Updating your model as a researcher

Doing research is hard work. Most people make their life easier by following a model. This model is made of a series of recipes used to carry forward research projects.

There are a few reasons why a researcher may want to update his research model:

  • you want to do research on a new topic: some of your recipes no longer apply;
  • you have new collaborators: they may not follow your rules;
  • you want to increase your long term productivity.

This winter, I updated my research model. Here are a few changes I have made:

  • I relaxed my focus on exploration: I used to spend months toying with random ideas with no precise purpose in mind;
  • I decided to spend more time managing my research by keeping track of precise tasks I need to accomplish;
  • I setup stronger filters: anything that is not closely related to my may research theme is ignored with higher probability than ever.

I did not follow through entirely on my new model. For example, I cannot resist exploring random research ideas. However, my focus has definitively become much narrower.

In a sense, this is a step backward. Indeed, as a Ph.D. student I used to focus on the subject of my thesis at the exclusion of everything else. After my Ph.D. was finished, I started learning about entirely different fields. For example, I know a thing or two about geophysics or image processing, whereas I completed a somewhat theoretical thesis on Wavelets. Now? I work on databases.

However, exploratory research is expensive. Yes, I have learned that I can pick any topic at random and eventually make a small contribution, but the effort is considerable. However, carrying several unrelated research issues is difficult for another reason, beyond just the obvious cost of becoming familiar with a new field. The problem is that you cannot maintain alive your different projects if you have too many and they are too unrelated. Hence, as you open a new front, you drop another. After several years of this process, you have proven that you can learn fast and be creative, but you are still not standing on firm ground. Things do not become easier as time passes.

Hence, I now spend a lot of time choosing which battles I am going to ignore. Am I more productive? Hard to tell. The catch is that, as a researcher, it is very difficult to establish solid grounding since you are constantly picking at it yourself. However, I feel less overwhelmed than I did a few years ago.

4 thoughts on “Updating your model as a researcher”

  1. I imagine that, by choosing your battles more carefully, you are rationally avoiding risk. Given that you are one researcher with some fraction of a lifetime of work ahead of you, this seems like a good strategy for maximizing the probability of worthwhile output.

    It is not intuitively clear to me that by focusing more you lower the risk. The opposite might be true (see my previous post on encouraging diversity).

    If you were managing or funding a large team of researchers, I imagine that you’d diversify more broadly. Indeed, I’d hope that the organizations funding your work are taking such a strategy.

    I used to be a researcher for the National Research Council of Canada, and in the IT institute, they kept asking us to collectively focus on a few things. They hated to have a broad range of research projects, and they wanted people to collaborate more. I spent a great deal of time trying to make large projects happen. Funding agencies tend to try to identify priorities and fund these above all else in order to get researchers to collectively focus on a few things.

  2. I imagine that, by choosing your battles more carefully, you are rationally avoiding risk. Given that you are one researcher with some fraction of a lifetime of work ahead of you, this seems like a good strategy for maximizing the probability of worthwhile output.

    If you were managing or funding a large team of researchers, I imagine that you’d diversify more broadly. Indeed, I’d hope that the organizations funding your work are taking such a strategy.

  3. Man’s discoveries about the world around him, put into effect, have created that vast structure of knowledge that we call science. We take scientific methods as for granted today. Scarcely anything we do or anything we use to make life easy and comfortable is unaffected by science.

    Scientific research is looked upon as a synonymous with progress, and without progress the elaborate sytucture of modern life will collapse. Our standard of living depends on science to find out new ways of using the resources we have to find and to find new producrs among the raw materials. Science may even decide the political future of man.

    It has often been supposed, that the man of science is a philosopher. Why then should is not be the right thing for the chemist to let the philosopher do the plilosohhizing? At a time like the present, when experience forces us to seek for a newer and more solid foundations say of chemistry, the chemist then can no simply surrender to the philosopher the critical contemplation of the theoretical models and foundations, for he himself knows the facts best. In looking for a new model he must try to make clear in his own mind just how far the concepts which he uses are experimentally justified though experiment.

    The scientific mind is a refinement of every day thinking. The researcher cannot proceed without considering critically a much more difficult problem, the problem of analyzing the nature of everyday thinking.

    On the stage of our subconscious mind appear in colorful succession sence experiences, memory pictures of them, representations and feelings to understand these connections between them.

    So we shall call models such concepts which are directly and intuitevely connected with typical complexes of sence experiences. All other notions are – from chemical point of view possessed of meaning, as long as as they are connected by logical links and mechanisms with the model. These mechanisms are partially definitions of the model and statements derived logically from them and partially mechanisms not derivable from the definitions, which express at least indirect relation between model, sence experiences and experiment.

  4. Diversity is a great strategy when you have enough money to bet on multiple horses. But if you have to spread yourself so thin that you are under-investing in all of the projects you pursue, then you just lose. And, as you point out, there’s a significant cost of entry to do research in a new field. If you could quantify all of those costs and risk-return trade-offs, you could derive an optimal strategy. šŸ™‚

    As for the funding agencies, I suspect that their preference for focus on a narrow range of projects is a mistake, but I admit I don’t have the data to back up my conjecture.

Leave a Reply

Your email address will not be published. Required fields are marked *