Why integrative pluralism

From the Publisher via CrossRef no proxy link. Configure custom resolver. The Structure of Scientific Revolutions. The Division of Cognitive Labor. Philip Kitcher - - Journal of Philosophy 87 1 The Disunities of the Sciences. Ingo Brigandt - - Erkenntnis 73 3 Chirimuuta - - Synthese 2 Elisabeth A.

Scientific Pluralism. Stephen H. Kellert , Helen E. Kenneth Waters eds. Galison and D. Fewell, J. Feyerabend, P.

Hacking, I. Kauffman S. Kitcher, P. Kuhn, T. Lakatos, I. Worrall and G. Levins, R. Mayr, E. Mitchell, S. Weingart, S. Mitchell, P. Richerson and S. Murray, J. Oster, G. Page Jr. Fine, M. Forbes and L. Reeve, H. Robinson, G. Breed and R. Seeley, T. Mitchell argues that all laws are in some sense contingent, but this point seems not to address these questions so much as set them to one side.

Counting this among the laws of nature seems, at the very least, to be counterintuitive. And, perhaps we should not set our intuitions aside so swiftly. Pragmatist theories of explanation have taught us well that whether or not a statement explains is a matter of context; or, what will count as a good answer to some question depends upon what sorts of contrast classes are presupposed.

And, Mitchell is correct that generalizations with different degrees of contingency, strength, or abstraction are more or less useful in different scientific contexts. However, these observations seem to pass over the hard problem of scientific explanation. What are scientific explanations for? How does the answer to this question vary in different scientific contexts? Do all scientific explanations require laws? Do they require laws at all? Her pragmatism, while very sensible, seems to favor pluralistic inclusion over widening the domain of philosophical questions even further.

However, perhaps this gives too much ground to Smart and Hempel. Why does Mitchell want to save the concept of law? More often than not, biologists construct a model or narrative and argue by appealing to several independent lines of evidence that this model or narrative may account for the phenomena.

Further, it is not clear that all biological explanations are necessarily causal explanations. Are there dependency relations that are not causal but nonetheless explanatory? When and how does something count as a causal explanation?

Are there population level causes? Even those most sympathetic to the project e. They argued that there needed to be complex bridge principles connecting higher and lower level sciences. There is a standard objection to this argument that Mitchell raises herself p. Whether or not reductionism is in fact a good way of characterizing science, the question is whether in principle reduction is possible. This argument leads to the following questions.

What kind of features does she have in mind? When are these features robust, such that no even in principle micro-level explanation might supplant them? While some scientists may restrict their interests to a specific level only, this is not necessarily the case. Pluralism better describes the causal models that, by modeling the contribution of individual causes, necessarily abstract away the operation of other compounding factors.

By so doing, they can make no incompatible claim about the operation of the ignored causes. Once this structure of causal models is recognized, one may understand why competitive interactions arise within a level e.

However, the model must be distinguished from its application. In application, one can immediately see that causal models that provide answers at different levels are indeed related. Thus, although pluralism is to be defended, it is not the pluralism of questions and the consequent independence of answers, but rather a plu-ralism of models of causal processes that may describe contributing factors in a given explanatory situation.

N ot all explanations are equally good. Hence, to defend a strategy of pluralism for causal models and criticism of explanatory applications of those models requires a further account of how idealized models are to be integrated into explaining concrete, nonideal cases. I have argued elsewhere that the dual complexity of the phenomena studied by scientists and the diverse interests and pragmatic constraints on the representations scientists devise to explain the phenomena conspire against simple pictures of scien-tific knowledge Mitchell, et al.

Correspondingly, the strategy for integrating diverse theories and explanations will not be algorithmic. This is evident from even a superficial investigation of how genetics and population biology are jointly modeled, or of current models of how the biochemistry of hormone production in a developing organism affects and is affected by the external environmental conditions in which the organism finds itself.

The genetics of a population will constrain the variation on which natural selection can operate, and the operation of natural selection can change the genetic constitution of the population. Complex systems, like those studied by biology, are going to harbor multiple, interacting forces at different scales, with variable temporal orders operating in diverse combinations in different particular situations.

Integration of theories and models in such cases will not be as simple or global as in the case of, say, vector addition of electromagnetic and gravitational forces in physics. The work of Michael Friedman and Philip Kitcher seems to acknowledge the persis-tence of multiple potential descriptions of individual phenomena — the pluralism side of the story — but they marry it to a unificationist goal rather than an integrationist goal.

Indeed, they argue that the unification of ever more phenomena under one theoretical schema is central to scientific explanation. Subsumption of diverse phenomena by ap-peal to increased generality and abstraction is indeed one way in which a plurality of accounts can be related.

This constitutes a type of theoretical integration see also Morrison, However, I do not think it is the only mode of relationship. Therefore, identifying theoretical unification as the only means of doing good science is a mistake that removes the impetus to understand the value of diverse integrative strategies in scientific inquiry. While selection characterized at this level of abstraction unifies quite a significant number of phe-nomena, there are reasons to go both more abstract and less abstract with corresponding increases and decreases in generality.

Darden and Cain move up the scale and beyond biology. See also Skipper, Within biology, even individual or organismic selection is broken down into r and k selection. The consequences of these different kinds of organismic selection are not always in concert. A number of studies both in the lab and in the field show mixed results of the relationship be-tween fecundity and survival: out of 22 lab studies, a negative relationship was found in seven and positive in five ; out of 41 field studies, a negative relationship was found in 23 and positive in four ; the remaining cases were nonsignificant Stearns, Indeed, the more concretely described individual processes that constitute organismic selection may operate antagonistically, additively, or synergistically.

Hence, collapsing the different processes constituent of natural selection operating on organismic variation in a population into a single representation of the process of selection can obscure what may be important differences. The point is that different levels of abstraction are required for different tasks see also Mitchell, for a version of this argument applied to chemistry.

Specific theoretical unifications, while being one form of integrating diverse causal models, must be justified by appeal to more than the fewer-the-better argument. Integration, the alternative to both reduction and isolation, occurs at many levels of abstraction and is driven by a variety of pragmatic interests.

Establish-ing the philosophical arguments for the need for some form of integrative pluralism is clearly only the first step toward a better understanding of science.

Indeed, the arguments I have given for expecting pluralism imply that the types of integration within science will also be varied and diverse. No single theoretical framework, no simple algorithm, will suffice. This is also evident from the type of case study-driven work that has already considered questions of integration. Bechtel and Richardson have further explored integrative strategies in their more recent work, especially with respect to crossing different levels of organization.

These studies call for further cases in order to catalog what appears to be a wide variety of ways in which integration proceeds. My own investigations of interdisciplinary work between developmental and evolutionary models Mitchell, et al. In that work I proposed three types of integration: 1 mechanical rules, 2 local theoretical unification, and 3 explanatory, concrete integration. Mechanical rules can be used to quantitatively determine the joint effects of independent additive causal processes explained by different theories.

Vector addition on the contributions of electromagnetic and gravitational forces to resultant motion is an example. The integration of theories is simply a demonstration that they are simultaneously applicable in a linear way.

Sewell-Wright attempted to do the same for the effects of mutation and selection on gene frequencies see Sober, Prima facie , this type of integration seems appropriate for causes that are additive and operate on the same entities for comparable time periods.

However, some biological phenomena do not seem to be amenable to mechanical rule integration. Think of the slime mold. When there is sufficient food in the environment, slime mold exists as independent amoebae. They move, feed on bacteria, and reproduce by cell division. This new association of cells then differentiates into a stalk supporting a fruiting body that produces spores. Therefore, theories explaining the causes of emergent phenomena requires consideration of interactions.

The second model ofintegration, local theoretical unification , aims to develop models in which a number of features of a complex process are jointly modeled. This is similar to the explanatory unification counseled by Friedman and Kitcher. However, as I argued above, the appropriate scope of the unity and corresponding degree of abstraction will be settled by a combination of pragmatic and ontological constraints.

The problem of scale in ecology illustrates this. Liebold, et al. The third type of integration, explanatory, concrete integration , appears to occur in cases of high complexity and pressing pragmatic goals see Oreskes, et al.

That is, when a large number of at most partially independent factors participate in structuring a biological process, and where those factors span time and dimension scales as well as standard scientific disciplines, even modest theoretical unification will be elusive.

Think of the changes of state of a complex ecosystem such as that of Lake Erie. The different factors contributing to these effects are large and diverse, including the chemicals silica, ammonia, nitrate, phosphate, total phosphorus, and phosphorus in sediments; five taxa of phytoplankton, six taxa of herbivorous zooplankton including zebra mussel veligers , and three taxa of predatory crustacean Zooplankton; zebra mussels and four taxa of other macrobenthos; and eleven taxa of planktivorous fish and six taxa of piscivorous fish.

The model also represents seasonal and spatial variation in solar radiation. Features ofthe method ofintegration of these multiple factors for a single lake may be local to Lake Erie or may be symptomatic of a class of situations, but are unlikely to be global and algorithmic. As such,. I suggest, it may be better described as explanatory, concrete integration. He concludes his investigation of the relative worth of using thing language, abstract language, or not speaking at all:.

To decree dogmatic prohibitions of certain linguistic forms instead of testing them by their success or failure in practical use is worse than futile; it is positively harmful because it may obstruct scientific progress. The history of science shows examples of such prohibitions based on prejudices derivingfrom religious, mythological, metaphysical, or other irrational sources, which slowed up the developments for shorter or longer periods oftime.

Let us learn from the lessons of history. Let us grant to those who work in any special field of investigation the freedom to use any form of expression which seems useful to them; the work in the field will sooner or later lead to the elimination of those forms which have no useful function.

I believe it should be applied not only to linguistic expressions within science, but also to philosophical expressions about science. In defending integrative pluralism, an image of science that makes room for compatible pluralism, I have attempted to steer clear of two undesirable methodological pitfalls. The first is an isolationist stance that partitions scientific investigations into discrete levels of questions and their corresponding answers in a way that precludes the satisfactory investigation of any of the levels.