Moti Mizrahi

In this paper, I reply to Seungbae Park’s (2020) critique of the view I defend in Chapter 6 of The Relativity of Theory: Key Positions and Arguments in the Contemporary Scientific Realism/Antirealism Debate (Cham: Springer, 2020), namely, Relative Realism. Relative Realism is the view that, of a set of competing scientific theories, the more predictively successful theory is comparatively true. Comparative truth is a relation between competing theories. So, to say that T1 is comparatively true is to say that T1 is closer to the truth than its competitors, T2, T3, ..., Tn. Park offers two arguments against Relative Realism. The first is an argument by analogy to NBA players, which is supposed to show that, contrary to what the relative realist argues, absolute judgments about the (approximate) truth and (predictive) success of competing theories are rationally justified. The second is what Park calls “The Argument from Double Spaces,” which is supposed to show that, contrary to what the relative realist argues, relative judgments about the (comparative) truth of competing theories are not rationally justified. I argue that Park’s arguments fail to do what he wants them to do.

The aim of this paper is to contribute to the debate over the nature of scientific progress in philosophy of science by taking a quantitative, corpus-based approach. By employing the methods of data science and corpus linguistics, the following philosophical accounts of scientific progress are tested empirically: the semantic account of scientific progress, the epistemic account of scientific progress, and the noetic account of scientific progress. Overall, the results of this quantitative, corpus-based study lend some empirical support to the epistemic and the noetic accounts over the semantic account of scientific progress, for they suggest that practicing scientists use the terms ‘knowledge’ and ‘understanding’ significantly more often than the term ‘truth’ when they talk about the aims or goals of scientific research in their published works. But the results do not favor the epistemic account over the noetic account, or vice versa, for they reveal no significant differences between the frequency with which practicing scientists use the terms ‘knowledge’ and ‘understanding’ when they talk about the aims or goals of scientific research in their published works.

This book offers a close and rigorous examination of the arguments for and against scientific realism and introduces key positions in the scientific realism/antirealism debate, which is one of the central debates in contemporary philosophy of science. On the one hand, scientific realists argue that we have good reasons to believe that our best scientific theories are approximately true because, if they were not even approximately true, they would not be able to explain and predict natural phenomena with such impressive accuracy. On the other hand, antirealists argue that the success of science does not warrant belief in the approximate truth of our best scientific theories. This is because the history of science is a graveyard of theories that were once successful but were later discarded. The author eventually settles on a middle ground position between scientific realism and antirealism called "relative realism."

In this paper, I propose that applying the methods of data science to “the problem of whether mathematical explanations occur within mathematics itself” (Mancosu 2018) might be a fruitful way to shed new light on the problem. By carefully selecting indicator words for explanation and justification, and then systematically searching for these indicators in databases of scholarly works in mathematics, we can get an idea of how mathematicians use these terms in mathematical practice and with what frequency. The results of this empirical study suggest that mathematical explanations do occur in research articles published in mathematics journals, as indicated by the occurrence of explanation indicators. When compared with the use of justification indicators, however, the data suggest that justifications occur much more frequently than explanations in scholarly mathematical practice. The results also suggest that justificatory proofs occur much more frequently than explanatory proofs, thus suggesting that proof may be playing a larger justificatory role than an explanatory role in scholarly mathematical practice.

It is a common view among philosophers of science that theoretical virtues (also known as epistemic or cognitive values), such as simplicity and consistency, play an important role in scientific practice. In this article, I set out to study the role that theoretical virtues play in scientific practice empirically. I apply the methods of data science, such as text mining and corpus analysis, to study large corpora of scientific texts in order to uncover patterns of usage. These patterns of usage, in turn, might shed some light on the role that theoretical virtues play in scientific practice. Overall, the results of this empirical study suggest that scientists invoke theoretical virtues explicitly, albeit rather infrequently, when they talk about models (less than 30%), theories (less than 20%), and hypotheses (less than 15%) in their published works. To the extent that they are mentioned in scientific publications, the results of this study suggest that accuracy, consistency, and simplicity are the theoretical virtues that scientists invoke more frequently than the other theoretical virtues tested in this study. Interestingly, however, depending on whether they talk about hypotheses, theories, or models, scientists may invoke one of those theoretical virtues more than the others.

In True enough,, Elgin argues against veritism, which is the view that truth is the paramount epistemic objective. Elgin’s argument against veritism proceeds from considering the role that models, idealizations, and thought experiments play in science to the conclusion that veritism is unacceptable. In this commentary, I argue that Elgin’s argument fails as an argument against veritism. I sketch a refutation by logical analogy of Elgin’s argument. Just as one can aim at gold medals and still find approximations to gold, such as silver and bronze medals, to be acceptable and honest achievements in competitive sports, one can aim at full truths as the paramount epistemic objective and still find approximations to truth, such as models and idealizations, to be acceptable and honest achievements in scientific inquiry.

When the phrase “playing God” is used in debates concerning the use of new technologies, such as cloning or genetic engineering, it is usually interpreted as a warning not to interfere with God’s creation or nature. I think that this interpretation of “playing God” arguments as a call to non-interference with nature is too narrow. In this paper, I propose an alternative interpretation of “playing God” arguments. Taking an argumentation theory approach, I provide an argumentation scheme and accompanying critical questions that capture the moral concerns expressed by “playing God” arguments. If I am right, then “playing God” arguments should be understood, not as a warning to leave God’s creation or nature alone, but rather as an invitation to think carefully about all the ways in which the use of new technologies could go seriously wrong.

There is an ongoing methodological debate in philosophy of science concerning the use of case studies as evidence for and/or against theories about science. In this paper, I aim to make a contribution to this debate by taking an empirical approach. I present the results of a systematic survey of the PhilSci-Archive, which suggest that a sizeable proportion of papers in philosophy of science contain appeals to case studies, as indicated by the occurrence of the indicator words “case study” and/or “case studies.” These results are confirmed by data mined from the JSTOR database on research articles published in leading journals in the field: Philosophy of Science, the British Journal for the Philosophy of Science (BJPS), and the Journal for General Philosophy of Science (JGPS), as well as the Proceedings of the Biennial Meeting of the Philosophy of Science Association (PSA). The data also show upward trends in appeals to case studies in articles published in Philosophy of Science, the BJPS, and the JGPS. The empirical work I have done for this paper provides philosophers of science who are wary of the use of case studies as evidence for and/or against theories about science with a way to do philosophy of science that is informed by data rather than case studies.

In this paper, I report the results of an empirical study, which was designed to test the following hypotheses: (H1) Many philosophers find scientism threatening because they see it as a threat to the future of philosophy as a major in colleges and universities; (H2) Many philosophers find scientism threatening because they see it as a threat to the soul or essence of philosophy as an a priori discipline. My results provide some empirical evidence in support of H2. These results are also in line with the results of other empirical studies that point to a methodological shift in philosophy from the armchair to the laboratory.

In this paper, I discuss an argument for the existence of God known as “The Argument from the Survival of the Jews.” This argument has the form of an Inference to the Best Explanation (IBE). It proceeds from the phenomenon of Jewish survival to the existence of God as the best explanation for this phenomenon. I will argue that, even if we grant that Jewish survival is a remarkable occurrence that demands an explanation, and even if we gloss over the difficulties in defining the terms “Jewish” and “survive,” the argument ultimately fails as an argument for the existence of God. It fails because it postulates divine supervision in order to explain Jewish endurance, but it doesn’t provide any clues as to what might be the underlying mechanism at work.

In a paper and a reply to critics published in _Informal Logic_, I argue that arguments from expert opinion are weak arguments. To appeal to expert opinion is to take an expert’s judgment that _p_ is the case as evidence for _p_. Such appeals to expert opinion are weak, I argue, because the fact that an expert judges that _p_ does not make it significantly more likely that _p_ is true or probable, as evidence from empirical studies on expert performance suggests. Unlike other critics of this argument, who take issue with the empirical evidence on expert performance, David Botting says that he wants to take issue with the premise that reliability is a necessary condition for the strength of appeals to expert opinion. I respond to Botting’s objections and argue that they miss their intended target. I also argue that his attempt to show that arguments from expert opinion are strong is unsuccessful.

In this paper, I respond to Sterpetti’s attempt to defend Kyle P. Stanford’s Problem of Unconceived Alternatives and his New Induction over the History of Science from my reductio argument outlined in Mizrahi :59–68, 2016a). I discuss what I take to be the ways in which Sterpetti has misconstrued my argument against Stanford’s NIS, in particular, that it is a reductio, not a dilemma, as Sterpetti erroneously thinks. I argue that antirealists who endorse Stanford’s NIS still face an absurd consequence of this argument, namely, that they should not believe their own brand of scientific antirealism.

In this paper, I argue that, if ‘the overrepresentation of Christian theists in analytic philosophy of religion is unhealthy for the field, since they would be too much influenced by prior beliefs when evaluating religious arguments’ (De Cruz and De Smedt (2016), 119), then a first step toward a potential remedy is this: analytic philosophers of religion need to restructure their analytical tasks. For one way to mitigate the effects of confirmation bias, which may be influencing how analytic philosophers of religion evaluate arguments in Analytical Philosophy of Religion (APR), is to consider other points of view. Applied to APR, this means considering religious beliefs, questions, and arguments couched in non-Christian terms. In this paper, I focus on Islam in particular. My aim is to show that Islam is a fertile ground of philosophical questions and arguments for analytic philosophers of religion to engage with. Engaging with questions and arguments couched in non-Christian terms would help make work in APR more diverse and inclusive of religions other than Christianity, which in turn would also be a first step toward attracting non-Christians to APR.

ABSTRACTThis discussion note aims to contribute to the ongoing debate over the nature of scientific progress. I argue against the semantic view of scientific progress, according to which scientific progress consists in approximation to truth or increasing verisimilitude. If the semantic view of scientific progress were correct, then scientists would make scientific progress simply by arbitrarily adding true disjuncts to their hypotheses or theories. Given that it is not the case that scientists could make scientific progress simply by arbitrarily adding true disjuncts to their hypotheses or theories, it follows that the semantic view of scientific progress is incorrect.

It is often said that ‘every logical truth is obvious’ (Quine 1970: 82), that the ‘axioms and rules of logic are true in an obvious way’ (Murawski 2014: 87), or that ‘logic is a theory of the obvious’ (Sher 1999: 207). In this chapter, I set out to test empirically how the idea that logic is obvious is reflected in the scholarly work of logicians and philosophers of logic. My approach is data-driven. That is to say, I propose that systematically searching for patterns of usage in databases of scholarly works, such as JSTOR, can provide new insights into the ways in which the idea that logic is obvious is reflected in logical and philosophical practice, i.e., in the arguments that logicians and philosophers of logic actually make in their published work.

In his latest attack, even though he claims to be a practitioner of “close reading” (Wills 2018b, 34), it appears that Wills still has not bothered to read the paper in which I defend the thesis he seeks to attack (Mizrahi 2017a), or any of the papers in my exchange with Brown (Mizrahi 2017b; 2018a), as evidenced by the fact that he does not cite them at all. This explains why Wills completely misunderstands Weak Scientism and the arguments for the quantitative superiority (in terms of research output and research impact) as well as qualitative superiority (in terms of explanatory, predictive, and instrumental success) of scientific knowledge over non-scientific knowledge.

In their reviews of The Kuhnian Image of Science: Time for a Decisive Transformation? (2018), both Markus Arnold (2018) and Amanda Bryant (2018) complain that the contributors who criticize Kuhn’s theory of scientific change have misconstrued his philosophy of science and they praise those who seek to defend the Kuhnian image of science. In what follows, then, I would like to address their claims about misconstruing Kuhn’s theory of scientific change. But my focus here, as in the book, will be the evidence (or lack thereof) for the Kuhnian image of science. I will begin with Arnold’s review and then move on to Bryant’s review.

In my (2017a), I defend a view I call Weak Scientism, which is the view that knowledge produced by scientific disciplines is better than knowledge produced by non-scientific disciplines. Scientific knowledge can be said to be quantitatively better than non-scientific knowledge insofar as scientific disciplines produce more impactful knowledge–in the form of scholarly publications–than non-scientific disciplines (as measured by research output and research impact). Scientific knowledge can be said to be qualitatively better than non-scientific knowledge insofar as such knowledge is explanatorily, instrumentally, and predictively more successful than non-scientific knowledge. Brown (2017a) raises several objections against my defense of Weak Scientism and I have replied to his objections (Mizrahi 2017b), thereby showing again that Weak Scientism is a defensible view. Since then, Brown (2017b) has reiterated his objections in another reply on SERRC. In this paper, I respond to Brown's objections, thereby showing once more that Weak Scientism is a defensible view.

In this paper, I argue that the “positive argument” for Constructive Empiricism (CE), according to which CE “makes better sense of science, and of scientific activity, than realism does” (van Fraassen 1980, 73), is an Inference to the Best Explanation (IBE). But constructive empiricists are critical of IBE, and thus they have to be critical of their own “positive argument” for CE. If my argument is sound, then constructive empiricists are in the awkward position of having to reject their own “positive argument” for CE by their own lights.

I have argued that Gettier cases are misleading because, even though they appear to be cases of knowledge failure, they are in fact cases of semantic failure. Atkins has responded to my original paper and I have replied to his response. He has then responded again to insist that he has the so-called “Gettier intuition.” But he now admits that intuitions are only defeasible, not conclusive, evidence for and/or against philosophical theories. I address the implications of Atkins’ admission in this paper and I again show that his attempts to revise Gettier’s original cases such that they do not involve semantic failures are unsuccessful.

In this paper, we set out to test empirically an idea that many philosophers find intuitive, namely that non-moral ignorance can exculpate. Many philosophers find it intuitive that moral agents are responsible only if they know the particular facts surrounding their action. Our results show that whether moral agents are aware of the facts surrounding their action does have an effect on people’s attributions of blame, regardless of the consequences or side effects of the agent’s actions. In general, it was more likely that a situationally aware agent will be blamed for failing to perform the obligatory action than a situationally unaware agent. We also tested attributions of forgiveness in addition to attributions of blame. In general, it was less likely that a situationally aware agent will be forgiven for failing to perform the obligatory action than a situationally unaware agent. When the agent is situationally unaware, it is more likely that the agent will be forgiven than blamed. We argue that these results provide some empirical support for the hypothesis that there is something intuitive about the idea that non-moral ignorance can exculpate.

In “What’s So Bad about Scientism?” (Mizrahi 2017), I argue that Weak Scientism, the view that “Of all the knowledge we have, scientific knowledge is the best knowledge” (Mizrahi 2017, 354; emphasis in original) is a defensible position. That is to say, Weak Scientism “can be successfully defended against objections” (Mizrahi 2017, 354). In his response to Mizrahi (2017), Christopher Brown (2017) provides more objections against Weak Scientism, and thus another opportunity for me to show that Weak Scientism is a defensible position, which is what I will do in this reply. In fact, I think that I have already addressed Brown’s (2017) objections in Mizrahi (2017), so I will simply highlight these arguments here.

This paper aims to contribute to the current debate about the status of the “Ought Implies Can” principle and the growing body of empirical evidence that undermines it. We report the results of an experimental study which show that people judge that agents ought to perform an action even when they also judge that those agents cannot do it and that such “ought” judgments exhibit an actor-observer effect. Because of this actor-observer effect on “ought” judgments and the Duhem-Quine thesis, talk of an “empirical refutation” of OIC is empirically and methodologically unwarranted. What the empirical fact that people attribute moral obligations to unable agents shows is that OIC is not intuitive, not that OIC has been refuted.