To anyone vaguely aware of Feyerabend, the title of this paper would appear as an oxymoron. For Feyerabend, it is often thought, science is an anarchic practice with no discernible structure. Against this trend, I elaborate the groundwork that Feyerabend has provided for the beginnings of an approach to organizing scientific research. Specifically, I argue that Feyerabend’s pluralism, once suitably modified, provides a plausible account of how to organize science. These modifications come from C.S. Peirce’s account of the economics of theory pursuit, which has since been corroborated by empirical findings in the social sciences. I go on to contrast this approach with the conception of a ‘well-ordered science’ as outlined by Kitcher (Science, truth, and democracy, Oxford University Press, New York, 2001), Cartwright (Philos Sci 73(5):981–990, 2006), which rests on the assumption that we can predict the content of future research. I show how Feyerabend has already given us reasons to think that this model is much more limited than it is usually understood. I conclude by showing how models of resource allocation, specifically those of Kitcher (J Philos 87:5–22, 1990), Strevens (J Philos 100(2):55–79, 2003) and Weisberg and Muldoon (Philos Sci 76(2):225–252, 2009), unwittingly make use of this problematic assumption. I conclude by outlining a proposed model of resource allocation where funding is determined by lottery and briefly examining the extent to which it is compatible with the position defended in this paper.
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Evolutionary accounts of science suppose that the order is maintained by selective pressures. Some, such as Popper (1972), suppose that these pressures come from methodology; explanatory realists presume that order is maintained by the impingements of the external world; Kuhnians suppose that pressures come from institutions (cf. Wray 2015). Regardless of the source of the pressures, all of these positions maintain that science is ‘ordered.’ See Allchin (2015) for a general discussion of ‘naturalistic’ approaches to organizing science via the ‘self-correcting hypothesis’.
This view is adopted and slightly modified by Cartwright (2006).
This point has been realized before, and discussed extensively by Poincaré (1902). Poincaré solves the problem of excessive facts with a distinction between simple facts, which have greater epistemic capabilities, and ordinary facts whereas Kitcher appeals to values to determine the significance of facts.
This is explicitly a normative claim and isn’t descriptive of all scientific practices. See Feyerabend (1965a, pp. 156–157) for an overview of the museum set up by the Royal Society that displayed random facts without any sort of ‘selective principle.’ This included the silliest ‘facts’ imaginable, such as the following: “1661, July 24: a circle was made with powder of unicorn’s horn, and a spider set in the middle of it, but it immediately ran out several times repeated. This spider once made some stay upon the powder” (Weld 1848/2011, p. 219). See pg. 93 for an appraisal of the museum as being “necessary for the welfare of science”.
This damnation of A is unfair since any metaphysics, including atheistic metaphysics, will provide criteria for what constitute ‘fundamental truths’ (or lack thereof). Even Kitcher’s earlier view of realism (cf. chap. 5 of Kitcher (1993)) commits him to the view since the best theories will provide us with sets of epistemic relations from which we can discern significance. A stronger justification comes from Kitcher’s adoption of pragmatism (cf. Kitcher 2013) where he accepts William James’ claim that we evaluate methods based on their consequences rather than their foundations (see James 1907 and Dewey 1908 for a critical discussion).
To be clear, throughout this paper I assume that any funding distribution will be two-tiered in that it involves both the salaries of scientists and the external funding of their projects. While most are not explicit about this, discussions of resource allocation are restricted to the latter.
Kitcher, at other points (cf. Kitcher 1997, pp. 296–267), argues that should not pursue lines of research that would interfere with the prospects of underprivileged groups pursuing their conception of the good life (e.g., sociobiology). I think these constraints have already been adequately responded to by Longino (2002) and Eigi (2012).
Toulmin, at times, adopts this view as well (Toulmin 1976, p. 661).
See Epstein’s (1995) discussion of the political debates over the construction of AIDS trials in California during the 1960 s and 70 s for an example of this.
The same point is made in Flory and Kitcher (2004). Their focus on medical research, however, should be seen as a specific instance of a broader category of scientific research that addresses the morally optimal needs.
See Barseghyan (2015, pp. 30–42) for a discussion of this.
I also take it that methods have content, indirectly at least, since they rely on theoretical assumptions.
Another model that has garnered increasing interest is Zollman’s which is based largely on decision theory and does not, to my knowledge, make use of the projection postulate (Zollman 2010). However, he does claim that “[e]xtending this model to cases where the probability of future success is determined by past success will be left to future research” (Zollman 2010, p. 24). If I am correct, this line of research may be a dead end.
See Frankel (1979) for a discussion of the early development of continental drift.
This is a non-negligible feature of scientific discovery. The locus classicus discussion of serendipity in discovery can be found in Roberts (1989) which has been increasingly confirmed in more recent investigations (García 2009; Hargrave-Thomas et al. 2012). For a more skeptical discussion, see (Jeste et al. 1979).
Topics can defined broadly or narrowly. The WM model is aimed to represent “the topic that a specialized research conference or advanced level monograph might be devoted to” (Weisberg and Muldoon 2009, p. 228).
Two assumptions have already been criticized. Thoma (2015) criticizes the assumption that agents can only move locally (i.e., coding of the controls have “those agents behaving like lethargic random walkers” (433) within their Moore neighborhood), and that the purported benefits of the division of labor are more limited in higher dimensional landscapes 425) especially given the fine-graininess of the distinction between adjacent patches (462). Alexander et al. (2015) criticize the breadth of kinds of agents chosen. These criticisms are distinct from the ones I am concerned with in this paper.
It is possible that Feyerabend’s aversion to the projection postulate is grounded in Popper’s arguments against historicism where we “cannot predict, by rational or scientific methods, the future growth of our scientific knowledge” (Popper 1957, p. vi). This influence is only speculative though, since Feyerabend never, to my knowledge, acknowledges his indebtedness to this view or endorses Popper’s criticisms of historicism more generally. Since Popper’s influence on Feyerabend was mixed, even at the beginning of his career (cf. Collodel 2016), we cannot automatically assume that this argument influenced Feyerabend’s arguments against the projection postulate.
I will speak here of the ‘value’ of ideas for ease of expression though, for obvious reasons, the content of an idea is closely linked to their value.
Additionally, there are many examples of ideas that had intended practical implications and were co-opted to have different practical implications at later points. See De Laet and Mol’s (2000) discussion of the Zimbabwe Bush Pump for a classic example of this.
Notice that if one follows Quine and many realists and argue that all we can ever know about the structure of the world is what we are committed to by our best scientific theories, then no principle could be invoked here since it would require knowledge of the content of future theories.
Feyerabend himself defends the views that our metaphysical theories should contradict, rather than be consistent with, scientific theories (Feyerabend 1965a, p. 183). However, this argument is meant to defend the use of metaphysics for future discoveries as a kind of heuristic and not because we think those theories are actually true.
Popper never extended the principle of testability to his own falsificationism. Lakatos claims that Popper has given an implicit answer, but he provides weak textual evidence to support this interpretation (Lakatos 1970). Feyerabend does, and so does Bartley (1962). See Watkins (1971) for a critical discussion of Bartley’s position.
See Longino (1990, Chapters 1–3) for a discussion of proceduralist methodologies versus ‘justificationist’ approaches to methodology.
Feyerabend actually provides a second, slightly different, argument in the following chapters of Against Method where he shows that counterinduction plays a certain role that induction cannot play (cf. Feyerabend 1975, Chapters 3–5). The claim that methodological pluralism is necessary for maximal testability and the claim that methodological pluralism is necessary because different methods have different functions are distinct.
See Stanford (2006, p. 174) for additional examples of scientists whose judgments were, from a retrospective point of view, mistaken.
Similar results were found in ethnographic studies of the European Research Council (Luukkonen 2012).
I should mention that there are attempts to improve peer-review. For instance, Jayasinghe et al. (2003) have found various markers for referee bias (North American reviewers give higher reviews than Australian reviewers, reviewers nominated by the researcher give higher reviews that those nominated by a granting agency, and scientists with fewer proposals tend to give higher ratings). However, these results still only improve reliability measures to 0.47 (the standard threshold for reliability is normally in between 0.8-0.9 (Marsh et al. 2008, 162)). This being said, enough tenacity on this research program may allow us to reformulate and better implement peer-review.
Roughly, Kuhn provides three primary reasons why this is the case. First, scientists are “freed” from the need to constantly renegotiate their fundamental convictions and focus exclusively on more esoteric phenomena (Kuhn 1962, p. 163). They do not need to worry about justifying the importance of their problem as they would have had they faced a heterodox audience. Secondly, progress is more assured since the past successes of the paradigm give the experimenter some assurance that there is a solution to their problem, a guarantee that isn’t available when experimenting within new frameworks.3 Finally, Kuhn lays out pedagogical reasons why paradigms are more conducive to progress. Rather than have students introduced to their fields by reading their respective “classics” (e.g. Newton’s Principia, Darwin’s Origin of Species, etc.), their textbooks already presuppose these accomplishments in formulating more precise and obscure questions. As such, graduate students are able to contribute to the field more quickly than if they had to learn the theoretical and philosophical foundations of their field (164). See also Kuhn (1959, 1963) for more extended discussions.
While Feyerabend often appears to ground this claim in its intuitive force, he also cites a variety of empirical studies to support this view. It is extremely difficult to assess how this claim fares in light of more contemporary empirical findings, but some preliminary discussions on this topic suggest that the psychological benefits of theoretical diversity Feyerabend promises are both reliable and robust (Preston 2005).
Such admissions can be found in Feyerabend’s earlier writings as well (cf. Feyerabend 1962, pp. 72–75). Feyerabend did not just rely on intuitions and anecdotes, but argued that these theses were empirically supported as well, though they also had some minor drawbacks (cf. Feyerabend 1965b, 130–132, 1970b, fn. 42 107).
The quotes within this quote come from Mill, whom Feyerabend leaned on heavily in his later career. For a discussion of Feyerabend’s relationship to Mill, see Lloyd (1997).
Feyerabend repeats this principle verbatim in the paper version of Against Method (Feyerabend 1970b, p. 25).
Feyerabend’s definition of ‘theory’ is explicitly broad enough to include Kuhn’s notion of ‘paradigm’.
Additionally, Feyerabend argues that the significance of refuting instances of theories change as the result of the presence of an alternative explanation (cf. Feyerabend 1965b, fn. 7 106).
Motterlini (1999, pp. 3–4) provides a nice reconstruction of Feyerabend and Lakatos’ dialogue about the possibility of a ‘time limit.’ Ultimately, Feyerabend argues that the original motivation for tenacity, to provide ‘breathing space’ for theories, remains true at any stage in a theories development (cf. Feyerabend 1970d, p. 215).
Some, such as proponents of the strong programme, may intentionally conflate empirical questions about science and the content of science. While Feyerabend never directly addresses this question, his manner of discussing theories suggests that he does not reduce the content of those theories to beliefs of scientists. For a critical discussion of this, see Sismondo (1993) and Brown (2004).
Other interpretations include the ‘generative interpretation’ where abduction provides a means for creating hypothesis (Nickles 1985) and the ‘justificatory interpretation’ where abduction serves as a means to infer general fallible knowledge claims (Misak 2000). I will not take a stance on which interpretation most accurately reflects Peirce’s ‘real’ views here.
See Radnitzky (1987) for an explication of falsificationism in economic terms.
Kuhn (1963) recognizes and stresses this point. However, he argues that the paradigm in place is exclusive in that proliferation is only to be engaged in during periods of revolution.
Before detailing these observations, it should be noted that there are also serious limitations with these models such as the inability to forecast future scientific labor markets (Leslie and Oaxaca 1993). Most estimated cost models also presuppose that technological costs will decrease linearly making substantive assumptions about progress in technology that aren’t well studied empirically.
There are also several examples of cheap experiments which had major initial impacts which were then followed up with more sophisticated, and expensive, experiments. For example, V.S. Ramachandran’s early experiments on phantom limbs were done with cardboard boxes and ordinary mirrors that have now become refined in virtual reality experiments. Scherer (1966) suggests that this trend is fairly robust and is also hinted at in Peirce’s example of Wollaston.
It is unclear, to me at least, whether ‘duplications’ are the same as ‘replications.’ If they are, fields undergoing a ‘replication crisis’ may consider this to be a moot point.
See Stephan (1996, pp. 1216–1217) and the citations therein.
See Feyerabend (1964) for his criticisms of induction.
“If they contradict a well-confirmed point of view, then this indicates their usefulness as an alternative. Alternatives are needed for the purpose of criticism. Hence metaphysical systems that contradict observational results or well-confirmed theories are most welcome starting points of such criticism. Far from being misfired attempts at anticipating, or circumventing, empirical research that have been deservedly exposed by reference to experiment, they are the only means we possess for examining the assumptions implicit in our observational results” (Feyerabend 1965a, p. 183).
I have bracketed concerns about justice and egalitarianism from this paper, though such concerns are of the utmost importance.
Herbert et al. (2013) estimate that 550 working years went into proposals submitted to the NHMRC in March, 2012. This is on top of the opportunity cost of reviewer hours and the administrative costs of funding bodies.
I am willing to admit that there is some grey area around the line of the cranks. After all, some reviewers are harsher than others. I don’t think this grey area extends very far and, therefore, we can simplify out discussion by discussing a strict dichotomy between the cranks and reasonable research.
Though see Feyerabend (2011, pp. 45–46) for some qualifications.
In the case of the Human Brain Project, many non-computational approaches in the mind-brain sciences lost funding and it diverted resources to solely pursuing computational approaches (of a very specific style). See Shaw (2018, pp. 89–93) for a discussion of this.
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Special thanks to Kathleen Okruhlik, Chris Smeenk, Gillian Barker, Anjan Chakravarrty, Eric Desjardins, and two anonymous referees for their helpful feedback on earlier versions of this paper.
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Shaw, J. Feyerabend’s well-ordered science: how an anarchist distributes funds. Synthese 198, 419–449 (2021). https://doi.org/10.1007/s11229-018-02026-3
- Funding distribution
- Well-ordered science
- Economics of theory pursuit
- Values in science