Reposted from my new blog.

A writer recently expressed to me the concern about her work being too simple, a concern triggered by, among other things, being told that her work was pedestrian (which I discussed n my previous post). But for the great majority of scholarly work, if done carefully, complexity is almost unavoidable. The real world is not simple, and a scholar trying to document the real world is not documenting something simple.  Analyzing data gathered in the process of documenting the real world is not simple, either.

My experience of writing blog posts often goes something like this: an idea formulates into a basic message and plan for what I will say; I start writing; I think of an example to use; I start to describe the example, and in so doing, I find complexity where I thought was simplicity. No matter the clarity of my plan, once I start writing, I discover complexity.

It’s easy to find complexity if you are being careful and trying to focus on details. All you need do is be curious and careful.

Suppose, for example, you try to describe a simple household process like getting a glass of water.  That’s simple, right? You get a glass; you hold the glass beneath the faucet; you turn on the water and the glass fills. But complexity lurks. Where do you get the glass, for example? In your own home, you know where the glasses are, but if you’re visiting somewhere, finding a glass may require extra steps, such as opening many cabinets or asking your host. Getting into details might lead to asking what criteria are used for choosing a glass: do you take the one closest to your hand? To which hand? Do you prefer a large glass or small? Do you look to make sure that there is no visible smudge or dirt on the glass? Do you prefer one material over another (glass vs. plastic, for example)? If a glass has a colored material or an image printed, does that matter?  Beyond these practical questions of how to get a glass (we haven’t even started talking about locating or operating a faucet yet), if our aim is to describe the process, we might choose to try to define what we mean by “glass”—does, for example, a mug get included? A mug is not a glass, but it will be effective for drinking a “glass of water” if we interpret the phrase loosely? In many contexts, such an interpretation suffices: imagine asking a friend for a glass of water and them giving you a mug filled with water. Would you complain that they had failed because your water was served in a mug not a glass? And beyond these questions relevant to getting a glass of water in practice, if we are describing the process of getting a glass of water, we might examine how or where the glasses (or mugs) were procured, and how they were made. Although they are not questions for the practical situation, for someone documenting or describing a process, those questions directly follow (even if we might decide that they are not sufficiently relevant to include in a description of getting a glass of water). So trying to describe something simple, quickly leads to complexity if you just ask questions.

Another way that complexity can arise for a writer is by trying to define terms. Suppose you want to write about [term/concept].  It’s good form as a scholar to define the crucial term to your audience, so you try to define [term/concept]. You may turn to a dictionary, where you find multiple different meanings of [term/concept]. You look at the literature in your field, and you find several different authors have all defined [term/concept] in their paper, and they have all done it differently. If the observed complexity of the use of the term hasn’t stymied you, you might sit down to try to write your own definition of the term. In that process you use [term2/concept2], and that leads to the question of whether you need to define [term2/concept2].  Defining terms is a rabbit hole of complexity, as every definition requires using terms that could themselves require definition.  In his beautiful essay “Avatars of the Tortoise,” Jorge Luis Borges describes this as an infinite regression first identified by a Greek Philosopher (whose name escapes me, and I don’t have the Borges text at hand). Defining terms/concepts is not simple, and scholarly writing requires definition.

Complexity arises in the process of argumentation/justification, and there is a similar regression of questions. Suppose, for example, I want to explain why I have chosen a specific research method—methodX.  Every statement I make in favor of methodX can be questioned. If I say I have chosen methodX because it’s appropriate to my research question, the natural question that follows is why (or whether) it is appropriate to the question. If I then offer two arguments—argument1 and argument2—for why the method is appropriate to the question, I have two new arguments that each require some defense. Logically speaking, any argument can be questioned, and each answer offers new arguments that can be questioned.  

It is exactly this kind of logical path from one question to the next that leads many writers down discursive rabbit holes that can inhibit the writing process. And it is one reason that citation is so valuable for the scholarly writer: you can end the string of questions by saying “because FamousAuthor said so.”  It’s not a logically perfect foundation, but what the heck…we all need to find a foundation, and even the greats rely on the foundation of the scholars who have come before—Newton said “If I have seen farther, it was by standing on the shoulders of giants.”

If you want to describe something, and you are careful about it, complexity will arise.  If you are a scholar, you’re supposed to be careful, and, in my experience, that leads to what most might consider a surprising result: good scholars almost almost always have too much to say. I’ve known lots of writers who worried that they had nothing to say, and I’ve known lots of writers who wrote very little for fear that they have nothing to say. But I can’t remember any writer who, once writing, wasn’t able to say enough. The far more common (and more difficult) problem for writers is to have to cut material to get their article or book down to a word limit. (Because of the difficulty of cutting down a draft, I strongly recommend writing first drafts that are short!)

So, don’t worry that your ideas are too simple, embrace that simplicity. Try to capture that simplicity in writing. If you’re careful and attentive to detail, complexity will arise. Indeed, so much complexity arises that there is great danger in getting lost in it, and the writer needs to learn to say “here’s where I stop asking questions.”

My problem with non-objectivist philosophies

Frequently, I quote from the opening verse of the Tao Te Ching: “the Tao that can be named is not the absolute Tao.” It’s an epistemological statement of limitation—a statement about our ability to know and communicate ideas—and one that reflects my understanding of our ability to know things. Knowledge, I believe, is not absolute. I do not, in short, accept the existence of “objective knowledge”—but that has implications for a scholar, philosopher, or researcher, and it becomes a problem.

Objective knowledge (if there is such a thing) is, by definition, true for everyone. That’s a great standard on which to drive a research agenda: “I’m going to discover something that everyone can agree upon!”
But if there is no objective knowledge—as generally asserted by post-modern and other philosophies (e.g., American Pragmatism, Hume's Skepticism, the Tao Te Ching)—what then prevents the slip of research into knowledge that is only meaningful for the individual?  If there is no objective knowledge, what makes my work valuable to anyone else?
This is one of the struggles for non-objectivist scholars: on the one hand, the limitations of knowledge are made central to any argument, and on the other, there is a desire to do work that is meaningful and even useful to others.

A lot of research strives to serve important social goals, but if the work is only “true” for a select group of people and not for others, can that serve the larger social goal?  This idea of being able to generalize is central to research methods, even those that accept limits to objective knowledge: the point of those methods are to give research work a foundation that others will accept, too.

For me, personally, I want to espouse ideas that will be “true” for everyone—ideas that any person would accept, given the evidence.  When I write about issues in writing and research, I want to write things that help others, and that requires other people to be able to apply my ideas to their view of the world.  But at the same time, one of the ideas that I write about is how ideas are limited, and how they are imperfect and uncertain, and that makes it difficult to make any claims.

So how to do I convince other people that my work has meaning and value to them?  This is especially difficult when dealing with people who generally accept the idea of objective truth.  After all, objective truth is a very comforting notion—even if the objective truth is unpleasant, it is, at least, certain and undeniable. A truth that is contingent on my limited knowledge and perspectives, on the other hand, is much more easily dismissed.

The problem, then, with non-objectivist philosophies, is how to convince others that they are meaningful and useful without resting on the idea that the claims are universally true.
My answer is generally driven by pragmatic concerns: because logical, certain proof is out of reach, and because I need to commit to something in writing (otherwise, I don’t write), I do my best. I accept what I accept for the best reasons that I can find and go from there.

On a certain level, that’s fine: personally, I’m ok making decisions in the face of uncertainty, and even though I’m sometimes wrong, I don’t belabor the decisions that were the best decisions I could make. But on another level, it’s a big problem if the audience doesn’t like what you have to say, or doesn’t accept what you have to say, especially if they want something certain—something solid that, if not objective, at least makes a claim to objectivity.

I don’t really have the answer to convincing a hostile audience. But I suppose on place to look is at your own concerns: what benefits might accrue from your research? If you suggest looking at some field of endeavor from a new perspective, what benefits could accrue? What can motivate interest in that view beyond just saying “here’s a different way of looking at things?” Focusing on benefits can reveal problems: if using a new perspective leads to doing things “better” in some way, that area of improvement could be viewed as a problem that you are addressing.

On advantage of focusing on benefits of a new idea is purely emotional for a writer—focusing on benefits keeps attention on the strong points of work, and helps sustain confidence.

I don’t have an answer for this. Without the anchor of objective certainty, how does one prevent the slippage towards ideas that are meaningful to the individual alone? If I am certain of anything, it is that there is no certain knowledge, but where does that lead me?

Somehow the scholar/philosopher/researcher who rejects objectivist philosophies needs to be able to make some claim that will convince their audience that their work is worth the time. But I’m not sure of the means of accomplishing this.

Controlled Experiments and Discoveries

Knowledge advances in two ways: intentionally and by accident (and these are, by definition, mutually exclusive: that which is not intentional is an accident, and vice versa).

It's worthwhile to understand what it is that constitutes knowledge and research, because having that fundamental understanding gives us the greatest opportunity to learn from the data we have.

I had considered titling this post "Found Art" because some of research is largely "found art": that which was discovered serendipitously, but was, perhaps, thought refuse.

But the motivation for this post was talking with a writer who had attempted to run an experiment, and the experiment failed. "I should try something else," he suggested. But I'm wondering what could be found in the wealth of data generated by what he did do. It may not be that the failed experiment will provide a gem of information, but it might provide valuable insights that will guide future research.

Controlled experiments are one of the paradigms of research--it is intentional research in its most extreme form: possible outcomes are limited as much as possible to that which can be accurately measured.

In the laboratory a great deal of control can be exerted to limit different kinds of variability. That kind of control cannot be exerted in the field. And so controlled experiments may break down for various reasons beyond the control of the researcher, eliminating the possibility of getting the results that had been desired and intended.

In the field, however, if you are documenting the process extensively, even a failed experiment will generate masses of data that can be processed and analyzed for insights that were missing when the experiment was set up.

The first place to look is the failures. Your experiment failed because of record-keeping lapses by the participants? What does this teach you about setting up an experiment that will work in similar conditions? Does this suggest a failure to engage in the experimental activities? Why? What can the failures of the experiment teach about setting up an experiment to study the issue that motivated the original study? The failures, in some cases, may tell you about the very thing that you're testing, too. Do they indicate any results that would indicate that there are problems with the general premises under which you are operating?

Careful examination of a "failed" study can be quite valuable because of all the data generated--it simply requires one to look at the data in a different way--to see it through different eyes--to see the urinal as art.

Quantitative and Qualitative (2)

Quantitative studies are studies that rely on counting and measurement...they rely on numbers. So if you want to do a quantitative study, you have to have some idea of what you are going to count or what you're going to measure.

Qualitative studies could be seen as any study that is not about counting, and not about applying numbers to things. It makes sense to look at this as an examination of the qualities of things, but qualitative studies can also operate in the same logical context as quantitative studies, if the qualitative study is viewed as an opportunity to examine possibilities (see my previous post on this).

The questions asked by quantitative studies and by qualitative studies are different.

Here are some quantitative questions.
"How many are there?"
"How often does this occur?"
"Are these measurements correlated?"
"Which occurs more frequently?"
"Is the rate of occurrence stable or changing?"
"How do these groups differ for a given measurement?"
"What are the likely results of an action, and what are the likelihoods/probabilities?"

Qualitative questions:
"What is it like to do X?"
"What are the experiences of group Y?"
"What are the perceptions of group Y?"
"What are the characteristics of group Y?"
"What has occurred?"
"What are possible consequences of that action?"
"What are different ways that Z can be interpreted?"

Quantitative and Qualitative

I started talking about the vast unconscious because I wanted to talk about quantitative and qualitative studies. Yesterday I asked "what is the point of research?" To some extent the point of the research depends on the type of research you're doing.

The point of quantitative research is different from the point of qualitative research (no kidding!). But knowing that they have different points is not the same as understanding what the point of each type of research is.

Here's my take on it:
Qualitative work is a study of what is possible; it looks at the world and describes it in different ways and explores the possibilities suggested by it. Qualitative research looks at what happened, at the quality of how it happens, and at possible causal paths.
Quantitative work is a study of frequencies and probabilities and magnitudes: how often does this occur? how likely is it to happen? how large is the effect?

That's the super-condensed version. I know I'm leaving out huge swaths of detail. I like to explain it this way because there is a prejudice against qualitative data: many people take qualitative data to be "soft" or not the product of "rigorous scientific thinking." But if we look at the logic underlying Qualitative research, it is no less sound than the logic underlying quantitative research, it is simply the case that a different kind of thing is being shown. The two types of research do different things. To dismiss qualitative research is to dismiss a whole segment of logical development.

Let's put it this way: empirical research--that is research based on observation of the world--is fundamentally inductive: it takes a number of specific observations, and reasons from those to a more general conclusion: some sort of rule explaining the observations, and presumably similar observations.

So, for example, we might be observing taxi cabs in NYC. We see several, and they're all yellow. Induction leads us to propose a rule: "all taxi cabs in NYC are yellow." Induction is problematic, however, because you never know for certain: just because you observed 100 yellow cabs, or a thousand, doesn't mean that there isn't one that isn't yellow (in fact there are, or at least used to be, "gypsy cabs" in NYC--not licensed by whoever licensed the yellow cabs, but cabs nonetheless. They weren't yellow, though). We never know with certainty that the future will resemble the past: the cab we see in the future may not be like the one we saw in the past. This problem is sometimes know as "Hume's Problem."

Karl Popper's response to this problem is to suggest that instead of proving the truth of hypotheses, we focus on proving their falsity. So we take the proposition "all cabs are yellow" and we test it. If we observe a cab that is not yellow, then we know that the proposition is false. This is the basis of the null hypothesis that forms the heart of many statistical tests: we propose that there is no causal relationship, and then we reject that null hypothesis, and instead seek an alternative hypothesis--that there is some causal relationship.
Quantitative methods are typically going to focus on how likely something is to be true--so with hypothesis tests, the level of significance is the probability that the result was caused at random. If the probability is very low, then that indicates that there might be some non-random effect. A regression, too, is looking for a probabilistic assessment of causality and of the magnitude of the causal effect.

Qualitative research can be looked at, on a preliminary level, as providing both the case that disproves a rule, and the case that suggests other rules. By observing, for example, a guinea pig, we can learn that all sorts of assertions are false: for example, guinea pigs aren't always fierce. Ok that's a silly example, but take for example a slightly more realistic question--someone might assert "all murderers had a bad family life", then studying a single murderer might be sufficient to dispel that assertion. (I did say "slightly more realistic".) Where there are stereotypes, qualitative studies are ways to work against the stereotype and to show where they fail.
On the other side, qualitative work can be used to generate suggestions. Do you want to understand why people become {axe muderers/haridressers/professional golfers/whatever}? Well, a good place to start is with a qualitative study, where close work with a single individual might suggest that people become hairdressers because they were frightened by their grandfather's comb-over or something. If you have even one person who says "I became a hairdresser for reason X" then you know that at least some people become hairdressers for reason X. From there you could do a quantitative study to see how often reason X plays a role in becoming a hairdresser.
Qualitative studies can give other valuable stuff, too, but I don't want to get into it now.

What's the point of research?

Yesterday I was writing about the vast unconscious and how it is important to try to bring the premises we reason on into our conscious, reflective mind.

One point which is not often considered consciously is the basic point of research. What is research, and why are we doing it? What is the value in it?

The answer is not simple.
We often think in terms of a correspondence theory of truth--I had a friend tell me that science was to "discover facts"; the fact that he had (and still has) a Ph.D. from UC Berkeley reveals how this theory of truth is accepted by even those with a great deal of education and intelligence. As a natural scientist there is great value in seeing the research project as one depending on a correspondence theory of truth, but as science deals with the quantum world, and many different aspects of physics, correspondence theories become more and more problematic.

If you are working in the social sciences, in literature, history, the arts and many other fields, the idea of a correspondence theory of truth will serve you less well.
The very idea of a correspondence theory of truth--indeed, the very idea of truth--has been challenged by many philosophers of reknown over the past century. Michel Foucault and Jacques Derrida are two famed exemplars of this general debate. It would be considered naive, I think, at this point to attempt to work with such a vision in some fields, unless one were well-prepared to acknowledge and rebut the arguments of those opposed to correspondence theories. In the absence of a correspondence theory, one must seek some other theory on which to base research--undersanding other theories of research, e.g., hermenutics or phenomenology, can help bring focus to the purpose of research.

By bringing into conscious discussion the premises on which you base your research, and on which you write it up, ou being to develop a basis on which your whole work can be structured in a coherent fashion. By understanding what the purpose of your research is, and by understanding what you are trying to show, and how you hope to show it, you build a framework for presenting the work, and for working in the different pieces necessary to make the research proejct work as a whole.

I can't answer the question of what research is for you, because I think that different kinds of research will have different purposes. If you can give a clear purpose for the work, it can often help stay away from questions of epistemology--for example, if you assert that your research is intended to help clinicians work with a certain population, you don't need to worry about theories of truth. Or if you are going to develop an algorithm, or some technological device; or if you're doing any of a number of things, you can focus directly on your immediate purpose.

On the other hand some projects have a much more difficult time stating a purpose. For example a history. What is the purpose of a history? Especially we might ask what is the purpose of a history, when we know that histories inevitably reflect the historian's concerns? Having an understanding of what the purposes of other writers in history can help--how are these other writers grounding their work and giving it a sense of purpose? We can always present a history as a cautionary tale, or an educational study that helps us understand situations that we want to ameliorate. Or we could take a history as a story that educates us about a population: what are these people like and why? In that context, we might look at a piece of evidence as suggestive of ideas and attitudes that we have no direct evidence of--thus we might look at a bureaucracy and its policies as indicating or suggesting certain motives. We might not be able to substantiate the existence of the motive, but we can still infer it and indicate how the evidence is suggestive. Such techniques might please some and infuriate others. But my main point returns: as we make ourselves consciously address the question "what's the point of research?," we begin to have answers that can help us structure our research and writing efforts. To the extent that we develop a scholarly understanding that generates a theory of research, we can save ourselves from losing time wondering what it is that we're trying to do, ad we can also give ourselves an understanding that helps us explain our intentions to others--and sometimes a good verbal explanation can really change how your professor reads your work.

The vast unconscious

I was thinking about writing a little about the difference between quantitative and qualitative studies, but then I regressed thinking about where to start. How do you talk about different types of research without having a good foundation on what research is about? And then I thought: how can I talk about research without setting a foundation of what knowledge is? And then I thought, how can I talk about knowledge without talking about the human cognitive system. I figured that would be a good starting place, though I could have regressed further. Logically speaking there is no clear point at which to stop regression, but that's beside the point. Here I am, considering the vast unconscious.

What is unconscious, are the basic ideas that bind how we see our world. We all adhere to some philosophy; most of us, however, simply accept a basic philosophy without examining it. For example, it is common to believe in a "real world". This is a basic ontological position that has been disputed by philosophers throughout the ages, but the person on the street most likely has a simpler view of this: they accept unconsciously the existence of a real world. Similarly, most people who have not studied issues of epistemology probably believe that knowledge is basically governed by what is called a "correspondence theory of truth": they believe that the truth of a statement or concept depends on whether it accurately reflects the real world.

We reason in terms of such deep understandings of the world. But philosophy, and academe (in which the traditional doctorate in many fields is the doctor of philosophy), the goal is to make such presumptions explicit and then to test them. Now, of course, at some point we choose not to question further, and we accept an understanding--a presumption that we accept as axiomatic. I accept the presumption that there is a real world--though I have consciously examined the idea and recognized weaknesses in the ability to prove the existence of a real world, it does not seem to me sensible or practical to reject the presumption that there is a real world.

Relying on such unconscious principles can cause problems when working in academia. In particular, understanding research and research principles is greatly facilitated if we can bring unconscious beliefs, like that of a correspondence theory of truth, into our conscious reasoning. Having a conscious understanding of these beliefs provides a good foundation from which to reason. If we reason from a conscious understanding of what the general project of research is about, it is easier to design a sound research project and to find a project that suits your interests.

Sadly, we often don't have a good understanding of these deep ideas. Research is often conducted on the basis of models: we imitate the research ideas of others. While this is a very effective technique in some ways--there is definitely value in modeling the behavior of others--it is also a technique that can hinder the writing up of a work, and can hinder your explanation of why you have arrived at a specific research method: "I copied someone else's research" isn't the strongest of arguments (it's not the weakest, either, but that's beside the point).

Of course, it takes time to make these things conscious, and to understand the issues at hand. But it seems to me that a researcher will facilitate his or her efforts by having a clear idea of the philosophical premises that they are trying to realize: what makes an argument strong and what doesn't?

Parables

In the Literary Mind, Mark Turner argues that narrative, and parables, are fundamental structures that govern human thought. Below is a passage from Turner's book. I've touched on this same passage in a different post, but I'll repeat it here:

"Story is a basic principle of mind. Most of our experience, our knowledge, and our thinking is organized as stories. The mental scope of story is magnified by projection--one story helps us make sense of another. The projection of one story onto another is parable, a basic cognitive principle that shows up everywhere,...
"Parable is the root of the human mind--of thinking, knowing, acting, creating, and plausibly even of speaking."

From one perspective, academic work is the job of creating parables: it tells stories that are meant to be projected onto another.

When we think about parables, often we may think in terms of the simple parables, like those in the Bible. Usually such stories are boiled down to a single idea--the moral of the story--though often such stories are complex and not easily simplified (e.g., is the prodigal son a story of forgiveness, a story of letting go of jealousy, or is it a story of contrition?).

When writing an academic work, it can help to boil the work down to a single core statement and use that to organize the material, because that core provides focus.

But that core can be hard to identify. One way to identify a core might be to think of the work as a parable: what does this story teach us about other stories? I'm not sure what the parable of the prodigal son is supposed to teach, but I see that its point is to suggest something about more general sets of behavior. It is not intended only for those who are in a family where one son goes off, ends up herding swine, and then returns. It is intended for a more general range of experiences.

So in what way does the parable of your project work?
If you're doing a study using inferential statistics, the parable is obvious: the statistics are meant to make inferences from a smaller population (the sample) to the population at large.
If you're doing qualitative work, or doing any sort of work that isn't quantitative, the parable might not be obvious. For that matter, it's possible that you haven't even thought of your work as a parable at all.

Thinking of a complex subject as a parable in a particular dimension can help organize complex material. So, for example, one might be looking at the interface between a specific group of people--(e.g., a racial/ethnic group, an occupational group, etc.)--and how that group interacted with a set of general bureaucratic systems. That story could become a parable about how people respond to bureaucracies, or it could be a story about how bureaucracies count people. It could be any number of other possibilities, but just taking these two, we can see that they organize the material and the focus of the writing differently. They both provide opportunities for the writer to mention the same material--e.g., material about the creation of a specific bureaucratic procedure, or newspaper/newsletter reports from the press within that group--though with aim to tell different stories.

Or, to take another example, one might be looking at the history of a local delicacy and how globalization of markets affected that delicacy. Does that become a parable about market operations? does it become a parable about policies of globalization? is it about food? about local culture?

Choosing one of the possibilities creates a focus and leads to structural requirements. Choosing one of the possibilities is not meant to eliminate discussion of the others, nor is it meant to exclude the other possibilities--maybe you can see that your study is a parable on many different levels and you want to try to convey that. Nonetheless, it can help to choose one as a focal point to guide the structure, and then to work in the other stories as sidelights to the main point.

I have spoken of using a parable as a perspective to help focus the complexity of the dissertation. But it worth keeping in mind the points I made at the beginning of the post: The second was that academia is in the business of making parables--of taking specific stories and using them to illustrate general positions (this is the basic issue of induction: making a generalization based on specifics). So what does your story tell about other stories? The first point was that we think in terms of parables. I know there's a lot of different ideas of how we think, different theories of cognition/psychology, so you may not accept this premise, which is why I listed it last. The fact that academia uses parables is a direct observation of academia, and it does not require the cognitive theory. I, however, find that theory an interesting and instructive one, so I like to explore what it means.

Symmetry of Ignorance (2)

I was thinking about the symmetry of ignorance today in terms of infinity.

Let's assume that there is an essentially infinite body of potential knowledge relevant to a problem. From a practical point of view we could argue this in terms of the size of the body of published literature, and the pace at which that body is growing, as long as the subject matter is defined sufficiently broadly, there is far more material than an individual can read in a practical amount of time.

If we accept this to be the case, and we also accept that the knowledge of any individual is finite, then it necessarily follows that each individual is faced with a practical infinity of material still to learn, no matter how much they have already learned. Therefore the amount we each don't know is equal, even when the amount that we each do know is unequal.

On a certain level, we might look at this argument as nothing more than sophistry of a sort--an argument for the sake of the argument. Can we even accept the notion that there is a practical infinity of knowledge in a well-defined field of study?

But on another level, we can see that part of the fundamental development of knowledge systems relies on the development of different perspectives--both those that are the incorporation of new ideas into older frameworks, and those that represent paradigmatic shifts to entirely new frameworks of reasoning (e.g., the Copernican revolution).

In a way, what every author has to offer is a new way to look at old questions or old material. This is inevitable: we are all different people with our ideas shaped by our experiences. Even if we closely share ideas with a person or group of people, there are probably ways in which our perspectives differ.

Even if you are reporting on things that have been reported on before, you can create something new by presenting that old material through a new context.

Symmetry of Ignorance

I was talking with a friend of mine on Sunday. She was telling me about her baby: "She's just a little learning machine," she told me. "And let's hope she stays that way for the next fifty or so years," I said. I still learn new things. It's a great shame to stop learning, because learning is itself an enjoyable activity, for all its difficult moments.

Horst Rittel, who I've mentioned in previous posts, suggested a notion of "a symmetry of ignorance." He suggested this concept in the context of planning problems--planning in the sense of large-scale urban planning. In a 1972 article titled "On the Palnning Crisis", he writes:

The expertise and ignorance is distributed over all participants in a wicked problem. There is a symmetry of ignorance among those who participate because nobody knows better by virtue of his degrees or his status. There are no experts (which is irritating for experts), and if experts there are, they are only experts in guiding the process of dealing with a wicked problem, but not for the subject matter of the problem.

This description (even if we ignore the concept of "wicked problems", which may not be familiar, which I've not defined here, and which, in my opinion, is not paticularly well described in wikipedia), obviously isn't quite appropriate to the writer who is working alone, or to the writer who is seeking to complete a dissertation.

But I think the notion of the symmetry of ignorance is still relevant to the writer. First of all, Rittel writes "nobody knows better by vitrue of his degrees or status." But is there any criteria by which somebody does know better? I would say no, and Rittel, I think, would say no, as well. Rittel writes:

an essential characteristic of wicked problems is that they cannot be correct or false, but only good or bad. But who says whether a plan and the solution to a problem is good or bad?

Who, indeed? With a dissertation, of course, we can identify the specific individuals who get to say whether it is good or bad, but we may not be easily able to assess what they would say is good or bad. But that's sort of beside the point: Rittel is suggesting that there is no absoulte standard by which to judge the work. If we are thinking about the work as a written piece and we want that written piece to be "good", who says whether it is good? We don't really know what will make it good ahead of time, and neither do our professors. This is not to say that neither we nor our professors can assess quality, but rather to say that until the paper is written we can't know exactly what it will take to make it good.
The symmetry of ignorance does not suggest that there is no point in trying to plan, and the idea that we don't know exactly what is needed for our dissertation, and neither do our professors, is not intended to suggest that we're just shooting in the dark. Rather this notion is important to the writer--to the academic writer, at least--to help keep in mind that the process of writing is one in which learning is going to take place: we don't know what it will take to finish the project, but we will learn that in the course of the writing. We don't know what the experiment will show, and so we learn from it. This idea that we must necessarily learn in the process might, perhaps, help us deal with the emotional difficulty of not knowing what we have to do: of course we don't know what we have to do, we are told by the principle of symmetry of ignorance, the challenge of the task is to understand what it is that we are going to write. And a natural corollary of this is that as we write--especially near the beginning of the process--we will necessarily do work that needs later revision, because it's work based on what we knew before we started learning during the process.

Borges and I

The great Jorge Luis Borges wrote a short piece titled "Borges and I" (or, at least, that's its title in translation; Borges wrote in Spanish). I take it from the book Labyrinths, which is a collection of short pieces. The piece is in a section of the book titled "Parables."

A "parable" is often defined as a story meant to teach a simple lesson.

The parable "Borges and I," is, as I read it, largely concerned with the public persona, and the persona captured in the public eye (i.e., the "Borges" of the title) as opposed to the internally experienced life. And this part of the parable, I have some trouble connecting with, because I do not really have a public persona--at least not that is strongly reflected back at me by others; unlike Borges, people do not write about me.

But the latter part of the parable (which is all of maybe 500 words) speaks to me of a different sense--a sense of the difference between who I am today and who I was in the past.

I recognize myself less in [Borges's] books than in many others or in the laborious strumming of a guitar. Years ago I tried to free myself from him and went from the mythologies of the suburbs to the games with time and infinity, but those games belong to Borges now and I shall have to imagine other things.

As we write, and as we explore ideas and work on learning from them, we change and grow. As a result our perspective changes. We come to deeper understanding.

When you're trying to write a work of 100 or more pages, you have the danger that what you write at the start will not match what you write near the end due to the natural learning process that we would expect.

I often find myself looking at what I wrote in the past and wondering how to reconstruct the idea that drove me then.

Stereotypes and Generalization

I guess my thinking was partially triggered by a conversation in which a writer told me that a book on dissertations said that a dissertation would take something like 1047 hours of work. I forget the exact number, and I'm not going to mention the title of the book lest my comments be construed as a criticism of the book, which I've not read. But to suggest such an exact number? It seems to me that it might make sense to discuss the rough order of magnitude of the time that goes into writing a dissertation, but not to try to claim such precision. It seems an undue, or inappropriate generalization.

Generalization is a very useful tool. But we want to be careful of it. Stereotypes are a form of generalization. There's nothing wrong with stereotypes, in themselves, but due caution is necessary in their use.

One writer I was talking with suggested that quantitative studies take less time than qualitative studies, and that therefore it would be easier to write a quantitative study. It is in reasoning like this that the use of generalizations goes wrong. Just because one can make a general statement about a group, doesn't mean that statement holds for all members of the group. It's like saying that because men are taller than women (a safe, and easily verifiable generalization), all men are taller than all women, which is, of course, absolute hooey. I meet plenty of women taller than I. I meet more women who are shorter than I, but that doesn't make the opposite true.

One reason to be careful of generalization is that if you use it poorly in academic writing, you open yourself to ridicule. I worked with a writer once who was writing a dissertation that explicitly argued against "essentialism" in reasoning, and against racism, yet the writer consistently made generalizations about race--in direct contradiction to the anti-essentialist positions she claimed to hold. It was a frustrating experience because much of the writing and thinking in the work would have been sound, but for the use of essentialist reasoning and the careless use of generalization--"all black people experience X," she would write, "and all white people experience Y."

But more importantly than looking like a fool for expressing oneself in crude generalizations, one can benefit by thinking things through properly.

I heard the "quantitative studies are easier" from one writer who had previously almost completely planned a good deal of her study. She had planned a qualitative study, and she had worked out many details related to structure of the study and recruitment. Then, on hearing from a friend that quantitative studies are shorter, she abandoned all the work she had previously done and spent several weeks just trying to orient herself to a new project. I don't know how much shorter the quantitative study was compared to the qualitative study, but I do know that a significant amount of past effort was scrapped and due to that decision, a significant amount of new effort was necessary. Now, if we know that a dissertation takes 1047 hours of work ;-), on average, what's the difference in the amount of work necessary to do the quantitative vs. the qualitative? 10% (or 100 hours)? or is it 5%? or 25%? The crude generalization doesn't really help us. And again, we might also think about the dissertation not in hours of work, but in weeks or months elapsed from start to finish. 1000 hours is 50 20-hour weeks. If the writer lost four or more weeks (which she did) switching topics, then her time cost was about 10% of a 50-week project, or 5% of a 100-week project. So for that writer, the generalization would only pay off in the case of her study being more than 5% shorter.

Anyway, this isn't really so much about writing, I suppose, as it is about logic. My basic point is that, while generalization can be useful in many ways, one must always check whether the generalization is apt to the specific case.

To put this in slightly different terms, two forms of logical inference depend on generalization. These two forms are very useful, each in their own way, but they are not logically certain in the same way that logical deduction is. The two logical forms: induction and abduction.

Counting

What Counts?
I'm thinking, in this case, particularly about what to count as "work accomplished", but it's a very interesting general question as well, because deciding "what counts" is a crucial decision.

Consider, for example, the United States Constitution in one of its darker moments:
Article 1, Section 2, paragraph 3: "Representatives...shall be apportioned among the several States...according to their respective numbers, which shall be determined by adding to the whole Number of free persons,...and excluding Indians not taxed, three fifths of all other persons."
Indians not taxed counted not at all in determining representation of the new federal government. "Other persons" counted 60% in determining numbers of representatives, but of course those other persons didn't get 60% of a vote, being slaves.

It's nice and dandy to think of numbers as objective. It's one of the lovely myths of science. But what we choose to count is determined by how we see the world. What gets counted depends on our subjective decisions concerning what to count. This is true whether we are a physical scientist looking data sets and trying to decide whether some data can be considered outliers, or whether we are social scientist trying to decide whether certain data are coded as one thing or as another, or whether we are a politician trying to decide who to count as eligible with respect to some policy. It is inevitable that a value-laden subjective determination is made considering what counts.

While I mention this as a general principle that all academics ought to be aware of, my real concern here is in thinking about writers and how writers can sabotage themselves. I had a writer lament to me the other day "I didn't get much done; I only wrote abut 2000 words." When I wrote back "That's great 2000 words is a considerable piece of work and if you keep up a pace like that you'll finish in no time," I got a response "Actually I only wrote about 1000 words."

Well, we all have to figure out what to count. It's easy to count the words that we have written: lots of word-processing software will do it for us. It's not so easy to count if we start saying "well, these words do count, but those don't." But the determination is ours: we have to make the subjective decision of what counts before we can start enumerating.

But I wasn't so much concerned with counting words, as I was with counting effort and counting progress. The effort we put in, and the progress we make are not perfectly measured in the number of words we write. I think that writers with writer's block and related problems often suffer from not being willing or able to count what they did as actual work or actual progress.

It's important to learn to celebrate the fruits of our efforts, and even more important to learn to count the fruits as actual fruits. If we spend a day of hard work, thinking through difficult problems and then say to ourselves "I got nothing done because I didn't write enough words," we are counting our effort as worthless. And what kind of emotional state does such a method of counting lead to? It leads to depression, one can easily imagine.

Dr. David Burns, M.D., author of the mass-market book on CBT titled Feeling Good, argues that there are "ten cognitive distortions that form the basis of all your depressions" (p.32). Number four on his list of cognitive distortions is "Disqualifying the Positive: You reject positive experiences by insisting they 'don't count' for some reason or other" (p.42). While I have reservations about any mass-market book on psychology, and don't know that I would accept Burns' contention that all depression stems from his ten cognitive distortions, I do believe that if we engage in his cognitive distortions we are creating a strong negative emotional state. If we reject our efforts as not counting, then each day that we make an effort, and each day we discount the effort of the day, we add to our negative feelings about ourselves and about our project.

It seems, therefore, important to be able to celebrate the effort, and to celebrate the actual progress that we do make, even if it isn't as much as we would have hoped. And in that celebration we definitely don't want to focus on the idea that it wasn't as much as we hoped.

In the long-term practice of writing it is crucial to be able to have days where the productivity seems low, and not berate ourselves for those days. Writing, like many practices, is uneven--some days go well, some go badly; sometimes we make a lot of progress in an easy, measurable sense. Sometimes we make progress by having some sort of epiphany--even sometimes when that epiphany leads us to want to throw away some old writing that we had previously intended to use. Writing is about creating a working whole: a complete, coherent written work. Some of the progress necessary in that endeavor will involve re-arranging ideas we had earlier in the process before we knew what we have learned during the process.

Finally, I want to note that yes, sometimes we get nothing done. Some days we don't try. Some days we may sit down and write nothing, or write a load of tripe that doesn't contribute to the project. It's okay to admit that you had an unproductive day. But it seems to me superior to try to focus--everyday--on the positive accomplishments, and to remember to count them and celebrate them. That whole load of tripe?: well at least you learned that that wasn't what your dissertation needed. Deciding what to count is a practice in itself; it's nice when we can get the practice to support us.

Wabi-Sabi and Silver Linings

Wabi-Sabi is a general philosophy associated with an aesthetic which, according to Wikipedia, "is sometimes described as one of beauty that is 'imperfect, impermanent, and incomplete' (according to Leonard Koren in his book Wabi-Sabi: for Artists, Designers, Poets and Philosophers)."

As a writer and philosopher, I cannot help but look at this aesthetic except as an extension of a more general philosophy (partly because the relationship between the Modernist aesthetic and philosophical positions--which are, after all, reflections of a general way of looking at the world--was an issue I considered at length in my dissertation)--please excuse the long digression--as I was saying Wabi-Sabi, as a philosophy, suits much of what I am see in the world
around and in the discourse of philosophy. In particular, notions of imperfection and incompleteness are of particular interest with respect to matters of logic, such as the ideas brought up by, among other things, Goedel's proof of the incompleteness of arithmetic (which has been interestingly and approachably covered in Hofstadter's "Goedel, Escher, Bach").

But I digress--What seems important to me, with respect to the problems facing the academic writer, is that our logic, our reasoning, and our work seem--from a logical perspective--to be fraught with imperfections completely independent of how hard we work on the problem. This is a very important logical issue for writers to recognize--especially if they're hung up on perfectionism: if it can't be perfect, then does that change how you react to it?

Beyond that, though, we see in Wabi-Sabi an aesthetic that valorizes the imperfection. And this aesthetic principle is also translatable to the idea of building an academic argument: academic arguments cannot be logically perfect. Wabi-Sabi allows us to see the beauty of these imperfections--which may help with our writing a limitations section in the results, or a representation of opposing views in the literature review. There is beauty (and strength) in an argument that recognizes its own weaknesses.

Seeing imperfection as something beautiful, or at least as part of a beautiful thing, is a matter of perspective and focus. It is something that we have some control over. And this is what brings me to silver linings: every cloud has a silver lining, so the saying goes, and Wabi-Sabi says that everything beautiful has an imperfection. We can see the beauty if we look for it--the "sri vision" that I wrote about a few days ago--or we can focus our attention on the things that are ugly and imperfect, and on how that ugliness and imperfection are problems.

Writer's block, and dissatisfaction with one's own work, often rely on our ability to focus on the dark cloud, or our ability to see the imperfection as detracting from our work.

Rules and principles; Structure and audience

I try to rely on principles rather than rules. To me the distinction depends on the difference between a goal I'm trying to achieve and a clearly defined prescription for behavior. This is something of a situationalist perspective: a principle guides, but does not bind, for the boundary cases where the proper path is not clear. By contrast a rule is a rule; it is to be followed.

As example we might contrast the Judeo-Christian rule: "Thou shalt not kill" with the principle (Buddhist, perhaps) of preserving life. The rule is clear cut: but what do you do in the rare (but much discussed) situation where your ability to take the life of one person will save the lives of many others? The rule is simple, clear cut. It does, however, put aside the difficult conflicting values in the problem. The principle is conflicted; judgment is left in the hands of the individual. It is more difficult to apply a principle in this kind of case than a rule--or at least the decision is more difficult.

Yesterday I was writing about structure and the structure of the Introduction. I got a question about the structure that said "...are we expected to...". I know I'm kind of misreading this, because the questioner, I think, is not looking at me as an authority figure who sets expectations that must be met (I hope). But it made me think about structure, formulas and why we use structures and formulas.

Part of what I wanted to show, in addition to suggesting a specific sort of structure, was that structure is motivated. The formula is not there simply as a formalism to be followed, but rather the formula is there because the writer has some purposes, and the formula helps the writer accomplish that purpose.

One purpose that all writers share is the desire to get the reader engaged. Hence there is an introduction of some sort. In fiction, writers introduce there work in ways that set up tension, or that address the reader; the reader of fiction has certain expectations, and the writer is going to play with those expectations. In academic writing the introduction is done differently: the academic writer wants to put all the cards on the table--or at least the most important one; he academic writer draws the academic reader in by convincing the reader that the work addresses a significant issue, and that the work is done well. What happens if the academic reader thinks the study deals with an insignificant issue, or the research was executed in a such a shoddy manner as to be worthless?

The point of structural formulas is that they help us engage the reader. The models have been used because they work, but they have also been used because they suit the writer's purpose. If you can see structure as a tool to help you reach the reader and convince the reader of the quality of your work, then you will deal with structural formulas in a different fashion: you will see them as suggestions that may help you act in accordance with a guiding principle (like the desire to engage the reader), rather than onerous prescriptions.

Uncertainty

The other day my yoga teacher was talking about the importance of the ability to embrace uncertainty. She mentioned to me a book by Pema Chodron called Comfortable with Uncertainty. I've not read the book, but if you don't write down your references when you remember them, you forget them (hard to believe, I know!).

Anyway, this is a principle that I think is useful on many levels. (As, indeed, are many ideas--which was almost the subject of this post--if I hadn't written about uncertainty.)

Logically speaking, we are faced with limits to our certainty. The work of David Hume, especially his Treatise of Human Nature, clearly framed the limits of our logical certainty in many different ways. On a very basic level Hume argued "that the supposition, that the future resembles the past, is not founded on arguments of any kind, but is deriv'd entirely from habit, by which we are determin'd to expect for the future the same train of objects, to which we have been accustom'd" (Treatise, Book I, Part III, Section XII, italics are Hume's). Essentially he is saying that there is no logical argument that proves that the future will resemble the past--logical in the sense of a priori logic--something that can be proved from basic premises. Yes, he says, we expect the future to resemble the past, because we have seen patterns repeat in the past, but this expectation is not certain--it is only probable (part III of book I is titled "Of knowledge and probability"). Later in the same section he says "even after the observation of the frequent or constant conjunction of objects, we have no reason to draw any inference concerning any object beyond those of which we have experience" (the italics, again, are Hume's).

This general logical principle, sometimes called "Hume's Problem," is also called the problem of induction. It is still debated; no response to Hume has swept away his claims. The most notable response was that of Karl Popper in The Logic of Scientific Discovery. Popper's response was to suggest that we cannot prove the truth of a claim through induction, but that we can prove the falsity of a claim, and therefore science can proceed using the hypotheses that have survived the most tests. But this too, one must note, is logically uncertain: we have certainty (perhaps) that we've rejected bad theories, but we have no certainty that the theory we have not yet rejected is actually good.

Well, the litany of sources of uncertainty in logic is long, and I don't want to go into it here. There are similar ideas outside the realm of Western Philosophy: is there not uncertainty in "The Tao that can be told of is not the absolute Tao."?

I think there are benefits in embracing uncertainty. Especially in logical debate: it's an escape hatch--if we know uncertainty exists, we can use that to justify some degree of imperfection in our argument: we simply cannot know everything; we must somewhere start with something unproven.

We embrace the uncertainty. Of course, we also need to act decisively: so we balance the uncertainty somehow. Ultimately we chose what we believe is important and act on that--if we cannot make such a choice then we're paralyzed.

Of course lots of people go through life thinking that they're certain about everything, but it's hard to get away with that as an academic--at least we're taught to question. So for the academic--or for any philosophical, thinking person--we look at the uncertainties that face us and choose among them the ones that seem best.
If we understand that we are choosing from a place of logical uncertainty, we have to embrace our beliefs for another reason. There's a certain freedom to believing in an idea and knowing that you may be wrong--there's a danger, but also a freedom.

Construction of Meaning and Imagination

I was just thinking about phlogiston and the aether and vacuum..among other ideas.
The imagination that was required to come up with these ideas is, to me, stunning.

If what we do is make up stories as a natural part of how we understand the world, then coming up with ideas like these seems to me beyond the imaginative efforts of a Tolkein or an Asimov.

Some ideas seem like they would come up logically eventually: I can see how an idea like infinity would arise through some logical debate.

Or evolution: that seems not too impossible: one sees groups of similar creatures and tells a story of how they all came from a similar source--it is especially plausible if you already know of breeding of animals and how traits can be strengthened from generation to generation (and I think we can say safely that 19th century England knew about animal breeding). It would take some imagination to come up with the idea of evolution, but the elements are there in experience.

But what about vacuum or the aether? These are ideas that I can hardly even attempt to explain. They both play key roles in various stories about the very nature of existence. But they are so far abstracted from experience that my imagination does not take me to such places easily.

Phlogiston is another one: the substance that is contained in elements that burned. Somehow this works with the four classical elements--earth, air, water, and fire--but how is phlogiston different from fire? I don't know. I haven't tried to explain it. I have a story that explains combustion--something about release of energy from carbon bonds and recombination with oxygen--I don't think about combustion much, so I don't need a very detailed story. But think about how the mind is stretching when it tries to explain fire by adding a new element to a list of elements that already has "fire" as one of the elements.

Hopefully we don't need to use quite so much imagination in the construction of our meaning for our own work. Much easier to imagine a complete world filled with creatures that resemble humans, and also other mythical creatures, than to imagine a completely new element. Hopefully it's easier still to imagine significance for your own work.

I think perhaps one of the greatest battles that I fought was with the internal voice that said to me "no one is going to care about this abstruse philosophical question you're studying, even if it is important." Partly I battled the voice by telling myself that the idea mattered even if it didn't reach anyone else (an odd position for one who believes that knowledge is fundamentally instrumental, but who ever said I was consistent?). The sense that your own work is important is crucial. A great shame is that so many people start out on dissertations (or at least start graduate programs) with a sense that they are in school to help the world, and they somehow get out of touch with that initial sense of purpose. If you can reconnect with the things that are meaningful for you, and you can imagine a path by which your research can tie into the initial passion that drove you, then you can work from a place of emotional strength--one where your emotions are not conflicted (or at least not as conflicted).

I also gained a measure of strength by reframing the project and finding meaning in my ability to overcome obstacles and successfully complete a project that--by the end--had swelled into a work of over 300 pages. No one may ever read that book again (and given that I needed a proofreader, I'm not sure that bothers me), but that matters not at all because I finished it.

I've been thinking a lot about how the stories we tell about our lives can help or hinder us. Those stories are construction of meaning. On the simplest level this may be just a matter of what we focus on: do we focus on the good things or the bad? On what we have or what we want? This may also be a matter of the difference between constructing a story in which things are connected and a story in which things are disconnected.

And then there are the different levels of meaning that we construct. What if we are seeking the thread that ties a whole work together--a thread that we sense is there, but can't quite tease out--and while we seek that thread we are telling ourselves a story like "I'll never find the thread"? If that story about our inadequacy is dragging us down emotionally, will it cut into the hours we would have worked if we were telling ourselves some other story--like "I'm sure I'll find it if I keep working," or even "I'll keep trying to find this thread, but if I can't find it, I'll go and work on another project because I'm not letting one setback stop me"? I don't know whether it's true, but here's the story I construct: being depressed takes away energy, and so if you tell yourself you're going to fail, you'll have less energy, ergo, you'll work less and therefore have less likelihood of success.

Somehow I slipped into full self-help/power-of-positive-thinking mode. I didn't really mean to--but the power of our imaginations and our construction of meaning led me into it.

Construction of Meaning (2)

In the previous post I was considering the construction of meaning as a conscious effort. And there is no question that we need to dedicate our efforts to constructing good meaning that is useful to our work. But it is worth recognizing that this construction of meaning is something that will occur: it is how we think.

The following quotation is taken from the Preface to Mark Turner's The Literary Mind: The Origins of Thought and Language:
"The literary mind is the fundamental mind. Although cognitive science is associated with mechanical technologies like robots and computer instruments that seem unliterary, the central issues for cognitive science are in fact the issues of the literary mind.
"Story is a basic principle of mind. Most of our experience, our knowledge, and our thinking is organized as stories. The mental scope of story is magnified by projection--one story helps us make sense of another. The projection of one story onto another is parable, a basic cognitive principle that shows up everywhere,...
"Parable is the root of the human mind--of thinking, knowing, acting, creating, and plausibly even of speaking."
The italics are Turner's; the boldface is my emphasis. I happen to find the book convincing, but then it fits well within the rubric of philosophy that I adopted studying with George Lakoff and Eve Sweetser at Berkeley. Lakoff and Turner co-wrote a book (More Than Cool Reason), so it is not surprising that the views fit together.
Whether you accept the premise or not is a matter of your research and study. But if we do accept this premise, what does it mean in terms of creating meaning? On one level it means that when faced with a phenomenon, we will create a story to explain it. Whether that story relies on God, or some group of gods, or simple random mechanical fate, or some highly detailed chemical process, it is still a story. How do we explain wine? We could explain it as the hand of a god touching the juice, or we could explain it in terms of fermentation processes that can be explained in great detail in chemical terms. How do we explain human creativity? Is that being touched by a god, or muse, or is it having a certain set of genes and a certain history? Or is it the effect of some unnatural stimulant?

That's really what our knowledge is: a bunch of stories about how things used to work, and how we expect them to work in the future. What is quantum physics but an attempt to make stories that explain incredibly detailed phenomena? When Newton proposed his mechanics, we had a detailed story of how the world worked. Einstein's relativity changed that story, but matched it fairly well in many respects. Einstein's relativity and the development of atomic theory began to tell us stories about atoms. I still remember some of those stories from high school science: when the salt (NaCl) is put into the water, the Na and Cl separate into ions. That's high school chemistry. But it's nothing more than a story.

We will construct meaning automatically and unconsciously. But we should also seek to construct meaning consciously. It is a place for the imagination. One wants to consider even those things that seem unlikely, and then test them. Once upon a time it seemed unlikely to most people that the earth revolved around the sun. Sherlock Holmes declared it impossible that anyone had gone through the door, but obviously for H.G. Wells it would not be impossible for a person to walk down a passage unobserved, and any number of technological possibilities could explain a door being opened without a key. As academics, of course, we don't want to tell stories that are so far from the realm of the discourse that we wouldn't be accepted, but we do want to use our imaginations to think about the different stories that are consistent with the questions we asked and the results we received. And for that matter, we just want to be able to imagine different stories that could explain a phenomenon of interest, because that consideration of different possibilities is the place where we generate the hypotheses that we can test.

Construction of Meaning

The answer may just leap out at us from the tables and graphs of evidence. We may find it somewhere in the pages of transcripts.

But whether you believe that meaning is something that exists out there in the world, or whether you believe that meaning is something that only exists when there is a thinking being thinking about it, meaning is something that will only emerge through a constructive process.
If a pattern is not immediately apparent in a set of data, that doesn't mean that the pattern is not there. The pattern may only become visible through a process of rearranging and reviewing the data many different times and many different ways. And this process of rearranging and reviewing the data requires mental effort to create different possible explanations.

Sherlock Holmes said to Watson: "How often have I said to you that when you have eliminated the impossible whatever remains, HOWEVER IMPROBABLE, must be the truth?" What is hidden here is that the construction of the improbable theory is no simple task. Holmes continues: "We know that he did not come through the door, the window, or the chimney. We also know that he could not have been concealed in the room, as there is no concealment possible. Whence, then, did he come?" Whence the other alternatives? We must look at the world--look at the crime scene, if you will, and look for other possibilities. These do not simply jump out at us in an obvious fashion--we have to seek explanations--stories that explain the data that we see. That explanation may be partially generated through looking at other sources, but there is a large element of this that is the individual imagination--the attempt to construct a hypothesis that fits the data at hand.

To some extent we can maybe see how this is a sort of gestalt experience: when we see four dots arranged in a square, we can see the whole square--we see the dots as related. With our data, the gestalt image may not jump out until we have created the right framework to appear: we must do constructive work in our minds just to create situations in which gestalts can appear.

But we may also want to see this as a process of creating a fiction of sorts. We look at our work as a whole as telling a coherent story--or at least that's a common expectation for a dissertation. If we practice the creation of different fictions--of alternative explanations or alternate hypotheses--we may find that some of these fictions will serve us well when we find that our data works with the hypothesis and the hypothesis has useful suggestions for future research and theoretical development.

Beyond Reason

I was wondering what to write about tonight.
Lacking any particular subject, I decided to write about an old favorite of mine, an essay by Jorge Luis Borges titled "Avatars of the Tortoise." The whole essay is maybe six pages long. I have it in a collection titled Labyrinths, translated by James E. Irby.

Many writers get caught in a sort of perfectionist trap: "I don't know enough," they cry. And then they flee to the library, or to the safety of someone else's writing. It's easy to feel like we don't know enough. There will always be something new to learn. As writers and researchers we need to be able to acknowledge this, so that instead of looking for perfect, complete explanations, we can finish our work.

"There is a concept which corrupts and upsets all others," opens the essay. "I refer not to Evil, whose limited realm is that of ethics; I refer to the infinite." The famed paradox of Zeno of Elea of Achilles and the Tortoise provides the basis for the essay's name: Borges looks at various manifestations of paradoxes caused by the concept of infinity.

Of particular interest to academic writers is Borges's attention to Agrippa the skeptic, who "denies that anything can be proven, since every proof requires a previous proof," and "Sextus Empiricus [, who] argues in a parallel manner that definitions are in vain, since one will have to define each of the words used and then define the definition."
What does this say to the academic writer about wanting complete knowledge? It suggests that there is no utter certainty. We must start from something else. Bertrand Russell, recognizing this problem in his Philosophy of Logical Atomism says that we need to start our arguments from somewhere, and as we have no access to truth, we must start from something that is "undeniable." But, of course, in this day and age on what point of interest can we find no debate?

We must choose some place to start our argument. Ideally that is what we can use the literature review to do: we can position our fundamental premises in terms of the discourse of our field. What it means is that we make a choice of where to start rather than having some logical rule that determines where to start. And what this means is that if you, the author, face your blank page and say "I don't have enough knowledge to start," it is worth sitting back a moment and asking yourself "can the material I already have provide a strong foundation for my first draft?" If the answer is yes, start writing. The sooner you start writing, the sooner you will finish.