The Nature of Classification

Relationships and Kinds in the Natural Sciences

J. Wilkins,M. Ebach

• Publisher: Palgrave Macmillan
• Year: 2013
• ISBN:
  9781137318121
• Topic: Filosofia
• Subtopic: Filosofia ed etica nella scienza

Discussing the generally ignored issue of the classification of natural objects in the philosophy of science, this book focuses on knowledge and social relations, and offers a way to understand classification as a necessary aspect of doing science.

1

The Nature of Science

The dance floor of science

About thirty years ago there was much talk that geologists ought only to observe and not to theorize; and I well remember someone saying that at this rate a man might as well go into a gravel pit and count the pebbles and describe their colours. How odd it is that anyone should not see that all observations must be for or some view if it is to be of any service. [Charles Darwin¹]

... the work of theory and observation must go hand in hand, and ought to be carried on at the same time, more especially if the matter is very complicated, for there the clue of theory is necessary to direct the observer. Though a man may begin to observe without any hypothesis, he cannot continue long without seeing some general conclusion ... he is led also to the very experiments and observations that are of the greatest importance ... [and] the criteria that naturally present themselves for the trial of every hypothesis. [John Playfair²]

In this chapter we describe a way to conceptualize science as a field of possibilities from active conceptualization (theorization) to passive conceptualization (classification), and from active observation (experiment) to passive observation (pattern recognition of phenomena), setting up the scene for later chapters.

According to traditional philosophy of science, by which of course we mean what Wilkins was taught as an undergraduate,³ what science does is to develop, test, and argue over theories. Oddly, what a scientific theory consists of is rarely discussed, although there is a consensus that a theory is a formal model of a family of models with ancillary hypotheses and interpretations of some kind.⁴ In this book we shall consider “theory” to cover any abstract representation or part of such an abstract representation including models. However, the focus has been on theories at least since John Stuart Mill’s A System of Logic in 1843,⁵ especially once that work was adopted as the basis for the burgeoning analytic philosophy movement in Britain and America, and the subsequent development of logical positivism and its heirs and successors.

Positivism was a two-dimensional or linear historical progressivist view about science. Comte himself held that societies moved through the theological, the metaphysical and then the positive stages. Likewise, individual sciences were also held to develop this way. This progressivism persisted long after positivism died or transmuted into logical empiricism. Even as the Baconian idea of sciences developing from masses of naive observation into laws and theories was being abandoned, people still held that there was a constrained historical sequence for the development of sciences. For example, Thomas Kuhn’s “normal science/revolutionary science” distinction, and in particular his “evolutionary metaphor”:

Imagine an evolutionary tree representing the development of the modern scientific specialities from their common origins in, say, primitive natural philosophy and the crafts. A line drawn up that tree, never doubling back, from the trunk to the tip of some branch would trace a succession of theories related by descent. Considering any two such theories, chosen from points not too near their origin, it should be easy to design a list of criteria that would enable an uncommitted observer to distinguish the earlier from the more recent theory time after time. Among the most useful would be: accuracy of prediction, particularly of quantitative prediction; the balance between esoteric and everyday subject matter; and the number of different problems solved. – Those lists are not yet the ones required, but I have no doubt they can be completed. If they can, then scientific development is, like biological, a unidirectional and irreversible process. Later scientific theories are better than earlier ones for solving puzzles in the often quite different environments to which they are applied. That is not a relativist’s position, and it displays the sense in which I am a convinced believer in scientific progress.⁶

History moves forward. Unfortunately, this is not necessarily true of biological evolution, and there is no reason to think it is true of cultural evolution either, so why should it be true in science? Why must science follow a set trajectory? Why can scientific history be Whiggish when the rest of history cannot?⁷ The presumption here is that the history of science is constrained to develop in particular ways. This is just false.

Philosophy of science once assumed that the early stages of a scientific discipline are marked by basically wandering about observing stuff until a theory, hypothesis or law suggests itself. Then it gets tested. Let us suppose that constructing a theory is a phase of active conceptualization. We take our ideas and put them together into a coherent and explanatory structure, and having done so, we subsequently run experiments to test this and ensure that what we test is just the theory, and not confounding variables. This, very roughly, is Popperian falsification. And it is, most of the time, precisely not what most scientists do. Karl Popper and his followers were criticized for failing to deliver any vestige of a logic of discovery, despite the English title of Popper’s masterwork. In fact, discovery was regarded as accidental, if anything. The real work was in the construction and testing of hypotheses, leading to models and thence to theories.

Philosophies of science tend to distinguish between the conceptual and empirical aspects of science. We might represent this as a field of possibilities, in which one axis is conceptual development, and the other of empirical observation. Even views based upon the theory-dependence of observation make the distinction, if only to assert the priority of one over another, so let us take this as a first approximation. Conceptual tasks are themselves divided into theoretical and classification tasks, the first being a representation of phenomena, and the second supposedly a systematization of the results of the dynamics captured by the theory/model.

These two conceptual tasks are usually held in opposition, although again some subordinate the one to the other, mostly holding that theory determines the sorts of categories into which things get sorted. More rarely, holding that one’s ontology, or classification of possible types of things, determines or constrains theories. Let us visualize each task as a set of goals connected by the common feature of being conceptual, like a dumb-bell. Empirical tasks, similarly, are divided into naive observation and more informed experimental testing, which involves knowledge of the theory. So, on this view of science, the “moments” between which scientific behavior “moves” look like Figure 1.1.

The Baconian Cycle (that is, the view held by those who thought they were doing Baconian induction) is shown in Figure 1.1 as sequence B, while the Popperian Cycle is shown as sequence P (Popper dismissed classification the way Rutherford did, as mere stamp collecting). Of course, all views of science hold it to be an iterative process, so if the results are not satisfactory, a movement can be indefinitely repeated. Let us now change the metaphor to a Cartesian graph with two axes: conceptual and empirical. A simple Popperian cycle, with theory-dependence, might inscribe a quite complex trajectory. If one is trying to work an experiment, or reformulate a model, loops will occur. The permutations for an extended process can become very extensive indeed. But what happens if we allow, as we surely must, that observation can inform classification, or that it can even, as Francis Bacon had it, inform a theory or a model? Let’s fill in all the blanks (Figure 1.2).

Figure 1.1 The Baconian (B) and Popperian (P) Cycles

Figure 1.2 The twelve movements and four moments of scientific processes

This characterizes all possible movements for any autonomous scientific process, from within the mental processes of a researcher, to the work of a research group, to a general research program, to the activity of an entire discipline. The influences from one scientific task (“moment”) to another are represented as outputs feeding into inputs (“movements”) (Table 1.1). The processes within the moments include data analysis and other transformations local to that aspect of science. Experimental techniques, classification sequencing, observational processes and technologies, and theory-building are all aspects of their respective black boxes (shown above as white circles).

On the B and P cycle and traditional post-Popperian views, we have basically ignored half or more of what it is that science does! There are twelve possible pathways for the methodological influence of one task type to lead to results in another, plus the four pathways of self-correction and revision, by, for example, taking observations again to ensure precision and accuracy. It seems quite feasible to think both that observation might be influenced by theoretical assumptions and expectations, and that we might develop theory-free classifications on the basis of our experience and the classification systems, neural and analytic, that we apply to such data.

The combinatorial possibilities for any realistic sequence of research are immense, and if we add the possibility that these moves might occur in parallel, and that the moves might be distributed (research groups typically have many brains to do their work on, especially the more pliable brains of doctoral and postdoctoral students), we begin to have an extremely complex dynamic system. We leave it as an exercise to the reader to work out how complex.

It doesn’t end there. Many recent treatments of science claim that the history of a science is not simply determined by its internal methodological workings (internalism) but that even the very facts with which it deals, no less than the ways experiments are run, theories are constructed, and classifications developed, is a process influenced entirely or in part by its social and political milieu, for example in “actor-network theory”.⁸ Even if we are able to hold that presumption to a minimum, every discipline, research program, or laboratory is influenced at some or each point by external factors such as funding, engineering and technological resources and equipment, and other disciplines, and this must be accommodated in a realistic view of science.

Table 1.1 Moments of scientific activity

The introduction of computers is a case in point; with effects of all three kinds – you have to pay for the hardware, the programmers...