Inside the Kunstkammer: the circulation of optical knowledge and instruments at the Dresden Court

The Kunstkammer of the Electors of Saxony, founded in Dresden around 1560, housed one of the richest collections of tools and scientific instruments in its day. A close analysis of the optical objects in the collection in the decades around 1600 is undertaken here—in particular, their arrangement by a mathematically trained curator, Lucas Brunn, and their use in an ‘experiment’ by a distinguished visitor, Johannes Kepler. It is argued that the selection, display and use of optical objects within this collection reflect a specific, playful image of optics promoted at the Saxon court.     

The scales of experience: Introduction to the special issue Experiencing the global environment

The Scales of Experience introduces the special issue Experiencing the Global Environment by focusing on three dimensions of the theme that are reflected to various degrees in the constitutive essays. First, the introduction highlights the links between the epistemological and political contexts of the historical constitution and development of the global environment (or global environments) in the earth and environmental sciences from the late nineteenth century to today. Second, it argues for a historical approach to the complex concept of scientific experience, whose mutable and contingent qualities are demonstrated by the contributions to the special volume. Lastly, the introduction presents one of the central issues to be tackled by the essays to follow: the development – and, at times, the failure – of strategies and technologies to bridge the seemingly incommensurate gulf between individual, localized experience and the all-encompassing scale of the global environment.     

Instruments and rules: R. B. Woodward and the tools of twentieth-century organic chemistry

The paper illustrates how organic chemists dramatically altered their practices in the middle part of the twentieth century through the adoption of analytical instrumentation — such as ultraviolet and infrared absorption spectroscopy and nuclear magnetic resonance spectroscopy — through which the difficult process of structure determination for small molecules became routine. Changes in practice were manifested in two ways: in the use of these instruments in the development of ‘rule-based’ theories; and in an increased focus on synthesis, at the expense of chemical analysis. These rule-based theories took the form of generalizations relating structure to chemical and physical properties, as measured by instrumentation. This ‘Instrumental Revolution’ in organic chemistry was two-fold: encompassing an embrace of new tools that provided unprecedented access to structures, and a new way of thinking about molecules and their reactivity in terms of shape and structure. These practices suggest the possibility of a change in the ontological status of chemical structures, brought about by the regular use of instruments. The career of Robert Burns Woodward (1917–1979) provides the central historical examples for the paper. Woodward was an organic chemist at Harvard from 1937 until the time of his death. In 1965, he won the Nobel Prize in Chemistry.     

Assessing climate model projections: State of the art and philosophical reflections

The present paper draws on climate science and the philosophy of science in order to evaluate climate-model-based approaches to assessing climate projections. We analyze the difficulties that arise in such assessment and outline criteria of adequacy for approaches to it. In addition, we offer a critical overview of the approaches used in the IPCC working group one fourth report, including the confidence building, Bayesian and likelihood approaches. Finally, we consider approaches that do not feature in the IPCC reports, including three approaches drawn from the philosophy of science. We find that all available approaches face substantial challenges, with IPCC approaches having as a primary source of difficulty their goal of providing probabilistic assessments.     

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.     

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.     

Thomas Reid and the problem of induction: from common experience to common sense

By the middle of the eighteenth century the new science had challenged the intellectual primacy of common experience in favor of recondite, expert and even counter-intuitive knowledge increasingly mediated by specialized instruments. Meanwhile modern philosophy had also problematized the perceptions of common experience — in the case of David Hume this included our perception of causal relations in nature, a fundamental precondition of scientific endeavor.In this article I argue that, in responding to the ‘problem of induction’ as advanced by Hume, Reid reformulated Aristotelian foundationalism in distinctly modern terms. An educator and mathematician self-consciously working within the framework of the new science, Reid articulated a philosophical foundation for natural knowledge anchored in the human constitution and in processes of adjudication in an emerging modern public sphere of enlightened discourse. Reid thereby transformed one of the bases of Aristotelian science — common experience — into a philosophically and socially justified notion of ‘common sense’. Reid's intellectual concerns had as much to do with the philosophy of science as they did with moral philosophy or epistemology proper, and were bound up with wider social and scientific changes taking place in the early modern period.     

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.     

Multiple time-series modelling: Another look at the canadian money and income data

The practice of modelling the components of a vector time series to arrive at a joint model for the vector is considered. It is shown that in some cases this is not unreasonable. A vector ARMA model is used to model the Canadian money and income data. We also use these data to discuss the issue of differencing a multiple time series. Finally, models based on first and second differences are compared using forecasts.     

Staphylococcus epidermidis in the circulating blood of normal and thrombocytopenic human subjects: Immunological data

Summary Immunological studies, performed with human sera and rabbit antisera upon some strains ofStaph. epidermidis carried in the circulating blood of normal and thrombocytopenic subjects, indicate that the reactivity is very low and almost completely related to antigenic properties common toStaph. aureus.     

Specification versus data fitting: SEM prediction and the Q‐class estimator

We propose a new class of limited information estimators built upon an explicit trade‐off between data fitting and a priori model specification. The estimators offer the researcher a continuum of estimators that range from an extreme emphasis on data fitting and robust reduced‐form estimation to the other extreme of exact model specification and efficient estimation. The approach used to generate the estimators illustrates why ULS often outperforms 2SLS‐PRRF even in the context of a correctly specified model, provides a new interpretation of 2SLS, and integrates Wonnacott and Wonnacott's (1970) least weighted variance estimators with other techniques. We apply the new class of estimators to Klein's Model I and generate forecasts. We find for this example that an emphasis on specification (as opposed to data fitting) produces better out‐of‐sample predictions. Copyright © 1999 John Wiley & Sons, Ltd.     

Computer simulation and the features of novel empirical data

In an attempt to determine the epistemic status of computer simulation results, philosophers of science have recently explored the similarities and differences between computer simulations and experiments. One question that arises is whether and, if so, when, simulation results constitute novel empirical data. It is often supposed that computer simulation results could never be empirical or novel because simulations never interact with their targets, and cannot go beyond their programming. This paper argues against this position by examining whether, and under what conditions, the features of empiricality and novelty could be displayed by computer simulation data. I show that, to the extent that certain familiar measurement results have these features, so can some computer simulation results.     

Quarterly GPPA earnings data: Time-series properties and predictive ability results in the airlines industry

This paper provides preliminary results regarding the impact of general purchasing power adjustments (GPPA) on quarterly earnings for 24 firms from the airlines industry. Findings indicated that GPPA transformations do not substantially alter the time-series properties of quarterly earnings data. Two Box-Jenkins models, (100) × (100) and (100) × (110) were identified as possible parsimonious models for the airlines industry. It is recommended that these structures be considered as viable candidates for earnings expectations models in market studies testing for informational content of GPPA earnings. The predictive findings demonstrated that predictions of historical cost quarterly earnings were significantly more accurate than GPPA predictions for four of the five horizons tested.     

Algorithmic compression of empirical data: reply to Twardy, Gardner, and Dowe

This discussion note responds to objections by Twardy, Gardner, and Dowe to my earlier claim that empirical data sets are algorithmically incompressible. Twardy, Gardner, and Dowe hold that many empirical data sets are compressible by Minimum Message Length technique and offer this as evidence that these data sets are algorithmically compressible. I reply that the compression achieved by Minimum Message Length technique is different from algorithmic compression. I conclude that Twardy, Gardner, and Dowe fail to establish that empirical data sets are algorithmically compressible.     

An interpretation of the non-symmetric responding logistic model in terms of price and experience effects

This paper presents an alternative derivation and a generalization of the non-symmetric responding logistic model of Easingwood, Mahajan and Muller (1981) based upon a combination of experience curve and price elasticity effects.     

Forecasting future canadian residential heating demand: An illustration of forecasting with aggregated and disaggregated data

This paper examines the sensitivity of forecasts to the level of aggregation of the data. A relative shares regression model and a multinominal logit model are tested with both aggregate and disaggregate survey data from 2109 respondents. The results indicate the appropriate model to use depends on whether the data are disaggregate or aggregate in form. Forecasts of solar heating of dwelling unit demand and market shares are also reported for Canada in terms of the solar price relative to the natural gas price and solar reliability relative to natural gas reliability.     

The effect of locality,breed and previous tick experience on seasonal changes in the resistance of cattle toBoophilus microplus (Ixodoidea: Ixodidae)

Summary A seasonal cycle in the expression of resistance to the tickBoophilus microplus occurs in cattle in central and southeastern Queensland, Australia. This is due to a seasonal fluctuation in the capacity of cattle to mount an effective immune response against the parasitic tick and is manifest as a waning of the expression of resistance in autumn and early winter which occurs irrespective of breed or the nutritional state of the cattle.