I teach at a business school, so many of my students are practically minded. Their research projects have problem statements like, “How can Xompany, Inc. meet ESG requirements while maintaining longterm growth?” When I talk to them, I sometimes challenge them to tell me what their empirical question is. They say things like, “Why is it hard to increase both shareholder value and ESG ratings?” Is that really an empirical question? I ask. It sounds more like a theoretical one. What is it you don’t know about Xompany that you want to learn with this project? What is it you can’t know until you’ve collected some data and analyzed it? That is your empirical question.
The how-question will be answered in their discussion and the why-question will be framed by their theory. The theory will provide the warrant for their practical recommendations; it will tell us why what they are proposing will work. But the real content of the answer will come from what-questions, which will be answered in the analysis.
This simple heuristic may be another way into the thorny issues of the philosophy of science, which I’m working on very deliberately these days. Empirical research tries to settle questions that are “framed” by concepts (theories) and “driven” by norms (values). But our theories and values can’t interact directly. They must meet on the solid ground of objective fact. Why-questions lead us to formulate explanations. How-questions lead us to formulate recommendations. But what-questions demand that we describe reality as it is, even if that reality puzzles us or thwarts our aims.
Nabokov arises early in the morning and works. He does his writing on filing cards, which are gradually copied, expanded, and rearranged until they become his novels.
I’m working through each section of a paper in the Craft of Research series this spring using an image that has worked for me in the past, and which is by no means original, but which I think I just found a good way to label. In general, I tell students to distinguish each section by their “bases” and their “aims”. The theory section, for example, is based on the literature and aims to activate the reader’s expectations of the object, while the analysis is based on the data and aims to challenge those expectations. (They can decide they have other bases and aims; the idea is to make sure they differ in ways they understand from section to section.) But I also tell them to compose their papers one paragraph at a time and we need some way to map the somewhat abstract aims and bases of the sections onto the paragraphs they comprise. This is where I think I may have hit on something.
Think of each paragraph as represented by an old-fashioned cardboard index card. In the title field (above the red line), imagine your key sentence, and then imagine a list of your sources on the rest of the card. I’ve always struggled to label that “rest”. Is it the “body” of the paragraph? Perhaps, but people also like to talk about “body paragraphs”, i.e., the paragraphs in an essay that are not the introduction or the conclusion. They also talk about “topic” sentences for these paragraphs, as distinct from the “thesis” statement of introductory paragraphs. But this doesn’t work for me because every paragraph, including those in the introduction, will have a “key” sentence, one of which will include the thesis statement, i.e., “This paper shows that…” And, in any case, to talk of “keys” and “bodies” seems to mix our metaphors (bodies don’t have locks), so I’ve always wanted another word for the the rest of the paragraph.
Now, while a paragraph is not “a box within which” but “a center around which,” it still occupies a definite volume. It has a form. And so we can talk about the “content” of the paragraph. The key sentence will set up a little difficulty for the paragraph to solve and the content of the paragraph provides the resources we need to solve it. The paragraph “contains” the information we need to support, elaborate, or defend the key sentence. Again, although a paragraph isn’t really a box, the key sentence gives us a particular kind of “access” to the materials that paragraphs presents. The contents are arranged in such a way that the reader will find it easier to believe, understand, or agree with the key sentence.
A research paper can consist of 20 or 40 or 80 paragraphs (or more). Each paragraph can be represented by its key and its content, which, in turn, can be all be summarized on a single 3″ x 5″ piece of cardboard. (It is sufficient that you imagine this finitude, appreciate it; you don’t have to run out to an office-supply store.) Since a paragraph consists of no more than 200 words and takes under a minute to read, there is a limit to how many texts you can cite or how much data you can invoke. Reminding yourself of these limits is a good way to begin to face the much smaller difficulty that writing a paragraph for your theory section constitutes when compared to actually having a theory. The same can be said of the much smaller difficulty that writing a paragraph of analysis constitutes when compared with actually discovering the truth about your object. Try to keep these difficulties distinct, a half page for each little problem.
Schematic of a Galilean telescope. Source: Wikipedia.
In preparation for a talk in the Craft of Research series that is coming up in a couple of months, I’m thinking a lot about the philosophy of science. I’ve also been talking to colleagues who have been tasked with teaching it to students in the social and applied sciences (business, nursing, engineering, etc.) and we all agree that it’s a difficult subject. The main problem is getting students, in a relatively short period of time (a few weeks or months), to understand the meaning of words like “epistemology” and “ontology”, “realism” and “positivism”, “hermeneutics” and “phenomenology”, and to use them to reflect on the foundations of the knowledge they’re acquiring, perhaps even the very nature of “truth”. Many students have more, let’s say, practical concerns, and, while they dutifully write a few pages based on the survey of these terms that they find in their methods handbooks (e.g., Bell et al. or Saunders et al.), they are not otherwise affected. I want to try to find another approach.
This morning a key distinction to teach students occurred to me. Quine pointed out that that what for ordinary people is sometimes understood “by construction” is, for working scientists, experienced as an observation. (See my post “Observation” for more, including the Quine reference.) We can go even further, however, and say that even scientists experience some things more directly than others. They observe what people say and do, but they construct what they mean. (See my post “Saying, Doing, Meaning” for more.) That is really what it means to “theorize a practice” or “conceptualize an object” and it seems to me that this distinction between observations and constructions can therefore be a good way to get students to think concretely about what it means to do “empirical” research. When I talk about writing up the analysis I often distinguish between observation and interpretation and this might be a good jumping off point for talking about how we “construct reality” out of what Lisa Robertson so poetically describes as our “shimmering” data. (See my posts “Observation, Interpretation, and Analysis” and “A Sense of Accomplishment” for more.)
This is just a short post to note down an insight I had while walking to work this morning. There’s a lot here to unpack over the next few weeks (the linked posts provide a starting point). If I’m lucky, I’ll have something useful to tell the students in April! Your comments are more than welcome.
A few years ago, a philosopher and a sociologist sought my advice on a paper they were working on. After they had explained the nature of their troubles, I asked them if they would let me assign a short, hour-and-a-half writing task them for them. They accepted. The task required them to each write — without discussing it in advance — a three-paragraph introduction for the paper they were struggling with. They were to go to their corners and spend a morning composing a paragraph about the world their research addressed, another about the science they were applying to the problem, and, finally, a paragraph about the paper itself. They were to write the first three of my “five easy paragraphs”, devoting no more than half an hour to each. Then, without showing each other what they had written, they were to send their work to me. After a few days, I received their introductions.
You can probably guess what happened next. It was now easy for me to tell them why this paper was difficult to write: they were writing two different papers, framed by two very different readings of the literature, and situated in two different practical contexts. At this point, I could only tell them that they would have to choose which of the two papers to write first. Or, of course, get clearer about why their takes on what they had been doing all these months were so different. When they felt they were ready, they could try the exercise again, this time more confident that the two introductions, while of course different in style, would be about the same thing. That is, still working on their own, they’d write two slightly different introductions to the same paper. Now they’d be ready to collaborate, to work together.
Once you understand the moral of this story, you don’t need a writing coach to facilitate this sort of insight. In fact, it occurred to me this morning that my recent aha! moment about Jeff Bezos’ “six-pager” provides a model for how any collaborative writing project can be focused, when the going gets a little blurry, by a group of co-authors of almost any size. (Within reason! I’m thinking thinking of the sort of collaborative project whose members you can gather in a conference room.) Have one of the members of the group (perhaps, but not necessarily, the lead author) write the introduction and conclusion of your paper (i.e., those five easy paragraphs) and then hold a Bezos-style “study hall” and “messy meeting” about it. Spend maybe 20 minutes reading it together in silence and then have an open discussion about the paper that is being summarized.
At the end of the meeting, assign someone (not necessarily the same author) the task of rewriting it in light of the discussion. Thereafter, apply the same procedure to each section (and perhaps sub-section) of the paper: background, theory, method, analysis, discussion. Have one member write a “crisp document” and then have an open discussion about it. Five paragraphs at a time. Each of these sections would take about two and half hours (for one member of the collaboration) to write and about an an hour to discuss (by all the members). Plan accordingly; appreciate your finitude. Rinse and repeat.
As I often stress to my students, knowledge is not just a resource; it is a competence. To be knowledgeable is to be able to know things and to be enabled to do things you would not otherwise be able to do. (My emphasis.) Notice that this means you can easily test your knowledge. If you want to know what exactly you have learned, go to work on some materials and see what you can do with them. If you want to know whether you have learned something, notice how well you are able to perform the relevant tasks.
And that, of course, is also at the basis of our system of examination. After a teacher has tried to teach you something, they give you an assignment that you can only successfully complete if you have the knowledge they were trying to impart. They propose a performance of your competence. This provides an objective test of whether you possess the knowledge, and a subjective test how well you have mastered it. Your teacher can tell you whether or not you succeeded; but only you really know how hard it was.
I was reminded of this when watching Joss Fong’s video for Vox (above) about AI and homework. As I said a couple of weeks ago, it’s great at capturing the current mood among students and teachers (and journalists). Mine is somewhat different.
For one thing Fong, like many teachers, locates on-site, invigilated writing on the “ban AI” path, while I think of such exams as a way of allowing students (and teachers) to use AI in any way they like. By requiring students to regularly “sit” without AI at their side and show us what they can do, we can safely let them experiment with it both inside and outside the classroom. Rejecting rigorous exam conditions as “policing” and “hall monitoring” is like rejecting refereed competitions in physical education. An exam is just an opportunity to find out what you have learned, what you are good at. We need to normalize these conditions all the more urgently now, not use the occasion to get rid of them altogether.
What the teachers and students in the video have come to understand is that you simply can’t tell what you have learned if the performance of your competence has been assisted by AI. AI is capable of contributing both facts and logic to your writing whether or not you asked it to. You may think you’re just letting it prime your brainstorming, but it is really giving you ideas you don’t yet have the knowledge to understand; you may think it is just cleaning up your language a little, but it may be correcting (or distorting) your whole line of argument. Letting AI into your process renders your own contribution unclear. As I often say to teachers who think the trick is just to design the assignment to test the students ability to use AI, I simply don’t know how to distinguish the student’s contribution from the AI, nor how to grade the former in the presence of the latter. No one has yet been able to explain to me how I could.
I like what Fong says about “desirable difficulties” in learning. She cites research showing that apps that provide turn-by-turn navigation impoverish our spatial knowledge. Like the calculator analogy, which I also use, it is a simplification, but it is instructive. It turns out that coordinating a map with a territory activates our brains in much deeper, richer way, than simply turning right and left when a pleasant voice tells us to. Perhaps this is what Gilles Deleuze and Felix Guattari had in mind when they recommended that we make “a map not a tracing”: “The map does not reproduce the unconscious closed in upon itself; it constructs the unconscious. It fosters connections between fields” (ATP, p. 13). Consider how much harder it is draw even a two dimensional image by looking at it than using tracing paper. Now consider the difference between drawing a three dimensional object and tracing over a photograph of it. One approach teaches you how to see; it even makes you more observant at an “unconscious” level; the other just requires a steady hand.
And, by relating this to writing, we can (literally) flesh out the analogy. Learning to write is not just “building a mental map of the world” it is articulating what Merleau-Ponty and Foucault (borrowing from Hegel) called “the prose of the world”. The “connections between fields” that Deleuze and Guattari are talking about is ultimately the body in the world, trying to find its way around. The grammar or “usage” of this world is represented in the grammar of our sentences and paragraphs. It is no accident that Hamlet’s melancholy, his loss of interest in “all the uses of this world,” was tied to his desire that his “too solid flesh would melt”. Meaning is use. Our prose works reality at the joints, coordinates our organs with our environment. It (literally) gives us meaning.
Literature is “equipment for living”, said Kenneth Burke. While higher education, and writing instruction specifically, should teach students how to articulate themselves, AI offers to articulate their minds and bodies for them. Ultimately, I fear, the effect will be to dismember them, to carve them (not their experience) up at the joints, to disintegrate the prose of their world. A piece of equipment, like a map, only helps if you know how to use it, how to read it. Getting students to write their own prose is no different from telling them to draw a map to show us (and them) they know their way around. We do them a disservice by not requiring them to show us how profitably they can make use of their world.
