Abstract
Although “theory” has been the prevalent unit of analysis in the meta-study of science throughout most of the twentieth century, the concept remains elusive. I further explore the leitmotiv of several authors in this issue: that we should deal with theorizing (rather than theory) in biology as a cognitive activity that is to be investigated naturalistically. I first contrast how philosophers and biologists have tended to think about theory in the last century or so, and consider recent calls to upgrade the role of theory in the life sciences against the background of the recent “data deluge” in molecular biology, systems biology, etc. I then review thinking about theory in biology in relation to physical theory as a positive or negative exemplar. I conclude by discussing various aspects of a positive program for “naturalizing theorizing.”
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Notes
Inspired by Schopenhauer and Nietzsche, the Lebensphilosophie of Wilhelm Dilthey, Henri Bergson, Ludwig Klages, and others was a reaction against the theoretical focus of neo-Kantianism, anti-religious naturalism, and the rise of positivism. It is superbly embodied by Ulrich, the protagonist in Musil’s The Man Without Qualities (1953–1954) who pursues a “hovering life” between science and mysticism.
The traditional goal of philosophy was practical: to orient one toward a life of έύδαιμονία (flourishing). Plato and Aristotle would have been perplexed by our plea for a pragmatic or pragmatist turn in thinking about theory.
As “the big picture of science” dealing with the fundamental laws of the universe, physics is characterized even today as the study of “the mind of God” (http://www.physicsforums.com/showthread.php?t=134150); see Fig. 1.
By no means does it follow from this that science has become “metaphysically neutral,” as many anti-creationism crusaders would have it. Metaphysical assumptions such as the principles of the uniformity of nature and causality continue to guide the theoretical and empirical study of nature heuristically, and are increasingly supported by scientific evidence (Wartofsky 1967; Fry 2012).
This label, apparently coined by Hilary Putnam in 1960, sounds rather dated today, but has become so entrenched that we continue to use it.
The literature abounds with references to the “nature” of theories, etc. “Nature” (in the sense used here) is a synonym of “essence.” What can this mean in a naturalistic perspective? “In keeping with evolutionary ideas, … nothing outside the realm of abstract constructions, such as a geometrical circle, has anything like an essence to be captured in an explicit definition” (Giere 2006b, p. 53). Yet most analytic philosophy continues to debate the proper account of concepts in terms of necessary and sufficient conditions, as if these concepts had essences. In sequences of exchanges, philosophers propose definitions, which are then “refuted” by a couple of counterexamples, upon which the definition is modified, etc. Such debates can go on until the participants must quit from sheer exhaustion (Kitcher 2012). In a broader societal context, philosophers have not on the whole been very effective in the creationism/intelligent design debate. If they don’t manage to demarcate science from religion or pseudoscience (Nickles 2006), who can do better? I suggest that rather than resting on their “quietist” oars philosophers reflect, for instance, on how it is that science museologists cope very well with the demarcation of science, for instance from art (Wagensberg 2006). What is their secret?
Philosophers of biology, being by and large scientific realists, have devoted little attention to prediction as distinguished from explanation after Hempel’s “symmetry thesis” was given up (Salmon 1989). But many scientists, including biologists, continue to invoke predictive power as a major virtue of theory. The US National Academy of Sciences (http://www.nap.edu/openbook.php?record_id=11876&page=11) states: “One of the most useful properties of scientific theories is that they can be used to make predictions about natural events or phenomena that have not yet been observed. … The evolutionary biologists who discovered Tiktaalik … predicted that they would find fossils intermediate between fish and limbed terrestrial animals in sediments that were about 375 million years old. Their discovery confirmed the prediction made on the basis of evolutionary theory. In turn, confirmation of a prediction increases confidence in that theory.”
One can safely bet that as one of Holton’s (1973) “themata,” reduction will remain on the agenda, the current “anti-reductionist consensus” in the philosophy of biology notwithstanding.
I agree with Hull (1988, p. 494): “one of the persistent goals of scientists is to present theories that are as universal and coherent as possible. … It is not a valid criticism of a theory that it is not currently totally global and coherent.” Aiming for generality within a theory should not be conflated with “the ideal of providing the single complete and comprehensive truth about a domain” (Kellert et al. 2006, p. xxiv).
By way of example: Hull’s “conceptual systems” at any one time are almost as heterogeneous as biological species. This conceptual heterogeneity even increases if one follows them through time. One could say that heterogeneity is constitutive of evolving entities. Hull also argued that the lack of conceptual homogeneity in science is often compensated by the social coherence resulting from the imperative to cooperate.
Theories are needed in all walks of life and well beyond. While most cognitive scientists agree today that explicit theories are not required to explain what humans do in many contexts, “there are important arenas of individual and organizational behavior where mental models or theories do play an important role” (Nelson 2008, p. 78).
Cf. Hull (1988, p. 485) on the “bracketing” of a widely held theory to see what the relevant phenomena look like without this presupposition, and Nelson and Winter (1982, p. 414) on how a different angle can provide “relief from distorting shadows.” See also the section, “Toward a Perspectivist Theoretical Biology.”
Isabella Sarto-Jackson correctly points out to me that “speculation”—a term that is often pejoratively loaded (cf. below)—should not be equated with “theorizing.” My claim derives from Mitroff’s (1984) tripartition of scientists into “experimentalists,” “middle-of-the-road,” and “speculative theorists” on the basis of a case study of the psychology of senologists (Rowan 1981, p. 39), in which “speculation” has a pejorative or positive connotation according to scientists’ position in the field. Experimentalists were characterized as analytical and precise, collecting data and publishing them with little interpretation, and often priding themselves on “not speculating at all.” Speculative theorists were said to be extremely brilliant, creative, and aggressive; biased and rigid in defense of their position; excelling at extrapolating from data (their own, or others’); and relishing theorizing about them, and synthesizing (coming out with a “big picture”). The majority of the senologists Mitroff studied were “middle of the road,” flexible in being able to get good data and interpret them in interesting ways. Prestige in the field was lowest for the experimentalists (sometimes dismissed as “technicians with PhDs”), and highest for speculative theorists—contradicting the widespread impression that medical research is anti-theoretically biased. Mitroff’s evidence was obviously limited; but I am quite confident that an investigation of other fields—say, animal behavior and cognition studies, or ecology—would reveal a similar pattern.
See Krohs and Callebaut (2007) and Callebaut (2012). The crude empiricist “forgets that even the greatest amount of collected facts as little constitutes a science as a heap of bricks constitutes a house” (von Bertalanffy 1932, p. 2); cf. Hull (1988, p. 488) on “the vision of armies of unlettered data gatherers” in pheneticism. It is this crude form of empiricism that invited Rutherford to tease that physics is the only real science, and the rest are just “stamp collecting.”
In the Dutch psychologist de Groot’s (1961) influential formulation, the cycle consists of five sequential stages, viz.: (1) observation: collecting and grouping of empirical facts; (2) induction: formulation of hypotheses; (3) deduction: inferring special consequences from the hypotheses in the form of testable predictions; (4) testing of the hypothesis/hypotheses on new evidence; (5) evaluation of the results of testing in relation to the proposed hypothesis/hypotheses or theory/theories, and in relation to possible new, follow-up research.
In reviews of this article, Stuart Glennan and Kim Sterelny made the important point that biologists tend to contrast data with models rather than theories. Given the intricate intertwining of modeling and theorizing (“Semantic Views and Their Limitations” and “Theory (Re)vindicated” sections), this may make much work in biology look less theoretical than it actually is. According to Sterelny, “it is the complexity and variability of living systems, not the empiricism of life scientists, that make the issue problematic.” I can agree as far as most biology most philosophers of biology are dealing with is concerned, but would exempt other fields, in particular “big data biology,” from his verdict.
The German botanist Johannes Reinke (1849–1931) introduced the idea of a “theoretical biology” in 1901: “The results of empirical biology are the objects of theoretical biology” (Reinke 1911, p. V). The German zoologist and developmental biologist Julius Schaxel (1887–1943), a student of Haeckel, was an early critic of the anti-science movement in Weimar culture: “Only one natural science, which … is not unambiguous, meets with approval. That is biology” (Schaxel 1919, p. 6). Schaxel emigrated to the Soviet Union in 1933, where he died in mysterious circumstances. Ludwig von Bertalanffy (1901–1972), who trained as a biologist in Austria (“One can always become a philosopher later!”), moved to the US in 1950. He is remembered most as one of the founders of General Systems Theory, which he hoped would provide “pre-Copernican” biology with a more solid scientific grounding.
“Anthropology still painfully remembers the stomach-ache it got from the too easy generalizations of many nineteenth century ‘arm-chair ethnologists’” (Kluckhohn 1939, p. 328).
At about the same time, another theoretical biologist, Rudolf Ehrenberg (1923, p. 5) wrote: “The fundamental biological law that will have to carry everything else will be characterized as ‘the law of the necessity of death.’ ” Freud’s “death drive” has been viewed as the psychological counterpart of this idea, which von Bertalanffy (1932, p. 3) criticized for being no more than the application of a brilliant, yet questionable aperçu. Like the paleontologist Louis Dollo (“evolution is irreversible”) before him, Ehrenberg was inspired by the entropy law of thermodynamics.
To a large extent, this scholastic tendency may be the direct result of institutional constraints the analytic mainstream imposes on scholars (Preston 2007). To some extent, I’m afraid, it just reflects many philosophers’ unworldliness—“Why should I talk to biologists? I’m a philosopher, I read [other philosophers]!”
While researching for this article I have found no good reasons, for the purposes at hand, to drive a philosophical wedge between the “conceptual” level (the term preferred by cognitive scientists) and the “theoretical” level. But see Downes (1992, p. 143) on putting a limit on what can be sensibly considered as a theory. Carnap’s conceptual–theoretical distinction is analyzed in Nersessian (1984).
In Callebaut (2012) I attempt to specify what Woese meant by a “guiding vision” in terms of “perspectives” and “images.”
In parallel, psychologists voice concern about the implications for their field of “evidence-based practice” (EBP), a generalization of “evidence-based medicine” that has grown to encompass many other disciplines and professions. EBP norms privilege quantitative studies at the expense of theoretical and qualitative studies. Dennis Wendt, for one, deplores “a rhetoric of objectivity that clouds over the interpretive and practical demands of the discipline, and the positivist assumption that discrete empirical findings somehow magically put themselves together in a coherent fashion.” He encourages psychologists “to take the evidence-based turn so seriously, as to become evidence-based nuisances in uncovering absurd claims by our colleagues” (http://www.theoreticalpsychologyblog.org/2012/06/06/bringing-the-evidence-based-turn-full-circle-critical-thinking-about-disciplinary-practices/).
A report brief is available at http://dels.nas.edu/resources/static-assets/materials-based-on-reports/reports-in-brief/role_of_theory_final.pdf.
Like Bertalanffy and others before them, the authors of the report fail to specify what it could mean for theory and evidence to be given “commensurate” attention. Hull’s “relevance to a powerful theory as the mark of a good description” seems to me a good starting point.
In a “Washington Watch” of the American Institute of Biological Sciences, science reporters Menninger and Gropp (2008) begin their overall positive presentation of the report thus: “Compared with other scientific disciplines, some leaders in the science community have said, biology is too heavily centered on facts, with too little emphasis on underlying theory. The propagation of this misperception in recent years has very likely contributed to a drive to allocate larger portions of the federal research budget to nonbiological disciplines” (emphasis added).
The mathematician G. H. Hardy, FRS, writing in the twentieth century, was even more adamant: “there is no scorn more profound, or on the whole more justifiable, than that of the men who make for the men who explain. Exposition, criticism, appreciation, is work for second-rate minds” (Hardy 1940, p. 1). Synthetic biologists could add this to their favorite Richard Feynman quote, “What I cannot create, I do not understand” (O’Malley 2009).
In a way, Aristotelianism married biology (teleology) and psychology (intentionality) while “postponing” the separation between the physical and the biological that we have come to view as obvious (Schaxel 1919).
Structuralism in contemporary philosophy of science is a way of representing theoretical, model, and data structures that aims to capture relevant relations—“horizontally,” between theories and models; and “vertically,” between models and data. Structuralists urge a shift in focus from object-oriented ontologies that “come and go through the history of science” to structures that “remain through theory change” (Steven French); see da Costa and French (2003), Ladyman et al. (2007), van Fraassen (2008).
Russell (1917, p. 173) famously said: “To me it seems that … the reason why physics has ceased to look for causes is that, in fact, there are no such things. The law of causality, I believe, like much that passes muster among philosophers, is a relic of a bygone age, surviving, like the monarchy, only because it is erroneously supposed to do no harm.” Quine similarly thought of causation as an outdated, anthropomorphic notion. This view is still endorsed today by the physicist Anderson (2011, p. 270), whose alternative is “searching for the simplest schematic structure which will explain all the observations.” For Anderson, the epistemology of modern science is “basically Bayesian induction with a very great emphasis on its Ockham’s razor consequences.” Notice, however, that Bayesians have never come up with a convincing explanation of why simplicity would be relevant to credibility or truth (Churchland 1990).
The NAS gives an interesting twist to the meaning of the notion of fact: “In science, a ‘fact’ typically refers to an observation, measurement, or other form of evidence that can be expected to occur the same way under similar circumstances. However, scientists also use the term ‘fact’ to refer to a scientific explanation that has been tested and confirmed so many times that there is no longer a compelling reason to keep testing it or looking for additional examples. In that respect, the past and continuing occurrence of evolution is a scientific fact. Because the evidence supporting it is so strong, scientists no longer question whether biological evolution has occurred and is continuing to occur. Instead, they investigate the mechanisms of evolution, how rapidly evolution can take place, and related questions.”
These rules were accounted for in quite different ways by inductivists, falsificationists, and Bayesians.
On Giere’s (1988, p. 84) original account, for instance, models were “nonlinguistic, though abstract entities.” But as we have seen in the “Hopes Set on Biological Theory in an Evidence-Based World” section, the category has since been relaxed to include verbal, mathematical, visual, and physical models. If theories are defined solely in terms of models, but models are allowed to be purely verbal, there seems to be no good reason to subsume verbal theories under the semantic view.
Meta-mathematics studies mathematics itself by means of formal (logical and mathematical) methods. It includes model theory, the study of (classes of) mathematical structures such as graphs or universes of set theory.
A state space is a directed graph where each possible state of a dynamical system is represented by a vertex, and there is a directed edge from a to b if and only if f(a) = b, where f defines the dynamical system.
Historians such as Israel (1996) and Morgan (2012) have argued that model-based science is, historically speaking, a relatively recent phenomenon. Godfrey-Smith (2006) compares John Maynard Smith and Eörs Szathmáry’s work on major transitions in evolution with Leo Buss’ work on the evolution of individuality, and argues that the former typifies a model-building approach whereas the latter doesn’t.
“Far from following through the alleged similarities between scientific theories and those of meta-mathematics, Giere brings in as many interpretations of the term ‘model’ as suit his ends” (Downes 1992, p. 150). “One puzzling aspect of Griesemer’s account is his insistence that he is enriching the semantic view of theories. By the time we have admitted laboratory specimens and physical objects to the domain of models, the idea that theories are families of models becomes quite inclusive” (p. 150). Godfrey-Smith (2006) similarly rejects the semanticists’ claim that the sense of “model” that is applied is either the logician’s sense, or something relevantly close to it.
“The effect of evolution on our sensory apparatus is known to have been particularly strong. Animals are capable of incredibly fine discriminations among objects in their environment without benefit of social conventions. And so—being fairly intelligent, talking primates—are we. … For at least some perceptual judgments, therefore, the fact of widespread agreement does not require a social explanation. The explanations of evolutionary biology and physiology are sufficient” (Giere 1988, p. 109). This is reminiscent of Quine (1969, p. 133): “A sense of comparative similarity … is one of man’s animal endowments. Insofar as it fits in with regularities of nature, so as to afford us reasonable success in our primitive inductions and expectations, it is presumably an evolutionary product of natural selection.” Quine employed this evolutionary argument to counter the appearance that science, in its reliance on subjunctive conditionals and singular causal statements, “is rotten to the core.”
Whereas van Fraassen’s pragmatic, erotetic account of explanation (“an explanation is an answer to a why-question”) trivializes it (Kitcher), Giere (1988, p. 105) more radically suggests abandoning philosophical accounts of explanation altogether, and replacing them by accounts in terms of the standards of the cognitive sciences. An “empirical theory of explaining” would be judged by “the sorts of evidence relevant to theories of other higher level cognitive activities such as language comprehension and problem solving.”
References
Alexandrescu V (ed) (2009) Branching off: the early Moderns in quest for the unity of knowledge. Zeta Books, Bucharest
Anderson PW (2011) More and different: notes from a thoughtful curmudgeon. World Scientific, Singapore
Apostel L (1953) Logique et preuve. Methodos 5:279–321
Apostel L (1960) Towards the formal study of models in the non-formal sciences. Synthese 12:125–161
Baetu T (2012) Mechanistic constraints on evolutionary outcomes. Philos Sci 79:276–294
Bechtel W (2006) Discovering cell mechanisms: the creation of modern cell biology. Cambridge University Press, Cambridge
Berg N, Gigerenzer G (2010) As-if behavioral economics: neoclassical economics in disguise? Hist Econ Ideas 18:133–165
Bonner JT (2013) Randomness in evolution. Princeton University Press, Princeton
Brenner S (2010) Sequences and consequences. Philos Trans R Soc B 365:207–212
Bressler SL, Kelso JAS (2001) Cortical coordination dynamics and cognition. Trends Cogn Sci 5:26–36
Callebaut W (1993) Taking the naturalistic turn, or how real philosophy of science is done. University of Chicago Press, Chicago
Callebaut W (2005) Again, what the philosophy of biology is not. Acta Biotheor 53:93–122
Callebaut W (2007) Simon’s silent revolution. Biol Theory 2:76–86
Callebaut W (2010) Innovation from EvoDevo to culture. In: O’Brien MO, Shennan SJ (eds) Innovation in cultural systems: contributions from evolutionary anthropology. MIT Press, Cambridge, MA, pp 81–95
Callebaut W (2011) Beyond generalized Darwinism. Biol Theory 6:338–365
Callebaut W (2012) Scientific perspectivism: a philosopher of science’s response to the challenge of big data biology. Stud Hist Philos Biol Biomed Sci 43:69–80
Campbell DT (1997) From evolutionary epistemology via selection theory to a sociology of scientific validity. Evol Cogn 3:5–38
Cartwright N, Shomar T, Suárez M (1995) The tool box of science: tools for building of models with a superconductivity example. In: Herfel WE et al (eds) Theories and models in scientific processes. Rodopi, Amsterdam, pp 137–139
Churchland PM (1990) On the nature of theories: a neurocomputational perspective. In: Savage CW (ed) Scientific theories. University of Minnesota Press, Minneapolis, pp 59–101
Committee on Defining and Advancing the Conceptual Basis of Biological Sciences in the 21st Century (2007) The role of theory in advancing 21st century biology: catalyzing transformative research. National Academies Press, Washington, DC
da Costa NCA, French S (2003) Science and partial truth: a unitary approach to models and scientific reasoning. Oxford University Press, Oxford
Danchin A (2002) The Delphic boat: what genomes tell us (Quayle A, trans). Harvard University Press, Cambridge, MA. French orig. 1998
Daston L, Stolleis M (eds) (2008) Natural law and laws of nature in early Modern Europe. Ashgate, Farnham
de Chadarevian S, Hopwood N (eds) (2004) Models: the third dimension of science. Stanford University Press, Stanford
de Groot AD (1961) Methodologie: grondslagen van onderzoek en denken in de gedragswetenschappen. Mouton, ‘s Gravenhage
De Mey M (1992) The cognitive paradigm: cognitive science, a newly explored approach to the study of cognition applied in an analysis of science and scientific knowledge. University of Chicago Press, Chicago. Orig. 1982
de Regt H, Leonelli S, Eigner K (2009) Scientific understanding: philosophical perspectives. University of Pittsburgh Press, Pittsburgh
Downes SM (1992) The importance of models in theorizing: a deflationary semantic view. In: Hull D et al (eds) PSA 1992, vol 1. Philosophy of Science Association, East Lansing, pp 142–153
Ehrenberg R (1923) Theoretische Biologie vom Standpunkt der Irreversibilität des elementaren Lebensvorganges. Julius Springer, Berlin
Freeman C (1993) The economics of hope: essays on technical change, economic growth, and the environment. Pinter, London
Frigg R, Hartmann S (2012) Models in science. In: Zalta EN (ed) The Stanford encyclopedia of philosophy, Fall. http://plato.stanford.edu/archives/fall2012/entries/models-science/. Accessed 20 March 2013
Frisch DP (2010) Recent developments in sociobiology and the scientific method. Trends Ecol Evol 26:57–58
Fry I (2012) Is science metaphysically neutral? Stud Hist Philos Biol Biomed Sci 43:665–673
Fuller S (2009) Philosophy of science in an age of neo-Darwinian apologetics. Ludus Vitalis 17:247–257
Giere RN (1988) Explaining science: a cognitive approach. University of Chicago Press, Chicago
Giere RN (1999) Science without laws. University of Chicago Press, Chicago
Giere RN (2006a) Scientific perspectivism. University of Chicago Press, Chicago
Giere RN (2006b) Modest evolutionary naturalism. Biol Theory 1:52–60
Giere RN (2006c) The role of agency in distributed cognitive systems. Philos Sci 75:710–719
Giere RN (2009) Essay review: scientific representation and empiricist structuralism. [Review of Van Fraassen 2008.]. Philos Sci 76:101–111
Gigerenzer G, Todd PM (2012) Ecological rationality: the normative study of heuristics. Oxford University Press, Oxford, pp 487–497, 498–551 (references)
Glennan S (2002) Rethinking mechanistic explanation. Philos Sci 69:S342–S353
Godfrey-Smith P (2006) The strategy of model-based science. Biol Philos 21:725–740
Gorelick R (2011) What is theory? Ideas Ecol Evol 4:1–10
Griesemer JR (2004) Three-dimensional models in philosophical perspective. In: de Chadarevian S, Hopwood N (eds) Models. Stanford University Press, Stanford, pp 433–442
Griesemer J (2011) Philosophy and tinkering. Biol Philos 26:269–279
Griesemer JR, Wimsatt WC (1989) Picturing Weismannism: a case study of conceptual evolution. In: Ruse M (ed) What the philosophy of biology is: essays for David Hull. Kluwer, Dordrecht, pp 75–137
Habermas J (1976) Zur Rekonstruktion des historischen Materialismus. Suhrkamp, Frankfurt
Hackett EJ et al (eds) (2007) The handbook of science and technology studies, 3rd edn. MIT Press, Cambridge, MA
Hallyn F (ed) (2000) Metaphor and analogy in science. Kluwer, Dordrecht
Halvorson H (2012) What scientific theories could not be. Philos Sci 79:183–206
Hanahan D, Weinberg RA (2000) The hallmarks of cancer. Cell 100:57–70
Hardy GH (1940) A mathematician’s apology. Cambridge University Press, Cambridge
Holton G (1973) Thematic origins of scientific thought: Kepler to Einstein. Harvard University Press, Cambridge, MA
Hull DL (1988) Science as a process: an evolutionary account of the social and conceptual development of science. University of Chicago Press, Chicago
Israel G (1996) La mathématisation du réel. Seuil, Paris
Jasanoff S et al (eds) (1995) Handbook of science and technology studies, 2nd edn. SAGE, Thousand Oaks
Jha SR (2002) Reconsidering Michael Polanyi’s philosophy. University of Pittsburgh Press, Pittsburgh
Kammerer P (1915) Allgemeine Biologie. Deutsche Verlags-Anstalt, Stuttgart
Kellert SH, Longino HE, Waters CK (2006) Introduction: the pluralist stance. In: Kellert SH et al (eds) Scientific pluralism. University of Minnesota Press, Minneapolis, pp vii–xxix
Khalifa K (2012) Inaugurating understanding or repackaging explanation? Philos Sci 79:15–37
Kitcher P (1993) The advancement of science: science without legend, objectivity without illusions. Oxford University Press, New York
Kitcher P (2012) Preludes to pragmatism: toward a reconstruction of philosophy. Oxford University Press, Oxford
Kluckhohn C (1939) The place of theory in anthropological studies. Philos Sci 6:328–344
Krakauer DC, Collins JP, Erwin D, Flack JC, Fontana W, Laubichler MD, Prohaska SJ, West GB, Stadler PF (2011) The challenges and scope of theoretical biology. J Theor Biol 276:269–276
Krohs U (2004) Eine Theorie biologischer Theorien. Status und Gehalt von Funktionsaussagen und informationstheoretischen Modellen. Springer, Berlin
Krohs U, Callebaut W (2007) Data without models merging with models without data. In: Boogerd FC et al (eds) Systems biology: philosophical foundations. Elsevier, Amsterdam, pp 181–213
Kuhn TS (1970) The structure of scientific revolutions, 2nd edn. University of Chicago Press, Chicago
Ladyman J, Ross D, Spurrett D, Collier J (2007) Every thing must go: metaphysics naturalized. Oxford University Press, Oxford
Laubichler MD, Müller GB (eds) (2007) Modeling biology: structures, behaviors, evolution. MIT Press, Cambridge, MA
Lehrer J (2012) Kin and kind: a fight about the genetics of altruism. N Yorker, March 5
Leonelli S (2009) Understanding in biology: the impure nature of biological knowledge. In: de Regt HW et al (eds) Scientific understanding. University of Pittsburgh Press, Pittsburgh, pp 189–209
Leonelli S (2012) Classificatory theory in data-intensive science: the case of open biomedical ontologies. Int Stud Philos Sci 26:47–65
Leontief V (1971) Theoretical assumptions and nonobserved facts. Am Econ Rev 61:1–7
Levins R (1966) The strategy of model building in population biology. Am Sci 54:421–431
Lewontin RC (1970) The units of selection. Annu Rev Ecol Syst 1:1–18
Lewontin RC (1974) The genetic basis of evolutionary change. Columbia University Press, New York
Lewontin RC (2000) The triple helix: gene, organism, and environment. Harvard University Press, Cambridge, MA
Lloyd EA (1988) The structure and confirmation of evolutionary theory. Greenwood Press, New York
Machamer PK, Darden L, Craver C (2000) Thinking about mechanisms. Philos Sci 57:1–25
Malafouris L, Renfrew C (eds) (2010) The cognitive life of things: recasting the boundaries of the mind. McDonald Institute for Archaeological Research, Cambridge
Mayr E (1982) The growth of biological thought: diversity, evolution, and inheritance. Belknap Press of Harvard University Press, Cambridge, MA
McKinsey JCC, Sugar AC, Suppes P (1953) Axiomatic foundations of classical particle mechanics. J Ration Mech Anal 2:253–272
McMullin E (1983) Values in science. PSA 1982 2:3–28
Medawar PB, Medawar JS (1983) Aristotle to zoos: a philosophical dictionary of biology. Harvard University Press, Cambridge, MA
Meheus J (ed) (2002) Inconsistency in science. Kluwer, Dordrecht
Menninger H, Gropp R (2008) Theory and funding for 21st century biology—maybe. Bioscience 58:198
Mitroff II (1984) The subjective side of science: philosophical inquiry into the psychology of the Apollo moon scientists. Elsevier, Amsterdam
Morgan MS (2012) The world in the model: how economists work and think. Cambridge University Press, Cambridge
Morgan MS, Morrison M (eds) (1999) Models as mediators: perspectives on natural and social science. Cambridge University Press, Cambridge
Morrison M (2007) Where have all the theories gone? Philos Sci 74:195–228
Morrison M, Morgan MS (1999) Introduction. In: Morgan MS, Morrison M (eds) Models as mediators. Cambridge University Press, Cambridge, pp 1–9
Musil R (1953–1954) The man without qualities, vol I, 1953; vol II, 1954. Coward-McCann, New York. German orig. 1930–1933
Nagel E (1961) The structure of science: problems in the logic of scientific explanation. Routledge and Kegan Paul, London
Nelson RR (2008) Bounded rationality, cognitive maps, and trial and error learning. J Econ Behav Organ 67:78–89
Nelson RR, Winter SG (1982) An evolutionary theory of scientific change. Belknap Press of Harvard University Press, Cambridge, MA
Nersessian NJ (1984) Faraday to Einstein: constructing meaning in scientific theories. Kluwer, Dordrecht
Nersessian NJ (2003) Kuhn, conceptual change, and cognitive science. In: Nickles T (ed) Thomas Kuhn. Cambridge University Press, Cambridge, pp 178–211
Nickles T (ed) (2003a) Thomas Kuhn. Cambridge University Press, Cambridge
Nickles T (2003b) Normal science: from logic to case-based and model-based reasoning. In: Nickles T (ed) Thomas Kuhn. Cambridge University Press, Cambridge, pp 142–177
Nickles T (2006) Problem of demarcation. In: Sarkar S, Pfeifer J (eds) The philosophy of science: an encyclopedia, vol 1. Routledge, New York, pp 188–197
Olson R (1971) Science as metaphor: the historical role of scientific theories in forming Western culture. Wadsworth, Belmont, CA
O’Malley MA (2009) Making knowledge in synthetic biology: design meets kludge. Biol Theory 4:378–389
O’Malley MA, Elliott KC, Burian RM (2010) From genetic to genomic regulation: iterativity in microRNA research. Stud Hist Philos Biol Biomed Sci 41:407–417
Pardo-Guerra JP (2012) Financial automation, past, present, and future. In: Knorr Cetina K, Preda A (eds) The Oxford handbook of the sociology of finance. Oxford University Press, Oxford, pp 567–586
Paton R (1992) Towards a metaphorical biology. Biol Philos 7:279–294
Paton R (1997) Glue, verb and text metaphors in biology. Acta Biotheor 45:1–15
Preston A (2007) Analytic philosophy: the history of an illusion. Continuum, London
Preston B (2013) A philosophy of material culture: action, function, and mind. Routledge, New York
Priest G (1987) In contradiction: a study of the transconsistent. Nijhoff, Dordrecht
Quine WV (1969) Ontological relativity and other essays. Columbia University Press, New York
Rádl E (1909) Geschichte der biologischen Theorien. II. Teil. Geschichte der Entwicklungstheorien in der Biologie des XIX. Jahrhunderts. Wilhelm Engelmann, Leipzig
Rádl E (1913) Geschichte der biologischen Theorien in der Neuzeit. I. Teil. Zweite gänzlich umgearbeitete Auflage. Wilhelm Engelmann, Leipzig. Orig. 1905
Rádl E (1930) The history of biological ideas (Hatfield EJ, trans). Oxford University Press, Oxford; Humphrey Milford, London. Abridged version of 1909 Czech Orig.
Reinke J (1911) Einleitung in die theoretische Biologie. Zweite umgearbeitete Auflage. Gebrüder Patel, Berlin. Orig. 1901
Rouse J (2002) How scientific practices matter: reclaiming philosophical naturalism. University of Chicago Press, Chicago
Rowan J (1981) The subjective side of science by Ian Mitroff: an appreciation. In: Reason P, Rowan J (eds) Human inquiry: a sourcebook of new paradigm research. Wiley, Chichester, pp 37–41
Rueger A (2005) Perspectival models and theory unification. Br J Philos Sci 56:579–594
Russell B (1917) Mysticism and logic. Allen and Unwin, London
Salmon WC (1989) Four decades of scientific explanation. University of Minnesota Press, Minneapolis
Schaxel J (1919) Grundzüge der Theorienbildung in der Biologie. Gustav Fischer, Jena
Shadish WR, Cook TD, Campbell DT (2002) Quasi-experimental designs for generalized causal inference. Houghton Mifflin, Boston
Simon HA (1947) The axioms of Newtonian mechanics. Philos Mag Ser 7 38:888–905
Simon HA (1997) An empirically based microeconomics. Cambridge University Press, Cambridge
Spiegel-Rösing I et al (eds) (1977) Science, technology and society: a cross-disciplinary perspective. SAGE, Beverly Hills
Stanley J (2011) Know how. Oxford University Press, Oxford
Suppe F (ed) (1977) The structure of scientific theories. University of Illinois Press, Urbana
Suppes P (1967) What is a scientific theory? In: Morgenbesser S (ed) Philosophy of science today. Basic Books, New York, pp 55–67
Swann WFG (1940) The significance of scientific theories. Philos Sci 7:273–287
Teller P (2001) Twilight of the perfect model. Erkenntnis 55:393–415
Thompson P (1989) The structure of biological theories. State University of New York Press, Albany
Trout JD (2002) Scientific explanation and the sense of understanding. Philos Sci 69:212–233
van Fraassen BC (2008) Scientific representation: paradoxes of perspective. Clarendon, Oxford
Van Valen L (1973) A new evolutionary law. Evol Theory 1:1–30
von Bertalanffy L (1932) Theoretische Biologie. Erster Band: Allgemeine Theorie, Physikochemie, Aufbau und Entwicklung des Organismus. Borntraeger, Berlin-Zehlendorf
von Bertalanffy L (1942) Theoretische Biologie. Zweiter Band: Stoffwechsel, Wachstum. Borntraeger, Berlin-Zehlendorf
Wagensberg J (2006) The total museum through conversation between architects and museologists. Sacyr, Barcelona
Wartofsky MW (1967) Metaphysics as heuristic for science. In: Cohen RS, Wartofsky MW (eds) In memory of Norwood Hanson. Reidel, Dordrecht, pp 164–170
Waters KC (2011) Okasha’s unintended argument for toolbox theorizing. Philos Phenomenol Res 82:232–240
Weinberg RA (2010) Point: hypotheses first. Nature 464:678
Weisberg M (2007) Who is a modeler? Br J Philos Sci 58:207–233
Whitehead AN (1933) Adventures of ideas. Macmillan, New York
Williams M (1970) Deducing the consequences of evolution: a mathematical model. J Theor Biol 29:343–385
Wimsatt WC (2007) Re-engineering philosophy for limited beings: piecewise approximations to reality. Harvard University Press, Cambridge, MA
Woese CR (2004) A new biology for a new century. Microbiol Mol Biol Rev 68:173–186
Wray KB (2011) Kuhn’s evolutionary social epistemology. Cambridge University Press, Cambridge
Zammito JH (2004) A nice derangement of epistemes: post-positivism in the study of science from Quine to Latour. University of Chicago Press, Chicago
Ziman J (1978) Reliable knowledge. Cambridge University Press, Cambridge
Acknowledgments
Warm thanks to my co-organizers, Massimo Pigliucci and Kim Sterelny; to the other participants in the 25th Altenberg Workshop in Theoretical Biology on “The Meaning of ‘Theory’ in Biology”; to KLI fellows, in particular Tudor Baetu, Rachael Brown, and Stuart Glennan; and in particular to Isabella Sarto-Jackson for her real biologist’s questioning. Error clause as usual. I gratefully acknowledge the financial support of the KLI Board, which made this event possible. I trust that my friend Ulrich Krohs will forgive me for borrowing the title of his (2004) book and giving it a twist in my own title. According to Suppes (1967, p. 57), “most philosophers find it easier to talk about theories than about models of theories.” Considering the difficult gestation of this article, I am no longer sure I can agree. I dedicate it, imperfect as it is, to the memory of Leo Apostel (1925–1995), my mentor at the University of Ghent, who was one of the first to take seriously the multiple roles models play in scientific practice (Apostel 1960; Frigg and Hartmann 2012). Apostel (1953) also paved the way for the pragmatic turn to theorizing that epitomized our workshop; after reading this article, Jean Piaget invited him to Geneva for what was to become a lifelong collaboration.
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Callebaut, W. Naturalizing Theorizing: Beyond a Theory of Biological Theories. Biol Theory 7, 413–429 (2013). https://doi.org/10.1007/s13752-013-0122-2
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DOI: https://doi.org/10.1007/s13752-013-0122-2