Models are indispensable tools of scientific inquiry, and one of their main uses is to improve our understanding of the phenomena they represent. How do models accomplish this? And what does this tell us about the nature of understanding? While much recent work has aimed at answering these questions, philosophers' focus has been squarely on models in empirical science. I aim to show that pure mathematics also deserves a seat at the table. I begin by presenting two (...) cases: Cramér’s random model of the prime numbers and the function field model of the integers. These cases show that mathematicians, like empirical scientists, rely on unrealistic models to gain understanding of complex phenomena. They also have important implications for some much-discussed theses about scientific understanding. First, modeling practices in mathematics confirm that one can gain understanding without obtaining an explanation. Second, these cases undermine the popular thesis that unrealistic models confer understanding by imparting counterfactual knowledge. (shrink)

Under the independence and competence assumptions of Condorcet’s classical jury model, the probability of a correct majority decision converges to certainty as the jury size increases, a seemingly unrealistic result. Using Bayesian networks, we argue that the model’s independence assumption requires that the state of the world (guilty or not guilty) is the latest common cause of all jurors’ votes. But often – arguably in all courtroom cases and in many expert panels – the latest such common cause is (...) a shared ‘body of evidence’ observed by the jurors. In the corresponding Bayesian network, the votes are direct descendants not of the state of the world, but of the body of evidence, which in turn is a direct descendant of the state of the world. We develop a model of jury decisions based on this Bayesian network. Our model permits the possibility of misleading evidence, even for a maximally competent observer, which cannot easily be accommodated in the classical model. We prove that (i) the probability of a correct majority verdict converges to the probability that the body of evidence is not misleading, a value typically below 1; (ii) depending on the required threshold of ‘no reasonable doubt’, it may be impossible, even in an arbitrarily large jury, to establish guilt of a defendant ‘beyond any reasonable doubt’. (shrink)

I give a defense of the Massive Modularity hypothesis: the view that the mind is composed of discrete, encapsulated, informationally isolated computational structures dedicated to particular problem domains. This view contrasts with Psychological Rationalism: the view that mental structures take the form of unencapsulated representational items, all available as inputs to one domain-general computational processor. I argue that although Psychological Rationalism is in principle able to overcome the `intractability objection', the view must borrow many features of a massively modular architecture (...) in order to do so, that although it can, in principle, overcome the `optimality objection', the way it does so does not correlate with the way we think, and that although it can, in principle, respond to the `argument from biology', it cannot do so without advancing an unrealistic and unsupported account of cognitive evolution. (shrink)

Ecological neutral theory has been controversial as an alternative to niche theory for explaining community structure. Neutral theory, which explains community structure in terms of ecological drift, is frequently charged with being unrealistic, but commentators have usually not provided an account of theory or model realism. In this paper, I propose a framework for comparing the “realism” or accuracy of alternative theories within a domain with respect to the extent to which the theories abstract and idealize. Using this framework (...) I argue, contrary to most previous commentators, that neutral and niche theories are similarly realistic. Realism cannot provide a basis for accepting or rejecting either type of theory; instead, community ecologists should continue working with a plurality of models. While theoretical unification may become possible, we should treat a plurality of complementary, partial models as the expected situation within community ecology. (shrink)

There is a striking contrast between the significance of Harold Hotelling’s contribution to industrial economics and the fact that his location model was invalid, unrealistic and non-robust. It is difficult to make sense of the explanatory value of Hotelling’s model based on philosophical accounts that emphasize logical validity, representational adequacy, and robustness as determinants of explanatory value. However, these accounts are misleading because they overlook the context within which the explanatory value added of a model is apprehensible. We present (...) Hotelling’s model in its historical context and show why it is an important and explanatory model despite its apparent deficiencies. (shrink)

Coherence and correspondence are classical contenders as theories of truth. In this paper we examine them instead as interacting factors in the dynamics of belief across epistemic networks. We construct an agent-based model of network contact in which agents are characterized not in terms of single beliefs but in terms of internal belief suites. Individuals update elements of their belief suites on input from other agents in order both to maximize internal belief coherence and to incorporate ‘trickled in’ elements of (...) truth as correspondence. Results, though often intuitive, prove more complex than in simpler models (Hegselmann & Krause 2002, 2006; Grim, Singer, Reade & Fisher 2015). The optimistic finding is that pressures toward internal coherence can exploit and expand on small elements of truth as correspondence is introduced into epistemic networks. Less optimistic results show that pressures for coherence can also work directly against the incorporation of truth, particularly when coherence is established first and new data is introduced later. (shrink)

I distinguish several doctrines that economic methodologists have found attractive, all of which have a positivist flavour. One of these is the doctrine that preference assignments in economics are just shorthand descriptions of agents' choice behaviour. Although most of these doctrines are problematic, the latter doctrine about preference assignments is a respectable one, I argue. It doesn't entail any of the problematic doctrines, and indeed it is warranted independently of them.

Recent work in cognitive modelling has found that most of the data that has been cited as evidence for the dual-process theory (DPT) of reasoning is best explained by non-linear, “monotonic” one-process models (Stephens et al., 2018, 2019). In this paper, I consider an important caveat of this research: it uses models that are committed to unrealistic assumptions about how effectively task conditions can isolate Type-1 and Type-2 reasoning. To avoid this caveat, I develop a coordinated theoretical, (...) experimental, and modelling strategy to better test DPT. First, I propose that Type-1 and Type-2 reasoning are defined as reasoning that precedes and follows metacognitive control, respectively. Second, I argue that reasoning that precedes and follows metacognitive control can be effectively isolated using debiasing paradigms that manipulate metacognitive heuristics (e.g., processing fluency) to prevent or trigger metacognitive control, respectively. Third, I argue that monotonic modelling can allow us to decisively test DPT only when we use them to analyse data from this particular kind of debiasing paradigm. (shrink)

In the social sciences, within the explanatory paradigm of structural individualism, a theory of action – like rational choice theory – models how individuals behave and interact at the micro level in order to explain macro observations as the aggregation of these individuals actions. A central epistemological issue is that such theoretical models are stuck in a dilemma between falsity of their basic assumptions and triviality of their explanation. On the one hand, models which have a great (...) empirical success often rest on unrealistic or even knowingly false assumptions; on the other hand, more complex models, with additional more realistic hypotheses, can (trivially) adapt to a wide range of situations and thus loose their explanatory power. Our purpose here is epistemological and consists in wondering to which extent demanding realistic assumptions in such cases is a relevant criterion with respect to the acceptance of a given explanatory model. Via an analogical reasoning with physics, we argue that this criterion seems too strong and actually irrelevant. General physical principles are not just idealized or unrealistic, they can also be formulated in many different yet equivalent ways which do not imply the same fundamental unobservable entities or phenomena. However, the classification of phenomena that such principles allow to highlight does not depend, at the end, on any particular formulation of these basic assumptions. This suggests that some hypotheses in theoretical models are actually not genuine empirical statements that could be independently tested but only substrates of modeling embodying a classification principle. Thus, we develop a structural invariance criterion that we then apply to rational choice models in the social sciences. We argue that this criterion allows to escape from the epistemological dilemma without condemning formal approaches like rational choice theory for their lack of realisticness nor being stuck to any antirealist viewpoint. (shrink)

The Austrian School seems to remain outside the debate on the realism of economic models. In principle, given the association of the term “model” with the Chicago School, and also for understanding that Hayek had critized the model of perfect competition as unrealistic. Even though in previous opportunities we showed how the theory of market as a process could be understood as the model of the Austrian School, and that Hayek’s criticism to the model of perfect competition was (...) not so much of unrealistic, but that it was wrongly stated (Zanotti & Borella, 2015), and we developed the ontological foundation of the model in Hayek’s thought (Borella, 2019), in this paper we will show how it is posible to compare pattern predictions with models, and how in this sense, the Austrian School, also seems to get near, even without sufficiently noticing it, to the discussion on models in economics and their realism. Keywords: Realism of models- Hayek- pattern predictions-models . (shrink)

To believe that every single scientist ought to be individually engaged in ethical thinking in order for science to be responsible at a collective level may be too demanding, if not plainly unrealistic. In fact, ethical labor is typically distributed across different kinds of scientists within the scientific community. Based on the empirical data collected within the Horizon 2020 ‘RRI-Practice’ project, we propose a classification of the members of the scientific community depending on their engagement in this collective activity. (...) Our classification offers, on the one hand, a model of how the ethical aspects of science are taken into consideration by scientists and, on the other, some indications on how to institutionalize ethics in science. (shrink)

In this chapter, I describe my “post-diagnosis” experiences as the parent of an autistic child, those years in which I tried, but failed, to make sense of the overwhelming and often nonsensical information I received about autism. I argue that immediately after being given an autism diagnosis, parents are pressured into making what amounts to a life-long commitment to a therapy program that (they are told) will not only dramatically change their child, but their family’s financial situation and even their (...) entire mode of existence. Moreover, despite information overload, many treatment programs for autism rely on empty jargon and make completely unrealistic promises, so parents are left feeling overwhelmed and panicked. Even well respected therapy programs encourage parents to spend liberally. Indeed, autistic therapists, who help construct what I refer to as the Culture of Autism, advise parents to commit to a minimum of 35 to 45 hours of intensive therapy every week. The implications are clear: for a parent who works full-time, their autistic child becomes a second full-time job. Autism is big business right now, and therapists are pushing parents to the brink of desperation. So it is not too surprising that there is a desperate cry for a more permanent solution—which is why researchers seek to cure autism. But there are two ways to conceptualize cure. A Therapeutic Cure model (TC) conceives of a cure as a beneficial treatment for the patient that eliminates or ameliorates the harms of the disease or condition. But the notion of a therapeutic cure for autism is highly implausible, given the complexities of autism. Indeed, at this point, the vast majority of researchers have come to the conclusion that the idea of a therapeutic cure for autism is simply a non-starter. Therefore the bulk of research seeking a cure for autism focuses instead on a second approach, which I refer to as the Negative Eugenics Cure model (NEC). With this model, the intention is to eliminate the disease or condition without regard for the health or well-being of the organism carrying the disease or condition. So, with regard to autism, researchers are focusing on identifying genetic markers for autism that can be detected in utero, or in embryos, so that autistic fetuses can be eliminated and autism eradicated by preventing the existence of autistic individuals. I review both models and argue that both fail to provide convincing arguments that the “solution” either offers is desirable. Both rest on the assumption that autism renders a life not worth living which, all things considered, is false. Instead of pushing to cure autism, an idea pervasive in this Culture of Autism, I contend that autistics are individuals with lives worth living. Moreover, rather than expend millions on research to search for the means to eliminate autism, we should instead expend our resources to ensure autistic individuals have access to support they may need. If the phenomenology of autism were better understood and appreciated, the panicked demand for a cure for autism might abate and perhaps autism could be seen as having value in and of its own right. (shrink)

This article explores the potential utility of the theory of Holism as developed by South African philosopher, British Commonwealth statesman and military leader, Jan Smuts, for philosophical counselling or practice. Central to the philosophical counseling process is philosophical counsellors or practitioners applying the work of philosophers to inspire, educate and guide their counselees in dealing with life problems. For example, Logic-Based Therapy, a method of philosophical counselling developed by Elliot Cohen, provides a rational framework for confronting problems of living, where (...) the counselor helps the counselee find an uplifting philosophy that promotes a guiding virtue that acts as an antidote to unrealistic and often self-defeating conclusions derived from irrational premises. We present the argument that Holism is one such uplifting philosophy which can be of utility to philosophical counselors or practitioners to help their counselees with confronting problems of living. Furthermore, we argue that Smuts’ articulation of freedom can act as a guiding virtue within this uplifting philosophy of Holism in accordance with the methodology of LBT. Smuts’ contribution to philosophy and psychology is arguably inadequately credited, and for this reason, and to the best of our knowledge, Smuts’ theory of Holism has yet to be discussed in the context of philosophical counseling or practice. Given these omissions, we begin this article with a discussion of his influence on 20th Century Anglo-American psychology. We then provide a brief historical context, and an introduction to the central argument of Smuts’ Holism, as well as a brief overview of the origins of Smut’s Holism and an introduction to his book Holism and Evolution. In the remainder of the article, we discuss several foundational concepts that underlie Smuts’ theory of Holism, as articulated and developed in his book Holism and Evolution, to substantiate our arguments. We conclude by highlighting the limitations of our article, limitations to Smuts’ model, and the challenges inherent in the use of a now largely antiquated theory, even by Smuts’ own admission nineteen years after its publication, for the purposes of contextualizing and substantiating the arguments and recommendations presented herein. (shrink)

In this paper I provide a frequentist philosophical-methodological solution for the stopping rule problem presented by Lindley & Phillips in 1976, which is settled in the ecological realm of testing koalas’ sex ratio. I deliver criteria for discerning a stopping rule, an evidence and a model that are epistemically more appropriate for testing the hypothesis of the case studied, by appealing to physical notion of probability and by analyzing the content of possible formulations of evidence, assumptions of models and (...) meaning of the ecological hypothesis. First, I show the difference in the evidence taken into account in different frequentist sampling procedures presented in the problem. Next, I discuss the inapplicability of the Carnapian principle of total evidence in deciding which formulation of evidence associated with a given sampling procedure and statistical model is epistemically more appropriate for testing the hypothesis in question. Then I propose a double-perspective (evidence and model) frequentist solution based on the choice of evidence which better corresponds to the investigated ecological hypothesis, as well as on the choice of a model that embraces less unrealistic ontological assumptions. Finally, I discuss two perspectives of the stopping rule dependence. (shrink)

Aims and Objectives The purpose of this paper was to clarify the concept of ethical conflict in nursing and highlight the importance of tackling this issue. -/- Background Ethical conflict is on the rise in the nursing context. It is associated with the compromise of nurses' well-being and patient care. However, there is no thorough conceptual understanding of this concept. -/- Design Concept analysis. -/- Methods Databases (PubMed, PsycINFO, CINAHL, Scopus, Embase, Web of Science and SocINDEX) were searched for studies (...) between 1984 and 2021. Both quantitative and qualitative studies related to ethical conflict in nursing were included. Walker and Avant's method of concept analysis was used to identify the defining attributes, antecedents and consequences of the concept of ethical conflict in nursing. We followed the PRISMA-ScR checklist to report the study. -/- Results Thirty studies were included for conceptualization. Defining attributes were divided into four categories: (1) emotional responses, (2) incompatible values, (3) competing interests and (4) ambiguous obligations. The antecedents were (1) ethical sensitivity, (2) negative ethical climate, (3) insufficient authority, (4) unrealistic expectations, (5) poor collaboration and (6) inadequate resources. The consequences were identified as (1) moral residue, (2) loss of identity, (3) professional burnout and (4) poor patient care. -/- Conclusions A unified conceptual model of ethical conflict in nursing shed light on the ethical issues nurses might come across in practice. Despite the fact that ethical conflict is inherently negative, we conceptualised this concept as a neutral fact and an opportunity for nursing action. The construct identification provides basis for both the development of practice and the development of staff support and education. (shrink)

In IEEE 802.15.4 standard for low-power low-range wireless communications, only one channel is employed for transmission which can result in increased energy consumption, high network delay and poor packet delivery ratio (PDR). In the subsequent IEEE 802.15.4-2015 standard, a Time-slotted Channel Hopping (TSCH) mechanism has been developed which allows for a periodic yet fixed frequency hopping pattern over 16 different channels. Unfortunately, however, most of these channels are susceptible to high-power coexisting Wi-Fi signal interference and to possibly some other ISM-band (...) transmissions. This interference manifests itself in the form of the presence/absence of other devices with either or both static and dynamic channel selection policies. In order to isolate channels with undesirable conditions, blacklisting mechanisms are defined to adapt the channel hopping process. However, the existing solutions which form blacklists unrealistically assume that the statistical model of the external interference remains fixed, and do not vary over time. In this paper, we realistically assume that the impact of external interferes on 802.15.4 may generally follow a non-stationary pattern, and accordingly formulate the adaptive channel hopping problem as a Dynamic Multi-Armed Bernoulli Bandit (Dynamic MABB) process from the machine learning theory. We then propose an online learning algorithm with track-ability properties for computing an adaptive hopping policy. Simulations confirm that when the statistics of the external interference has a switching regime, the proposed solution outperforms the previous schemes in terms of both energy efficiency as well as two important KPIs for TSCH-based networks, i.e., PDR and latency. (shrink)

This thesis-on macro-ontology, physics, logic, and metalogical principles presents the findings, results, theorems, and metatheory that correct long-standing defects and deficiencies of current standard model (SM) physics and cosmology. It eliminates artificial SM anomalies, paradoxes, logical fallacies, absurdities, and conflicts with reality (and the findings of plasma physics, astronomy, ontology, epistemics, etc.). New theorems and metatheorems eliminate the illogic maintaining distortions of post-Einsteinian physics, its wildly speculative conjectures, and shibboleths (its unrealistic assumptions commonly accepted as facts). In critiques of (...) misperceptions, misconceptions and misinterpretations of observations and data, this work exposes the common failure to recognize the severe deficiencies of theory, science, ontology, and metamathematics. New results prove that chronic failure to differentiate realities from theorems, hypotheses, conjectures, opinions, and beliefs prevents progress to better physics and STEM education. Therefore, this work also enables resolution of the long-standing logical incongruency of physics, psychology, cognitive science, and philosophy, especially ontology. So, the facts and proofs presented here can enable a new era of discovery, creativity, and technological progress. (shrink)

This thesis-on macro-ontology, physics, logic, and metalogical principles presents the findings, results, theorems, and metatheory that correct long-standing defects and deficiencies of current standard model (SM) physics and cosmology. It eliminates artificial SM anomalies, paradoxes, logical fallacies, absurdities, and conflicts with reality (and the findings of plasma physics, astronomy, ontology, epistemics, etc.). New theorems and metatheorems eliminate the illogic maintaining distortions of post-Einsteinian physics, its wildly speculative conjectures, and shibboleths (its unrealistic assumptions commonly accepted as facts). In critiques of (...) misperceptions, misconceptions and misinterpretations of observations and data, this work exposes the common failure to recognize the severe deficiencies of theory, science, ontology, and metamathematics. New results prove that chronic failure to differentiate realities from theorems, hypotheses, conjectures, opinions, and beliefs prevents progress to better physics and STEM education. Therefore, this work also enables resolution of the long-standing logical incongruency of physics, psychology, cognitive science, and philosophy, especially ontology. So, the facts and proofs presented here can enable a new era of discovery, creativity, and technological progress. (shrink)

This thesis-on macro-ontology, physics, logic, and metalogical principles presents the findings, results, theorems, and metatheory that correct long-standing defects and deficiencies of current standard model (SM) physics and cosmology. It eliminates artificial SM anomalies, paradoxes, logical fallacies, absurdities, and conflicts with reality (and the findings of plasma physics, astronomy, ontology, epistemics, etc.). New theorems and metatheorems eliminate the illogic maintaining distortions of post-Einsteinian physics, its wildly speculative conjectures, and shibboleths (its unrealistic assumptions commonly accepted as facts). In critiques of (...) misperceptions, misconceptions and misinterpretations of observations and data, this work exposes the common failure to recognize the severe deficiencies of theory, science, ontology, and metamathematics. New results prove that chronic failure to differentiate realities from theorems, hypotheses, conjectures, opinions, and beliefs prevents progress to better physics and STEM education. Therefore, this work also enables resolution of the long-standing logical incongruency of physics, psychology, cognitive science, and philosophy, especially ontology. So, the facts and proofs presented here can enable a new era of discovery, creativity, and technological progress. (shrink)

It is argued that rather than a well defined F-Twist, Milton Friedman’s “Methodology of positive economics” offers an F-Mix: a pool of ambiguous and inconsistent ingredients that can be used for putting together a number of different methodological positions. This concerns issues such as the very concept of being unrealistic, the goal of predictive tests, the as-if formulation of theories, explanatory unification, social construction, and more. Both friends and foes of Friedman’s essay have ignored its open-ended unclarities. Their removal (...) may help create new common ground for more focused debate in economics. Here I show how F53 can be reread/rewritten as a socially constructivist fallibilist, and realist statement – in contrast to the received instrumentalist interpretation. (shrink)

In this paper, we develop an analysis of unrealistic fiction that captures the everyday sense of ‘unrealistic’. On our view, unrealistic fictions are a species of inconsistent fictions, but fictions for which such inconsistency, given the supporting role we claim played by genre, needn’t be a critical defect. We first consider and reject an analysis of unrealistic fiction as fiction that depicts or describes unlikely events; we then develop our own account and make an initial statement (...) of it: unrealistic fictions are those that invite us to believe something false. We further develop this account and restate it in terms of the notion of “import-export inconsistency.” That is, unrealistic fictions invite us to import certain propositions true in the actual world then invite us to export propositions entailing the negation of those imported. Finally, we consider whether for fiction being unrealistic is always an aesthetic flaw. (shrink)

Suppose justice depends on some very unlikely good behavior. In that case the true (or correct, or best) theory of justice might have no practical value. But then, what good would it be? I consider analogies with science and mathematics in order to test various ways of tying their the value of intellectual work to practice, though I argue that these fail. If their value, or that of some political theory, is not practical then what is good about them? As (...) for political theory, I consider the question of what would even count as an answer to this question, and I conclude with the tentative proposal that it is valuable to come to understand something that is, itself, important. (shrink)

Current work in language models (LMs) helps us speed up or even skip thinking by accelerating and automating cognitive work. But can LMs help us with critical thinking -- thinking in deeper, more reflective ways which challenge assumptions, clarify ideas, and engineer new concepts? We treat philosophy as a case study in critical thinking, and interview 21 professional philosophers about how they engage in critical thinking and on their experiences with LMs. We find that philosophers do not find LMs (...) to be useful because they lack a sense of selfhood (memory, beliefs, consistency) and initiative (curiosity, proactivity). We propose the selfhood-initiative model for critical thinking tools to characterize this gap. Using the model, we formulate three roles LMs could play as critical thinking tools: the Interlocutor, the Monitor, and the Respondent. We hope that our work inspires LM researchers to further develop LMs as critical thinking tools and philosophers and other 'critical thinkers' to imagine intellectually substantive uses of LMs. (shrink)

Science and fiction seem to lie at opposite ends of the cognitive-epistemic spectrum. The former is typically seen as the study of hard, real-world facts in a rigorous manner. The latter is treated as an instrument of play and recreation, dealing in figments of the imagination. Initial appearances notwithstanding, several central features of scientific modeling in fact suggest a close connection with the imagination and recent philosophers have developed detailed accounts of models that treat them, in one way or (...) another, as akin to fictions. This chapter will critically discuss the fictions approach as an epistemology of scientific modeling. (shrink)

This paper provides a general introduction to the use of causal models in the metaphysics of causation, specifically structural equation models and directed acyclic graphs. It reviews the formal framework, lays out a method of interpretation capable of representing different underlying metaphysical relations, and describes the use of these models in analyzing causation.

This paper addresses the question of what constitutes an apt interpreted model for the purpose of analyzing causation. I first collect universally adopted aptness principles into a basic account, flagging open questions and choice points along the way. I then explore various additional aptness principles that have been proposed in the literature but have not been widely adopted, the motivations behind their proposals, and the concerns with each that stand in the way of universal adoption. I conclude that the remaining (...) work of articulating aptness for a SEM analysis of causation is tied up with issue to do with modality, ontology, and mereology. Continuing this work is therefore likely to shed light on the relationship between these areas and causation more generally. (shrink)

Are institutional principles of justice subject to a minimal realism constraint to the effect that, in order to be valid, they must not make wildly unrealistic demands? Most of us say “yes.” David Estlund says, “no.” However, while Estlund holds that 1) institutional principles of justice are not subject to a minimal realism constraint, he accepts that 2) institutional principles of justice are subject to an *attainability constraint* to the effect that, in order to be valid, they must not (...) make demands we are unable to meet; and 3) what he calls “institutional proposals” are subject to a minimal realism constraint. I argue that these three theses do not represent a plausible combination, at least given Estlund’s account of the principle/proposal distinction. Given this account, Estlund is either wrong to reject a minimal realism constraint on institutional principles of justice, or wrong to accept an attainability constraint on institutional principles of justice and/or a minimal realism constraint on institutional proposals. Either way, this has significant implications for the plausibility of his overall case against the minimal realism constraint on institutional principles of justice. (shrink)

I argue that normative formal epistemology (NFE) is best understood as modelling, in the sense that this is the reconstruction of its methodology on which NFE is doing best. I focus on Bayesianism and show that it has the characteristics of modelling. But modelling is a scientific enterprise, while NFE is normative. I thus develop an account of normative models on which they are idealised representations put to normative purposes. Normative assumptions, such as the transitivity of comparative credence, are (...) characterised as modelling idealisations motivated normatively. I then survey the landscape of methodological options: what might formal epistemologists be up to? I argue the choice is essentially binary: modelling or theorising. If NFE is theorising it is doing very poorly: generating false claims with no clear methodology for separating out what is to be taken seriously. Modelling, by contrast, is a successful methodology precisely suited to the management of useful falsehoods. Regarding NFE as modelling is not costless, however. First, our normative inferences are less direct and are muddied by the presence of descriptive idealisations. Second, our models are purpose-specific and limited in their scope. I close with suggestions for how to adapt our practice. (shrink)

The juxtaposition of models of God and Christian faith may seem repugnant to many, as models are tentative and faith aims at an abiding certainty. In fact, for many Christians, using models of God in worship amounts to idolatry. By examining Biblical and extra-Biblical views of idolatry, I argue that models are not idols. To the contrary, the practice of God-modeling inoculates Christians against one of the most seductive idols of our age: the love of certainty. (...) Furthermore, by examining meditations upon certainty in Melville’s Moby Dick and the early discourses of the Buddha, I suggest that overweening conviction is a vice that hinders rather than guarantees Christian discipleship, and that Christian faith is better defined as any or all of the following: relative confidence in propositions, faithful relationship, and a virtue of disciplined credulity. (shrink)

How does our language relate to reality? This is a question that is especially pertinent in set theory, where we seem to talk of large infinite entities. Based on an analogy with the use of models in the natural sciences, we argue for a threefold correspondence between our language, models, and reality. We argue that so conceived, the existence of models can be underwritten by a weak notion of existence, where weak existence is to be understood as (...) existing in virtue of language. (shrink)

One might be inclined to assume, given the mouse donning its cover, that the behavior of interest in Nicole Nelson's book Model Behavior (2018) is that of organisms like mice that are widely used as “stand-ins” for investigating the causes of human behavior. Instead, Nelson's ethnographic study focuses on the strategies adopted by a community of rodent behavioral researchers to identify and respond to epistemic challenges they face in using mice as models to understand the causes of disordered human (...) behaviors associated with mental illness. Although Nelson never explicitly describes the knowledge production activities in which her behavioral geneticist research subjects engage as “exemplary”, the question of whether or not these activities constitute “model behavior(s)”—generalizable norms for engaging in scientific research—is one of the many thought-provoking questions raised by her book. As a philosopher of science interested in this question, I take it up here. (shrink)

This paper introduces and defends an account of model-based science that I dub model pluralism. I argue that despite a growing awareness in the philosophy of science literature of the multiplicity, diversity, and richness of models and modeling practices, more radical conclusions follow from this recognition than have previously been inferred. Going against the tendency within the literature to generalize from single models, I explicate and defend the following two core theses: any successful analysis of models must (...) target sets of models, their multiplicity of functions within science, and their scientific context and history and for almost any aspect x of phenomenon y, scientists require multiple models to achieve scientific goal z. (shrink)

I defend Christopher Peacocke's and Robert Hopkins's experienced resemblance accounts of depiction against criticisms put forward by Gavin McIntosh in a recent article in this journal. I argue that, while there may be reasons for rejecting Peacocke's and Hopkins's accounts, McIntosh fails to provide any.

Models as Make-Believe offers a new approach to scientific modelling by looking to an unlikely source of inspiration: the dolls and toy trucks of children's games of make-believe.

Should models of consciousness be detailed _mechanistic_ models of particular types of systems, or should they be _minimal_ models that abstract away from the underlying mechanistic details and provide generalisations? Detailed mechanistic models may afford a complete and precise account of consciousness in human beings and other, physiologically similar mammals. But they do not provide a good model of consciousness in other animals, such as non-vertebrates, let alone artificial systems. Minimal models can be applicable to (...) a wide range of different conscious systems. But do they provide genuine explanations that are autonomous from explanations by detailed mechanistic models? This paper provides a taxonomy of minimal models and measures of consciousness, clarifies their relation to detailed mechanistic models, and highlights benefits of different minimalist approaches to consciousness. (shrink)

Batterman and Rice ([2014]) argue that minimal models possess explanatory power that cannot be captured by what they call ‘common features’ approaches to explanation. Minimal models are explanatory, according to Batterman and Rice, not in virtue of accurately representing relevant features, but in virtue of answering three questions that provide a ‘story about why large classes of features are irrelevant to the explanandum phenomenon’ ([2014], p. 356). In this article, I argue, first, that a method (the renormalization group) (...) they propose to answer the three questions cannot answer them, at least not by itself. Second, I argue that answers to the three questions are unnecessary to account for the explanatoriness of their minimal models. Finally, I argue that a common features account, what I call the ‘generalized ontic conception of explanation’, can capture the explanatoriness of minimal models. (shrink)

Despite an enormous philosophical literature on models in science, surprisingly little has been written about data models and how they are constructed. In this paper, I examine the case of how paleodiversity data models are constructed from the fossil data. In particular, I show how paleontologists are using various model-based techniques to correct the data. Drawing on this research, I argue for the following related theses: first, the ‘purity’ of a data model is not a measure of (...) its epistemic reliability. Instead it is the fidelity of the data that matters. Second, the fidelity of a data model in capturing the signal of interest is a matter of degree. Third, the fidelity of a data model can be improved ‘vicariously’, such as through the use of post hoc model-based correction techniques. And, fourth, data models, like theoretical models, should be assessed as adequate for particular purposes. (shrink)

Detailed examinations of scientific practice have revealed that the use of idealized models in the sciences is pervasive. These models play a central role in not only the investigation and prediction of phenomena, but in their received scientific explanations as well. This has led philosophers of science to begin revising the traditional philosophical accounts of scientific explanation in order to make sense of this practice. These new model-based accounts of scientific explanation, however, raise a number of key questions: (...) Can the fictions and falsehoods inherent in the modeling practice do real explanatory work? Do some highly abstract and mathematical models exhibit a noncausal form of scientific explanation? How can one distinguish an exploratory "how-possibly" model explanation from a genuine "how-actually" model explanation? Do modelers face tradeoffs such that a model that is optimized for yielding explanatory insight, for example, might fail to be the most predictively accurate, and vice versa? This chapter explores the various answers that have been given to these questions. (shrink)

I provide a theory of causation within the causal modeling framework. In contrast to most of its predecessors, this theory is model-invariant in the following sense: if the theory says that C caused (didn't cause) E in a causal model, M, then it will continue to say that C caused (didn't cause) E once we've removed an inessential variable from M. I suggest that, if this theory is true, then we should understand a cause as something which transmits deviant or (...) non-inertial behavior to its effect. (shrink)

In this paper I propose an account of representation for scientific models based on Kendall Walton’s ‘make-believe’ theory of representation in art. I first set out the problem of scientific representation and respond to a recent argument due to Craig Callender and Jonathan Cohen, which aims to show that the problem may be easily dismissed. I then introduce my account of models as props in games of make-believe and show how it offers a solution to the problem. Finally, (...) I demonstrate an important advantage my account has over other theories of scientific representation. All existing theories analyse scientific representation in terms of relations, such as similarity or denotation. By contrast, my account does not take representation in modelling to be essentially relational. For this reason, it can accommodate a group of models often ignored in discussions of scientific representation, namely models which are representational but which represent no actual object. (shrink)

Although some previous studies have investigated the relationship between moral foundations and moral judgment development, the methods used have not been able to fully explore the relationship. In the present study, we used Bayesian Model Averaging (BMA) in order to address the limitations in traditional regression methods that have been used previously. Results showed consistency with previous findings that binding foundations are negatively correlated with post-conventional moral reasoning and positively correlated with maintaining norms and personal interest schemas. In addition to (...) previous studies, our results showed a positive correlation for individualizing foundations and post-conventional moral reasoning. Implications are discussed as well as a detailed explanation of the novel BMA method in order to allow others in the field of moral education to be able to use it in their own studies. (shrink)

The introspective devices framework proposed by Kammerer and Frankish (this issue) offers an attractive conceptual tool for evaluating and developing accounts of introspection. However, the framework assumes that different views about the nature of introspection can be easily evaluated against a set of common criteria. In this paper, I set out to test this assumption by analysing two formal models of introspection using the introspective device framework. The question I aim to answer is not only whether models developed (...) outside of philosophy can be successfully evaluated against the set of conceptual criteria proposed by Kammerer and Frankish, but also whether this kind of evaluation can reveal some limitations inherent to the framework. (shrink)

In a recent special issue dedicated to Dani Rodrik’s (2015) influential monograph Economics Rules, Grüne-Yanoff and Marchionni (2018) raise a potentially damning problem for Rodrik’s suggestion that progress in economics should be understood and measured laterally, by a continuous expansion of new models. They argue that this could lead to an “embarrassment of riches”, i.e. the rapid expansion of our model library to such an extent that we become unable to choose between the available models, and thus needs (...) to be solved to make ‘model pluralism’ viable. Drawing on Veit’s (2019a) ‘model pluralism’ account, this paper argues that model pluralism as a thesis about the relationship between science and nature undermines the very idea of a general model selection framework for policy making. (shrink)

We introduce a novel point of view on the “models as mediators” framework in order to emphasize certain important epistemological questions about models in science which have so far been little investigated. To illustrate how this perspective can help answer these kinds of questions, we explore the use of simplified models in high energy physics research beyond the Standard Model. We show in detail how the construction of simplified models is grounded in the need to mitigate (...) pressing epistemic problems concerning the uncertainty inherent in the present theoretical and experimental contexts. (shrink)

I propose a distinct type of robustness, which I suggest can support a confirmatory role in scientific reasoning, contrary to the usual philosophical claims. In model robustness, repeated production of the empirically successful model prediction or retrodiction against a background of independentlysupported and varying model constructions, within a group of models containing a shared causal factor, may suggest how confident we can be in the causal factor and predictions/retrodictions, especially once supported by a variety of evidence framework. I present (...) climate models of greenhouse gas global warming of the 20th Century as an example, and emphasize climate scientists’ discussions of robust models and causal aspects. The account is intended as applicable to a broad array of sciences that use complex modeling techniques. (shrink)

This paper constitutes a radical departure from the existing philosophical literature on models, modeling-practices, and model-based science. I argue that the various entities and practices called 'models' and 'modeling-practices' are too diverse, too context-sensitive, and serve too many scientific purposes and roles, as to allow for a general philosophical analysis. From this recognition an alternative view emerges that I shall dub model anarchism.

Many biological investigations are organized around a small group of species, often referred to as ‘model organisms’, such as the fruit fly Drosophila melanogaster. The terms ‘model’ and ‘modelling’ also occur in biology in association with mathematical and mechanistic theorizing, as in the Lotka–Volterra model of predator-prey dynamics. What is the relation between theoretical models and model organisms? Are these models in the same sense? We offer an account on which the two practices are shown to have different (...) epistemic characters. Theoretical modelling is grounded in explicit and known analogies between model and target. By contrast, inferences from model organisms are empirical extrapolations. Often such extrapolation is based on shared ancestry, sometimes in conjunction with other empirical information. One implication is that such inferences are unique to biology, whereas theoretical models are common across many disciplines. We close by discussing the diversity of uses to which model organisms are put, suggesting how these relate to our overall account. 1 Introduction2 Volterra and Theoretical Modelling3 Drosophila as a Model Organism4 Generalizing from Work on Model Organisms5 Phylogenetic Inference and Model Organisms6 Further Roles of Model Organisms6.1 Preparative experimentation6.2 Model organisms as paradigms6.3 Model organisms as theoretical models6.4 Inspiration for engineers6.5 Anchoring a research community7 Conclusion. (shrink)

This book analyses the impact computerization has had on contemporary science and explains the origins, technical nature and epistemological consequences of the current decisive interplay between technology and science: an intertwining of formalism, computation, data acquisition, data and visualization and how these factors have led to the spread of simulation models since the 1950s. -/- Using historical, comparative and interpretative case studies from a range of disciplines, with a particular emphasis on the case of plant studies, the author shows (...) how and why computers, data treatment devices and programming languages have occasioned a gradual but irresistible and massive shift from mathematical models to computer simulations. -/- . (shrink)

This paper constructs a model of metaphysical indeterminacy that can accommodate a kind of ‘deep’ worldly indeterminacy that arguably arises in quantum mechanics via the Kochen-Specker theorem, and that is incompatible with prominent theories of metaphysical indeterminacy such as that in Barnes and Williams (2011). We construct a variant of Barnes and Williams's theory that avoids this problem. Our version builds on situation semantics and uses incomplete, local situations rather than possible worlds to build a model. We evaluate the resulting (...) theory and contrast it with similar alternatives, concluding that our model successfully captures deep indeterminacy. (shrink)

We argue that concerns about double-counting—using the same evidence both to calibrate or tune climate models and also to confirm or verify that the models are adequate—deserve more careful scrutiny in climate modelling circles. It is widely held that double-counting is bad and that separate data must be used for calibration and confirmation. We show that this is far from obviously true, and that climate scientists may be confusing their targets. Our analysis turns on a Bayesian/relative-likelihood approach to (...) incremental confirmation. According to this approach, double-counting is entirely proper. We go on to discuss plausible difficulties with calibrating climate models, and we distinguish more and less ambitious notions of confirmation. Strong claims of confirmation may not, in many cases, be warranted, but it would be a mistake to regard double-counting as the culprit. 1 Introduction2 Remarks about Models and Adequacy-for-Purpose3 Evidence for Calibration Can Also Yield Comparative Confirmation3.1 Double-counting I3.2 Double-counting II4 Climate Science Examples: Comparative Confirmation in Practice4.1 Confirmation due to better and worse best fits4.2 Confirmation due to more and less plausible forcings values5 Old Evidence6 Doubts about the Relevance of Past Data7 Non-comparative Confirmation and Catch-Alls8 Climate Science Example: Non-comparative Confirmation and Catch-Alls in Practice9 Concluding Remarks. (shrink)