Public scientific testimony in the scientific image

In this paper, I draw on philosophy of science to address a challenge for science communication. Empirical research indicates that some people who trust a meteorologist's report that they are in the path of a storm do not trust a climate scientist's report that we are on a path to global warming. Such selective skepticism about climate science exemplifies a more general challenge:

The Challenge of Selective UptakeLaypersons who generally accept public scientific testimony nevertheless fail to accept public scientific testimony concerning select, equally well warranted, scientific hypotheses.

A prominent response arising from the novel interdisciplinary science of science communication is a principle called Consensus Reporting. According to this principle, science reporters should, whenever feasible, report the scientific consensus or lack thereof for a reported scientific view.However, philosophy of science may offer a different perspective on the issue. This perspective is critical insofar as it indicates some inadequacies of Consensus Reporting. But it is also constructive insofar as it guides the development of an alternative principle, Justification Reporting, according to which science reporters should, whenever feasible, report aspects of the nature and strength of scientific justification or lack thereof for a reported scientific view. A central difference between these proposals is that Consensus Reporting appeals to the authority of the scientists whereas Justification Reporting appeals to the authority of scientific justification. As such, Justification Reporting reflects the image of science.The paper considers the philosophical and empirical motivation for Justification Reporting and its limitations. This includes prospects and problems for implementing it in a way that addresses The Challenge of Selective Uptake. From a methodological point of view, the paper illustrates how empirically informed philosophy of science may help address challenges for science communication.     

Value management and model pluralism in climate science

Non-epistemic values pervade climate modelling, as is now well documented and widely discussed in the philosophy of climate science. Recently, Parker and Winsberg have drawn attention to what can be termed “epistemic inequality”: this is the risk that climate models might more accurately represent the future climates of the geographical regions prioritised by the values of the modellers. In this paper, we promote value management as a way of overcoming epistemic inequality. We argue that value management can be seriously considered as soon as the value-free ideal and inductive risk arguments commonly used to frame the discussions of value influence in climate science are replaced by alternative social accounts of objectivity. We consider objectivity in Longino's sense as well as strong objectivity in Harding's sense to be relevant options here, because they offer concrete proposals that can guide scientific practice in evaluating and designing so-called multi-model ensembles and, in fine, improve their capacity to quantify and express uncertainty in climate projections.     

Computer models and the evidence of anthropogenic climate change: An epistemology of variety-of-evidence inferences and robustness analysis

To study climate change, scientists employ computer models, which approximate target systems with various levels of skill. Given the imperfection of climate models, how do scientists use simulations to generate knowledge about the causes of observed climate change? Addressing a similar question in the context of biological modelling, Levins (1966) proposed an account grounded in robustness analysis. Recent philosophical discussions dispute the confirmatory power of robustness, raising the question of how the results of computer modelling studies contribute to the body of evidence supporting hypotheses about climate change. Expanding on Staley’s (2004) distinction between evidential strength and security, and Lloyd’s (2015) argument connecting variety-of-evidence inferences and robustness analysis, I address this question with respect to recent challenges to the epistemology robustness analysis. Applying this epistemology to case studies of climate change, I argue that, despite imperfections in climate models, and epistemic constraints on variety-of-evidence reasoning and robustness analysis, this framework accounts for the strength and security of evidence supporting climatological inferences, including the finding that global warming is occurring and its primary causes are anthropogenic.     

Defending the selective confirmation strategy

Most scientific realists today in one way or another confine the object of their commitment to certain components of a successful theory and thereby seek to make realism compatible with the history of theory change. Kyle Stanford calls this move by realists the strategy of selective confirmation and raises a challenge against its contemporary, reliable applicability. In this paper, I critically examine Stanford's inductive argument that is based on past scientists' failures to identify the confirmed components of their contemporary theories. I argue that our ability to make such identification should be evaluated based on the performance of the scientific community as a whole rather than that of individual scientists and that Stanford's challenge fails to raise a serious concern because it focuses solely on individual scientists' judgments, which are either made before the scientific community has reached a consensus or about the value of the posit as a locus for further research rather than its confirmed status.     

Modelling and representing: An artefactual approach to model-based representation

The recent discussion on scientific representation has focused on models and their relationship to the real world. It has been assumed that models give us knowledge because they represent their supposed real target systems. However, here agreement among philosophers of science has tended to end as they have presented widely different views on how representation should be understood. I will argue that the traditional representational approach is too limiting as regards the epistemic value of modelling given the focus on the relationship between a single model and its supposed target system, and the neglect of the actual representational means with which scientists construct models. I therefore suggest an alternative account of models as epistemic tools. This amounts to regarding them as concrete artefacts that are built by specific representational means and are constrained by their design in such a way that they facilitate the study of certain scientific questions, and learning from them by means of construction and manipulation.     

“Global warming” versus “climate change”: A replication on the association between political self-identification,question wording,and environmental beliefs

Climate change is one of the greatest threats to humanity and requires immediate action. Schuldt, Konrath, and Schwarz (2011) suggested that beliefs in environmental phenomena can be influenced by the terminology used to describe it: changing question wording from global warming to climate change resulted in a 6.3 percentage point increase in belief in environmental phenomena. This association was moderated by political self-identification, with Republicans being 16.2 percentage points more likely to believe in climate change than in global warming, with Democrats showing no difference. The potential for connotative meanings to shift over time and the sociopolitical changes since the original study, potential policy and environmental campaign implications, and an expansion of these findings to other countries, motivated an attempt to replicate this important finding. This pre-registered study repeated the original procedures in the United States of America and two other countries (United Kingdom and Australia; total N = 5,717). Although question wording no longer had a significant effect on beliefs in climate change/global warming, the association of political self-identification with beliefs in environmental phenomena replicated in all three countries, with Conservatives consistently believing less in climate change/global warming than Liberals. The potential impacts of temporal and methodological differences on the discrepancies between this study's and the original's findings are discussed.     

“Global warming” versus “climate change”: A replication on the association between political self-identification,question wording,and environmental beliefs

Climate change is one of the greatest threats to humanity and requires immediate action. Schuldt, Konrath, and Schwarz (2011) suggested that beliefs in environmental phenomena can be influenced by the terminology used to describe it: changing question wording from global warming to climate change resulted in a 6.3 percentage point increase in belief in environmental phenomena. This association was moderated by political self-identification, with Republicans being 16.2 percentage points more likely to believe in climate change than in global warming, with Democrats showing no difference. The potential for connotative meanings to shift over time and the sociopolitical changes since the original study, potential policy and environmental campaign implications, and an expansion of these findings to other countries, motivated an attempt to replicate this important finding. This pre-registered study repeated the original procedures in the United States of America and two other countries (United Kingdom and Australia; total N = 5,717). Although question wording no longer had a significant effect on beliefs in climate change/global warming, the association of political self-identification with beliefs in environmental phenomena replicated in all three countries, with Conservatives consistently believing less in climate change/global warming than Liberals. The potential impacts of temporal and methodological differences on the discrepancies between this study's and the original's findings are discussed.     

‘Working in a new world’: Kuhn,constructivism, and mind-dependence

In The Structure of Scientific Revolutions, Kuhn famously advanced the claim that scientists work in a different world after a scientific revolution. Kuhn's view has been at the center of a philosophical literature that has tried to make sense of his bold claim, by listing Kuhn's view in good company with other seemingly constructivist proposals. The purpose of this paper is to take some steps towards clarifying what sort of constructivism (if any) is in fact at stake in Kuhn's view. To this end, I distinguish between two main (albeit not exclusive) notions of mind-dependence: a semantic notion and an ontological one. I point out that Kuhn's view should be understood as subscribing to a form of semantic mind-dependence, and conclude that semantic mind-dependence does not land us into any worrisome ontological mind-dependence, pace any constructivist reading of Kuhn.     

Constructing dystopian experience: A Neurath-Cartwrightian approach to the philosophy of social technology

Social situations, the object of the social sciences, are complex and unique: they contain so many variable aspects that they cannot be reproduced, and it is even difficult to experience two situations that are alike in many respects. The social scientists' past experiences that serve as their background knowledge to intervene in an existent situation is poor compared to what a traditional epistemologist would consider ideal. A way of dealing with the variable and insufficient background of social scientists is by means of models. But, then, how should we characterize social scientific models? This paper examines Otto Neurath's scientific utopianism as an attempt to deal with this problem. Neurath proposes that social scientists work with utopias: broad imaginative plans that coordinate a multitude of features of a social situation. This notion can be used in current debates in philosophy of science because we notice that utopias, in Neurath's sense, are comparable to models and nomological machines in Nancy Cartwright's conception. A model-based view of science lays emphasis on the fact that scientists learn from the repeated operation of such abstract entities, just as they learn from the repetition of experiments in a laboratory. Hence this approach suggests an approximation between the natural and the social sciences, as well as between science and utopian literature. This is exemplified by analyzing the literary dystopia We, written by Yevgeny Zamyatin, to show that reasoning from and debating about utopian writings, even if fictional and pessimistic, creates phenomena of valuation, which are fundamental for constituting a background of experiences in the social sciences.     

Constructing Failure: Leonard Hayflick,Biomedicine, and the Problems with Tissue Culture

By examining the use of tissue culture in post-war American biomedicine, this paper investigates how scientists experience and manage failure. I study how Leonard Hayflick forged his new definition of failure and ways of managing it by refuting Alexis Carrel's definition of failure alongside his theory of the immortality of cultured cells. Unlike Carrel, Hayflick claimed that every vertebrate somatic cell should eventually die, unless it transformed into a tumour cell. This claim defined cell death, which had been a problem leading to a laboratory failure, as a normal phenomenon. On the other hand, permanent life, which had been considered a normal cellular characteristic, became a major factor causing scientific failure, since it implied malignant transformation that scientists hoped to control. Hayflick then asserted that his cell strains and method would partly enable scientists to manage this factor—especially that occurred through viral infection—alongside other causes of failure in routine tasks, including bacterial contamination. I argue that the growing biomedical enterprise fostered this work of Hayflick's, which had repercussions in both his career and the uses of cells in diverse investigations. His redefinition of failure in the age of biomedicine resulted in the broad dissemination of his cells, medium, and method as well as his long struggle with the National Institutes of Health (NIH), which caused his temporarily failed career.     

Against defaultism and towards localism in the contingency/inevitability conversation: Or,why we should shut up about putting-up

Philosophers and historians of science have for some time now debated whether the results of current science are ‘contingent’ or ‘inevitable’. Scholars have noted that inevitabilism often enjoys the status of a presumptive default position. Consequently, contingentists are, from the outset, lumbered with the burden of proof. This is evident in the case of the inevitabilist demand that the contingentist “put up or shut up” (PUSU). This paper adds to the existing case which says that inevitabilism's default-status is unjustified. However, whilst some have suggested that contingentism should replace inevitabilism as the default position, I argue that the contingency/inevitability (C/I) conversation should proceed sans default. This move is motivated largely by my claim that the C/I issue is best conceived as a ‘local’, rather than a global or universal one. The main problem with taking inevitabilism or contingentism as the default is the globalist nature of such a tack. Whilst localism is arguably an emergent reality of the growing C/I literature, its implications have not been fully realised. I suggest that fully and explicitly embracing localism, including the closely related move of doing away with defaults, represents the most promising way forward for the C/I conversation. In addition, I will show how these moves entail that we stop worrying about the inevitabilist PUSU demand, or more bluntly, that we shut up about putting-up.     

Scientific authorship in the age of collaborative research

I examine two challenges that collaborative research raises for science. First, collaborative research threatens the motivation of scientists. As a result, I argue, collaborative research may have adverse effects on what sorts of things scientists can effectively investigate. Second, collaborative research makes it more difficult to hold scientists accountable. I argue that the authors of multi-authored articles are aptly described as plural subjects, corporate bodies that are more than the sum of the individuals involved. Though journal editors do not currently conceive of the authors of multi-authored articles this way, this conception provides us with the conceptual resources to make sense of how collaborating scientists behave.     

Evaluating community science

Community science—scientific investigation conducted partly or entirely by non-professional scientists—has many advantages. For example, community science mobilizes large numbers of volunteers who can, at low cost, collect more data than traditional teams of professional scientists. Participation in research can also increase volunteers’ knowledge about and appreciation of science. At the same time, there are worries about the quality of data that community science projects produce. Can the work of non-professionals really deliver trustworthy results? Attempts to answer this question generally compare data collected by volunteers to data collected by professional scientists. When volunteer data is more variable or less accurate than professionally collected data, then the community science project is judged to be inferior to traditional science. I argue that this is not the right standard to use when evaluating community science, because it relies on a false assumption about the aims of science. I show that if we adopt the view that science has diverse aims which are often in tension with one another, then we cannot justify holding community science data to an expert accuracy standard. Instead, we should evaluate the quality of community science data based on its adequacy-for-purpose.     

Contemporary Darwinism as a worldview

The most public-facing forms of contemporary Darwinism happily promote its worldview ambitions. Popular works, by the likes of Richard Dawkins, deflect associations with eugenics and social Darwinism, but also extend the reach of Darwinism beyond biology into social policy, politics, and ethics. Critics of the enterprise fall into two categories. Advocates of Intelligent Design and secular philosophers (like Mary Midgley and Thomas Nagel) recognise it as a worldview and argue against its implications. Scholars in the rhetoric of science or science communication, however, typically take the view that Darwinism isn't a worldview, but a scientific theory, which has been improperly embellished by some; they uphold the distinction between is and ought and argue that science is restricted to the former. This prompts an is–ought problem on another level. I catalogue the ways in which Darwinism plainly is a worldview and why commentators' beliefs that it ought not to be distorts their analysis. Hence, it is their own worldview that precludes them from accepting Darwinism's worldview implications.     

Immanent philosophy of X

In this paper I examine the relationship between historians, philosophers and sociologists of science, and indeed scientists themselves. I argue that (i) they co-habit a shared intellectual territory (science and its past); and (ii) they should be able to do so peacefully, and with mutual respect, even if they disagree radically about how to describe the methods and results of science. I then go on to explore some of the challenges to mutually respectful cohabitation between history, philosophy and sociology of science. I conclude by identifying a familiar kind of project in the philosophy of science which seeks to explore the worldview of a particular scientific discipline, and argue that it too has a right to explore the shared territory even though some historians and sociologists may find it methodologically suspect.     

Mechanics without mechanisms

At the time of Heinrich Hertz's premature death in 1894, he was regarded as one of the leading scientists of his generation. However, the posthumous publication of his treatise in the foundations of physics, Principles of Mechanics, presents a curious historical situation. Although Hertz's book was widely praised and admired, it was also met with a general sense of dissatisfaction. Almost all of Hertz's contemporaries criticized Principles for the lack of any plausible way to construct a mechanism from the “hidden masses” that are particularly characteristic of Hertz's framework. This issue seemed especially glaring given the expectation that Hertz's work might lead to a model of the underlying workings of the ether.In this paper I seek an explanation for why Hertz seemed so unperturbed by the difficulties of constructing such a mechanism. In arriving at this explanation, I explore how the development of Hertz's image-theory of representation framed the project of Principles. The image-theory brings with it an austere view of the “essential content” of mechanics, only requiring a kind of structural isomorphism between symbolic representations and target phenomena. I argue that bringing this into view makes clear why Hertz felt no need to work out the kinds of mechanisms that many of his readers looked for. Furthermore, I argue that a crucial role of Hertz's hypothesis of hidden masses has been widely overlooked. Far from acting as a proposal for the underlying structure of the ether, I show that Hertz's hypothesis ruled out knowledge of such underlying structure.     

Values and uncertainties in climate prediction,revisited

Philosophers continue to debate both the actual and the ideal roles of values in science. Recently, Eric Winsberg has offered a novel, model-based challenge to those who argue that the internal workings of science can and should be kept free from the influence of social values. He contends that model-based assignments of probability to hypotheses about future climate change are unavoidably influenced by social values. I raise two objections to Winsberg’s argument, neither of which can wholly undermine its conclusion but each of which suggests that his argument exaggerates the influence of social values on estimates of uncertainty in climate prediction. I then show how a more traditional challenge to the value-free ideal seems tailor-made for the climate context.     

Pure science and the problem of progress

How should we understand scientific progress? Kuhn famously discussed science as its own internally driven venture, structured by paradigms. He also famously had a problem describing progress in science, as problem-solving ability failed to provide a clear rubric across paradigm change—paradigm changes tossed out problems as well as solving them. I argue here that much of Kuhn’s inability to articulate a clear view of scientific progress stems from his focus on pure science and a neglect of applied science. I trace the history of the distinction between pure and applied science, showing how the distinction came about, the rhetorical uses to which the distinction has been put, and how pure science came to be both more valued by scientists and philosophers. I argue that the distinction between pure and applied science does not stand up to philosophical scrutiny, and that once we relinquish it, we can provide Kuhn with a clear sense of scientific progress. It is not one, though, that will ultimately prove acceptable. For that, societal evaluations of scientific work are needed.     

Explanation,understanding, and unrealistic models

How can false models be explanatory? And how can they help us to understand the way the world works? Sometimes scientists have little hope of building models that approximate the world they observe. Even in such cases, I argue, the models they build can have explanatory import. The basic idea is that scientists provide causal explanations of why the regularity entailed by an abstract and idealized model fails to obtain. They do so by relaxing some of its unrealistic assumptions. This method of ‘explanation by relaxation’ captures the explanatory import of some important models in economics. I contrast this method with the accounts that Daniel Hausman and Nancy Cartwright have provided of explanation in economics. Their accounts are unsatisfactory because they require that the economic model regularities obtain, which is rarely the case. I go on to argue that counterfactual regularities play a central role in achieving ‘understanding by relaxation.’ This has a surprising implication for the relation between explanation and understanding: Achieving scientific understanding does not require the ability to explain observed regularities.     

The role of ‘complex’ empiricism in the debates about satellite data and climate models

Climate scientists have been engaged in a decades-long debate over the standing of satellite measurements of the temperature trends of the atmosphere above the surface of the earth. This is especially significant because skeptics of global warming and the greenhouse effect have utilized this debate to spread doubt about global climate models used to predict future states of climate. I use this case from an understudied science to illustrate two distinct philosophical approaches to the relations among data, scientist, measurement, models, and theory. I argue that distinguishing between ‘direct’ empiricist and ‘complex’ empiricist approaches helps us understand and analyze this important scientific episode. I also introduce a complex empiricist account of testing and evaluation, and contrast it with the basic Hypothetico-Deductive approach to the climate models used by the direct empiricists. This more developed complex empiricist approach will serve philosophy of science well, as computational models become more widespread in the sciences.