Traditionally, empiricism has relied on the specialness of human observation, yet science is rife with sophisticated instrumentation and techniques. The present article advances a conception of empirical evidence applicable to actual scientific practice. I argue that this conception elucidates how the results of scientific research can be repurposed across diverse epistemic contexts: it helps to make sense of how evidence accumulates across theory change, how different evidence can be amalgamated and used jointly, and how the same evidence can be used (...) to constrain competing theories in the service of breaking local underdetermination. (shrink)

Despite an enormous philosophical literature on models in science, surprisingly little has been written about data models and how they are constructed. In this paper, I examine the case of how paleodiversity data models are constructed from the fossil data. In particular, I show how paleontologists are using various model-based techniques to correct the data. Drawing on this research, I argue for the following related theses: first, the ‘purity’ of a data model is not a measure of its epistemic reliability. (...) Instead it is the fidelity of the data that matters. Second, the fidelity of a data model in capturing the signal of interest is a matter of degree. Third, the fidelity of a data model can be improved ‘vicariously’, such as through the use of post hoc model-based correction techniques. And, fourth, data models, like theoretical models, should be assessed as adequate for particular purposes. (shrink)

This paper distinguishes between two arguments based on measurement robustness and defends the epistemic value of robustness for the assessment of measurement reliability. I argue that the appeal to measurement robustness in the assessment of measurement is based on a different inferential pattern and is not exposed to the same objections as the no-coincidence argument which is commonly associated with the use of robustness to corroborate individual results. This investigation sheds light on the precise meaning of reliability that emerges from (...) measurement assessment practice. In addition, by arguing that the measurement assessment robustness argument has similar characteristics across the physical, social and behavioural sciences, I defend the idea that there is continuity in the notion of measurement reliability across sciences. (shrink)

Archaeological data are shadowy in a number of senses. Not only are they notoriously fragmentary but the conceptual and technical scaffolding on which archaeologists rely to constitute these data as evidence can be as constraining as it is enabling. A recurrent theme in internal archaeological debate is that reliance on sedimented layers of interpretative scaffolding carries the risk that “preunderstandings” configure what archaeologists recognize and record as primary data, and how they interpret it as evidence. The selective and destructive nature (...) of data capture in archeology further suggests that there may be little scope for putting “legacy” data to work in new ways. And yet archaeologists have been strikingly successful in mining old datasets for new insights. I situate these concerns in the broader context of debate about the epistemic standing of the historical sciences, and then consider three strategies by which archaeologists address the challenges posed by legacy data. The first two – secondary retrieval and recontextualization – are a matter of reconfiguring the scaffolding that underpins evidential reasoning. The third turns on redeploying old data in the context of computational models that support the experimental simulation of the cultural systems and contexts under study. (shrink)

The vagaries of evidential reasoning in archaeology are notorious: the material traces that comprise the archaeological record are fragmentary and profoundly enigmatic, and the inferential gap that archaeologists must cross to constitute them as evidence of the cultural past is a peren­nial source of epistemic anxiety. And yet we know a great deal about the cultural past, including vast reaches of the past for which this material record is our only source of evidence. The contents of this record stand as (...) evidence only under interpretation, but however much a construct it is, archaeological evidence has a striking capacity to disrupt settled assump­tions, redirecting inquiry and expanding interpretive horizons in direc­tions no one could have anticipated. It is this capacity for constraining inference and interpretation that I am concerned to understand. I outline a model of evidential reasoning based on archaeological practice that integrates insights drawn from philosophical theories of confirmation, model building and hypothesis testing. Given growing interest in the uses of material evidence in fields that had been resolutely text-based, the archaeological principles of evidential reasoning may have much wider reach than this particular social/historical discipline. (shrink)

This article develops a model-based account of the standardization of physical measurement, taking the contemporary standardization of time as its central case-study. To standardize the measurement of a quantity, I argue, is to legislate the mode of application of a quantity-concept to a collection of exemplary artefacts. Legislation involves an iterative exchange between top-down adjustments to theoretical and statistical models regulating the application of a concept, and bottom-up adjustments to material artefacts in light of remaining gaps. The model-based account clarifies (...) the cognitive role of ad hoc corrections, arbitrary rules and seemingly circular inferences involved in contemporary timekeeping, and explains the stability of networks of standards better than its conventionalist and constructivist counterparts. (shrink)

This article develops a model-based account of the standardization of physical measurement, taking the contemporary standardization of time as its central case study. To standardize the measurement of a quantity, I argue, is to legislate the mode of application of a quantity concept to a collection of exemplary artefacts. Legislation involves an iterative exchange between top-down adjustments to theoretical and statistical models regulating the application of a concept, and bottom-up adjustments to material artefacts in light of remaining gaps. The model-based (...) account clarifies the cognitive role of ad hoc corrections, arbitrary rules, and seemingly circular inferences involved in contemporary timekeeping, and explains the stability of networks of standards better than its conventionalist and constructivist counterparts. 1 Introduction2 Making Time Universal2.1 Stability and accuracy2.2 Multiple realizability2.3 The challenges of synchronicity2.4 Divergent standards2.5 The leap second3 The Two Faces of Stability3.1 An explanatory challenge3.2 Conventionalist explanations3.3 Constructivist explanations4 Models and Standardization4.1 A third alternative4.2 Stability reconceived4.3 Legislative freedom4.4 Discovering gaps4.5 Nature and society entangled4.6 Remark on scope5 Conclusions. (shrink)

Contrary to the claim that measurement standards are absolutely accurate by definition, I argue that unit definitions do not completely fix the referents of unit terms. Instead, idealized models play a crucial semantic role in coordinating the theoretical definition of a unit with its multiple concrete realizations. The accuracy of realizations is evaluated by comparing them to each other in light of their respective models. The epistemic credentials of this method are examined and illustrated through an analysis of the contemporary (...) standardization of time. I distinguish among five senses of ‘measurement accuracy’ and clarify how idealizations enable the assessment of accuracy in each sense. (shrink)

This article explores some of the roles of computer simulation in measurement. A model-based view of measurement is adopted and three types of measurement—direct, derived, and complex—are distinguished. It is argued that while computer simulations on their own are not measurement processes, in principle they can be embedded in direct, derived, and complex measurement practices in such a way that simulation results constitute measurement outcomes. Atmospheric data assimilation is then considered as a case study. This practice, which involves combining information (...) from conventional observations and simulation-based forecasts, is characterized as a complex measuring practice that is still under development. The case study reveals challenges that are likely to resurface in other measuring practices that embed computer simulation. It is also noted that some practices that embed simulation are difficult to classify; they suggest a fuzzy boundary between measurement and non-measurement. 1 Introduction2 A Contemporary View of Measurement3 Three Types of Measurement4 Can Computer Simulations Measure Real-World Target Systems?5 Case Study: Atmospheric Data Assimilation5.1 Why data assimilation?5.2 A complex measuring practice under development5.3 Epistemic iteration6 The Boundaries of Measurement7 Epistemology, Not Terminology. (shrink)

This article considers the temporal dimension of data processing and use and the ways in which it affects the production and interpretation of knowledge claims. I start by distinguishing the time at which data collection, dissemination, and analysis occur from the time in which the phenomena for which data serve as evidence operate. Building on the analysis of two examples of data reuse from modeling and experimental practices in biology, I then argue that Dt affects how researchers select and interpret (...) data as evidence and identify and understand phenomena. (shrink)

This article develops a historico-critical analysis of uncertainty and accuracy in measurement through a case-study of the adjustment of the fundamental physical constants, in order to investigate the sceptical “problem of unknowability” undermining realist accounts of measurement. Every scientific result must include a “measurement uncertainty”, but uncertainty cannot be be eval- uated against the unknown, and therefore cannot be taken as an assessment of “accuracy”, defined in the metrological vocabulary as the closeness to the truth. The way scientists use and (...) interpret uncertainty in the adjustment activity illustrates how they try to overcome this predicament. I iden- tify two operative roles of measurement uncertainty, in the comparison and in the combination of measurement results. This duality implies a tension between selection and combination when aggregating results, leading to a crucial question: should the evaluation of uncertainties favour safety over precision? I present contrasting answers and identify a specific account of physicists who implicitly try to conciliate realism with the problem of unknowability. I argue that this invites us to reconsider accuracy from a dynamical standpoint, as the gradual achievement of scientific progress through error correction. Finally, I present two interpretations of measurement uncertainty, objective and epistemic, which I criticize and suggest improvements to. (shrink)

We discuss the scientific task of historical reconstruction and the problem of epistemic access. We argue that strong epistemic support for historical claims consists in the consilience of multiple independent lines of evidence, and analyze the impact hypothesis for the End-Cretaceous mass extinction to illustrate the accrual of epistemic support. Although there are elements of the impact hypothesis that enjoy strong epistemic support, the general conditions for this are strict, and help to clarify the difficulties associated with reconstructing the deep (...) past. (shrink)

The goal of this dissertation is to contribute to the epistemology of science by addressing a set of related questions arising from current discussions in the philosophy and science of climate change: (1) Given the imperfection of computer models, how do they provide information about large and complex target systems? (2) What is the relationship between consilient reasoning and robust evidential support in the production of scientific knowledge? (3) Does taking the mean of a set of model outputs provide epistemic (...) advantages over using the output of a single ‘best model’? Synthesizing research in philosophy and science, the thesis analyzes connections among consilient inductions, robustness analysis, and the aggregation of various sources of evidence, including computer simulations, by investigating case studies of climate change that exemplify the strength of consilient reasoning and the security of robust evidential support. It also explains the rationale and epistemic conditions for improving estimates by averaging multiple estimates, comparing a simple case of averaging estimates to practices in multi-model ensemble studies. I argue: (A) the concepts of consilience and robustness account for the strength and security of inferences that rely on imperfect computer modelling methods, (B) consilient reasoning is conducive to attaining robust evidential support, and (C) an analogy can explain why averaging the outputs of multiple models can improve estimates of a target system, given that conditions of model independence, skill and unequal weighting are taken into account. (shrink)