Simplicity, Not Simplism: In Defence of Occam's Razor as Scientific Necessity

1 Simplicity, Not Simplism † Formatting note: All quoted emphases are editorial. Working Paper - Version 2.2 (Dec 10, 2025) © 2025 Arseniy Vodopyanov. Licensed under CC BY 4.0 (Creative Commons Attribution). Simplicity, Not Simplism: In Defence of Occam’s Razor as Scientific Necessity Author: Arseniy Vodopyanov 1 Pre-print archived at SSRN Electronic Journal: http://doi.org/10.2139/ssrn.5570539 Pre-print indexed on PhilPapers: https://philpapers.org/rec/VODBFP 1 ORCID: 0009-0007-1900-6073 Email: [email protected] Affiliation: Center for Studies in Foundational Dualism 2 Simplicity, Not Simplism Abstract Occam’s Razor (also known as the principle of parsimony and ontological reductionism ) is regularly dismissed as an ornamental vestige—no longer worthy of its longstanding status as a fundamental scientific principle. An interpretation thereof called Verificational Simplicity or Blind Faith Parsimony is offered, which identifies the most scientific hypothesis as that yielding the fullest account of corresponding data while necessitating least verifiability-averse assumption. In light of such interpretation, Occam’s razor is argued to still be of paramount scientific importance and even to underlie virtually all integral scientific principles. Three corresponding arguments are offered. Argument 1 highlights the often-overlooked agility with which Occam’s Razor accords to latest data. Argument 2 shows that without parsimony to block ad hoc hypotheses , falsifiability is impossible—rendering science itself untenable. While argument 3 focuses upon the enormous burden of proof reasonable corresponding dismissals must shoulder. Keywords : Philosophy of Science, Parsimony, Verifiability, Falsifiability, Reductionism, Bayesian Probabilism 3 Simplicity, Not Simplism Introduction Dismissals As summarized by McFadden: “Occam’s razor... has recently been attacked as a cultural bias without rational foundation” (2023, 8). He adds: This criticism of the influence of Occam’s razor in science remains common. [It] has been attacked with claims that ‘its rhetorical purpose [is] as an old saw persuading us to champion the supposed virtue of simplicity.’ 44 In systems biology, for example, it has been claimed that because life is ‘irreducibly complex’ Occam’s razor has no role in model selection. 45 Recent popular science articles by influential authors have made similar claims… arguing that Occam’s razor represents the ‘tyranny of simple explanations’ 46 or that it is ‘appealing, widely believed, and deeply misleading’. 47 … Likely contribut[ing] to what has been described as ‘a worrying trend to favour unnecessarily complex interpretations’ 48 (2023, 11). Occam’s Razor Itself Oxford Reference’s Dictionary of Epidemiology (Porta, 2014) describes Occam’s Razor as: “The principle of scientific parsimony (parsimony in the sense of unwillingness to use unnecessary resources, [which is also sometimes referred to as scientific] frugality, austerity). An ancient principle often attributed to the philosopher… William of Ockham (c.1285-c.1349), who said:… assumptions to explain a phenomenon must not be multiplied beyond necessity.” The Routledge Probability, Choice, and Reason textbook by Prof. Leighton Vaughan Williams, elaborates thus: “Occam’s Razor has come to embody the method of eliminating unnecessary hypotheses. Essentially, [it] holds that the theory which explains all (or the most) while assuming the least is the most likely to be correct. … This is the principle of parsimony” (2021, 186). Williams (2021, 189) then expands: “Occam’s Razor… points to the simplest explanation that is consistent with the data available at a given time, but even so the simplest explanation may be ruled out as new data become available. This does not invalidate the Razor, which does not state that simpler theories are necessarily more true than more complex theories, but that when more than one theory explains the same data, the simpler should be accorded more probabilistic weight. So Occam’s Razor… is also consistent with multiplying entities which are in fact necessary to explain a phenomenon.” As expanded-upon in Argument 1 below, said data/evidence consistency point is absolutely crucial—leading Occam’s Razor to apply as enduringly to the McFadden-mentioned scientific field of “systems biology,” as to any other. 4 Simplicity, Not Simplism Three Apropos Corollary Principles The Williams-mentioned “probabilistic” application of Occam’s Razor, quickly proves a logical necessity. E.g., This is so because treating spectra as binaries at the cost of crucial corresponding data—is demonstrably at odds with being “consistent with the data available.” I.e., To yielding the fullest account thereof. Which leads naturally to an Occam’s Razor corollary known as Bayesian Probabilism/Inference . Two other apropos such corollary principles, are known as: a. Hitchens’s razor: “What [is] asserted without evidence can… be dismissed without evidence” (2007, 150). b. Sagan standard: “Extraordinary claims require extraordinary evidence” 2 (1979, 73). Argument 1: Data Consistency The most popular corresponding example is known simply as duck test . Dictionary.com briefly elaborates: “If it looks like a duck, swims like a duck, and quacks like a duck, says Occam’s razor, it’s probably a duck. Not a goose disguised as a duck that infiltrated the flock.” This is so because the added convolution/extraordinariness of that latter goose-infiltrator hypothesis, proves superfluous (and therefore unscientific) when the extraordinary evidence needed to substantiate it—is missing. Occam’s Razor compelling researchers to prioritize the more logically straightforward and therefore more scientific duck hypothesis instead. As keenly observed by Williams above however, this would cease to be the case if “new data became available” which revealed the goose hypothesis to be more logically straightforward after all. E.g., If the animal was actually verified to take off its duck costume; without which it indeed looked, acted and sounded like a goose. In light of this extraordinary new data, it is then the disguised-goose hypothesis that proves the more logically straightforward, less convoluted and therefore more scientific of the two. Because it would then be even more convoluted to claim that it was nonetheless a duck all along. Which would have had to successfully disguise itself as a goose who, in turn, disguised itself as a duck. Unless even more extraordinary evidence/data came to light, which rendered this even more-extraordinary hypothesis the most straightforward, plausible option. And so on. 2 As Tressoldi (2011, 1) notes, this principle is Sagan’s popular rewording of “Laplace’s principle[:] ‘the weight of evidence for an extraordinary claim must be proportioned to its strangeness’ (Gillispie et al., 1999).” 5 Simplicity, Not Simplism In either case, Occam’s Razor indeed remains ever helpful and intact. Simply reminding researchers to prioritize whichever hypothesis matches the available corresponding data most verifiably. Keeping the extent of blind assumption required to accept it, down to minimum and thus keeping said hypothesis as scientific as humanly possible. Which brings us to the notion that interpreting Occam’s Razor merely as preferring superficial simplicity—is simplistic and erroneous. A more accurate interpretation of its aim being Verificational Simplicity. I.e., Blind Faith Parsimony: the most scientific hypothesis is whichever yields fullest account of corresponding data, while necessitating least verifiability-averse assumption . This is a critical distinction that is too often overlooked in arguments against Occam’s Razor being scientifically fundamental. Argument 2: No Parsimony → No Falsifiability → No Science The following 3-step argument establishes corresponding fundamentality further yet. 1. No Falsifiability = No Science Despite occasional challenges (often in serving fashionable theories which themselves increasingly prove unfalsifiable), the notion that falsifiability is central to identifying pseudoscientific theories—is well founded and established in mainstream academia. As briefly demonstrated below. The New Dictionary of the History of Ideas ’ falsifiability entry (Nickles, 2025) states: “Falsifiability [has become] the most commonly invoked ‘criterion of demarcation’ of science from nonscience.” McFadden (2023, 8) adds: “Philosophy of science is rarely taught as a component of scientific education, but if pushed to identify the defining feature of their disciplines most scientists generally choose the principle of falsifiability (attributable to Karl Popper). 14 ” A prominent example of corresponding contextualization is Michael Ruse’s (Bertrand Russell Society award) tellingly titled 1982 “Creation Science Is Not Science”: “Religion [and] creationscience is not science [because genuine] science must be open to change, however confident one 6 Simplicity, Not Simplism may feel at present. Fanatical dogmatism is just not acceptable. … If the facts speak against a theory, then it must go. A [genuine] body of science must be falsifiable.” Stanford Encyclopedia of Philosophy (Thornton, 2023) expands upon the corresponding position thus: “If a theory is incompatible with possible empirical observations it is scientific; conversely, a theory which is compatible with all such observations… is unscientific.” Cambridge dictionary adds: “Falsifiable [means] able to be proved... false. [E.g.,] All good science must be falsifiable .” Why falsifiability is so scientifically-essential, is further delineated via Oxford Reference. According to which, science itself is: “The systematic study of the structure and behavior of the physical and natural world through observation, experimentation, and the testing of theories against the evidence obtained” (As cited in McHugh 2024, 88). Ergo, if a theory cannot be falsified when “test[ed] against evidence”, then it simply isn’t genuinely evidence-based and therefore—isn’t scientific. Particularly so, when testable alternatives exist (as is virtually always the case). 2. No Parsimony = No Falsifiability Per Popper (2008, 731): “Falsification of a theor[y] can always be avoided by introducing an auxiliary hypothesis.” These are also referred to as ad hoc hypotheses, immunizing stratagems or instances of special pleading. Schindler (2024, 71) elaborates: When introduced to save a theory, ad hoc hypotheses would reduce the theory’s falsifiability, and therefore ‘degrees of ad hoc-ness are related (inversely) to degrees[ 3 ] of testability and significance’ (Popper, 1959). … Ad hoc hypotheses are hypotheses which may make independent predictions, but for which there [is] no support. This view is incredibly popular… (Schaffner, 1974; Leplin, 1975; …). The following example is often invoked to motivate the view (e.g., Worrall, 2002): when an irregularity was discovered in the planet Uranus, Adams and Le Verrier in 1845-46 proposed that a new planet in the vicinity of Uranus might cause the discrepancy. At first, the ‘Neptune hypothesis’ was ad hoc, because it was introduced to save Newton’s theory. But after Neptune was discovered, 3 Once again, it being far more accurate to assess such factors in “degrees” rather than in simplistic binary terms. 7 Simplicity, Not Simplism the hypothesis was independently confirmed and thus lost its ad hoc status. 15 Or as eloquently rephrased in the Wikipedia Occam’s Razor entry 4 : “Even if some increases in complexity are sometimes necessary, there still remains a justified general bias toward the simpler of two competing explanations. To understand why, consider that for each accepted explanation of a phenomenon, there is always an infinite number of possible, more complex, and ultimately incorrect, alternatives. This is so because one can always burden a failing explanation with an ad hoc hypothesis.. prevent[ing it] from being falsified. … This endless supply of elaborate competing explanations… cannot be technically ruled out – except by using Occam’s razor.” I.e., In lieu of the data/evidence needed to defend a particular theory, “one can always [prop it up] with an ad hoc hypothesis”. E.g., Dinosaur fossils contradict the Biblical account, prompting some Christians to famously claim that said fossils were planted by God himself to test humanity’s faith. Which is ad hoc because it relies on a deeply-selective survey of corresponding data, while necessitating a vast comparative measure of verifiability-averse assumption . A maneuver that is no more scientific than invoking that disguised-goose hypothesis on little to no corresponding evidence. 3. Ergo: No Parsimony = No Science Given the two preceding points, it should indeed be clear that “endless… elaborate competing [ad hoc] hypotheses, cannot be technically ruled out – except by using Occam ’ s razor ” in some form. I.e., That unless researchers first employ such parsimony to help weigh scientific probabilities against one another—all hypotheses become unfalsifiable; and as such—unscientific. Leaving no means to objectively discern more scientific, straightforward and likely explanations from their more unscientific, convoluted and unlikely kin; to distinguish needless blind faith from that, asyet scientifically unavoidable. 4 As with Dictionary.com, Wikipedia is used here as a tertiary source due primarily to the soundness of its phrasing. The underlying concepts having been (a) established elsewhere in this paper via both basic reasoning and primary sources, as well as (b) established via corresponding sources cited by Wikipedia itself (e.g., Stanovich, 2007, 19–33; Carroll 2008; Swinburne 1997). 8 Simplicity, Not Simplism Argument 3: Burden Of Proof Key Challenge The Blind Faith Parsimony interpretation of Occam’s Razor moreover leaves critics to tackle questions like: a. After centuries of study, can so much as a single example be clearly identified where abovedetailed pitfalls are avoided and yet the corresponding principle fails? I.e., Is there a single hypothesis which yields fullest account of corresponding data while necessitating least verifiability-averse assumption and yet proves less scientific than the alternative(s)? So prior to new corresponding data becoming available? b. Even if such a case can be corroborated, can it reasonably be characterized as not an exception that proves the rule ? c. If the answer to ‘b’ (much less ‘a’) above is ‘no’—does this leave any reasonable room for doubt over whether such parsimony is a core scientific principle? Corresponding dismissals need demonstrate not only that putative exceptions are genuine and significant, but also: i. That a viable alternative avoids comparatively more thereof. ii. That this alternative either differs in essence from said principle or is even more fundamental. Otherwise it could not constitute a genuine alternative to Occam’s razor, but only another corollary and/or complement thereto at most. Lesser Challenge Let us lastly consider how exceedingly unlikely the key challenge above is to be reasonably met —given how difficult even lesser corresponding challenges can prove. E.g., The challenge of identifying so much as a single integral scientific value, which (in its optimal form) is not underlain by such parsimony. I.e., A single integral scientific value, which does not appear further along the logical path initiated thereby. From falsifiability, verifiability, Hitchens’s Razor, Sagan Standard and Bayesian probability as shown above, to other such values like coherence, predictive power and explanatory scope. A hypothesis scoring poorly on either such front, 9 Simplicity, Not Simplism invariably proving to be less capable of yielding a full account of corresponding data and/or of minimizing verifiability-averse assumption. Conclusion Only misinterpretation and misuse of Occam’s Razor proves antithetical to genuine science. Such as conflating the verificational simplicity preferred thereby with simplism (e.g., ignoring extraordinary counterevidence so as to artificially bolster simplistic explanations). Whereas genuine Occam’s Razor expressly forbids such misuse, proving itself essential to genuine science after all.