“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 constrained 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…

“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 by 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 points 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.

“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. 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 Latin 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.

“A theory is a program of perception.” (Pierre Bourdieu)

I’m holding a talk on how to write theory for students working on their research projects this afternoon. My aim will be to show them how to use theory to bring together the results of their literature review. In fact, I intend, albeit with some trepidation, to pass on Ezra Zuckerman’s advice: “Never write literature reviews.” Instead, they should use the literature to frame an interesting problem; or, as I like to put it, they should write a theory section. Now, some of their teachers will disagree with me about this, and where there’s a disagreement between a writing coach and a thesis supervisor, the supervisor is, of course, right. In those cases, I will suggest that students write the literature review as a narrative that leads up to the theory, which will be a representation of the current “state of the art” that the student wants to practice. Everyone agrees that the literature should inform your research, and we see this formation of your perspective very clearly, very explicitly, in the theory section. Theories shape our expectations of our object; they condition our observations of practice; and they frame our models of reality. Lets look at each of these functions in turn with our reader in mind.

Theories are systems of expectation. Just telling your reader about your object (the social practice your project is about) doesn’t suggest anything very specific about what your analysis will show. Your reader needs to know how you will be approaching the material. So, by invoking theories of organization, or culture, or sensemaking, or institution, or finance, or governance, or discourse, or … you activate particular expectations in the appropriate reader. A reader that doesn’t recognize your theory will not really know what to expect, but, to be frank, they aren’t part of your intended audience. Address yourself to a reader that knows enough about your theories to form relevant general expectations of what your analysis might show. And then write your theory section with the aim of making those expectations more specific and vivid. Theories guide our thinking; they have consequences for what we think will happen in the analysis. They should lead us to reasonable hypotheses — first, what Ezra calls a “compelling null” and, then, after a bit more of what Karl Weick calls “disciplined imagination”, some interesting testable hypotheses to investigate. We might also say that theories are conceptual frameworks.

Concepts are categories of observation. For Kant, they really did discipline our imagination, ensuring that things appear to us as knowable objects in experience. Indeed, one important function of a good concept is to make some things immediately recognizable to us. Other things we have to think a little more about (and we use our concepts to do this thinking.) That is, concepts lead us more or less directly from a brute experience to the conclusion that something is true in the world. Our theoretical concept of, say, “identity” can lead us from statements that were made in an interview to claims about who the interviewee thinks she is. The concept includes a sense of the indicators that lets us apply it to experience, to our data. This makes them important analytical tools but, in the theory section, we just remind the reader of the possibilities implicit in the concepts we intend to use. We make clear what sorts of data would make the sorts of claims that use these concepts true. We activate the reader’s imagination and direct it towards particular features of empirical reality. Bringing together several concepts, we can go on to build a model.

If concepts are the working parts of theories, models are collections of concepts, along with a set of assumptions that mediate between the theory as a whole and the specific practice you are studying. They are theoretical constructs. They do not model the objects as such (the things in themselves) but the relationships that the theory establishes among them. That’s why we sometimes say that models are never “true”. They are merely instruments for interpreting and predicting features of the practices you are studying. They will match your observations only approximately, but these approximations will help you and your reader make sense of what you see. It may be useful to think of your model as the “output device” of your theory section. It applies your concepts with enough specificity to let you generate hypotheses on the basis of some well-chosen assumptions. The literature review (if you choose to write one) leads to your theoretical framework (of concepts) which then lets you build a model. The model, in turn, frames your hypotheses, which really are the actual “output” of theory, making the expectations of reader concrete, and setting up your analysis.

The most important thing when writing about a theory, is to imagine a reader who is already familiar with it. This makes writing about theory very different from writing your background or analysis sections, where you should not assume your reader already understands what you will say. At the end of he day, the reason that you should carry out a literature review is, not to learn a new theory (though you may of course need to do this too), but to get to know your reader, who has presumably read the same books and articles that you have. Obviously, that’s not really going to be the case — everyone has a slightly different reading background — but you can presume that your reader is as “aware” of the literature as you are. Having spent some time in the library, you know what’s out there, and you can identify the major figures. So can your reader, who will feel at home among the texts you cite. It is not presumptuous to assume that your peers have read and understood the same things that you have read and understand. That’s what makes you peers. You should write with the familiarity that comes with this reasonable presumption.

We have a tendency to overthink the syllabus. A year ago, I started fantasizing about a simpler life, teaching Shakespeare at some small, selective liberal arts college. I imagined twelve three-hour lectures/seminars devoted entirely to Hamlet, teaching one act at a time, and assigning a five-paragraph essay every two weeks. I wrote five posts (one for each act), and had planned to write a couple more about larger issues and the final exam. I’ll write those soon, but today I want to talk only about the required reading, where a very simple solution immediately presents itself. Like last year, I want to emphasize that the choice of Hamlet is arbitrary — just an example. You can choose any classic text in your discipline as the focus of your class. As they say, it’s your fantasy.

You will, of course, assign the play in some authoritative edition, such as the Arden Shakespeare. Could students make do with another edition? Of course. But you should remind them that their peer reader has the one you assign, including the critical introduction and the notes. That’s the edition that the reader will be referring to when you cite the play directly, and this image of the reader checking your references is important. You are trying to get your students to imagine real flesh-and-blood “peers”, people engaging in the same sort of intellectual work that they themselves are engaged in. They will be of comparable intelligence and linguistic ability, and they will struggle and learn in comparable ways with the same text. By putting the very same book in each of their hands, you are facilitating their empathy, a sense of intellectual camaraderie. That can be a powerful influence on the class and will do much of the work for you.

What about “the critical literature”? The more classic your key text is, the easier this will be. In my fantasy, for example, I simply assign the Arden Critical Reader. The students now have two solid books to organize a community around, a sort of paradigm for the class. By the final exam, everyone is expected to have read both books in their entirety. This defines a horizon for their discourse, both in class and in their essays. The syllabus will tell them what a legitimate participant in today’s discussion will be expected to have read. Yes, this means that they can either remain silent or pretend otherwise if they haven’t read the day’s readings. There is a risk of exposure, of course, but it’s not so serious that they can’t have fun with it. More importantly, if they have read the assigned reading, they will be able to assume knowledge on the part of their classmates, and use this as a resource to more effectively communicate their insights. Here it is important to emphasize that a horizon is not a boundary: your range of vision is not your range of imagination. Just because your interlocutor can’t see something, does not mean you can’t talk about it.

You might be wondering where the primary literature in the critical tradition has gone. When will the students read Bradley, Wilson, Eliot, Knight, and Kittredge, not to mention Freud (or, better, Jones) and Lacan? These names, of course, come up in the critical reader I’ve already assigned, so my first suggestion is simply to let the students look up the sources as they go, guided, in the first instance, by their curiosity. But as the classroom discussion develops, I would also encourage the students to make some collective decisions about which of the classic works of criticism they should commit each other to having read. If Eliot’s “objective correlative” ends up playing an important role in their assessment of the play, then they should read Eliot’s seminal essay. If Bradley’s theory of Shakespearean tragedy stimulates their thinking, then get them to agree to read it. If a debate rages about whether Freud or Lacan … or Deleuze! … is right about Hamlet’s state of mind, then by all means, suggest they get into the psychoanalysis of the character. That is, let part of the reading list grow organically.

Notice that you are defining a rhetorical situation for the students. What counts as a bright idea or a good question or a witty remark will be determined by a common store of materials that grows as the class proceeds. They can test themselves at any time simply by taking one of their classmates aside and talking about the things that interest them or puzzle them or frustrate them about the play. (They will quickly identify the serious students that make this exercise worthwhile — for both parties.) It is because the scholarly conversation around Hamlet (and all great works of literature) already exists that your work as a teacher — and syllabus designer — does not have to be arduous. You make a few quick, standard selections and establish them as shared reference points for the class. You then let the students contribute their interest and intelligence, and, most importantly, their curiosity. There are countless paths to take through major works of literature and their critical reception. You just have to pick a place to begin.