We provide an analysis of the public's having warranted epistemic trust in science, that is, the conditions under which the public may be said to have well-placed trust in the scientists as providers of information. We distinguish between basic and enhanced epistemic trust in science and provide necessary conditions for both. We then present the controversy regarding the connection between autism and measles–mumps–rubella vaccination as a case study to illustrate our analysis. The realization of warranted epistemic public trust in science (...) requires various societal conditions, which we briefly introduce in the concluding section. (shrink)
Although there is universal consensus both in the science education literature and in the science standards documents to the effect that students should learn not only the content of science but also its nature, there is little agreement about what that nature is. This led many science educators to adopt what is sometimes called “the consensus view” about the nature of science (NOS), whose goal is to teach students only those characteristics of science on which there is wide consensus. This (...) is an attractive view, but it has some shortcomings and weaknesses. In this article we present and defend an alternative approach based on the notion of family resemblance. We argue that the family resemblance approach is superior to the consensus view in several ways, which we discuss in some detail. (shrink)
The idea of family resemblance, when applied to science, can provide a powerful account of the nature of science (NOS). In this chapter we develop such an account by taking into consideration the consensus on NOS that emerged in the science education literature in the last decade or so. According to the family resemblance approach, the nature of science can be systematically and comprehensively characterised in terms of a number of science categories which exhibit strong similarities and overlaps amongst diverse (...) scientific disciplines. We then discuss the virtues of this approach and make some suggestions as to how one can go about teaching it in the classroom. (shrink)
This article develops an account of distributive epistemic justice in the production of scientific knowledge. We identify four requirements: (a) science should produce the knowledge citizens need in order to reason about the common good, their individual good and pursuit thereof; (b) science should produce the knowledge those serving the public need to pursue justice effectively; (c) science should be organized in such a way that it does not aid the wilful manufacturing of ignorance; and (d) when making decisions about (...) epistemic risks, scientists should make sure that there aren’t social groups or weighty interests that are neglected. After discussing these requirements, we examine the relationship between discriminatory and distributive epistemic injustice in science and argue that they often compound each other. (shrink)
Building, restoring and maintaining well-placed trust between scientists and the public is a difficult yet crucial social task requiring the successful cooperation of various social actors and institutions. Kitcher’s takes up this challenge in the context of liberal democratic societies by extending his ideal model of “well-ordered science” that he had originally formulated in his. However, Kitcher nowhere offers an explicit account of what it means for the public to invest epistemic trust in science. Yet in order to understand how (...) his extended model and its implementation in the actual world address the problem of trust as well as to evaluate it critically, an explicit account of epistemic public trust in science needs to be given first. In this article we first present such an account and then scrutinize his project of building public trust in science in light of it. We argue that even though Kitcher’s ideal model and his proposals for its implementation in the real world face a number of problems, they can be addressed with the resources of our account. (shrink)
We compare Carnap's and Kuhn's views on science. Although there are important differences between them, the similarities are striking. The basis for the latter is a pragmatically oriented semantic conventionalist picture of science, which suggests that the view that post-positivist philosophy of science constitutes a radical revolution which has no interesting affinities with logical positivism must be seriously mistaken.
In this article we develop an account of justice in the distribution of knowledge. We first argue that knowledge is a fundamental interest that grounds claims of justice due to its role in individuals’ deliberations about the common good, their personal good and the pursuit thereof. Second, we identify the epistemic basic structure of a society, namely, the institutions that determine individuals’ opportunities for acquiring knowledge and discuss what justice requires of them. Our main contention is that a systematic lack (...) of opportunity to acquire knowledge one needs as an individual and a citizen because of the way the epistemic basic structure of a society is organized is an injustice. Finally, we discuss how our account relates to John Rawls’s influential theory of justice. (shrink)
Thomas Kuhn's post-1980 writings have increasingly emphasized the role played by language in the characterization of scientific revolutions and incommensurability. We argue that Kuhn's `linguistic turn' can be understood best against the background of a Whorfian conception of language and certain neo-Kantian themes. While this enables Kuhn to refine and unify his earlier views, it also creates some difficulties.
Certain segments of science are becoming increasingly commercialized. This article discusses the commercialization of academic science and its impact on various aspects of science. It also aims to provide an introduction to the articles in this special issue. I briefly describe the major factors that led to this phenomenon, situate it in the context of the changing social regime of science and give a thumbnail sketch of its costs and benefits. I close with a general discussion of how the topic (...) of commercialization of academic science is relevant to science education. (shrink)
This paper argues against Papineau's claim that causal relations can be reduced to correlations and defends Cartwright's thesis that they can be nevertheless boot-strapped from them, given sufficiently rich causal background knowledge.
Philosophers of science have paid little attention, positive or negative, to Lyotard’s book The postmodern condition, even though it has been popular in other fields. We set out some of the reasons for this neglect. Lyotard thought that sciences could be justified by non-scientific narratives. We show why this is unacceptable, and why many of Lyotard’s characterisations of science are either implausible or are narrowly positivist. One of Lyotard’s themes is that the nature of knowledge has changed and thereby so (...) has society itself. However much of what Lyotard says muddles epistemological matters about the definition of ‘knowledge’ with sociological claims about how information circulates in modern society. We distinguish two kinds of legitimation of science: epistemic and socio-political. In proclaiming ‘incredulity towards metanarratives’ Lyotard has nothing to say about how epistemic and methodological principles are to be justified. He also gives a bad argument as to why there can be no epistemic legitimation, which is based on an act/content confusion, and a confusion between making an agreement and the content of what is agreed to. As for socio-political legitimation, Lyotard’s discussion remains at the abstract level of science as a whole rather than at the level of the particular applications of sciences. Moreover his positive points can be accepted without taking on board any of his postmodernist account of science. Finally we argue that Lyotard’s account of paralogy, which is meant to provide a ‘postmodern’ style of justification, is a failure.Author Keywords: Lyotard; Postmodernism; Science; Knowledge; Legitimation; Philosophy of science. (shrink)
This Introduction to the Special Issue on “Responsible Research and Innovation” outlines features of the philosophical debate about the concepts involved and summarizes the papers assembled in this issue. The topic of RRI is widely discussed in science studies and has made its way into science policy. This SI is intended to make the contributions of philosophers of science more visible. The philosophically relevant parts of the field concern, among others, the processes of public participation in science and their impact (...) on the knowledge produced, the notion of justified public trust in science, and the idea of research pursued for the common good. Such topics bring social procedures together with epistemic and ethical considerations and thus raise philosophical challenges. RRI is subject to the tension between committing research to creating knowledge in harmony with public expectations, on the one hand, while not complying with public wishful thinking, on the other. RRI embodies a friction between serving people’s aspirations and correcting people’s expectations. This special issue is intended to explore the narrow pathway left between these conflicting demands. (shrink)
Causal modeling methods such as path analysis, used in the social and natural sciences, are also highly relevant to philosophical problems of probabilistic causation and statistical explanation. We show how these methods can be effectively used (1) to improve and extend Salmon's S-R basis for statistical explanation, and (2) to repair Cartwright's resolution of Simpson's paradox, clarifying the relationship between statistical and causal claims.
The papers collected in this Synthese special issue are the result of a conference that one of us (ES) casually suggested and the other (GI) organized, which took place at Bo˘gaziçi University in Istanbul, in May 2008, to commemorate the seventieth anniversary of the publication of Experience and Prediction. These papers are historical and philosophical in varying degrees. Reichenbach is now often lumped together with the logical positivists of the Vienna Circle, but his ideas, especially those in Experience and Prediction, (...) were often developed in opposition to positivism. We hope that the essays collected here will be a resource for philosophers who work on the problems that Reichenbach addressed, and also that these essays will be useful to historians who want to develop a deeper understanding of Reichenbach in his historical context. (shrink)
Recent philosophical studies of probabilistic causation and statistical explanation have opened up the possibility of unifying philosophical approaches with causal modeling as practiced in the social and biological sciences. This unification rests upon the statistical tools employed, the principle of common cause, the irreducibility of causation to statistics, and the idea of causal process as a suitable framework for understanding causal relationships. These four areas of contact are discussed with emphasis on the relevant aspects of causal modeling.
Fleeing from the Nazi regime, along with many German refugees, Hans Reichenbach came to teach at Istanbul University in 1933, accepting the invitation of the Turkish government and stayed in Istanbul until 1938. While much is known about his work and life in Istanbul, the existing literature relies mostly on his letters and works. In this article I try to shed more light on Reichenbach's scholarly activities and personal life by also taking into account the Turkish sources and the academic (...) context in which Reichenbach taught and worked. (shrink)
Humean accounts of law are at the same time accounts of causation. Accordingly, since laws are nothing but contingent cosmic regularities, to be a cause is just to be an instance of such a law. Every particular cause-effect pair, according to these accounts, instantiates some law of nature. I argue that this claim is false. Singular causation without being governed by any law is logically and physically possible. Separating causes from laws enables us to see the distinct role each plays (...) in science, especially in matters related to prediction and explanation. (shrink)
From its early origins to the present, the development of mainstream economic theory has taken a direction which has excluded the analysis of human needs as a basis for social policy. The problems associated with this orientation are increasingly recognized both by economists and non-economists. As Sen points out, it is indeed strange for a discipline concerned with the well-being of people to neglect the question of needs. Currently, some writers such as Doyal and Gough, post-Keynesian economists such as Lavoie, (...) and those such as Davis and O'Boyle who work in the newly emerging school of social economics have begun to address the question of human needs, especially in relation to problems of policy assessment and evaluation. The approaches of some development economists who have dealt with similar issues were also instrumental in drawing attention to the significance of the long-neglected concept of needs. (shrink)
I argue that Nancy Cartwright's largely methodological arguments for capacities and against Hume's regularity account of causation are only partially successful. They are especially problematic in establishing the primacy of singular causation and the reality of mixed-dual capacities. Therefore, her arguments need to be supported by ontological ones, and I propose the propensity interpretation of causal probabilities as a natural way of doing this.
Drawing on the recent revisionary scholarship regarding logical positivism and its relation to the early post-positivism, I display and question the standard historical understanding of the analytical philosophy of science from the late 1920s to the mid-1970s. I then propose an alternative account based on the internal-external distinction. I conclude by showing some advantages of my alternative narrative that does more justice to the logical positivism than the standard understanding and suggest some further lines of research that it opens up.