Randy Westgren dropped me a line about my post on knowledge and imagination. He was kind enough to let me quote from his mail. He began by reminding me of the “distinction between understanding and explanation in the philosophy of science.” This always gets my attention because I wrote my master’s on the philosophy of explanation. I was therefore particularly attuned to this point that Randy made:

Understanding is meaningful only with respect to the audience. An explanation of solar movements or social movements to primary school students – to help them understand – must necessarily be less comprehensive and either more or less abstract than for an audience of doctoral students. An explanation of a phenomenon in science has a goal greater than understanding; one seeks to explain causes, regularities, or other parts of the phenomenon.

This reminded me of a distinction I struggled with in my thesis: the difference between explanation as a rhetorical event and as logical structure. It is true that we sometimes say we will try to “explain something” and mean by this that we will try “get someone to understand” it. Even philosophers, I discovered, have a hard time keeping this straight, but I will insist that this use of the word “explain” has nothing to do with the philosophy of explanation. It certainly makes it difficult to make a sharp distinction between explanation and understanding.

And I think we need this distinction.  “Turco and Zuckerman,” Randy suggested, “are content to say that understanding is good enough for sociology, in many cases.” I’m not sure that’s the right emphasis. On my reading, they were arguing that understanding is necessary, but not sufficient. They were not lamenting the demand for explanation, but the abandonment of understanding.

Randy also suggested that there is “there is a great deal of room for scientific inquiry between law-based explanation and Verstehen.” My view is that the classical “deductive-nomological” account of explanation provides a regulative ideal for explanation, which can only ever be approximated in practice. In real life, nothing is fully explained, no explanation is complete and “understanding” covers the remaining intellectual real estate. Or rather, let’s say that explanations construct a series of extensionless points around which our understanding operates.

I think understanding should be seen as a minimal condition of knowing. I agree with Randy that explanation sets a somewhat higher standard. Or, rather, perhaps it just sets a different standard. Does the relativistic explanation of the precession of the perihelion of Mercury hold to a “higher” standard than our historical understanding of the progress achieved by the civil rights movement?

Sometimes we have to make do with “merely” understanding something. Sometimes we have an actual explanation. Sometimes we have a partial explanation and an understanding of its partiality. Or an explanation along with an understanding of how it might be falsified. I guess I seek an understanding that always tends towards (or at least strives for) explanations. You don’t have to explain Hamlet’s actions in order to understand them. But you build your understanding as you pursue an explanation for his actions and inaction.

“In whatever manner and by whatever means a mode of knowledge may relate to objects, intuition is that through which it is in immediate relation to them, and to which all thought as a means is directed.” (Immanuel Kant, Critique of Pure Reason)

I’ve always like Kant’s definition of intuition. It is that through which we know objects immediately. There’s an interesting tension in that definition since a medium is something that a thing passes through. So intuition appears to be that through which something passes without passing through anything. “The medium of immediacy,” as I sometimes call it.

These days, however, we lack immediacy. We have a tendency to appeal to empirical data to support claims as though we have no immediate access to the objects in question. In the social sciences, this leaves a somewhat uncanny sensation. But I would argue that in the philosophy of science, evidence is almost absurd. Our thoughts, as Kant points out, should be directed not at objects (represented by data) but at intuitions, i.e., at those aspects of objects that are immediately present to us.

I’ve been doing a lot of reading about literacy lately and this uncanniness (and absurdity) is never far from my mind. Even such concrete questions as “what is a research paper?” has been turned into an empirical question requiring detailed ethnographic study of scholars, teachers and students to settle. Shouldn’t it be the most ordinary object in the world to a scholar? After all, it’s something each of us encounters every day, and makes sense of everyday. Do we really need a science to tell us what we’re doing when we read and write a research paper.

Kierkegaard said that faith is immediacy. I think we have, in a profound sense, lost our faith in scholarship. Our constant search for empirical answers to questions that we should already know the answers to, indeed, that our very ability to read and write presupposes we know the answers to,  is a testament to confusion. Our obsession with “new media” is certainly a sign of it. I think it is time we approach the problem more immediately. We need to start saying plainly what is on our minds.

1. Always decide the day before what you will write and when you will write, one key sentence and 27 minutes at a time.

2. Never write about something you just learned this week. Always write about something you knew last week at the latest.

3. Always write a single paragraph of at least six sentences and at most 200 words in support, elaboration or defense of a single well-defined claim expressed in the key sentence.

4. Never write a paragraph that you have not planned the day before. Never write at a time you did not plan to.

5. Start on time and finish on time. If you start late, still finish on time.

6. Always take a three-minute break after writing the paragraph. In this break you must do something that is not related to either your writing or the rest of your day’s tasks.

7. Do not write from your sources. Write from your notes or from your memory.

8. Do not leave “chores” like proofreading and referencing “for later”. They are part of the activity of writing the paragraph for 27 minutes.

9. Read your paragraph out loud sometime in the last five minutes of each 27-minute writing moment.

10. Do not write more than six paragraphs per day. That is, do not write for more than three hours each day.

11. Do not render any absolute judgment on your paragraphs. At most once a week, simply rank them from best to worst.

____________
*To be followed by the scholar seeking to become a better prose writer during eight weeks (40 days) of deliberate effort directed to that end.

[Download PDF Version]

Ezra Zuckerman recently pointed me toward a comment he wrote with Catherine Turco on Duncan Watts’s critique of interpretative or “empathetic” (as opposed to explanatory or “causal”) approaches to sociology . We had been exchanging views about the replication crisis in the social sciences, and Ezra suggested that one of the reasons our theorizing has run wild is the assumption that the mechanism we posit to explain phenomena need not be intuited. In the comment, he and Turco put it as follows:

…our lack of intuition for the mechanisms means that the sole basis for acceptance of such research lies in the results that are presented. Empathetic theories do not rely solely on empirical validation but also on how plausible it is that reasonable individuals would act in the manner supposed by the theory; this sets a higher bar for acceptance of the theory independent of empirical results. (p. 6)

I’m not sure people have to be presumed to be “reasonable” in order for their actions to be “plausible”. It’s long been my view that humans are as distinctly passionate as they are reasonable and that their plausibility, therefore, is as bounded by their passions as their reasons. (Note, indeed, that we’re talking about “empathetic theories”.) But the general point that they are making here is a strong and important one: whatever mechanism is proposed must make intuitive sense.

Another way to put this is that we must be able to imagine it. We must be able to “make ourselves pictures of the facts,” as Wittgenstein famously put it, except that these are not the “cold” facts of natural science. They are facts with which we are also intimately familiar. A description of the mechanism must be recognizable to us, as it were, from the inside. It is not merely something that explains certain effects, but resonates within us as that which moves and is moved by things.

Ezra and Turco emphasize that there’s a substantive issue here:

There can be no debating Watts’s premise that the two modes of inquiry and associated standards are distinct. As he points out, the physical sciences operate purely in the causal mode. Physical scientists do not find it productive to imagine what it would be like to be an electron or cell in order to explain its behavior.

This reminded me of Hayek’s suggestion in the The Counter-Revolution of Science:

The physicist who wishes to understand the problems of the social sciences with the help of an analogy from his own field would have to imagine a world in which he knew by direct observation the inside of the atoms and had neither the possibility of making experiments with lumps of matter nor opportunity to observe more than the interactions of a comparatively few atoms during a limited period.

In a certain sense, physicists do imagine “what it would be like” to be an electron or cell. It’s just that they imagine it would be a very simple and utterly causal (stimulus-response-type) experience. They don’t imagine that the cell or electron would make up its mind about its behavior, not even retrospectively, and this would-be act of sensemaking is therefore quite understandably–quite plausibly, if you will–left out of account in the explanation.

But in the case of human behavior we have to imagine people behaving in one way or another with some awareness of what they are doing. They must, at the very least, live with what they have done. They are not merely gears grinding inputs into outputs. They are conscious beings. Moreover, given our (admittedly somewhat intermittent) empathy with them, we aren’t able to throw them together in all manner of “experimental” situations to test their limits. Social experiments are constrained by our ethics, and those ethics are, presumably, also already constraints on the human behavior that our experiments are designed to help us understand.

There is too much to say about all this in a single blog post. I will take up Ezra Pound’s idea that “the arts provide the data for ethics” in another post. What I wanted to emphasize here is that there can be no knowledge of things without imagination. When it comes to a cell or an electron we have no need to imagine its “inner” workings (at least not in the sense of their subjectivity), but when we turn our science on each other we cannot rest until we have proposed a mechanism that makes intuitive sense of our own lives. Otherwise we end up with a social theory that requires us to be nothing more than pigeons or worms or, indeed, cells or electrons. Like I say, that may already be ethically inadequate, but it is certainly counter-intuitive.

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

I recently stumbled on the DoctoralWritingSIG blog (HT Julia Molinari). “What does it mean to ‘theorise’ research?” asks Cally Guerin in a recent post . This is something I happen to have a lot of ideas about, so I posted a quick comment about what  I tell students and researchers: “Theory” is really just the expectations you share with your reader about your object, or at least the expectations you shared with them before you analyzed your data. In your theory section, then, you are setting your reader up for an artful disappointment. You are reminding the reader of what they expect, well aware that what you have found will challenge those expectations and therefore occasion learning.

In classical hypothesis-testing approaches the theory would serve as the basis for constructing the null. The hypotheses that are constructed are normally sought to be confirmed, not disappointed. That is, the “artful disappointment” comes from the rejection of the null, not the hypotheses. Though I don’t pretend to be an expert here, theory can, as I understand it, be used in a similar way by Bayesians (like Andrew Gelman) to construct the “prior”. In both cases, “theory” includes the empirical results of past studies, which allows to estimate effect sizes. That is, theory is not just a set of causal laws, but also some generalized initial conditions.

But a “softer” approach to theory-as-expectation can also be taken to qualitative research. The theory provides a schema of expectations. So, by announcing that you are deploying, say, Genette’s theory of narrative, you are fostering an expectation that the analysis will identify the order, frequency, and duration of events, and provide an account of the voice and mood of the telling. The theory section will be written with a presumption that the reader is familiar with Genette’s narratology, and with what past applications have found “works” (and does not work) in particular narratives. As in statistical analysis, the theory gets us to anticipate anticipate “effects” in the material to be analyzed.

Given only the theory and description of the data (in the methods section) the properly trained (“peer”) reader should be able to form a qualified opinion about what the analysis will show. That opinion should, preferably, be shown to be incomplete in the paper. But I should stress that the importance of publishing null results is becoming increasingly clear in many fields.

In fact, I need to rethink this view of nulls, priors and expectations in light of the growing “replication crisis” in social science. An important guiding insight here, which has been with me for a long time, has come from Ezra Zuckerman, who emphasizes the importance of constructing a “compelling null”. And here we have to keep in mind that what we find compelling is always changing. So, in the early days of research into so-called “priming” and “implicit bias”, the null was supposed to be that such effects did not exist. Today, however, the orthodoxy (albeit one that is somewhat besieged) is that such biases do affect our thinking. Now, the question is: how much and under what conditions?

The general point, I dare say, still holds: our theory structures our expectations of our object. And those expectations are shared, communal. Our research, likewise, should be designed to challenge those expectations, but they should probably be published even where their challenge fails and the expectations hold. I guess there’s a sort of meta-theoretical twist here: although our theories tell us what to expect, we also expect that all theories leave something to be desired. In a sense, we expect to be disappointed. Some people, and especially students, sometimes forget that and let the disappointment, when it inevitably comes, frustrate them. What has actually happened, like I say, is that they learned something.