literature, including handbooks and the papers you found in your review of the literature. The trick here is to demonstrate an awareness of what might go wrong–sources of error–more specifically, you must anticipate what your reader thinks might go wrong.

Your methods section, then, should be centered on what you actually did to collect and organize your data. But what is data? Here again, we can go back to the Greek roots of the word: the “given”, “in classical use originally ‘a fact given as the basis for calculation in mathematical problems.'” Today, we generalize beyond mathematics and take data to consist of facts given as the basis for any analysis. Notice the difference between this and, say, a fact derived from an analysis, i.e., a fact that is not the basis of something but is, rather, based on something. Both are facts, but what counts as “data” depends on what happens in your analysis. We can say that what is “given” to us can be “taken for granted” in the analysis. What the people you study think or believe will come out as a result of your analysis; but what they said (in an interview or response to a survey) will be a fact that is given to us as analysts. The purpose of your methods section is to give you the basis, if you will, to let the you take your data for granted in this way. That means describing how you collected it in a way that lets your reader trust it.

This sets up an essential rhetorical tension in your methods section. On the one hand, you want to present your approach to data collection in the most persuasive way possible. On the other, you must be honest about what you did. If you say you sent out a thousand surveys that may impress your reader. But if you only sent out a hundred, you’re lying. Likewise, if you say, truthfully, that you sent out a thousand surveys, and report, truthfully, that 80% of respondents were satisfied with their work load, you are obligated to report, just as truthfully, the, let’s say, 48% non-response rate. Otherwise your reader may be mislead into thinking that 800 people said they were satisfied. Of course, careful readers (with high methodological standards) will have noticed you left out the non-response rate. They will find your data less trustworthy, less credible. They won’t be able to take them as “given”. In an important sense, you haven’t “given” them what they need.

(There are lots of other ethical issues to consider. Does your method respect your respondents privacy? Did you secure informed consent where necessary? But I think I’ll need to take those up in a post of their own.)

The important thing is to make sure that the reader gets a good sense of both the potential and the limitations of your data. Whatever conclusions you’re going to reach, you need to make sure that the data you have gathered provides a plausible basis for them. And you have to show your reader that you understand your own limitations. (This is why I always recommend including the “limitations” in your methods section, not saving them for your discussion.) You demonstrate a working understanding of the difference between your personal experiences (planning your research, calling up subjects, travelling to their places of work, setting up the recorder) and the empirical data that this produces if you do it right, i.e., according to the standards that govern your field. If your theory section made a spectacle, let’s say, of your “disciplined imagination”, your goal in the methods section is to persuade your reader that you also have a disciplined sensibility. You look at the world in an orderly and reliable way. As your reader would. In fact, if the reader wanted to, they could see almost exactly what you have seen, simply by following your instructions, and doing as you did.