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.     

An appraisal of Mendeleev’s contribution to the development of the periodic table

Historians and philosophers of science generally conceptualize scientific progress to be dichotomous, viz., experimental observations lead to scientific laws, which later facilitate the elaboration of explanatory theories. There is considerable controversy in the literature with respect to Mendeleev’s contribution to the origin, nature, and development of the periodic table. The objectives of this study are to explore and reconstruct: a) periodicity in the periodic table as a function of atomic theory; b) role of predictions in scientific theories and its implications for the periodic table; and c) Mendeleev’s contribution: theory or an empirical law? The reconstruction shows that despite Mendeleev’s own ambivalence, periodicity of properties of chemical elements in the periodic table can be attributed to the atomic theory. It is argued that based on the Lakatosian framework, predictions (novel facts) play an important role in the development of scientific theories. In this context, Mendeleev’s predictions played a crucial role in the development of the periodic table. Finally, it is concluded that Mendeleev’s contribution can be considered as an “interpretative” theory which became “explanatory” after the periodic table was based on atomic numbers.     

Dynamic mechanistic explanation: computational modeling of circadian rhythms as an exemplar for cognitive science

We consider computational modeling in two fields: chronobiology and cognitive science. In circadian rhythm models, variables generally correspond to properties of parts and operations of the responsible mechanism. A computational model of this complex mechanism is grounded in empirical discoveries and contributes a more refined understanding of the dynamics of its behavior. In cognitive science, on the other hand, computational modelers typically advance de novo proposals for mechanisms to account for behavior. They offer indirect evidence that a proposed mechanism is adequate to produce particular behavioral data, but typically there is no direct empirical evidence for the hypothesized parts and operations. Models in these two fields differ in the extent of their empirical grounding, but they share the goal of achieving dynamic mechanistic explanation. That is, they augment a proposed mechanistic explanation with a computational model that enables exploration of the mechanism’s dynamics. Using exemplars from circadian rhythm research, we extract six specific contributions provided by computational models. We then examine cognitive science models to determine how well they make the same types of contributions. We suggest that the modeling approach used in circadian research may prove useful in cognitive science as researchers develop procedures for experimentally decomposing cognitive mechanisms into parts and operations and begin to understand their nonlinear interactions.     

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.     

Edge cases in animal research law: Constituting the regulatory borderlands of the UK's Animals (Scientific Procedures) Act

This paper explores how the boundaries of the UK's Animals (Scientific Procedures) Act (A(SP)A) are constituted, as illustrative of the rising importance of legal procedures around animal research and how these are continuously being challenged and questioned. Drawing on empirical work in animal research communities, we consider how it is decided whether activities are undertaken for an “experimental or other scientific purpose”. We do this by focusing on “edge cases”, where debates occur about whether to include an activity within A(SP)A's remit. We demonstrate that the boundaries of animal research regulation in the UK are products of past and present decisions, dependencies, and social relationships. Boundaries are therefore not clear-cut and fixed, but rather flexible and changing borderlands. We particularly highlight the roles of: historical precedent; the management of risk, workload, and cost; institutional and professional identities; and research design in constituting A(SP)A's edges. In doing so, we demonstrate the importance of paying attention to how, in practice, animal law requires a careful balance between adhering to legal paragraphs and allowing for discretion. This in turn has real-world implications for what and how science is done, who does it, and how animals are used in its service.     

Chemistry in the French tradition of philosophy of science: Duhem, Meyerson, Metzger and Bachelard

At first glance twentieth-century philosophy of science seems virtually to ignore chemistry. However this paper argues that a focus on chemistry helped shape the French philosophical reflections about the aims and foundations of scientific methods. Despite patent philosophical disagreements between Duhem, Meyerson, Metzger and Bachelard it is possible to identify the continuity of a tradition that is rooted in their common interest for chemistry. Two distinctive features of the French tradition originated in the attention to what was going on in chemistry.French philosophers of science, in stark contrast with analytic philosophers, considered history of science as the necessary basis for understanding how the human intellect or the scientific spirit tries to grasp the world. This constant reference to historical data was prompted by a fierce controversy about the chemical revolution, which brought the issue of the nature of scientific changes centre stage.A second striking—albeit largely unnoticed—feature of the French tradition is that matter theories are a favourite subject with which to characterize the ways of science. Duhem, Meyerson, Metzger and Bachelard developed most of their views about the methods and aims of science through a discussion of matter theories. Just as the concern with history was prompted by a controversy between chemists, the focus on matter was triggered by a scientific controversy about atomism in the late nineteenth-century.     

Knowledge transfer in agent-based computational social science

This article addresses knowledge transfer dynamics in agent-based computational social science. The goal of the text is twofold. First, it describes the tensions arising from the convergence of different disciplinary traditions in the emergence of this new area of study and, second, it shows how these tensions are dealt with through the articulation of distinctive practices of knowledge production and transmission. To achieve this goal, three major instances of knowledge transfer dynamics in agent-based computational social science are analysed. The first instance is the emergence of the research field. Relations of knowledge transfer and cross-fertilisation between agent-based computational social science and wider and more established disciplinary areas: complexity science, computational science and social science, are discussed. The second instance is the approach to scientific modelling in the field. It is shown how the practice of agent-based modelling is affected by the conflicting coexistence of shared methodological commitments transferred from both empirical and formal disciplines. Lastly, the third instance pertains internal practices of knowledge production and transmission. Through the discussion of these practices, the tensions arising from converging dissimilar disciplinary traditions in agent-based computational social science are highlighted.     

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.     

A place for pragmatism in the dynamics of reason?

In Dynamics of Reason Michael Friedman proposes a kind of synthesis between the neokantianism of Ernst Cassirer, the logical empiricism of Rudolf Carnap, and the historicism of Thomas Kuhn. Cassirer and Carnap are to take care of the Kantian legacy of modern philosophy of science, encapsulated in the concept of the relativized a priori and the globally rational or continuous evolution of scientific knowledge, while Kuhn’s role is to ensure that the historicist character of scientific knowledge is taken seriously. More precisely, Carnapian linguistic frameworks, guarantee that the evolution of science proceeds in a rational manner locally, while Cassirer’s concept of an internally defined conceptual convergence of empirical theories provides the means to maintain the global continuity of scientific reason. In this paper it is argued that Friedman’s Neokantian account of scientific reason based on the concept of the relativized a priori underestimates the pragmatic aspects of the dynamics of scientific reason. To overcome this shortcoming, I propose to reconsider C.I. Lewis’s account of a pragmatic priori, recently modernized and elaborated by Hasok Chang. This may be considered as a first step to a dynamics of an embodied reason, less theoretical and more concrete than Friedman’s Neokantian proposal.     

The theory theory thrice over: the child as scientist, Superscientist or social institution?

Alison Gopnik and Andrew Meltzoff have argued for a view they call the ‘theory theory’: theory change in science and children are similar. While their version of the theory theory has been criticized for depending on a number of disputed claims, we argue that there is a fundamental problem which is much more basic: the theory theory is multiply ambiguous. We show that it might be claiming that a similarity holds between theory change in children and (i) individual scientists, (ii) a rational reconstruction of a Superscientist, or (iii) the scientific community. We argue that (i) is false, (ii) is non-empirical (which is problematic since the theory theory is supposed to be a bold empirical hypothesis), and (iii) is either false or doesn't make enough sense to have a truth-value. We conclude that the theory theory is an interesting failure. Its failure points the way to a full, empirical picture of scientific development, one that marries a concern with the social dynamics of science to a psychological theory of scientific cognition.     

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.     

A philosophical study of the transition from the caloric theory of heat to thermodynamics: Resisting the pessimistic meta-induction

I began this study with Laudan's argument from the pessimistic induction and I promised to show that the caloric theory of heat cannot be used to support the premisses of the meta-induction on past scientific theories. I tried to show that the laws of experimental calorimetry, adiabatic change and Carnot's theory of the motive power of heat were (i) independent of the assumption that heat is a material substance, (ii) approximately true, (iii) deducible and accounted for within thermodynamics.I stressed that results (i) and (ii) were known to most theorists of the caloric theory and that result (iii) was put forward by the founders of the new thermodynamics. In other words, the truth-content of the caloric theory was located, selected carefully, and preserved by the founders of thermodynamics.However, the reader might think that even if I have succeeded in showing that laudan is wrong about the caloric theory, I have not shown how the strategy followed in this paper can be generalised against the pessimistic meta-induction. I think that the general strategy against Laudan's argument suggested in this paper is this: the empirical success of a mature scientific theory suggests that there are respects and degrees in which this theory is true. The difficulty for — and and real challenge to — philosophers of science is to suggest ways in which this truth-content can be located and shown to be preserved — if at all — to subsequent theories. In particular, the empirical success of a theory does not, automatically, suggest that all theoretical terms of the theory refer. On the contrary, judgments of referential success depend on which theoretical claims are well-supported by the evidence. This is a matter of specific investigation. Generally, one would expect that claims about theoretical entities which are not strongly supported by the evidence or turn out to be independent of the evidence at hand, are not compelling. For simply, if the evidence does not make it likely that our beliefs about putative theoretical entities are approximately correct, a belief in those entities would be ill-founded and unjustified. Theoretical extrapolations in science are indespensable , but they are not arbitrary. If the evidence does not warrant them I do not see why someone should commit herself to them. In a sense, the problem with empricist philisophers is not that they demand that theoretical beliefs must be warranted by evidence. Rather, it is that they claim that no evidence can warrant theorretical beliefs. A realist philosopher of science would not disagree on the first, but she has good grounds to deny the second.I argued that claims about theoretical entities which are not strongly supported by the evidence must not be taken as belief-worthy. But can one sustaon the more ambitious view that loosely supported parts of a theory tend to be just those that include non-referring terms? There is an obvious excess risk in such a generalisation. For there are well-known cases in which a theoretical claim was initially weakly supported by the evidence     

Priority and privilege in scientific discovery

The priority rule in science has been interpreted as a behavior regulator for the scientific community, which benefits society by adequately structuring the distribution of intellectual labor across pre-existing research programs. Further, it has been lauded as an intuitively fair way to reward scientists for their contributions, as a special case of society’s “grand reward scheme”. However, we will argue that the current formal framework utilized to model the priority rule idealizes away important aspects of credit attribution, and does so in a way that impacts the conclusions drawn regarding its function in scientific communities. In particular, we consider the social dynamics of credit attribution in order to show that the priority rule can foster structural disadvantages in socially diverse science, as well as drive the distribution of intellectual labor away from optimal.     

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.     

State of the field: Are the results of science contingent or inevitable?

This paper presents a survey of the literature on the problem of contingency in science. The survey is structured around three challenges faced by current attempts at understanding the conflict between “contingentist” and “inevitabilist” interpretations of scientific knowledge and practice. First, the challenge of definition: it proves hard to define the positions that are at stake in a way that is both conceptually rigorous and does justice to the plethora of views on the issue. Second, the challenge of distinction: some features of the debate suggest that the contingency issue may not be sufficiently distinct from other philosophical debates to constitute a genuine, independent philosophical problem. And third, the challenge of decidability: it remains unclear whether and how the conflict could be settled on the basis of empirical evidence from the actual history of science. The paper argues that in order to make progress in the present debate, we need to distinguish more systematically between different expressions that claims about contingency and inevitability in science can take. To this end, it introduces a taxonomy of different contingency and inevitability claims. The taxonomy has the structure of an ordered quadruple. Each contingency and each inevitability claim contains an answer to the following four questions: (how) are alternatives to current science possible, what types of alternatives are we talking about, how should the alternatives be assessed, and how different are they from actual science?     

The Reception of Miller's Ether-Drift Experiments in the USA: The History of a Controversy in Relativity Revolution

This paper analyses documents from several US archives in order to examine the controversy that raged within the US scientific community over Dayton C. Miller's ether-drift experiments. In 1925, Miller announced that his repetitions of the famous Michelson-Morley experiment had shown a slight but positive result: an ether-drift of about 10 kilometres per second. Miller's discovery triggered a long debate in the US scientific community about the validity of Einstein's relativity theories. Between 1926 and 1930 some researchers repeated the Michelson-Morley experiment, but no one found the same effect as Miller had. The inability to confirm Miller's result, paired with the fact that no other ether theory existed that could compete with special relativity theory, made his result an enigmatic one. It thus remained of little interest to the scientific community until 1954, when Robert S. Shankland and three colleagues reanalysed the data and proposed that Miller's periodic fringe shift could be attributed to temperature effects. Whereas most of the scientific community readily accepted this explanation as the conclusion of the matter, some contemporary anti-relativists have contested Shankland's methodology up to now. The historical accounts of Miller's experiments provide contradictory reports of the reaction of the US scientific community and do not analyse the mechanisms of the controversy. I will address this shortcoming with an examination of private correspondence of several actors involved in these experiments between 1921 and 1955. A complex interconnection of epistemic elements, sociological factors, and personal interests played a fundamental role in the closure of this experimental controversy in the early 1930s, as well as in the reception of Shankland's reanalysis in the 1950s.     

The value-ladenness of transparency in science: Lessons from Lyme disease

Both philosophers and scientists have recently promoted transparency as an important element of responsible scientific practice. Philosophers have placed particular emphasis on the ways that transparency can assist with efforts to manage value judgments in science responsibly. This paper examines a potential challenge to this approach, namely, that efforts to promote transparency can themselves be value-laden. This is particularly problematic when transparency incorporates second-order value judgments that are underwritten by the same values at stake in the desire for transparency about the first-order value judgments involved in scientific research. The paper uses a case study involving research on Lyme disease to illustrate this worry, but it responds by elucidating a range of scenarios in which transparency can still play an effective role in managing value judgments responsibly.     

从文献计量分析看世界合成生物学研究现状

合成生物学是生物学的一个新兴分支学科.以美国科学引文索引数据库扩展版数据库(SCI-EXPANDED)收录入库,发表于1990～2010年的3 949篇与合成生物学相关的论文为研究对象,通过对论文的产出规模、地域分布、机构分布、研究热点、学科关联性、知识基础等方面的计量分析,在一定程度上揭示出近年来世界合成生物学的发展是一种成果产出不断丰富,理论研究与应用研究均得到积极推进,与众多学科发展联系紧密,各国科研投入力量在显著加强以及美国在全球一枝独秀的局面.     

The natural selection of conservative science

Social epistemologists have argued that high risk, high reward science has an important role to play in scientific communities. Recently, though, it has also been argued that various scientific fields seem to be trending towards conservatism—the increasing production of what Kuhn (1962) might have called ‘normal science’. This paper will explore a possible explanation for this sort of trend: that the process by which scientific research groups form, grow, and dissolve might be inherently hostile to such science. In particular, I employ a paradigm developed by Smaldino and McElreath (2016) that treats a scientific community as a population undergoing selection. As will become clear, perhaps counter-intuitively this sort of process in some ways promotes high risk, high reward science. But, as I will point out, risky science is, in general, the sort of thing that is hard to repeat. While more conservative scientists will be able to train students capable of continuing their successful projects, and so create thriving lineages, successful risky science may not be the sort of thing one can easily pass on. In such cases, the structure of scientific communities selects against high risk, high rewards projects. More generally, this project makes clear that there are at least two processes to consider in thinking about how incentives shape scientific communities—the process by which individual scientists make choices about their careers and research, and the selective process governing the formation of new research groups.