by Judith Curry
The savage budgetary pressures we will have at least into the 21st Century are part of the reason why we must attempt to develop a fresh contract between science and government. – Donald Stokes
The linear model of science to policy is summarized on the blog Shaping Science, illustrated by this figure:
Of the numerous alternatives/critiques that I’ve seen, I think that Donald Stokes’ Pasteur’s quadrant is the most provocative in suggesting a new model that seems broadly applicable across the different sciences. Stokes has written a book entitled Pasteur’s Quadrant: Basic Science and Technological Innovation. The punchline of the book is encapsulated in this article by Stokes [link].
A great deal of the vision of the nature of basic science and its relationship to technological innovation is contained in two aphorisms in the Bush report. Each was cast in the form of a statement about basic research – a term that was given currency by the Bush report.
The first of those aphorisms is that basic science is performed without thought of practical ends. Bush made it quite clear that the defining characteristic of basic research is its attempt to find more general physical and natural laws to push back the frontiers of fundamental understanding.
What that aphorism came to mean, instead, was that there is an inherent tension between the drive toward fundamental understanding on the one hand, considerations of use on the other, and by extension, a radical separation between the categories of basic and applied science. Bush went on to endorse a kind of Gresham’s Law in which an attempt to mix the applied and pure in research was sure to result in the applied driving out the pure.
Having written that canon of basic research, Bush wrote down a second. It was that basic research is the pacemaker of technological improvement. If you insulate basic science from short-circuiting by premature thoughts of practical use, it will turn out to be a remote but powerful dynamo of technological innovation – the advances of basic science will be converted into technology by the processes of technology transfer, moving from basic to applied research, to development, to production or operations, according to whether the innovation is a new product or a process.
It is interesting to note that both those canons came to be captured by very simple, one dimensional graphics. The first was represented by the ever-popular idea of a spectrum of research from basic to applied. The dynamic version, the second canon of basic research, was represented by the equally popular idea of the linear model that moves from basic research to applied research via the processes of technology transfer. [The] third element in Bush’s argument is the notion that the nation will recapture the technological benefit of its investment in basic science.
Admiring as we all can be of the success of the paradigm view set out in Science: The Endless Frontier and its ushering in of the Golden Age of American science, the incompleteness of this view of the nature of basic science and its relationship to technological innovation has been increasingly clear.
Let’s first of all return to the first of Bush’s canons, that basic research is performed without thought of practical use. The rise of microbiology in the late 19th Century is a conspicuous example of the development of a whole new branch of inquiry because of considerations of use, not only the quest of fundamental understanding.
And that example is not a solitary one. Lord Kelvin’s view of physics was profoundly industrial and inspired in substantial part by the needs of empire. The work of the synthetic organic chemists over the turn of the century as they laid the basis of the chemical dye industry, and later, pharmaceuticals, was equally a melding of those two motives. Keynes sought an understanding of economies and their dynamics at the most fundamental level, but he sought that to lift the grinding misery of depression.
I have created a little bit of graphic reasoning to try to move one step in a more realistic direction. This array presents a new model of scientific research, which provides a more accurate depiction than Bush’s linear model. I call it “Pasteur’s Quadrant.”
Research is inspired by:
- Considerations of use? No Yes
- Quest for fundamental understanding? No Yes
[This represents] a two-dimensional conceptual plane, with the vertical dimension representing the degree to which a given body of research is motivated by the quest of fundamental understanding, and the horizontal dimension the extent to which it’s motivated by considerations of use.
Take a moment to consider the quadrants that are presented. The one at the upper left is for the pure voyages of discovery, the voyages of Newton. Let me call it Bohr’s Quadrant, since there were no immediate considerations of use in mind as Niels Bohr groped toward an adequate model of the structure of the atom; although note that when he found it, his ideas remade the world.
The quadrant at the lower right might be called Edison’s Quadrant since Edison never allowed himself or those working with him in Menlo Park five minutes to consider the underlying side of the significance of what they were discovering in their headlong rush toward commercial illumination.
But there certainly is “Pasteur’s Quadrant,” for work that is directly influenced in its course both by the quest of fundamental understanding and the quest of applied use – the sort of quadrant that supplies a home for what Gerald Holton has called, “work that locates the center of research in an area of basic scientific ignorance that lies at the heart of a social problem.”
Indeed, we’re going into the 21st Century with two closely interwoven trends: one, which is commonplace, is that more and more technology will be science-based. The other, which is still very widely under-appreciated, is that more and more science will be technology-based in just the sense that I’ve expressed and not merely in the sense of instrumentation, which has been important in Western science at least since the time of Galileo.
If we were to present a rival image for the one-dimensional linear model, it would be much more like the rise in fundamental scientific understanding and the rise in technological know-how as two loosely coupled trajectories. They are loosely coupled because the increase in scientific understanding is, at times, the result of pure science with very little intervention from technology, while the increase in technological capacity is often the result of engineering, design, or tinkering at the bench, in which there is no intervention by fresh advances of fundamental science. But at times, each of those trajectories profoundly influences the other. The influence can go in either direction with use-inspired basic research often cast in the linking role.
If the society was told that a heavy investment in pure science would produce the technology to handle a full spectrum of society’s needs, it was bound several decades later to stop and say, “Now just a moment, we have some unmet technological needs. Indeed, we have some that have been created by the technology spun off of your science – the deal is off.”
It must make the case for continued societal investment in realistic terms of the problem-solving capacity of science, terms that command the support and enthusiasm of the policy community and the country behind it.
JC comments: There is a growing trend in U.S. science to focus on ‘use-inspired’ basic research, e.g. Pasteur’s quadrant. This is evident in NSF proposal requirements, which require addressing ‘broader impacts‘ that includes benefits to society. More explicitly, a recent call for NSF SEES proposals stated:
In order to enhance the broader applicability and transferability of this research, linkages within and between universities; research centers; state, local, and tribal governments; community organizations; federal agencies and national labs; and private organizations are encouraged. Engaging partners and stakeholders in the early phases of problem identification and definition, and iterative subsequent engagement can lead to novel paths of scientific inquiry and facilitate application of new scientific insights. Proponents are also encouraged to look for synergies with existing activities, facilities, networks, and centers.
With regards to climate science, the concern that I have is that there is too much research in the lower half of Stokes’ diagram, scoring low on making advances to fundamental understanding. Applied research that is useful and used is a good thing, but at the end of the day I don’t see all that much applied climate research actually getting used by decision makers. The primary problem being that there is too much focus on the climate models, and the climate models are not yet up to the task.
This leaves us with the unnamed 4th quadrant, which is often characterized as ‘taxonomy’, i.e. research that is neither useful nor contributes to fundamental understanding. Climate model taxonomy is characterized by endless analysis of IPCC climate model runs and projection of ‘dangerous impacts’ . If these are not being used by decision makers, then they are in the 4th quadrant.
More research in the upper half of the diagram, please. In the ‘use-inspired’ box is arguably climate model development research to support the IPCC. This is ok (we definitely need better climate models), but I think too much funding for this mostly ends up feeding the relatively pointless 4th quadrant research. I really like the NSF SEES model for use-inspired research, which is stimulating massively interdisciplinary research that has the potential to be useful and used, while at the same time advancing basic understanding of newly defined knowledge frontiers.
In the pure basic research box lies the really tough challenges, including solar physics, synchronized chaos, multiphase dynamics, turbulence, mixing in the deep ocean, etc. There is unfortunately far too little activity in this quadrant, and better climate models and the attendant applications do depend on this very basic research. JC note to NSF, universities, and professional societies: How to stimulate more activity in this quadrant is a key challenge for our field – too many of the ‘rewards’ are going to climate model engineering and taxonomy.