Historians tend to speak of the problem of the origin of species or the species question, as if it were a monolithic problem. In reality, the phrase refers to a, historically, surprisingly fluid and pluriform scientific issue. It has, in the course of the past five centuries, been used in no less than ten different ways or contexts. A clear taxonomy of these separate problems is useful or relevant in two ways. It certainly helps to disentangle confusions that have (...) inevitably emerged in the literature in its absence. It may, secondly, also help us to gain a more thorough understanding, or sharper view, of the history of evolutionary thought. A consequent problem-centric look at that history through the lens of various origin of species problems certainly yields intriguing results, including and particularly for our understanding of the genesis of the Wallace–Darwin theory of evolution through natural selection. (shrink)

Historians tend to speak of the problem of the origin of species or the species question, as if it were a monolithic problem. In reality, the phrase refers to a, historically, surprisingly fluid and pluriform scientific issue. It has, in the course of the past five centuries, been used in no less than ten different ways or contexts. A clear taxonomy of these separate problems is useful or relevant in two ways. It certainly helps to disentangle confusions that have (...) inevitably emerged in the literature in its absence. It may, secondly, also help us to gain a more thorough understanding, or sharper view, of the history of evolutionary thought. A consequent problem-centric look at that history through the lens of various origin of species problems certainly yields intriguing results, including and particularly for our understanding of the genesis of the Wallace–Darwin theory of evolution through natural selection. (shrink)

Almost everyone has an intuitive notion of what a random number is. For example, consider these two series of binary digits: 01010101010101010101 01101100110111100010 The first is obviously constructed according to a simple rule; it consists of the number 01 repeated ten times. If one were asked to speculate on how the series might continue, one could predict with considerable confidence that the next two digits would be 0 and 1. Inspection of the second series of digits yields no such comprehensive (...) pattern. There is no obvious rule governing the formation of the number, and there is no rational way to guess the succeeding digits. The arrangement seems haphazard; in other words, the sequence appears to be a random assortment of 0's and 1's. (shrink)

What could be more certain than the fact that 2 plus 2 equals 4? Since the time of the ancient Greeks mathematicians have believed there is little---if anything---as unequivocal as a proved theorem. In fact, mathematical statements that can be proved true have often been regarded as a more solid foundation for a system of thought than any maxim about morals or even physical objects. The 17th-century German mathematician and philosopher Gottfried Wilhelm Leibniz even envisioned a ``calculus'' of reasoning such (...) that all disputes could one day be settled with the words ``Gentlemen, let us compute!'' By the beginning of this century symbolic logic had progressed to such an extent that the German mathematician David Hilbert declared that all mathematical questions are in principle decidable, and he confidently set out to codify once and for all the methods of mathematical reasoning. (shrink)

Human beings are strange animals. Although evolutionary theory has brilliantly accounted for the features we share with other creatures—from the genetic code that directs the construction of our bodies to the details of how our muscles and neurons work—we still stand out in countless ways. Our brains are exceptionally large, we alone have truly grammatical language, and we alone compose symphonies, drive cars, eat spaghetti with a fork and wonder about the origins of the universe.

A scientific community cannot practice its trade without some set of received beliefs. These beliefs form the foundation of the "educational initiation that prepares and licenses the student for professional practice". The nature of the "rigorous and rigid" preparation helps ensure that the received beliefs are firmly fixed in the student's mind. Scientists take great pains to defend the assumption that scientists know what the world is like...To this end, "normal science" will often suppress novelties which undermine its foundations. (...) Research is therefore not about discovering the unknown, but rather "a strenuous and devoted attempt to force nature into the conceptual boxes supplied by professional education". (shrink)

A study in the philosophy of science, proposing a strong form of the doctrine of scientific realism' and developing its implications for issues in the philosophy of mind.

In this paper, I propose that the debate in epistemology concerning the nature and value of understanding can shed light on the role of scientific idealizations in producing scientific understanding. In philosophy of science, the received view seems to be that understanding is a species of knowledge. On this view, understanding is factive just as knowledge is, i.e., if S knows that p, then p is true. Epistemologists, however, distinguish between different kinds of understanding. Among epistemologists, there are (...) those who think that a certain kind of understanding—objectual understanding—is not factive, and those who think that objectual understanding is quasi-factive. Those who think that understanding is not factive argue that scientific idealizations constitute cognitive success, which we then consider as instances of understanding, and yet they are not true. This paper is an attempt to draw lessons from this debate as they pertain to the role of idealizations in producing scientific understanding. I argue that scientific understanding is quasi-factive. (shrink)

Scientific realism is the view that our best scientific theories give approximately true descriptions of both observable and unobservable aspects of a mind-independent world. Debates between realists and their critics are at the very heart of the philosophy of science. Anjan Chakravartty traces the contemporary evolution of realism by examining the most promising strategies adopted by its proponents in response to the forceful challenges of antirealist sceptics, resulting in a positive proposal for scientific realism today. He examines (...) the core principles of the realist position, and sheds light on topics including the varieties of metaphysical commitment required, and the nature of the conflict between realism and its empiricist rivals. By illuminating the connections between realist interpretations of scientific knowledge and the metaphysical foundations supporting them, his book offers a compelling vision of how realism can provide an internally consistent and coherent account of scientific knowledge. (shrink)

This article identifies and analyses issues related to defining and evaluating the so-called scientific imperialism. It discusses John Dupré's account, suggesting that it is overly conservative and does not offer a definition of scientific imperialism in not presenting it as a phenomenon of interdisciplinarity. It then discusses the recent account by Steve Clarke and Adrian Walsh, taking issue with ideas such as illegitimate occupation, counterfactual progress, and culturally significant values. A more comprehensive and refined framework of my own (...) is then summarized. It suggests types and aspects of scientific imperialism as a dynamic interdisciplinary relationship, distinguishing between imperialism of scope, style and standing, for example. It also suggests normative constraints on scientific imperialism. This enables us to distinguish, in principle, recommendable from non-recommendable kinds of it, while recognizing the difficulties involved in trying to do this in practice. (shrink)

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. (shrink)

I examine whether or not it is apt to attribute knowledge to groups of scientists. I argue that though research teams can be aptly described as having knowledge, communities of scientists identified with research fields, and the scientific community as a whole are not capable of knowing. Scientists involved in research teams are dependent on each other, and are organized in a manner to advance a goal. Such teams also adopt views that may not be identical to the views (...) of the individual members of the group. (shrink)

Since the beginning of the 20th century, philosophers of science have asked, "what kind of thing is a scientific theory?" The logical positivists answered: a scientific theory is a mathematical theory, plus an empirical interpretation of that theory. Moreover, they assumed that a mathematical theory is specified by a set of axioms in a formal language. Later 20th century philosophers questioned this account, arguing instead that a scientific theory need not include a mathematical component; or that the (...) mathematical component need not be specified by a set of axioms in a formal language. We survey various accounts of scientific theories entertained in the 20th century -- removing some misconceptions, and clearing a path for future research. (shrink)

Alexander Bird argues for an epistemic account of scientific progress, whereas Darrell Rowbottom argues for a semantic account. Both appeal to intuitions about hypothetical cases in support of their accounts. Since the methodological significance of such appeals to intuition is unclear, I think that a new approach might be fruitful at this stage in the debate. So I propose to abandon appeals to intuition and look at scientific practice instead. I discuss two cases that illustrate the way in (...) which scientists make judgments about progress. As far as scientists are concerned, progress is made when scientific discoveries contribute to the increase of scientific knowledge of the following sorts: empirical, theoretical, practical, and methodological. I then propose to articulate an account of progress that does justice to this broad conception of progress employed by scientists. I discuss one way of doing so, namely, by expanding our notion of scientific knowledge to include both know-that and know-how. (shrink)

The articulation of an overarching account of scientific explanation has long been a central preoccupation for the philosophers of science. Although a while ago the literature was dominated by two approaches—a causal account and a unificationist account—today the consensus seems to be that the causal account has won. In this paper, I challenge this consensus and attempt to revive unificationism. More specifically, I aim to accomplish three goals. First, I add new criticisms to the standard anti-unificationist arguments, in order (...) to motivate the need for a revision of the doctrine. Second, and most importantly, I sketch such a revised version. Then I argue that, contrary to widespread belief, the causal account and this revised unificationist account of explanation are compatible. Moreover, I also maintain that the unificationist account has priority, since a most satisfactory theory of explanation can be obtained by incorporating the causal account, as a sub-component of the unificationist account. The driving force behind this reevaluation of the received view in the philosophy of explanation is a reconsideration of the role of scientific understanding. (shrink)

Thats logic. LEWIS CARROLL, Through the Looking Glass 1-1. The fundamental problem of this work is the question of the nature of scientific inference.

This essay presents a fully inferentialist-expressivist account of scientific representation. In general, inferentialist approaches to scientific representation argue that the capacity of a model to represent a target system depends on inferences from models to target systems. Inferentialism is attractive because it makes the epistemic function of models central to their representational capacity. Prior inferentialist approaches to scientific representation, however, have depended on some representational element, such as denotation or representational force. Brandom’s Making It Explicit provides a (...) model of how to fully discharge such representational vocabulary, but it cannot be applied directly to scientific representations. Pursuing a strategy parallel to Brandom’s, this essay begins with an account of how surrogative inference is justified. Scientific representation and the denotation of model elements are then explained in terms of surrogative inference by treating scientific representation and denotation as expressive, analogous to Brandom’s account of truth. The result is a thoroughgoing inferentialism: M is a scientific representation of T if and only if M has scientifically justified surrogative consequences that are answers to questions about T. (shrink)

Over the last two decades, the debate over scientific realism has been dominated by two arguments that pull in contrary directions: the 'no miracle' argument and the 'pessimistic induction'. The latter suggests that the historical record destroys the realist's belief in an explanatory connection between truthlikeness and genuine empirical success. This paper analyzes the structure of the 'pessimistic induction', presents a move--the divide et impera move--that neutralizes it, and motivates a substantive yet realistic version of scientific realism. This (...) move is also compared with Worrall's and Kitcher's recent reactions to the 'pessimistic induction'. (shrink)

Baised upon the Tarner Lectures given by Braithwaite in 1946, Scientific Explanation aims to examine the logical features common to all the sciences. Scientific advancement is by means of testing the conclusions of proffered hypotheses by observation and experiment. Braithwaite attempts to explain how the implications of this process may throw light upon seemingly mysterious features of scientific procedure and should resolve many of the fundamentals of scientific procedures, including the function of mathematics, probability, and models (...) in science and the nature of theoretical concepts. (shrink)

In this paper, we demonstrate how a systematic taxonomy of stances can help elucidate two classic debates of the historical turn—the Lakatos–Feyerabend debate concerning theory rejection and the Feyerabend–Kuhn debate about pluralism during normal science. We contend that Kuhn, Feyerabend, and Lakatos were often talking at cross-purposes due to the lack of an agreed upon taxonomy of stances. Specifically, we provide three distinct stances that scientists take towards theories: acceptance of a theory as the best available description of its domain, (...) use of a theory in practical applications, and pursuit (elaboration) of a theory. We argue that in the Lakatos–Feyerabend debate, Lakatos was concerned with acceptance whereas Feyerabend was mainly concerned with pursuit. Additionally, we show how Feyerabend and Kuhn’s debate on the role of pluralism/monism in normal science involved a crucial conflation of all three stances. Finally, we outline a few general lessons concerning the process of scientific change. (shrink)

This paper examines the interplay between conceptual structure and the evolution of scientific concepts, arguing that concepts are fundamentally ‘forward-looking’ constructs. Drawing on empirical studies of similarity and categorization, I explicate the way in which the conceptual taxonomy highlights the ‘relevant respects’ for similarity judgments involved in categorization. I then propose that this taxonomy provides some of the cognitive underpinnings of the ongoing development of scientific concepts. I use the concept synapse to illustrate my proposal, showing how conceptual (...) taxonomy both facilitates and constrains the accommodation of newly discovered phenomena. I end by briefly considering the implications of the proposed approach for a normative evaluation of scientific concepts. (shrink)

Philosophers of science are divided over the interpretations of scientific normativity. Larry Laudan defends a sort of goal-directed rules for scientific methodology. In contrast, Gerard Doppelt thinks methodological rules are a mixed batch of rules in that some are goal-oriented hypothetical rules and others are goal-independent categorical rules. David Resnik thinks that the debate between them is at a standstill now. He further thinks there are certain rules, such as the rule of consistency which is goal independent. However, (...) he proposes a holistic understanding of the scientific methodology. Taking a thread from Resnik, the present paper also advocates a holistic understanding of the scientific methodology. Given that many scientific practices deal with systems, the focus will be given to the systems by assuming each as a constellation of methodological norms. By taking each system as a set of mutually supportive methodological rules whose instrumental values underwrite the coherence relation among them, the paper aims to provide what could be a viable holistic epistemological account that can explain scientific normativity at work in a scientific system. The paper will lay down specific holistic criteria for understanding the scientific methodology. They will be used to show how a holistic account could satisfactorily account for the success of the Compact Muon Solenoid (CMS) experiment in discovering the Higgs boson and how the holistic account can account for the instrumental error behind the apparent faster-than-light neutrino anomaly of the Oscillation Project with Emulsion-t Racking Apparatus (OPERA) experiments respectively. (shrink)

Scientific articles exemplify standard functional units constraining argumentative structures. Severe space limitations demand every paragraph and illustration contribute to establishing the paper's claims. Philosophical testing and confirmation models should take into account each paragraph, table, and illustration. Hypothetico-Deductive, Bayesian Inductive, and Inference-to-the-Best-Explanation models do not, garbling the logic of papers. Micro-analysis of the fundamental paper in plate tectonics reveals an argumentative structure commonplace in science but ignored by standard philosophical accounts that cannot be dismissed as mere rhetorical embellishment. Papers (...) with illustrations often display a second argumentative structure differing from the text's. Constraints on adequate testing and confirmation analyses are adduced. “Experiments are about the assembly of persuasive arguments, ones that will stand up in court. … The task at hand is to capture the building-up of a persuasive argument about the world even in the absence of the logician's certainty.”—Galison, How Experiments End, 277. (shrink)

Scientists strive to understand the world. Traditionally, philosophers of science have thought that this is a matter of constructing explanations, based on theories and laws, thereby gaining understanding of phenomena by explaining them. This thesis takes a radically different approach, instead relating the notion of understanding to the activities that scientists perform. Scientific understanding is not just a matter of representing or explaining the world, but a matter of practical and intelligent doing. Philosophers of science have continued to sell (...) short the project of making sense of scientific understanding, limiting their views to the articulated and well-formed products of inquiry, like theory and explanation. In taking a pragmatist approach to the epistemology of understanding, I reorientate our theorising about understanding from products to processes, and from explanations to methods and concepts. I thereby provide an ecumenical account of scientific understanding that can accommodate the dynamics and heterogeneity of scientific practice. In Chapter 1, I argue against the dominant focus on explanatory understanding in philosophy of science, thereby making room for my own account of operational understanding. Chapter 2 provides an account of how concepts are essential constituents of understanding. Concepts frame entities so that scientists can think and talk about and interact with them intelligently. Chapter 3 gives an account of understanding-how, through my notion of operational understanding, which relates to the methods that structure and guide successful performances of activities. In Chapter 4, I take up the task of describing the psychology of understanding, the kind of state that understanding is, which I argue is accounted for in terms of skill. In Chapter 5, I develop an account of how cognitive devices — tools for thinking, like models and thought-experiments — facilitate and produce understanding. (shrink)

Without doubt, there is a widespread usage of visualisations in science. However, what exactly the _epistemic status_ of these visual representations in science may be remains an open question. In the following, I will argue that at least some scientific visualisations are indispensible for our cognitive processes. My thesis will be that, with regard to the activity of _learning_, visual representations are of relevance in the sense of contributing to the aim of _scientific_ _understanding_. Taking into account that understanding (...) can be regarded as an epistemic desideratum in its own right, I will argue that, at least in some instances, no understanding can be achieved without the aid of visualisations. Consequently, they are of crucial importance in this process. Moreover, to support this thesis we will make use of some findings in educational psychology. (shrink)

Researchers in the biological and biomedical sciences, particularly those working in laboratories, use a variety of artifacts to help them perform their cognitive tasks. This paper analyses the relationship between researchers and cognitive artifacts in terms of integration. It first distinguishes different categories of cognitive artifacts used in biological practice on the basis of their informational properties. This results in a novel classification of scientific instruments, conducive to an analysis of the cognitive interactions between researchers and artifacts. It then (...) uses a multidimensional framework in line with complementarity-based extended and distributed cognition theory to conceptualize how deeply instruments in different informational categories are integrated into the cognitive systems of their users. The paper concludes that the degree of integration depends on various factors, including the amount of informational malleability, the intensity and kind of information flow between agent and artifact, the trustworthiness of the information, the procedural and informational transparency, and the degree of individualisation. (shrink)

In this essay, I examine the role of dissimilarity in scientific representation. After briefly reviewing some of the philosophical literature which places a strong emphasis on the role of similarity, I turn to examine some work from Carroll and Borges which demonstrates that perfect similarity is not valuable in the representational use of maps. Expanding on this insight, I go on to argue that this shows that dissimilarity is an important part of the representational use of maps—a point I (...) then extend to the case of scientific representation. Relying on some work from Latour, I argue that dissimilarity plays an essential role in representational practice, by providing novel forms of manipulation and use which affords the achievement of various epistemic and nonepistemic aims. After showing how this point connects to some other literature on scientific representation, I discuss some examples of the value of dissimilarity in the use of representational vehicles. Overall, I argue that to understand scientific representation, we will need to consider more than just similarity. We will need to explore dissimilarities as well. (shrink)

First, I discuss the older “theory-centered” and the more recent semantic conception of scientific theories. I argue that these two perspectives are nothing more than terminological variants of one another. I then offer a new theory-centered view of scientific theories. I argue that this new view captures the insights had by each of these earlier views, that it’s closer to how scientists think about their own theories, and that it better accommodates the phenomenon of inconsistent scientific theories.