There is not a unique inductive skeptical position; there are grades of inductive skepticism. There is nothing much to say about complete skepticism, but some more restricted skeptical positions may be profitably analyzed.

The structure of Reichenbach's pragmatic vindication of induction is analysed in detail. The argument is seen to proceed in two stages, the first being a pragmatic justification of the frequency interpretation of probability which is taken as a license for considering the aim of induction to be the discovery of limiting relative frequencies, and the second being the pragmatic justification of induction itself. Both justifications are found to contain flaws, and the arguments used to support Reichenbach's definition of the aim (...) of induction presuppose the availability of a type of predicate which generates paradoxes closely related to Goodman's "grue-bleen" paradox. Next, Salmon's "Criterion of Linguistic Invariance" is evaluated as a canon of inductive logic, which singles out the "straight rule" from an infinite class of convergent inductive rules. Upon close examination, its credentials are seen to be unimpressive. In connection with Salmon's work on linguistic invariance, we take a closer look at the impact of the Goodman paradox on probability estimator rules like Reichenbach's "straight rule." We find that its undesirable consequences for such systems of inductive logic cannot be escaped by Salmon's solution, or indeed by any solution whose motivating idea is to rule "queer" predicates out of court. Finally, the discussion of the Goodman paradox leads us to a modest methodological proposal for systems of inductive logic which incorperate probability estimator rules of the type at issue. (shrink)

Positivism has been used to establish a standard that Information Systems (IS) research must meet to be scientific. According to such positivistic beliefs in IS, scientific research should: 1) be generalizable, 2) focus on stable independent variables, 3) have certain ontological assumptions, and 4) use statistical or quantitative methods rather than qualitative methods. We argue that logical positivist philosophers required none of these. On the contrary, logical positivist philosophers regarded philosophizing in general and ontological considerations in particular as nonsense. Moreover, (...) the positivists’ preferred empirical research method was not a survey, but rather a qualitative observation recorded by field notes. In addition, positivist philosophers required neither statistical nor nonstatistical generalizability. At least some positivist philosophers also acknowledged the study of singular cases as being scientific. Many research orientations (e.g., single-setting research, examination of change, qualitative research) that are deemed “unscientific” by positivism in IS seem to be “scientific” (in principle) according to logical positivism. In turn, generally speaking, what has been justified as scientific by positivism in IS (e.g., requirements of statistical or nonstatistical generalizability, surveys, independent variables, ontological views) were either not required by logical positivists or were regarded as nonsensical by logical positivists. Furthermore, given that positivism is sometimes associated (or confused) with logical empiricism in IS, we also briefly discuss logical empiricism. Finally, realizing that certain influential, taken-forgranted assumptions that underlie IS research are unwarranted could have ground-breaking implications for future IS research. (shrink)

Reichenbach's well-known distinction between the context of discovery and the context of justification has recently come under attack from several quarters. In this paper I attempt to reconsider the distinction and evaluate various recent criticisms of it. These criticisms fall into two main groups: those which directly challenge Reichenbach's distinction; and those which (I argue) indirectly but no less seriously challenge that distinction by rejecting the related distinction between psychology and epistemology, and defending the "naturalizing" of epistemology. I argue that (...) these recent criticisms fail, and that the distinction remains an important conceptual tool necessary for an adequate understanding of the way in which scientific claims purport to appropriately portray our natural environment. (shrink)

This paper examines a twofold tension in Gerhard Schurz’s (2019) recent proposal to solve Hume’s problem of induction. Schurz concedes to the skeptic that there is no non-circular epistemic justification of the reliability of induction, but then argues for the optimality of meta-induction so that if any prediction method is reliable, then meta-induction is. There is a tension in this proposal between meta-induction and our inductive practice: Are we supposed to abandon our inductive practice in favor of meta-induction? Schurz claims (...) that given the actual way the world has been, the meta-inductive method supports the standard inductive method. There then arises a second tension: The challenges Schurz cites against the reliability of induction—such as the anti-inductive hypothesis and the state-uniform probability distribution—cast doubt on Schurz’s claim that meta-induction supports induction. The reasoning in this paper moves in the opposite direction: There are ways of answering these challenges in defense of Schurz’s claim that meta-induction supports induction, but these ways also point to ways of defending induction directly without the mediation of meta-induction. (shrink)

Popper is well known for rejecting a logic of discovery, but he is only justified in rejecting the same type of logic of discovery that is denied by consequentialism. His own account of hypothesis generation, based on a natural selection analogy, involves an error-eliminative logic of discovery and the differences he admits between biological and conceptual evolution suggest an error-corrective logic of discovery. These types of logics of discovery are based on principles of plausibility that are used in the generation (...) as opposed to the preliminary evaluation of hypotheses. The normative relevance of these principles is grounded in the distinction between strategic and definitory rules. (shrink)

Popper is well known for rejecting a logic of discovery, but he is only justified in rejecting the same type of logic of discovery that is denied by consequentialism. His own account of hypothesis generation, based on a natural selection analogy, involves an error-eliminative logic of discovery and the differences he admits between biological and conceptual evolution suggest an error-corrective logic of discovery. These types of logics of discovery are based on principles of plausibility that are used in the generation (...) as opposed to the preliminary evaluation of hypotheses. The normative relevance of these principles is grounded in the distinction between strategic and definitory rules. (shrink)

Despite the by now historical tendency to demarcate scientific epistemology sharply from virtually all others, especially theological “epistemology,” it has recently been recognized that both enterprises share a great deal in common, at least as far as the epistemology of discovery is implicated. Such a claim is founded upon a psychological analysis of figuration, where, it is argued, metaphor plays a crucial role in the mediation of discovery, in the domains of science and religion alike. Thus, although the conventionally conceived (...) scientific method is crucial to the enterprise, primacy must nonetheless be accorded to discovery, which drives virtually all disciplines. (shrink)

In his influential paper, 'Why Was the Logic of Discovery Abandoned?', Laudan contends that there has been no philosophical rationale for a logic of discovery since the emergence of consequentialism in the 19th century. It is the purpose of this paper to show that consequentialism does not involve the rejection of all types of logic of discovery. Laudan goes too far in his interpretation of the historical shift from generativism to consequentialism, and his claim that the context of pursuit belongs (...) to neither discovery nor justification is based on narrow interpretations of the contexts of discovery and justification. As a result, Laudan draws unwarranted conclusions concerning both the early and contemporary defenders of a logic of discovery. A methodological logic of discovery - which involves self-corrective methods of hypothesis generation that promote the long-term goals of science and which require consequential support for justification - is a type of logic of discovery that survives the shift to consequentialism. (shrink)

Reichenbach's Philosophy of Space and Time (1928) avoids most of the logical positivist pitfalls it is generally held to exemplify, notably both conventionalism and verificationism. To see why, we must appreciate that Reichenbach's interest lies in how mathematical structures can be used to describe reality, not in how words like 'distance' acquire meaning. Examination of his proposed "coordinative definition" of congruence shows that Reichenbach advocates a reductionist analysis of the relations figuring in physical geometry (contrary to common readings that attribute (...) to him a holistic conventionalism), while embracing a thoroughly holistic understanding of empirical confirmation (contrary to rival operationalist readings). (shrink)

In this paper, I take a closer look at Hans Reichenbach’s relation to metaphysics and work out some interesting parallels between his account and that of the proponents of inductive metaphysics, a tradition that emerged in the mid- and late 19th century and the early 20th century in Germany. It is in particular Hans Reichenbach’s conception of the relation between the natural sciences and metaphysics, as displayed in his treatment of the question of the existence of the external world, that (...) shows some very interesting similarities with inductive metaphysics. By a comparison with the position of the inductive metaphysician Erich Becher and his handling of the problem of realism, I work out the parallels between Reichenbach’s program and inductive metaphysics. I come to the conclusion that while there are certainly some respects in which Reichenbach’s logical empiricism is closer to the positions of the representatives of the Vienna Circle, it turns out that with regard to his views on metaphysics there is a greater affinity with the program of inductive metaphysics. (shrink)

This article suggests a ‘best alternative' justification of induction (in the sense of Reichenbach) which is based on meta-induction . The meta-inductivist applies the principle of induction to all competing prediction methods which are accessible to her. It is demonstrated, and illustrated by computer simulations, that there exist meta-inductivistic prediction strategies whose success is approximately optimal among all accessible prediction methods in arbitrary possible worlds, and which dominate the success of every noninductive prediction strategy. The proposed justification of meta-induction is (...) mathematically analytical. It implies, however, an a posteriori justification of object-induction based on the experiences in our world. *Received November 2005; revised March 2008. †To contact the author, please write to: Department of Philosophy, University of Duesseldorf, Universitaetsstrasse 1, Geb. 23.21, Duesseldorf, Germany D-40225; e-mail: [email protected]. (shrink)

This is a response to the papers in the special issue Logical Perspectives on Science and Cognition—The Philosophy of Gerhard Schurz.

In recent years there has been a revival of the debate about the relation between history and philosophy of science. This article seeks to contribute to the discussion by approaching the issue from a new angle. To rethink the relation between the two domains of study, I apply an important insight about scientific practice to the practice of integrating the history and philosophy of science: the insight that the scientific paper does not give a faithful account of the actual research (...) pursued in the laboratory or in the field. Arguably, the scholarly article about science is also not a transparent window to the activity of producing such an article. But if it is not, we need to redirect our attention. If we want to understand the nature and merits of integrating the history and philosophy of science, we need to examine both the actual activity of integrating and the scholarly paper produced by it. To consider what one can learn from such an inquiry, I reflect on my own activity of studying scientific justification through the combination of historical and philosophical analysis. Probing a concrete historical episode, micro-anatomical research on the retina in the 19th century, I pursue two related questions, the first-order question, 'What exactly is scientific justification in the given case?' and the meta-question, 'How do I go about analysing justificatory practices?' I then characterise the nature of my analysis and consider what can be learned from the study of the practice of integrating the history and philosophy of science. (shrink)

In this paper Reichenbach's best alternative account to induction is examined. In the first section, three versions of the BAA are distinguished that have been discussed in the literature. The major objections against all three versions are presented. In the second section it is shown by a text analysis that Reichenbach argues for all three versions of the BAA and does not sufficiently distinguish between them. In the third section it is explained how Reichenbach's third version of the BAA can (...) be transformed into a provable optimality theorem within the account of meta-induction. (shrink)

In this essay, I develop and defend a virtue-theoretic conception of rationality as a capacity whose function is understanding, as opposed to mere truth or correctness. I focus on two main potential advantages of this view. First, its ability to explain the rationality of forms of explanatory reasoning, and second, its ability to offer a more unified account of theoretical and practical rationality.

Phenomenologists usually insist that their approach involves going “back” to and “starting” with technoscientific experience—that is, returning to the actual existing or living through of technoscientific life—after centuries of privileging the analysis of how things are “objectively” known and denigrating accounts of how they are “subjectively” lived with. But then who says this and how is this understood? “Who” is really a phenomenologist, when so many diverse thinkers claim the title? This paper considers some of the reasons why this is (...) such a difficult question and argues that it is wrong to look for The Answer to it. (shrink)

. This paper discusses the claim that science is “messy.” Part I argues first, that a good portion of today’s discussions about messy science is just a portrayal of familiar features of science in new terms. In the paper, I refer to this as “messy science talk.” Second, Part I draws out rhetorical functions of messy science talk, namely the denigration of science in the popular media and the celebration of the maverick. Part II identifies one way in which it (...) is enlightening to think about mess in current science, namely in reference to the problems that scientists need to address. It also shows that we do not need an entirely new conceptual inventory to analyze these problems. “Mess” and “wicked problems” were a theme in operations research and theories of social planning in the 1970s. These older analyses can illuminate important characteristics of today’s scientific problems. Wicked problems cut across different disciplines, engage different stakeholders, are fluid, and cannot even be clearly formulated. They are urgent and need to be addressed before sufficient evidence is in. (shrink)

This article identifies a fundamental distinction in scientific practice: the mismatch between what scientists do and what they state they did when they communicate their findings in their publications. The insight that such a mismatch exists is not new. It was already implied in Hans Reichenbach's distinction between the contexts of discovery and justification, and it is taken for granted across the board in philosophy of science and science studies. But while there is general agreement that the mismatch exists, the (...) epistemological implications of that mismatch are not at all clear. Philosophers, historians, and sociologists of different stripes have expressed widely different views about how one should understand and interpret the relation between what scientists do and what they state they did. This article surveys a number of approaches to the mismatch. Based on this survey, I offer an assessment of the epistemological significance of the mismatch and identify the major meta-epistemological challenges that it poses for the analysis of scientific practice. *Received May 2007; revised April 2008. †To contact the author, please write to: Department of History and Philosophy of Science, 1011 East Third Street, Goodbody Hall 130, Indiana University, Bloomington, IN 47405; e-mail: [email protected]. (shrink)

With his distinction between the "context of discovery" and the "context of justification", Hans Reichenbach gave the traditional difference between genesis and validity a modern standard formulation. Reichenbach's distinction is one of the well-known ways in which the expression "context" is used in the theory of science. My argument is that Reichenbach's concept is unsuitable and leads to contradictions in the semantic fields of genesis and validity. I would like to demonstrate this by examining the different meanings of Reichenbach's context (...) distinction. My investigation also shows how the difference between genesis and validity precedes Reichenbach's context distinction and indicates approaches for meaningful applications of the concept of context to the phenomena designated by Reichenbach. I will begin by reconstructing the way in which Reichenbach introduces the distinction between discovery and justification as a difference of contexts (I). Drawing on the numerous meanings of the term "context", I will then emphasize some chief characteristics and review, through exemplification, the usage of this term. First of all, I turn to the context of discovery as the nonrational part of all scientific knowledge and show that this meaning cannot be defined consistently (la). For the context of justification, one can distinguish two main cases: the context of justification is either contrasted with the context of discovery, or it forms a unit there with. In the first case, the use of the context term becomes paradoxical, insofar as justification separated from scientific practice does not represent a field of reference which could be specifically contrasted with another field of reference (I b). In the second case, the unifying definitions contradict the contextual meaning of discovery and justification (1 c). In the last section, I point to a useful application of the concept of context which can be found in Reichenbach's argumentation and which refers to the practical conditions of justification(2). (shrink)

This paper analyzes three contrasting strategies for modeling intentional agency in contemporary analytic philosophy of mind and action, and draws parallels between them and similar strategies of scientific model-construction. Gricean modeling involves identifying primitive building blocks of intentional agency, and building up from such building blocks to prototypically agential behaviors. Analogical modeling is based on picking out an exemplary type of intentional agency, which is used as a model for other agential types. Theoretical modeling involves reasoning about intentional agency in (...) terms of some domain-general framework of lawlike regularities, which involves no detailed reference to particular building blocks or exemplars of intentional agency. Given the contrasting procedural approaches that they employ and the different types of knowledge that they embody, the three strategies are argued to provide mutually complementary perspectives on intentional agency. (shrink)

Carnap’s work was instrumental to the liberalization of empiricism in the 1930s that transformed the logical positivism of the Vienna Circle to what came to be known as logical empiricism. A central feature of this liberalization was the deployment of the Principle of Tolerance, originally introduced in logic, but now invoked in an epistemological context in “Testability and Meaning”. Immediately afterwards, starting with Foundations of Logic and Mathematics, Carnap embraced semantics and turned to interpretation to guide the choice of a (...) theoretical language for science. The first thesis of this paper is that recourse to an intended interpretation led to a partial retrenchment of the conventionalism implied by the Principle of Tolerance. It required that the choice of a language be based on abstraction from a context; this procedure later became a component of the process of explication that was distinctive to Carnap’s mature views. The interpretive origin of formal systems also ensured their likely syntactic consistency, an issue on which Carnap was strongly criticized by figures such as Beth and Gödel. The second thesis of this paper is that this reliance on an intended interpretation enabled constructed formal systems to be relevant to the development of empirical science. (shrink)

In this paper, I discuss the key role played by Carl G. Hempel's work on theoretical realism and scientific explanation in effecting a crucial philosophical transition between the beginning and the end of the twentieth century. At the beginning of the century, the dominant view was that science is incapable of furnishing explanations of natural phenomena; at the end, explanation is widely viewed as an important, if not the primary, goal of science. In addition to its intellectual benefits, this transition (...) has important practical consequences with respect to dealing with the global problems humans everywhere will face in the twenty-first century. (shrink)

Reichenbach sought to resolve Hume's problem of the justification of induction by means of a pragmatic vindication that relies heavily on the convergence properties of his rule of induction. His attempt to rule out all other asymptotic methods by an appeal to descriptive simplicity was unavailing. We found that important progress in that direction could be made by invoking normalizing conditions (consistency) and methodological simplicity (as a basis for invariance), but that they did not do the whole job. I am (...) proposing that, in the end, Reichenbach's own distinction between discovery and justification holds the key to the solution. (shrink)

The aim of this contribution is to provide a rather general answer to Hume’s problem. To this end, induction is treated within a straightforward formal paradigm, i.e., several connected levels of abstraction. Within this setting, many concrete models are discussed. On the one hand, models from mathematics, statistics and information science demonstrate how induction might succeed. On the other hand, standard examples from philosophy highlight fundamental difficulties. Thus it transpires that the difference between unbounded and bounded inductive steps is crucial: (...) while unbounded leaps of faith are never justified, there may well be reasonable bounded inductive steps. In this endeavour, the twin concepts of information and probability prove to be indispensable, pinning down the crucial arguments, and, at times, reducing them to calculations. Essentially, a precise study of boundedness settles Goodman’s challenge. Hume’s more profound claim of seemingly inevitable circularity is answered by obviously non-circular hierarchical structures. (shrink)

The availability of unitarily inequivalent representations of the canonical commutation relations constituting a quantization of a classical field theory raises questions about how to formulate and pursue quantum field theory. In a minimally technical way, I explain how these questions arise and how advocates of the Hilbert space and of the algebraic approaches to quantum theory might answer them. Where these answers differ, I sketch considerations for and against each approach, as well as considerations which might temper their apparent rivalry.

Deviant forms of human thought may provide insight into epistemic standards, such as rationality. A comparative analysis of paranoia and reinforced dogmatism suggests that reinforced dogmatism, such as pseudo-science a-la-Popper, demonstrates a primary epistemic lack of critical rationality, that is, of testability, whereas paranoia demonstrates a lack of range of alternative statements leading secondarily to a lack of testability. This reflects the importance to both epistemology and psychiatry of epistemic standards in addition to testability, such as relevance to problems, and (...) emphasizes the distinction of the context of introduction from the contexts of discovery and of justification. Key Words: context of introduction • paranoia • reinforced dogmatism • relevance • testability. (shrink)

Philosophical discussion of the general methodology of qualitative research, such as that used in some health research, has been inductivist or relativist to date, ignoring critical rationalism as a philosophical approach with which to discuss the general methodology of qualitative research. This paper presents a discussion of the general methodology of qualitative research from a critical rationalist perspective (inspired by Popper), using as an example mental health research. The widespread endorsement of induction in qualitative research is positivist and is suspect, (...) if not false, particularly in relation to the context of justification (or rather theory testing) as compared to the context of discovery (or rather theory generation). Relativism is riddled with philosophical weaknesses and hence it is suspect if not false too. Theory testing is compatible with qualitative research, contrary to much writing about and in qualitative research, as theory testing involves learning from trial and error, which is part of qualitative research, and which may be the form of learning most conducive to generalization. Generalization involves comparison, which is a fundamental methodological requirement of any type of research (qualitative or other); hence the traditional grounding of quantitative and experimental research in generalization. Comparison—rather than generalization—is necessary for, and hence compatible with, qualitative research; hence, the common opposition to generalization in qualitative research is misdirected, disregarding whether this opposition’s claims are true or false. In conclusion, qualitative research, similar to quantitative and experimental research, assumes comparison as a general methodological requirement, which is necessary for health research. (shrink)

Both Popper and van Fraassen have used evolutionary analogies to defend their views on the aim of science, although these are diametrically opposed. By employing Price's equation in an illustrative capacity, this paper considers which view is better supported. It shows that even if our observations and experimental results are reliable, an evolutionary analogy fails to demonstrate why conjecture and refutation should result in: (1) the isolation of true theories; (2) successive generations of theories of increasing truth-likeness; (3) empirically adequate (...) theories; or (4) successive generations of theories of increasing proximity to empirical adequacy. Furthermore, it illustrates that appeals to induction do not appear to help. It concludes that an evolutionary analogy is only sufficient to defend the notion that the aim of science is to isolate a particular class of false theories, namely those that are empirically inadequate. (shrink)

In this article, I seek to shed new light on a lesser-known stage of the development of Hans Reichenbach’s thought, namely his research, output and teaching activities at Istanbul University. I argue that the experience of Turkish exile was decisive in the elaboration of Reichenbach’s probability theory of meaning and knowledge. His work Experience and Prediction, produced while in Istanbul, should therefore be put in its Turkish context of elaboration and reception. To this end, I will take into consideration not (...) only Reichenbach’s efforts to popularize and extend the Berlin Group’s program of scientific philosophy in Turkey and throughout Europe in the 1930s, but also the forgotten work of Reichenbach’s students—most of them women—at Istanbul University. (shrink)

What is the relation of epistemology, understood as the study of the evaluation of knowledge claims, and empirical psychology, understood as the study of the causal generation of a person's beliefs? Quine maintains that the relation is one of “mutual containment”.Epistemology in its new setting, conversely, is contained in natural science, as a chapter of psychology. … We are studying how the human subject of our study posits bodies and projects his physics from his data, and we appreciate that our (...) position in the world is just like his. Our very epistemological enterprise, therefore, and the psychology wherein it is a component chapter, and the whole of natural science wherein psychology is a component book—all this is our own construction or projection from stimulations like those we were meting out to our epistemological subject. There is thus reciprocal containment, though containment in different senses: epistemology in natural science and natural science in epistemology. (shrink)

I I set out my view that all inference is essentially deductive and pinpoint what I take to be the major shortcomings of the induction rule.II The import of data depends on the probability model of the experiment, a dependence ignored by the induction rule. Inductivists admit background knowledge must be taken into account but never spell out how this is to be done. As I see it, that is the problem of induction.III The induction rule, far from providing a (...) method of discovery, does not even serve to detect pattern. Knowing that there is uniformity in the universe is no help to discovering laws. A critique of Reichenbach's justification of the straight rule is constructed along these lines.IV The induction rule, by itself, cannot account for the varying rates at which confidence in an hypothesis mounts with data. The mathematical analysis of this salient feature of inductive reasoning requires prior probabilities. We also argue, against orthodox statisticians, that prior probabilities make a substantive contribution to the objectivity of inductive methods, viz. to the design of experiments and the selection of decision rules.V Carnap's general criticisms of various estimation rules, like the straight rule and the ‘impervious rule’, are seen to be misguided when the prior densities to which they correspond are taken into account.VI Analysis of Hempel's definition of confirmation qua formalization of the enumerative (naive) conception of instancehood. We show that from the standpoint of the quantitative measure P(H/E):P(H) for the degree to which E confirms H, Hempel's classificatory concept yields correct results only for sampling at large from a finite population with a two-way classification all of whose compositions are equally probable. We extend the analysis to Goodman's paradox, finding cases in which grue-like hypotheses do receive as much confirmation as their opposite numbers. We argue, moreover, the irrelevancy of entrenchment, and maintain that Goodman's paradox is no more than a straightforward counter-example to the enumerative conception of instancehood embodied in Hempel's definition.VII We rebutt the objection that prior probabilities, qua inputs of Bayesian analysis, can only be obtained by enumerative induction (insofar as they are objective). The divergence in the prior densities of two rational agents is less a function of subjectivity, we maintain, than of vagueness.VIII Our concluding remarks stress that, for Bayesians, there is no problem of induction in the usual sense. (shrink)

Replicability is widely taken to ground the epistemic authority of science. However, in recent years, important published findings in the social, behavioral, and biomedical sciences have failed to replicate, suggesting that these fields are facing a “replicability crisis.” For philosophers, the crisis should not be taken as bad news but as an opportunity to do work on several fronts, including conceptual analysis, history and philosophy of science, research ethics, and social epistemology. This article introduces philosophers to these discussions. First, I (...) discuss precedents and evidence for the crisis. Second, I discuss methodological, statistical, and social-structural factors that have contributed to the crisis. Third, I focus on the philosophical issues raised by the crisis. Finally, I discuss proposed solutions and highlight the gaps that philosophers could focus on. (shrink)

Advocates of the self-corrective thesis argue that scientific method will refute false theories and find closer approximations to the truth in the long run. I discuss a contemporary interpretation of this thesis in terms of frequentist statistics in the context of the behavioral sciences. First, I identify experimental replications and systematic aggregation of evidence (meta-analysis) as the self-corrective mechanism. Then, I present a computer simulation study of scientific communities that implement this mechanism to argue that frequentist statistics may converge upon (...) a correct estimate or not depending on the social structure of the community that uses it. Based on this study, I argue that methodological explanations of the “replicability crisis” in psychology are limited and propose an alternative explanation in terms of biases. Finally, I conclude suggesting that scientific self-correction should be understood as an interaction effect between inference methods and social structures. (shrink)

Taking its clues from Popperian philosophy of science, cladistics adopted a number of assumptions of the empiricist tradition. These include the identification of a dichotomy between observation reports and theoretical statements and its subsequent abandonment on the basis of the insight that all observation reports are theory-laden. The neglect of the ‘context of discovery’, which is the step of theory (hypothesis) generation. The emphasis on coherentism in the ‘context of justification’, which is the step of evaluation of the relative merits (...) of alternative theories. The appeal to a total evidence approach in phylogenetic inference. And finally, a silence about causation, which results in an instrumentalist approach to phylogeny reconstruction. This paper explores how these empiricist assumptions are embedded in phylogenetic systematics, and why these assumptions are problematic for cladists (or any taxonomists). (shrink)

Constructivism is the idea that we construct our own world rather than it being determined by an outside reality. Its most consistent form, Radical Constructivism (RC), claims that we cannot transcend our experiences. Thus it doesn't make sense to say that our constructions gradually approach the structure of an external reality. The mind is necessarily an epistemological solipsist, in contrast to being an ontological solipsist who maintains that this is all there is, namely a single mind within which the only (...) world exists. RC recognizes the impossibility of the claim that the world does not exist. Yet, RC has the potential to go much further. I claim that RC provides the foundation of a new world-view in which we can overcome hard scientific problems. Thus, the paper is urging us to carry RC further, not just on philosophical grounds, but also into the domain of science. (shrink)

This essay looks at some of the key aspects of Hans Reichenbach’s career as a radio engineer, broadcaster, and producer. It argues that some of the themes of Reichenbach’s logical empiricism can be illuminated by looking at them in relation to his work as a radio engineer during and after World War One. It also argues that attention to the educational activities he undertook in the new broadcast radio medium can help us understand that affinities he saw between logical empiricism (...) and other modernizing projects of Weimar Germany. (shrink)

In recent years, many philosophers of science have rejected the “value-free ideal” for science, arguing that non-epistemic values have a legitimate role to play in scientific inquiry. However, this philosophical position raises the question of how to distinguish between legitimate and illegitimate influences of values in science. In this paper, we argue that those seeking to address this “new” demarcation problem can benefit by drawing lessons from the “old” demarcation problem, in which philosophers tried to find a way of distinguishing (...) between science and non-science. Many of those who worked on this problem ultimately found that efforts to provide necessary and sufficient conditions for defining science failed, and most concluded that the best solution to the problem was to characterize scientific hypotheses, theories, and research programs in terms of some common norms. We suggest that those seeking to distinguish between legitimate and illegitimate value influences on science would do well to adopt a similar approach. Rather than attempting to establish necessary and sufficient conditions for identifying appropriate value influences, it will be more fruitful to evaluate scientific activities based on their adherence to a set of epistemic and ethical norms that can be implemented in scientific practice by means of rules, conventions, policies, and procedures. (shrink)

InScience and Values (1984) and other, more recent, works, e.g. (1987a, 1987b, 1989a, 1989b, 1990), Larry Laudan proposes a theory of scientific debate he dubs the reticulated model of scientific rationality (Laudan, 1984, pp. 50–66). The model stands in sharp contrast to hierarchical approaches to rationality exemplified by Popper (1959), Hempel (1965), and Reichenbach (1938), as well as the conventionalist views of rationality defended by Carnap (1950), Popper (1959), Kuhn (1962), and Lakatos (1978). Ironically, the model commits some of the (...) same errors Laudan finds in hierarchicalist and conventionalists approaches to scientific rationality. This paper will show that the model can be fixed by recognizing that criteria of goal assessment have no privileged status. These rules are best viewed as simply rules of rationality (or rules of scientific method) by another name. (shrink)

We propose a model of cognition grounded in ancient Greek philosophy which encompasses Aristotle’s categories. Taking for First Principles the brute facts of the mental actions of separation, aggregation and ordering, we derive Aristotle’s categories as follows. First, Separation lets us see single entities, giving the simple concept of an individual. Next, Aggregation lets us see instances of some kind, giving the basic concept of a particular. Then, Ordering lets us see both wholes-with-parts as well as parts-of-some-whole, giving the subtle (...) concept of a relational or Gestalt. The basic and the subtle concept give us the major and minor categories. The categories constitute a top-level ontology and describe universal usage so that any other category necessarily describes particular or domain usage. (shrink)

In the production of knowledge about social life, two social contexts come together: the context of investigation, consisting of the social world of the investigator, and the context of explanation, consisting of the social world of the actors who are the subject of study. The nature of, and relationship between, these contexts is imagined in philosophy; managed, rewarded, and sanctioned in graduate seminars, journal reviews, and tenure cases; and practiced in research. Positivism proposed to produce objective knowledge by suppressing the (...) nonlogical and nonobservational aspects of the contexts. Attacks on positivism disputed the effectiveness and rationality of this strategy. Thus " postpositivism " can be understood as a series of attempts to reconstitute the relation between the contexts as the basis for accurate social knowledge. Two of the most important of these attempts—grounded theory and postmodern anthropology—are considered, and a synthesis, which draws from the insights of cultural sociology, is proposed. (shrink)

The debates between Bayesian, frequentist, and other methodologies of statistics have tended to focus on conceptual justifications, sociological arguments, or mathematical proofs of their long run properties. Both Bayesian statistics and frequentist (“classical”) statistics have strong cases on these grounds. In this article, we instead approach the debates in the “Statistics Wars” from a largely unexplored angle: simulations of different methodologies’ performance in the short to medium run. We conducted a large number of simulations using a straightforward decision problem based (...) around tossing a coin with unknown bias and then placing bets. In this simulation, we programmed four players, inspired by Bayesian statistics, frequentist statistics, Jon Williamson’s version of Objective Bayesianism, and a player who simply extrapolates from observed frequencies to general frequencies. The last player functions as a benchmark: a statistical methodology should at least outperform a crude form of induction. We focused on the performance of these methodologies in guiding the players towards good decisions. Unlike an earlier simulation study of this type, we found no systematic difference in performance between the Bayesian and frequentist players, provided the Bayesian used a flat prior and the frequentist used a low confidence level. Unlike that study, we were able to use Big Data methods to mitigate problems of random error in the simulation results. The Williamsonian player, who is a novel element of our study, also had no systematic differences in their performance, provided that they use a low confidence level. These players performed similarly even in the very short run, when players were making different decisions. Our study indicates that all three methodologies should be taken seriously by philosophers and practitioners of statistics. However, the frequentist and Williamsonian performed poorly when their confidence levels were high, and the Bayesian was surprisingly harmed by biased priors, providing some unexpected lessons for these methodologies when facing this type of decision problem. (shrink)