Model-as-replica,model-as-instrument: Representational power and contextual versatility in animal models

Existing scholarship on animal models tends to foreground either of the two major roles research organisms play in different epistemic contexts, treating their representational and instrumental roles separately. Based on an empirical case study, this article explores the changing relationship between the two epistemic roles of a research organism over the span of a decade, while the organism was used to achieve various knowledge ends. This rat model was originally intended as a replica of human susceptibility to cardiac arrest. In a fortunate stroke of serendipity, however, the experimenters detected the way mother-infant interactions regulated the pups’ resting cardiac rate. This intriguing outcome thus became the model’s new representational target and began driving the development of an experimental system. Henceforth, the model acquired an instrumental function, serving to detect and measure system-specific differences. Its subsequent development involved creating stimulus-response measures to explain and theorize those differences. It was this instrumental use of the model that pushed the experimenters into unchartered territory and conferred to the model an ability to adapt to varied epistemic contexts. Despite the prominence of this instrumental role, however, the model’s representational power continued to guide research. The model’s representational target was widened beyond heart rate to reflect other functional phenomena, such as behavioral activity and sleep/wake rhythm. The rat model was thus transformed from an experimental organism designed to instantiate cardiac regulation to a model organism taken to represent the development of a whole, intact animal under the regulatory influence of maternal care. This article examines this multifaceted transformation within the context of the salient shifts in modeling practice and variations in the model’s representational power. It thus explores how the relationship between the representational and instrumental uses of the model changed with respect to the varying exigencies of the investigative context, foregrounding its contextual versatility.     

The landing zone – Ground for model transfer in chemistry

This essay proposes a new notion - the landing zone - in order to identify conceptual features that allow modelers to transfer mathematical tools across disciplinary borders. This discussion refers to the transferable models as ‘templates’. Templates are functions, equations, or computational methods that are capable of being generalized from a particular subject matter. There are formal and conceptual prerequisites for the transfer of a template to a new domain. A landing zone is an ontology that contributes to the satisfaction of these conditions for successful transfer. This paper presents a case study on a model in chemistry - the Quantum Theory of Atoms in Molecules (QTAIM) - that makes use of transferred templates from physics - the virial theorem and the wave function. The landing zone in this case is a new ontological notion, that of the topological atom, which prepares ground for the use of the virial theorem and the wave function in chemistry. The virial theorem requires that there exists in-principle stability to the system that it represents, and the wave function requires transformation in its representation that is justified. The ontology of QTAIM - the landing zone for these templates - grounds the scientific use of these templates in the context of chemistry.     

A periodization of research technologies and of the emergency of genericity

According to the historian and sociologist of science Terry Shinn, the creator of the concept of ‘research technologies’: “Research technologies may sometimes generate promising packets of instrumentation for yet undefined ends. They may offer technological answers to questions that have hardly been raised. Research technologists׳s instruments are then generic in the sense that they are base-line apparatus which can subsequently be transformed by experimenters into products tailored to specific economic ends or adapted by experimenters to further cognitive ends in academic research.”¹ Genericity thus manifests one of three fundamental characteristics of research technologies. At the same time, however, each research technology emerges out of the specific disciplinary context in which it is initially developed with entirely concrete aims. Consequently, genericity does not exist from the outset but first has to form, along a path that remains to be clarified. It is produced or constructed by the actors on two levels: as an instrument in the laboratory and as a way of speaking at the representational level. This issue yields the structure of this paper. Three options for the transition of a specific technique into a generic research technology are compared. One of them proves to be the most frequent pattern of this dynamic. This is explored further, taking as paradigmatic examples ‘computed tomography’ (CT), ‘nuclear magnetic resonance׳ (NMR) and its application known as ‘magnetic resonance imaging’ (MRI), together with several additional examples.     

Understanding climate phenomena with data-driven models

In climate science, climate models are one of the main tools for understanding phenomena. Here, we develop a framework to assess the fitness of a climate model for providing understanding. The framework is based on three dimensions: representational accuracy, representational depth, and graspability. We show that this framework does justice to the intuition that classical process-based climate models give understanding of phenomena. While simple climate models are characterized by a larger graspability, state-of-the-art models have a higher representational accuracy and representational depth. We then compare the fitness-for-providing understanding of process-based to data-driven models that are built with machine learning. We show that at first glance, data-driven models seem either unnecessary or inadequate for understanding. However, a case study from atmospheric research demonstrates that this is a false dilemma. Data-driven models can be useful tools for understanding, specifically for phenomena for which scientists can argue from the coherence of the models with background knowledge to their representational accuracy and for which the model complexity can be reduced such that they are graspable to a satisfactory extent.     

Quantum reality: A pragmaticized neo-Kantian approach

Despite remarkable efforts, it remains notoriously difficult to equip quantum theory with a coherent ontology. Hence, Healey (2017, 12) has recently suggested that “quantum theory has no physical ontology and states no facts about physical objects or events”, and Fuchs et al. (2014, 752) similarly hold that “quantum mechanics itself does not deal directly with the objective world”. While intriguing, these positions either raise the question of how talk of ‘physical reality’ can even remain meaningful, or they must ultimately embrace a hidden variables-view, in tension with their original project. I here offer a neo-Kantian alternative. In particular, I will show how constitutive elements in the sense of Reichenbach (1920) and Friedman (1999, 2001) can be identified within quantum theory, through considerations of symmetries that allow the constitution of a ‘quantum reality’, without invoking any notion of a radically mind-independent reality. The resulting conception will inherit elements from pragmatist and ‘QBist’ approaches, but also differ from them in crucial respects. Furthermore, going beyond the Friedmanian program, I will show how non-fundamental and approximate symmetries can be relevant for identifying constitutive principles.     

Modeling for fairness: A Rawlsian approach

In this paper we introduce the overlapping design consensus for the construction of models in design and the related value judgments. The overlapping design consensus is inspired by Rawls’ overlapping consensus. The overlapping design consensus is a well-informed, mutual agreement among all stakeholders based on fairness. Fairness is respected if all stakeholders’ interests are given due and equal attention. For reaching such fair agreement, we apply Rawls’ original position and reflective equilibrium to modeling. We argue that by striving for the original position, stakeholders expel invalid arguments, hierarchies, unwarranted beliefs, and bargaining effects from influencing the consensus. The reflective equilibrium requires that stakeholders’ beliefs cohere with the final agreement and its justification. Therefore, the overlapping design consensus is not only an agreement to decisions, as most other stakeholder approaches, it is also an agreement to their justification and that this justification is consistent with each stakeholders’ beliefs. For supporting fairness, we argue that fairness qualifies as a maxim in modeling. We furthermore distinguish values embedded in a model from values that are implied by its context of application. Finally, we conclude that for reaching an overlapping design consensus communication about properties of and values related to a model is required.     

The nomological image of nature: explaining the tide in the thirteenth century

The paper examines the relevance of the nomological view of nature to three discussions of tide in the thirteenth century. A nomological conception of nature assumes that the basic explanatory units of natural phenomena are universally binding rules stated in quantitative terms. (1) Robert Grosseteste introduced an account of the tide based on the mechanism of rarefaction and condensation, stimulated by the Moon's rays and their angle of incidence. He considered the Moon's action over the sea an example of the general efficient causality exerted through the universal activity of light or species. (2) Albert the Great posited a plurality of causes which cannot be reduced to a single cause. The connaturality of the Moon and the water is the only principle of explanation which he considered universal. Connaturality, however, renders neither formulation nor quantification possible. While Albert stressed the variety of causes of the tide, (3) Roger Bacon emphasized regularity and reduced the various causes producing tides into forces. He replaced the terminology of ‘natures’ by one of ‘forces’. Force, which in principle can be accurately described and measured, thus becomes a commensurable aspect of a diverse cosmos. When they reasoned why waters return to their place after the tide, Grosseteste argued that waters return in order to prevent a vacuum, Albert claimed that waters ‘follow their own nature’, while Bacon held that the ‘proper force’ of the water prevails over the distant force of the first heaven. I exhibit, for the thirteenth century, moments of the move away from the Aristotelian concerns. The basic elements of these concerns were essences and natures which reflect specific phenomena and did not allow for an image of nature as a unified system. In the new perspective of the thirteenth century the key was a causal link between the position of the Moon and the tide cycle, a link which is universal and still qualitative, yet expressed as susceptible to quantification.     

Layered history: Styles of reasoning as stratified conditions of possibility

This paper depicts Ian Hacking’s ‘styles of reasoning’ as conditions of possibility. After distinguishing between possibilities and causes, it articulates the implicit stratigraphical metaphor used to describe the relationship between different conditions of possibility, with ‘lower’ layers being necessary for ‘higher’ ones. It notes the use of this stratigraphical metaphor in the work of multiple scholars in history and in science studies. The paper suggests three ways in which this model can be useful: clarifying the definition and use of ‘context’ in history of science; redefining counterfactuals as ‘possible historical worlds’; and thinking up new forms of ‘big picture’ histories of science.     

Essay Review: The Historicity of Sound and Hearing

This paper investigates the extent of overseas migration by British chemists over the period 1887–1971. Notwithstanding the ‘brain drain’ alarms of the 1960s, overseas employment was characteristic of some 19% of British chemists’ careers throughout our period, though its nature changed considerably. Our study examines the overseas employment histories of four cohorts of members of the [Royal] Institute of Chemistry in the ‘Chemists’ Database’ at the Open University. Those employed abroad were not only highly qualified but also both geographically mobile and occupationally versatile. Over the period, the pattern of chemists’ migration was broadly similar to that of British migration trends more generally. Except in the interwar years, chemists’ rate of migration was relatively constant. However, the length of time they spent abroad declined markedly over the period: long-term migration became less characteristic than short-term overseas employment for purposes of career development. From the late nineteenth century, British chemists staffed the Empire, but also found employment in the expanding US economy. After 1945, chemists’ destinations shifted more markedly towards North America, including Canada, and later also to Europe. Our work thus provides a new perspective on the dynamics of scientists’ migration and contributes to studies on the brain drain.     

What’s so special about model organisms?

This paper aims to identify the key characteristics of model organisms that make them a specific type of model within the contemporary life sciences: in particular, we argue that the term “model organism” does not apply to all organisms used for the purposes of experimental research. We explore the differences between experimental and model organisms in terms of their material and epistemic features, and argue that it is essential to distinguish between their representational scope and representational target. We also examine the characteristics of the communities who use these two types of models, including their research goals, disciplinary affiliations, and preferred practices to show how these have contributed to the conceptualization of a model organism. We conclude that model organisms are a specific subgroup of organisms that have been standardized to fit an integrative and comparative mode of research, and that it must be clearly distinguished from the broader class of experimental organisms. In addition, we argue that model organisms are the key components of a unique and distinctively biological way of doing research using models.     

Seeking representations of phenomena: Phenomenological models

A distinction is made between theory-driven and phenomenological models. It is argued that phenomenological models are significant means by which theory is applied to phenomena. They act both as sources of knowledge of their target systems and are explanatory of the behaviors of the latter. A version of the shell-model of nuclear structure is analyzed and it is explained why such a model cannot be understood as being subsumed under the theory structure of Quantum Mechanics. Thus its representational capacity does not stem from its close link to theory. It is shown that the shell model yields knowledge about the target and is explanatory of certain behaviors of nuclei. Aspects of the process by which the shell model acquires its representational capacity are analyzed. It is argued that these point to the conclusion that the representational status of the model is a function of its capacity to function as a source of knowledge and its capacity to postulate and explain underlying mechanisms that give rise to the observed behavior of its target.     

Measurement in French Experimental Physics from Regnault to Lippmann. Rhetoric and Theoretical Practice

This paper explores the legacy of the great French experimental physicist Victor Regnault through the example of Gabriel Lippmann, whose engagement with electrical standardization during the early 1880s was guided by Regnault's methodological precept to measure ‘directly’. Lippmann's education reveals that the theoretical practice of ‘direct’ measurement entailed eliminating extraneous physical effects through the experimental design, rather than, like physicists in Britain and Germany, making numerical ‘corrections’ to measured values. It also provides, paradoxically, exemplars of the qualitative theoretical practices that sustained Regnault's misguided ambition to avoid theory. By considering the largely negative reactions to Lippmann's proposals for selecting suitable electrical units and methods of measuring the ohm, this paper associates these theoretical practices with the ineffectual rhetorical strategies employed by Lippmann to promote his work, and thereby indicates that the practice of direct measurement was limited to French experimental physics. Whilst this result aligns readily with the existence of divergent nineteenth century British and German cultures of precision, it emerges from a very different disciplinary context in which the practice of precision electrical measurement developed independently of submarine telegraphy. This is because, as this paper illustrates, telegraphic engineering and experimental physics remained separate professions in France.     

Climates as commodities: Jean Pierre Purry and the modelling of the best climate on Earth

The paper looks at how an early eighteenth-century climatological model of the ‘best climate’ on Earth became a platform for political, economic, and demographic action of extraordinary significance for the colonization of new commodity environments. It analyzes the science used by an early modern business adventurer to model ‘climate’ as an economic tool informing imperial governance and exploitation of local resources. Jean Pierre Purry’s construction of ‘model climate’ portrayed North Carolina’s township at Yamassee River as an ideal environment geared toward mercantilist principles of trade but also as a model community based on skilled labor and optimal climatic capital. His climatological analysis was a purposeful act of policy making based on a science of colonial expansion similar to more recent calls at economic modelling of future climate impact.     

Collective cell migration has distinct directionality and speed dynamics

When a constraint is removed, confluent cells migrate directionally into the available space. How the migration directionality and speed increase are initiated at the leading edge and propagate into neighboring cells are not well understood. Using a quantitative visualization technique—Particle Image Velocimetry (PIV)—we revealed that migration directionality and speed had strikingly different dynamics. Migration directionality increases as a wave propagating from the leading edge into the cell sheet, while the increase in cell migration speed is maintained only at the leading edge. The overall directionality steadily increases with time as cells migrate into the cell-free space, but migration speed remains largely the same. A particle-based compass (PBC) model suggests cellular interplay (which depends on cell–cell distance) and migration speed are sufficient to capture the dynamics of migration directionality revealed experimentally. Extracellular Ca²⁺ regulated both migration speed and directionality, but in a significantly different way, suggested by the correlation between directionality and speed only in some dynamic ranges. Our experimental and modeling results reveal distinct directionality and speed dynamics in collective migration, and these factors can be regulated by extracellular Ca²⁺ through cellular interplay. Quantitative visualization using PIV and our PBC model thus provide a powerful approach to dissect the mechanisms of collective cell migration.     

Reducing uncertainty in short-term projections: Linkage of monthly and quarterly models

This paper shows how monthly data and forecasts can be used in a systematic way to improve the predictive accuracy of a quarterly macroeconometric model. The problem is formulated as a model pooling procedure (equivalent to non-recursive Kalman filtering) where a baseline quarterly model forecast is modified through ‘add-factors’ or ‘constant adjustments’. The procedure ‘automatically’ constructs these adjustments in a covariance-minimizing fashion to reflect the revised expectation of the quarterly model's forecast errors, conditional on the monthly information set. Results obtained using Federal Reserve Board models indicate the potential for significant reduction in forecast error variance through application of these procedures.     

Some practical aspects of forecasting in organizations

This paper presents the writer's experience, over a period of 25 years, in analysing organizational systems and, in particular, concentrates on the overall forecasting activity. The paper first looks at the relationship between forecasting and decision taking–with emphasis on the fact that forecasting is a means to aid decision taking and not an end in itself. It states that there are many types of forecasting problems, each requiring different methods of treatment. The paper then discusses attitudes which are emerging about the relative advantages of different forecasting techniques. It suggests a model building process which requires‘experience’and‘craftsmanship’, extensive practical application, frequent interaction between theory and practice and a methodology that eventually leads to models that contain no detectable inadequacies. Furthermore, it argues that although models which forecast a time series from its past history have a very important role to play, for effective policy making it is necessary to augment the model by introducing policy variables, again in a systematic not an ‘ad hoc’ manner. Finally, the paper discusses how forecasting systems can be introduced into the management process in the first place and how they should be monitored and updated when found wanting.     

“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.