Relative Realism: The Best of Both Worlds

Mizrahi, Moti

doi:10.1007/978-3-030-58047-6_6

Moti Mizrahi¹⁰

Part of the book series: Synthese Library ((SYLI,volume 431))

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Abstract

This chapter consists of a discussion of my own brand of scientific realism, namely, Relative Realism, first proposed in Mizrahi (Int Stud Phil Sci 27(4):393–407, 2013). Relative Realism provides a middle ground position between scientific realism and antirealism. I take Relative Realism to be a middle ground position between scientific realism and antirealism because it acknowledges the antirealist’s point that theory evaluation is comparative (see Chap. 5, Sect. 5.3 on the Underconsideration Argument) while, at the same time, retaining the realist’s optimism about science’s ability to get closer to the truth (that is, to make scientific progress). Unlike other realist positions, Relative Realism is not supported by Inferences to the Best Explanation (IBE), such as the Positive Argument (the so-called “no miracles” argument) for scientific realism (see Chap. 4, Sect. 4.1). Instead, the arguments for Relative Realism are deductive arguments from the comparative nature of theory evaluation and the relative nature of the predictive success of scientific theories, and so they are not subject to the criticisms leveled against many of the realist positions in the scientific realism/antirealism debate that rely on IBE. As such, they are arguments that proceed from premises that both scientific realists and antirealists could accept.

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Notes

1.
Some text from Mizrahi (2013) is reused in this chapter with permission from Taylor and Francis (license number 4793050820383).
2.
As Anjan Chakravartty (2017) observes, “it is widely held, not least by realists, that even many of our best scientific theories are likely false, strictly speaking.”
3.
As we have seen in Chap. 2, however, providing a precise formal (or even an informal) definition of approximate truth has proved to be very difficult. See Chap. 2, Sect. 2.1.
4.
According to Hasok Chang (2004, p. 52), “it is now widely agreed that observations are indeed affected by the theories we hold, thanks to the well-known persuasive arguments to that effect by Thomas Kuhn, Paul Feyerabend, Marry Hesse, Norwood Russell Hanson and even Karl Popper, as well as various empirical psychologists.” See also Bogen (2020).
5.
According to Stathis Psillos (1999, p. 76), “That the methods by which scientists derive and test theoretical predictions are theory-laden is undisputed. [...] All aspects of scientific methodology are deeply theory-informed and theory-laden.”
6.
Natalie Alana Ashton (2020, p. 83) makes a similar point about Michela Massimi’s (2018) Perspectival Realism. Perspectival Realism, which stems from the work of Ronald Giere (2006), is the view that there is a single way the world is (cf. the metaphysical stance/thesis of scientific realism in Chap. 2, Sect. 2.1), but there are many, equally legitimate ways in which one might come to know about that world. In that respect, Perspectival Realism seems more like Nicholas Rescher’s Relativistic Realism (see the main text) than Relative Realism, since truth or knowledge is relativized to a perspective taken by a knower.
7.
For more on the structure of IBE, see Psillos (2007).
8.
According to Igor Douven (2017), “philosophers of science have argued that abduction is a cornerstone of scientific methodology.”
9.
As we have seen in Chap. 5, Sect. 5.2, even though antirealists (specifically, constructive empiricists) reject IBE as an illegitimate form of inference in science, they sometimes fall back on IBE when giving a “positive argument” for their own antirealist position (specifically, Constructive Empiricism). See Mizrahi (2018).
10.
IDE is also distinct from what Alexander Bird (2007b, p. 425) calls “Inference to the Only Explanation” (IOE), which is an inference to “the truth of some hypothesis since it is the only possible hypothesis left unrefuted by the evidence. It is the form of inference advocated by Sherlock Holmes in his famous dictum ‘Eliminate the impossible, and whatever remains, however improbable, must be the truth’.”
11.
When philosophers of science talk about “novel predictions,” they typically mean a prediction that was not known to be true (or was expected to be true or false) at the time the theory was constructed.
12.
The phrase was coined by Gilbert Harman (1965).
13.
Daniel Campos (2011, p. 419) argues against the “tendency in the philosophy of science literature to link abduction to the inference to the best explanation (IBE), and in particular, to claim that Peircean abduction is a conceptual predecessor to IBE.”
14.
For example, Alan Baker (2010, pp. 37–38) defines IBE as “A method of reasoning, also known as abduction, in which the truth of an hypothesis is inferred on the grounds that it provides the best explanation of the relevant evidence. In general, inference to the best explanation (IBE) is an ampliative (i.e., non-deductive) method” (emphasis in original).
15.
For more on the structure of IBE, see Psillos (2007).
16.
According to Kuipers (2019, p. 316), empirical progress occurs “when it is concluded on the basis of ‘sufficient’ comparative testing that the new theory is persistently empirically more successful than the old one” (emphasis added). Accordingly, Kuipers acknowledges that empirical testing or theory evaluation in science is comparative. By contrast, his IDE arguments for Comparative Realism do not seem to require a similar sort of comparative evaluation of theories.
17.
Cf. Putnam’s (1975, p. 73) claim that scientific realism “is the only philosophy that doesn’t make the success of science a miracle” (emphasis added) and what Alexander Bird (2007b) calls “Inference to the Only Explanation” (IOE). See Chap. 4, Sect. 4.1.
18.
Or what Alexander Bird (2007b, p. 425) calls “Inference to the Only Explanation” (IOE).
19.
Kyle Stanford (2000) offers another antirealist explanation of the success of science in terms of “predictive similarity.” According to Stanford, the predictive success of an abandoned theory can be explained by pointing out how closely its predictions approximate those of the accepted theory. For example, we “explain the success of the (revised) Ptolemaic system of epicycles by pointing out how closely its predictions approximate those of the true Copernican hypothesis. Let us call this relationship the predictive similarity of the Ptolemaic system to the Copernican ” (Stanford 2000, p. 273).
20.
See also Gerald Doppelt (2005, p. 1080), who asks, “What novel predictions do scientific realists make?”
21.
According to Alan Guth’s (1997) theory of cosmic inflation, or the “inflationary universe,” the early universe has undergone a rapid exponential expansion the result of which was many “pocket” universes, or a “multiverse,” where “the physical conditions vary greatly from pocket to pocket” (Steinhardt and Turok 2007, p. 227).
22.
See Otávio Bueno’s (2016) discussion of skepticism in the context of philosophy of science.
23.
Darrell Rowbottom has argued against the epistemic account and in defense of the semantic account of scientific progress. See his (2010) and (2015).
24.
Seungbae Park has argued against the noetic account and in defense of the epistemic account of scientific progress. See his (2017b) and (2020).
25.
Another account of scientific progress that should be mentioned here is the “functional-internalist” account of scientific progress according to which “An episode [in science] shows scientific progress precisely when it achieves a specific goal of science, where that goal is such that its achievement can be determined by scientists at that time (e.g. solving scientific puzzles) ” (Bird 2008, p. 279). Thomas Kuhn’s account of scientific progress is a functional-internalist account of scientific progress, where “the solved problem is the basic unit of scientific progress” and “the aim of science is to maximize the scope of solved empirical problems” (Laudan 1977, p. 66). However, the current debate over the nature of scientific progress in contemporary philosophy of science has been focused mostly on the semantic, epistemic, and noetic accounts.
26.
Another antirealist who has found the analogy to evolution somewhat useful for understanding scientific development is Thomas Kuhn. James Marcum (2018) provides a useful discussion of the evolutionary elements in Kuhn’s philosophy of science.
27.
Admittedly, this is a matter of some debate in Putnam scholarship. This is partly because “Putnam’s internal realism appears as an alternative to a philosophical stance that he had stanchly defended, i.e., metaphysical realism” (Silva 2008, p. 13; emphasis added). Also, recall that Putnam himself made a Positive Argument for scientific realism, the so-called “no miracles” argument (see Chap. 4, Sect. 4.1). Since the focus of this book is the scientific realism/antirealism debate in contemporary philosophy of science, however, we can gloss over these earlier stages of the debate.
28.
That science is fallible is a view shared by not only most scientific realists but also many practicing scientists. For example, according to the physicist, Allan Franklin (2002, p. 1), “we must remember that science is fallible.”
29.
According to Sherri Roush (2010, p. 35), “There is no disagreement today that our science is fallible, that is, that we could be wrong, that our evidence is not strong enough to imply the truth of our theories. The issue is not whether we are fallible, but whether given that we are we can nevertheless have a right to confidence that our theories are true” (emphasis in original).

References and Further Readings

Ansdell, M., & Hanson, C. A. (2016). Biogeography, microbial. In R. M. Kliman (Ed.), Encyclopedia of evolutionary biology (Vol. I, pp. 179–185). Amsterdam: Elsevier.
Chapter Google Scholar
Ashton, N. A. (2020). Scientific perspectives, feminist standpoints, and non-silly relativism. In A. M. Crețu & M. Massimi (Eds.), Knowledge from a human point of view (pp. 71–85). Cham: Springer.
Chapter Google Scholar
Baker, A. (2010). Inference to the best explanation. In F. Russo & J. Williamson (Eds.), Key terms in logic (pp. 37–38). London: Continuum.
Google Scholar
Baxby, D. (1999). Edward Jenner’s inquiry: A bicentenary analysis. Vaccine, 17(4), 301–307.
Article Google Scholar
Ben-Menahem, Y. (2005). Introduction. In Y. Ben-Menahem (Ed.), Hilary Putnam (pp. 1–16). New York: Cambridge University Press.
Chapter Google Scholar
Bird, A. (2007a). What is scientific progress? Noûs, 41(1), 64–89.
Article Google Scholar
Bird, A. (2007b). Inference to the only explanation. Philosophy and Phenomenological Research, 74(2), 424–432.
Article Google Scholar
Bird, A. (2008). Scientific progress as accumulation of knowledge: A reply to Rowbottom. Studies in History and Philosophy of Science Part A, 39(2), 279–281.
Article Google Scholar
Bogen, J. (2020). Theory and observation in science. In E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy, Summer 2020 Edition. https://plato.stanford.edu/archives/sum2020/entries/science-theory-observation/
Bradley, D. (2009). Multiple universes and observation selection effects. American Philosophical Quarterly, 46(1), 61–72.
Google Scholar
Bueno, O. (2016). Epistemology and philosophy of science. In P. Humphreys (Ed.), The Oxford handbook of philosophy of science (pp. 233–251). New York: Oxford University Press.
Google Scholar
Campos, D. G. (2011). On the distinction between Peirce’s abduction and Lipton’s inference to the best explanation. Synthese, 180(3), 419–442.
Article Google Scholar
Chakravartty, A. (2017). Scientific realism. In E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy, Summer 2017 Edition. https://plato.stanford.edu/archives/sum2017/entries/scientific-realism/
Chang, H. (2004). Inventing temperature: Measurement and scientific progress. New York: Oxford University Press.
Book Google Scholar
Chang, H. (2011). The persistence of epistemic objects through scientific change. Erkenntnis, 75(3), 413–429.
Article Google Scholar
Cordero, A. (2000). Realism, and the case of rival theories without observable differences. In E. Agazzi & M. Pauri (Eds.), The reality of the unobservable: Observability, unobservability and their impact on the issue of scientific realism (pp. 191–206). Dordrecht: Kluwer Academic Publishers.
Chapter Google Scholar
Dellsén, F. (2016). Scientific progress: Knowledge versus understanding. Studies in History and Philosophy of Science, 56, 72–83.
Article Google Scholar
Dellsén, F. (2018a). Scientific progress, understanding, and knowledge: Reply to Park. Journal for General Philosophy of Science, 49(3), 451–459.
Article Google Scholar
Dellsén, F. (2018b). Scientific progress: Four accounts. Philosophy Compass, 13(11), e12525.
Article Google Scholar
Doppelt, G. (2005). Empirical success or explanatory success: What does current scientific realism need to explain? Philosophy of Science, 72(5), 1076–1087.
Article Google Scholar
Douven, I. (2017). Abduction. In E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy, Summer 2017 Edition. https://plato.stanford.edu/archives/sum2017/entries/abduction/
Fenner, F., Henderson, D. A., Arita, I., Ježek, Z., & Ladnyi, I. D. (1988). Smallpox and its eradication. Geneva: World Health Organization. http://apps.who.int/iris/bitstream/10665/39485/1/9241561106.pdf
Fetzer, J. H. (2010). Is evolution an optimizing process? In E. Eells & J. H. Fetzer (Eds.), The place of probability in science: In honor of Ellery Eells (1953–2006) (pp. 163–179). Dordrecht: Springer.
Chapter Google Scholar
Fine, A. (1986). Unnatural attitudes: Realist and instrumentalist attachments to science. Mind, 95(378), 149–179.
Article Google Scholar
Franklin, A. (2002). Selectivity and discord: Two problems of experiment. Pittsburgh: University of Pittsburgh Press.
Google Scholar
Frost-Arnold, G. (2010). The no-miracles argument for realism: Inference to an unacceptable explanation. Philosophy of Science, 77(1), 35–58.
Article Google Scholar
Garrison, T., & Ellis, R. (2016). Oceanography: An invitation to marine science (9th ed.). Boston: Cengage Learning.
Google Scholar
Giere, R. N. (2006). Scientific perspectivism. Chicago: The University of Chicago Press.
Book Google Scholar
Greene, B. (2011). The hidden reality: Parallel universes and the deep laws of the cosmos. New York: First Vintage Books.
Google Scholar
Guth, A. (1997). The inflationary universe: The quest for a new theory of cosmic origins. New York: Basic Books.
Google Scholar
Harman, G. H. (1965). The inference to the best explanation. The Philosophical Review, 74(1), 88–95.
Article Google Scholar
Hurley, P. J. (2006). A concise introduction to logic (9th ed.). Belmont: Wadsworth.
Google Scholar
Jenner, E. (1800). An inquiry into the causes and effects of the variolae vaccinae, a disease discovered in some of the western counties of England, particularly Gloucestershire, and known by the name of the Cow Pox (2nd ed.). London: Sampson Low.
Google Scholar
Kaufmann, S. H. E. (2008). Immunology’s foundation: The 100-year anniversary of the Nobel prize to Paul Ehrlich and Elie Metchnikoff. Nature Immunology, 9, 705–712.
Article Google Scholar
Kitcher, P. (1993). The advancement of science: Science without legend, objectivity without illusions. New York: Oxford University Press.
Google Scholar
Kitcher, P. (2002). Scientific knowledge. In P. K. Moser (Ed.), The Oxford handbook of epistemology (pp. 385–407). New York: Oxford University Press.
Chapter Google Scholar
Kuhn, T. S. (1962/1996). The structure of scientific revolutions. Chicago: The University of Chicago Press.
Google Scholar
Kuipers, T. A. F. (2019). Nomic truth approximation revisited. Cham: Springer.
Book Google Scholar
Kvanvig, J. (2003). The value of knowledge and the pursuit of understanding. New York: Cambridge University Press.
Book Google Scholar
Ladyman, J. (2002). Understanding philosophy of science. London: Routledge.
Google Scholar
Ladyman, J. (2007). Ontological, epistemological, and methodological positions. In T. Kuipers (Ed.), General philosophy of science: Focal issues (pp. 303–376). Amsterdam: Elsevier.
Chapter Google Scholar
Laudan, L. (1977). Progress and its problems: Towards a theory of scientific growth. Berkeley: University of California Press.
Google Scholar
Laudan, L. (2004). The epistemic, the cognitive, and the social. In P. Machamer & G. Wolters (Eds.), Science, values, and objectivity (pp. 14–23). Pittsburgh: University of Pittsburgh Press.
Chapter Google Scholar
Leplin, J. (1997). A novel defense of scientific realism. New York: Oxford University Press.
Google Scholar
Lim, D. (2003). Microbiology (3rd ed.). Dubuque: Kendall/Hunt Publishing Co.
Google Scholar
Lipton, P. (1993). Is the best good enough? Proceedings of the Aristotelian Society, 93(1), 89–104.
Article Google Scholar
Manson, N. A. (2009). The fine-tuning argument. Philosophy Compass, 4(1), 271–186.
Article Google Scholar
Marcum, J. A. (2018). Revolution or evolution in science? A role for the incommensurability thesis? In M. Mizrahi (Ed.), The Kuhnian image of science: Time for a decisive transformation? (pp. 155–173). London: Rowman and Littlefield.
Google Scholar
Massimi, M. (2004). Non-defensible middle ground for experimental realism: Why we are justified to believe in colored quarks. Philosophy of Science, 71(1), 36–60.
Article Google Scholar
Massimi, M. (2018). Four kinds of perspectival truth. Philosophy and Phenomenological Research, 96(2), 342–359.
Article Google Scholar
McMullin, E. (1992). The inference that makes science. Milwaukee: Marquette University Press.
Google Scholar
Mizrahi, M. (2012). Why the ultimate argument for scientific realism ultimately fails. Studies in History and Philosophy of Science Part A, 43(1), 132–138.
Article Google Scholar
Mizrahi, M. (2013). The argument from underconsideration and relative realism. International Studies in the Philosophy of Science, 27(4), 393–407.
Article Google Scholar
Mizrahi, M. (2018). The “positive argument” for constructive empiricism and inference to the best explanation. Journal for General Philosophy of Science, 49(3), 1–6.
Article Google Scholar
Musgrave, A. (2017). Strict empiricism versus explanation in science. In E. Agazzi (Ed.), Varieties of scientific realism: Objectivity and truth in science (pp. 71–94). Cham: Springer.
Chapter Google Scholar
Nickles, T. (2020). Historicist theories of scientific rationality. In E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy, Spring 2020 Edition. https://plato.stanford.edu/archives/spr2020/entries/rationality-historicist/
Niiniluoto, I. (2014). Scientific progress as increasing verisimilitude. Studies in History and Philosophy of Science Part A, 46, 73–77.
Article Google Scholar
Niiniluoto, I. (2018). Scientific progress. In J. Saatsi (Ed.), The Routledge handbook of scientific realism (pp. 187–199). New York: Routledge.
Google Scholar
Niiniluoto, I. (2019). Scientific progress. In E. N. Edward Zalta (Ed.), The Stanford encyclopedia of philosophy, Winter 2019 Edition. https://plato.stanford.edu/archives/win2019/entries/scientific-progress/
Park, S. (2015). Explanatory failures of relative realism. Epistemologia, 38(1), 16–28.
Google Scholar
Park, S. (2017a). Critiques of minimal realism. PRO, 92(2017), 102–114.
Google Scholar
Park, S. (2017b). Does scientific progress consist in increasing knowledge or understanding? Journal for General Philosophy of Science, 48(4), 569–579.
Article Google Scholar
Park, S. (2020). Scientific understanding, fictional understanding, and scientific progress. Journal for General Philosophy of Science, 51(1), 173–184.
Article Google Scholar
Popper, K. R. (1972). Objective knowledge: An evolutionary approach. Oxford: Clarendon Press.
Google Scholar
Prindle, D. F. (2009). Stephen Jay Gould and the politics of evolution. New York: Prometheus Books.
Google Scholar
Psillos, S. (1999). Scientific realism: How science tracks truth. London: Routledge.
Google Scholar
Psillos, S. (2007). The fine structure of inference to the best explanation. Philosophy and Phenomenological Research, 74(2), 441–448.
Article Google Scholar
Putnam, H. (1975). Mathematics, matter and method. New York: Cambridge University Press.
Google Scholar
Putnam, H. (1981). Reason, truth, and history. New York: Cambridge University Press.
Book Google Scholar
Putnam, H. (1994). In J. Conant (Ed.), Words and life. Cambridge, MA: Harvard University Press.
Google Scholar
Rescher, N. (1990). A useful inheritance: Evolutionary aspects of the theory of knowledge. Savage: Rowman and Littlefield.
Google Scholar
Rosenberg, A. (2000). Philosophy of science: A contemporary introduction. New York: Routledge.
Google Scholar
Roush, S. (2010). Optimism about the pessimistic induction. In P. D. Magnus & J. Busch (Eds.), New waves in philosophy of science (pp. 29–58). Houndsmill: Palgrave Macmillan.
Chapter Google Scholar
Rowbottom, D. P. (2010). What scientific progress is not: Against Bird’s epistemic view. International Studies in the Philosophy of Science, 24(3), 241–255.
Article Google Scholar
Rowbottom, D. P. (2015). Scientific progress without increasing verisimilitude: In response to Niiniluoto. Studies in History and Philosophy of Science Part A, 51, 100–104.
Article Google Scholar
Rowbottom, D. P. (2019). Extending the argument from unconceived alternatives: Observations, models, predictions, explanations, methods, instruments, experiments, and values. Synthese, 196(10), 3947–3959.
Article Google Scholar
Sankey, H. (2008). Scientific realism and the rationality of science. Hampshire: Ashgate.
Google Scholar
Silva, C. C. (2008). Introduction: Putnam and the notion of “reality”. In C. C. Silva, C. M. Vidal, & M. U. R. Monroy (Eds.), Following Putnam’s trail: on realism and other issues (pp. 9–16). Amsterdam: Rodopi.
Chapter Google Scholar
Simon, H. A. (1979). Models of thought. New Haven: Yale University Press.
Google Scholar
Stanford, K. P. (2000). An antirealist explanation of the success of science. Philosophy of Science, 67(2), 266–284.
Article Google Scholar
Steinhardt, P. J., & Turok, N. (2007). Endless universe: Beyond the big bang. New York: Doubleday.
Google Scholar
Topper, D. R. (2013). How Einstein created relativity out of physics and astronomy. Dordrecht: Springer.
Book Google Scholar
Tulodziecki, D. (2016). From zymes to germs: Discarding the realist/anti-realist framework. In R. Scholl & T. Sauer (Eds.), The philosophy of historical case studies (pp. 265–284). Basel: Springer.
Google Scholar
van Fraassen, B. C. (1980). The scientific image. New York: Oxford University Press.
Book Google Scholar
van Fraassen, B. C. (1983). Calibration: A frequency justification for personal probability. In R. S. Cohen & L. Laudan (Eds.), Physics, philosophy and psychoanalysis (pp. 295–319). Dordrecht: D. Reidel.
Chapter Google Scholar
van Fraassen, B. C. (1989). Laws and symmetry. Oxford: Clarendon Press.
Book Google Scholar
Wray, B. K. (2007). A selectionist explanation for the success and failures of science. Erkenntnis, 67(1), 81–89.
Article Google Scholar
Wray, B. K. (2008). The argument from underconsideration as grounds for anti-realism: A defence. International Studies in the Philosophy of Science, 22(3), 317–326.
Article Google Scholar
Wray, B. K. (2010). Selection and predictive success. Erkenntnis, 72(3), 365–377.
Article Google Scholar
Wray, B. K. (2012). Epistemic privilege and the success of science. Noûs, 46(3), 375–385.
Article Google Scholar
Wray, B. K. (2018). Resisting scientific realism. Cambridge: Cambridge University Press.
Book Google Scholar

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Moti Mizrahi

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Glossary

Antirealism: An agnostic or skeptical attitude toward the theoretical posits (that is, unobservables) of scientific theories. Antirealism comes in different varieties, such as Constructive Empiricism (see Chap. 3, Sect. 3.3) and Instrumentalism (see Chap. 3, Sect. 3.2).
Approximate truth: Closeness to the truth or truthlikeness. To say that a theory is approximately true is to say that it is close to the truth. According to some scientific realists, approximate truth is the aim of science. (See Chap. 2, Sect. 2.1).
Case study: A particular, detailed description of a scientific activity, a scientific practice, or an episode from the history of science. (See Chap. 2, Sect. 2.2).
Comparative truth: A relation between competing theories. To say that T₁ is comparatively true is to say that T₁ is closer to the truth than its competitors, T₂, T₃, ..., T_n. (See Sect. 6.1).
Constructive Empiricism: The view that the aim of science is to construct empirically adequate theories. A theory is empirically adequate when what the theory says about what is observable (by us) is true. (See Chap. 3, Sect. 3.3).
Empirical success: A scientific theory is said to be empirically successful just in case it is both explanatorily successful (that is, it explains natural phenomena that would otherwise be mysterious to us) and predictively successful (that is, it makes predictions that are borne out by observation and experimentation). (See Chap. 3, Sect. 3.1).
The epistemic account of scientific progress: An account of scientific progress according to which progress in science consists in the accumulation of scientific knowledge. (See Sect. 6.6).
The epistemic dimension (or stance) of scientific realism: The thesis that our best scientific theories, in particular, those that are empirically successful, are approximately true. (See Chap. 2, Sect. 2.1).
Epistemic Structural Realism (ESR): The view that the best scientific theories give us knowledge about the unobservable structure of the world. (See Chap. 3, Sect. 3.5).
Explanatory success: A scientific theory is said to be explanatorily successful just in case it explains natural phenomena that would otherwise be mysterious to us. (See Chap. 3, Sect. 3.1).
Hasty generalization: A fallacious inductive argument from a sample that is not representative of the general population that is the subject of the conclusion of the argument (because the sample is too small or cherry-picked rather than randomly selected). (See Chap. 2, Sect. 2.2).
Inference to the Best Explanation (IBE): An ampliative (or non-deductive) form of argumentation that proceeds from a phenomenon that requires an explanation to the conclusion that the best explanation for that phenomenon is probably true. (See Chap. 4, Sect. 4.1).
The metaphysical dimension (or stance) of scientific realism: The thesis that there are things out there in the world for scientists to discover and that those things out there in the world are independent of the human minds that study them. (See Chap. 2, Sect. 2.1).
Modus ponens: A form of argument with a conditional premise, a premise that asserts the antecedent of the conditional premise, and a conclusion that asserts the consequent of the conditional premise. That is, “if A, then B, A; therefore, B,” where A and B stand for statements. Modus ponens is a valid form of inference, and so an argument in natural language that takes this logical form is valid. On the other hand, the following logical form is invalid: “if A, then B, B; therefore, A.” It is known as the fallacy of affirming the consequent. (See Chap. 4, Sect. 4.1).
Modus tollens: A form of argument with a conditional premise, a premise that denies the consequent of the conditional premise, and a conclusion that denies the antecedent of the conditional premise. That is, “if A, then B, not B; therefore, not A,” where A and B stand for statements. Modus tollens is a valid form of inference, and so an argument in natural language that takes this logical form is valid. On the other hand, the following logical form is invalid: “if A, then B, not A; therefore, not B.” It is known as the fallacy of denying the antecedent. (See Chap. 5, Sect. 5.1).
The noetic account of scientific progress: An account of scientific progress according to which progress in science consists in increasing understanding. (See Sect. 6.6).
Predictive success: A scientific theory is said to be predictively successful just in case it makes predictions that are borne out by observation and experimentation. (See Chap. 3, Sect. 3.1).
Relative Realism: The view that, of a set of competing scientific theories, the more empirically successful theory is comparatively true, that is, closer to the truth relative to its competitors in the set. (See Sect. 6.1).
Scientific realism: An epistemically positive attitude toward those aspects of scientific theories that are worthy of belief. Scientific realism comes in different varieties, such as Explanationist Realism (see Chap. 3, Sect. 3.1), Entity Realism (see Chap. 3, Sect. 3.4), Structural Realism (see Chap. 3, Sect. 3.5), and Relative Realism (see Sect. 6.1).
Selectionist explanation for the success of science: An explanation for the empirical success of our best scientific theories according to which a selection process akin to natural selection by which fit species survive and unfit species go extinct explains the survival of successful theories and the extinction of unsuccessful theories. (See Chap. 4, Sect. 4.1).
The semantic account of scientific progress: An account of scientific progress according to which progress in science consists in increasing approximation to truth or the accumulation of scientific truth. (See Sect. 6.6).
Theoretical virtues: Properties of scientific theories, such as unification, testability, coherence, and simplicity, that make theories that have them good theories. Scientific realists tend to think of such properties as epistemic or truth conducive, whereas antirealists tend to think of them as merely pragmatic. (See Chap. 4, Sect. 4.1).

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Mizrahi, M. (2020). Relative Realism: The Best of Both Worlds. In: The Relativity of Theory. Synthese Library, vol 431. Springer, Cham. https://doi.org/10.1007/978-3-030-58047-6_6

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