Model choice and crucial tests. On the empirical epistemology of the Higgs discovery

Our paper discusses the epistemic attitudes of particle physicists on the discovery of the Higgs boson at the Large Hadron Collider (LHC). It is based on questionnaires and interviews made shortly before and shortly after the discovery in 2012. We show, to begin with, that the discovery of a Standard Model (SM) Higgs boson was less expected than is sometimes assumed. Once the new particle was shown to have properties consistent with SM expectations – albeit with significant experimental uncertainties –, there was a broad agreement that ‘a’ Higgs boson had been found. Physicists adopted a two-pronged strategy. On the one hand, they treated the particle as a SM Higgs boson and tried to establish its properties with higher precision; on the other hand, they searched for any hints of physics beyond the SM. This motivates our first philosophical thesis: the Higgs discovery, being of fundamental importance and establishing a new kind of particle, represented a crucial experiment if one interprets this notion in an appropriate sense. Duhemian underdetermination is kept at bay by embedding the LHC into the tradition of previous precision experiments and the experimental strategies thus established. Second, our case study suggests that criteria of theory (or model) preference should be understood as epistemic and pragmatic values that have to be weighed in factual research practice. The Higgs discovery led to a shift from pragmatic to epistemic values in physicists’ assessment of the mechanisms of electroweak symmetry breaking. Complex criteria, such as naturalness, combine epistemic and pragmatic values, but are coherently applied by the community.     

Closing the door to cloud-cuckoo land: a reply to Šešelja and Straßer

Šešelja and Straßer’s critique fails to hit its target for two main reasons. First, the argument is not that Kuhn is a rationalist because he is a coherentist. Although Kuhn can be taken as a rationalist because of his commitment to epistemic values, coherence analysis provides a more comprehensive characterisation of cognitive process in scientific change than any of these values alone can offer. Further, we should understand Kuhn as characterising science as the best form of rationality we have outside logic, which rules out algorithmic rationality and allows non-cognitive factors to play a role in theory change. Second, Šešelja and Straßer overemphasise the importance of a priori reasoning in Kuhn, which was only an alternative to his earlier historical-empirical approach. My suggestion is that Kuhn’s neo-Kantian historical cognitivism integrates the earlier empirical and the later a-prioristic orientations. According to it, that any understanding of the world is preconditioned by some kind of mental module that is liable to change, detected as a discontinuity in the historical record of science.     

Kuhn, the correspondence theory of truth and coherentist epistemology

Kuhn argued against both the correspondence theory of truth and convergent realism. Although he likely misunderstood the nature of the correspondence theory, which it seems he wrongly believed to be an epistemic theory, Kuhn had an important epistemic point to make. He maintained that any assessment of correspondence between beliefs and reality is not possible, and therefore, the acceptance of beliefs and the presumption of their truthfulness has to be decided on the basis of other criteria. I will show that via Kuhn’s suggested epistemic values, specifically via problem-solving, his philosophy can be incorporated into a coherentist epistemology. Further, coherentism is, in principle, compatible with convergent realism. However, an argument for increasing likeness to truth requires appropriate historical continuity. Kuhn maintained that the history of science is full of discontinuity, and therefore, the historical condition of convergent realism is not satisfied.     

Does environmental science crowd out non-epistemic values?

While no one denies that science depends on epistemic values, many philosophers of science have wrestled with the appropriate role of non-epistemic values, such as social, ethical, and political values. Recently, philosophers of science have overwhelmingly accepted that non-epistemic values should play a legitimate role in science. The recent philosophical debate has shifted from the value-free ideal in science to questions about how science should incorporate non-epistemic values. This article engages with such questions through an exploration of the environmental sciences. These sciences are a mosaic of diverse fields characterized by interdisciplinarity, problem-orientation, policy-directedness, and ubiquitous non-epistemic values. This article addresses a frequently voiced concern about many environmental science practices: that they ‘crowd out’ or displace significant non-epistemic values by either (1) entailing some non-epistemic values, rather than others, or by (2) obscuring discussion of non-epistemic values altogether. With three detailed case studies – monetizing nature, nature-society dualism, and ecosystem health – we show that the alleged problem of crowding out emerges from active debates within the environmental sciences. In each case, critics charge that the scientific practice in question displaces non-epistemic values in at least one of the two senses distinguished above. We show that crowding out is neither necessary nor always harmful when it occurs. However, we do see these putative objections to the application of environmental science as teaching valuable lessons about what matters for successful environmental science, all things considered. Given the significant role that many environmental scientists see for non-epistemic values in their fields, we argue that these cases motivate lessons about the importance of value-flexibility (that practices can accommodate a plurality of non-epistemic values), transparency about value-based decisions that inform practice, and environmental pragmatism.     

Collaboration,interdisciplinarity, and the epistemology of contemporary science

Over the last decades, science has grown increasingly collaborative and interdisciplinary and has come to depart in important ways from the classical analyses of the development of science that were developed by historically inclined philosophers of science half a century ago. In this paper, I shall provide a new account of the structure and development of contemporary science based on analyses of, first, cognitive resources and their relations to domains, and second of the distribution of cognitive resources among collaborators and the epistemic dependence that this distribution implies. On this background I shall describe different ideal types of research activities and analyze how they differ. Finally, analyzing values that drive science towards different kinds of research activities, I shall sketch the main mechanisms underlying the perceived tension between disciplines and interdisciplinarity and argue for a redefinition of accountability and quality control for interdisciplinary and collaborative science.     

Does democracy require value-neutral science? Analyzing the legitimacy of scientific information in the political sphere

Philosophers now commonly reject the value free ideal for science by arguing that non-epistemic values, including personal or social values, are permissible within the core of scientific research. However, little attention has been paid to the normative political consequences of this position. This paper explores these consequences and shows how political theory is fruitful for proceeding in a world without value-neutral science. I draw attention to an oft-overlooked argument employed by proponents of the value free ideal I dub the “political legitimacy argument.” This argument claims that the value-free ideal follows directly from the foundational principles of liberal democracy. If so, then the use of value-laden scientific information within democratic decision making would be illegitimate on purely political grounds. Despite highlighting this unaddressed and important argument, I show how it can be rejected. By appealing to deliberative democratic theory, I demonstrate scientific information can be value-laden and politically legitimate. The deliberative democratic account I develop is well suited for capturing the intuitions of many opponents of the value free ideal and points to a new set of questions for those interested in values in science.     

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.     

Catching the WAVE: The Weight-Adjusting Account of Values and Evidence

It is commonly argued that values “fill the logical gap” of underdetermination of theory by evidence, namely, values affect our choice between two or more theories that fit the same evidence. The underdetermination model, however, does not exhaust the roles values play in evidential reasoning. I introduce WAVE – a novel account of the logical relations between values and evidence. WAVE states that values influence evidential reasoning by adjusting evidential weights. I argue that the weight-adjusting role of values is distinct from their underdetermination gap-filling role. Values adjust weights in three ways. First, values affect our trust in the testimony of others. Second, values influence the evidential thresholds required for justified epistemic judgments. Third, values influence the relative weight of a certain type of evidence within a body of multimodal discordant evidence. WAVE explains, from an epistemic perspective, rather than psychological, how smokers, for example, can find the same evidence about the dangers of smoking less persuasive than non-smokers. WAVE allows for a wider effect of values on our accepted scientific theories and beliefs than the effect for which the underdetermination model allows alone; therefore, science studies scholars must consider WAVE in their research and analysis of evidential case studies.     

Kuhn’s Structure of Scientific Revolutions between sociology and epistemology

The aim of the paper is to clarify Kuhn’s theory of scientific revolutions. We propose to discriminate between a scientific revolution, which is a sociological event of a change of attitude of the scientific community with respect to a particular theory, and an epistemic rupture, which is a linguistic fact consisting of a discontinuity in the linguistic framework in which this theory is formulated. We propose a classification of epistemic ruptures into four types. In the paper, each of these types of epistemic ruptures is illustrated by examples from physics. The classification of epistemic ruptures can be used as a basis for a classification of scientific revolutions and thus for a refinement of our view of the progress of science.     

Bias and values in scientific research

When interests and preferences of researchers or their sponsors cause bias in experimental design, data interpretation or dissemination of research results, we normally think of it as an epistemic shortcoming. But as a result of the debate on science and values, the idea that all ‘extra-scientific’ influences on research could be singled out and separated from pure science is now widely believed to be an illusion. I argue that nonetheless, there are cases in which research is rightfully regarded as epistemologically deficient due to the influence of preferences on its outcomes. I present examples from biomedical research and offer an analysis in terms of social epistemology.     

Subjectivity and emotion in scientific research

A persistent puzzle for philosophers of science is the well-documented appeal made by scientists to their aesthetic emotions in the course of scientific research. Emotions are usually viewed as irremediably subjective, and thus of no epistemological interest. Yet, by denying an epistemic role for scientists’ emotional dispositions, philosophers find themselves in the awkward position of ignoring phenomena which scientists themselves often insist are of importance. This paper suggests a possible solution to this puzzle by challenging the wholesale identification of emotion with subjectivity. The proposed method is a naturalistic and externalist one, calling for empirical investigation into the intersubjective processes by which scientists’ emotional dispositions become refined and attuned to specific objects of attention. The proposal is developed through a critical discussion of Michael Polanyi’s theory of scientific passions, as well as plant geneticist Barbara McClintock’s celebrated “feeling for the organism.”     

Value-entanglement and the integrity of scientific research

Throughout much of the 20th century, philosophers of science maintained a position known as the value-free ideal, which holds that non-epistemic (e.g., moral, social, political, or economic) values should not influence the evaluation and acceptance of scientific results. In the last few decades, many philosophers of science have rejected this position by arguing that non-epistemic values can and should play an important role in scientific judgment and decision-making in a variety of contexts, including the evaluation and acceptance of scientific results. Rejecting the value-free ideal creates some new and vexing problems, however. One of these is that relinquishing this philosophical doctrine may undermine the integrity of scientific research if practicing scientists decide to allow non-epistemic values to impact their judgment and decision-making. A number of prominent philosophers of science have sought to show how one can reject the value-free ideal without compromising the integrity of scientific research. In this paper, we examine and critique their views and offer our own proposal for protecting and promoting scientific integrity. We argue that the literature on research ethics and its focus on adherence to norms, rules, policies, and procedures that together promote the aims of science can provide a promising foundation for building an account of scientific integrity. These norms, rules, policies, and procedures provide a level of specificity that is lacking in most philosophical discussions of science and values, and they suggest an important set of tasks for those working in science and values—namely, assessing, justifying, and prioritizing them. Thus, we argue that bringing together the literature on research ethics with the literature on science and values will enrich both areas and generate a more sophisticated and detailed account of scientific integrity.     

Colligation in modelling practices: From Whewell’s tides to the San Francisco Bay Model

“Colligation”, a term first introduced in philosophy of science by William Whewell (1840), today sparks a renewed interest beyond Whewell scholarship. In this paper, we argue that adopting the notion of colligation in current debates in philosophy of science can contribute to our understanding of scientific models. Specifically, studying colligation allows us to have a better grasp of how integrating diverse model components (empirical data, theory, useful idealization, visual and other representational resources) in a creative way may produce novel generalizations about the phenomenon investigated. Our argument is built both on the theoretical appraisal of Whewell’s philosophy of science and the historical rehabilitation of his scientific work on tides. Adopting a philosophy of science in practice perspective, we show how colligation emerged from Whewell’s empirical work on tides. The production of idealized maps (“cotidal maps”) illustrates the unifying and creative power of the activity of colligating in scientific practice. We show the importance of colligation in modelling practices more generally by looking at its epistemic role in the construction of the San Francisco Bay Model.     

The National Science Foundation and philosophy of science's withdrawal from social concerns

At some point during the 1950s, mainstream American philosophy of science began increasingly to avoid questions about the role of non-cognitive values in science and, accordingly, increasingly to avoid active engagement with social, political and moral concerns. Such questions and engagement eventually ceased to be part of the mainstream. Here we show that the eventual dominance of ‘value-free’ philosophy of science can be attributed, at least in part, to the policies of the U.S. National Science Foundation's “History and Philosophy of Science” sub-program. In turn, the sub-program's policies were set by logical empiricists who espoused value-free philosophy of science; these philosophers' actions, we also point out, fit a broad pattern, one in which analytic philosophers used institutional control to marginalize rival approaches to philosophy. We go on to draw on existing knowledge of this pattern to suggest two further, similar, contributors to the withdrawal from value-laden philosophy of science, namely decisions by the editors of Philosophy of Science and by the editors of The Journal of Philosophy. Political climate was, we argue, at most an indirect contributor to the withdrawal and was neither a factor that decided whether it occurred nor one that was sufficient to bring it about. Moreover, we argue that the actions at the National Science Foundation went beyond what was required by its senior administrators and are better viewed as part of what drove, rather than as what was being driven by, the adoption of logical empiricism by the philosophy of science community.     

The epistemic value of good sense

This paper examines competing interpretations of Pierre Duhem’s theory of good sense recently defended by David Stump and Milena Ivanova and defends a hybrid reading that accommodates the intuitions of both readings. At issue between Stump and Ivanova is whether Duhemian good sense is a virtue theoretic concept. I approach the issue from the broader perspective of determining the epistemic value of good sense per se, and argue for a mitigated virtue theoretic reading that identifies an essential role for good sense in theory choice. I also show that many important issues in both philosophy of science and ‘mainstream’ value driven epistemology are illuminated by the debate over the epistemic value of good sense. In particular, philosophical work on the nature of cognitive character, rule governed rationality and the prospects of epistemic value t-monism are illuminated by virtue theoretic readings of Duhemian good sense.     

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.     

Scientific progress: Knowledge versus understanding

What is scientific progress? On Alexander Bird's epistemic account of scientific progress, an episode in science is progressive precisely when there is more scientific knowledge at the end of the episode than at the beginning. Using Bird's epistemic account as a foil, this paper develops an alternative understanding-based account on which an episode in science is progressive precisely when scientists grasp how to correctly explain or predict more aspects of the world at the end of the episode than at the beginning. This account is shown to be superior to the epistemic account by examining cases in which knowledge and understanding come apart. In these cases, it is argued that scientific progress matches increases in scientific understanding rather than accumulations of knowledge. In addition, considerations having to do with minimalist idealizations, pragmatic virtues, and epistemic value all favor this understanding-based account over its epistemic counterpart.     

The diverse aims of science

There is increasing attention to the centrality of idealization in science. One common view is that models and other idealized representations are important to science, but that they fall short in one or more ways. On this view, there must be an intermediary step between idealized representation and the traditional aims of science, including truth, explanation, and prediction. Here I develop an alternative interpretation of the relationship between idealized representation and the aims of science. I suggest that continuing, widespread idealization calls into question the idea that science aims for truth. If instead science aims to produce understanding, this would enable idealizations to directly contribute to science's epistemic success. I also use the fact of widespread idealization to motivate the idea that science's wide variety aims, epistemic and non-epistemic, are best served by different kinds of scientific products. Finally, I show how these diverse aims—most rather distant from truth—result in the expanded influence of social values on science.     

No-go theorems: What are they good for?

No-go theorems have played an important role in the development and assessment of scientific theories. They have stopped whole research programmes and have given rise to strong ontological commitments. Given the importance they obviously have had in physics and philosophy of physics and the huge amount of literature on the consequences of specific no-go theorems, there has been relatively little attention to the more abstract assessment of no-go theorems as a tool in theory development. We will here provide this abstract assessment of no-go theorems and conclude that the methodological implications one may draw from no-go theorems are in disagreement with the implications that have often been drawn from them in the history of science.     

A mid-level approach to modeling scientific communities

This paper provides an account of mid-level models which calibrate highly theoretical agent-based models of scientific communities by incorporating empirical information from real-world systems. As a result, these models more closely correspond with real-world communities, and are better suited for informing policy decisions than extant how-possibly models. I provide an exemplar of a mid-level model of science funding allocation that incorporates bibliometric data from scientific publications and data generated from empirical studies of peer review into an epistemic landscape model. The results of my model show that on a dynamic epistemic landscape, allocating funding by modified and pure lottery strategies performs comparably to a perfect selection funding allocation strategy. These results support the idea that introducing randomness into a funding allocation process may be a tractable policy worth exploring further through pilot studies. My exemplar shows that agent-based models need not be restricted to the abstract and the apriori; they can also be informed by empirical data.