Descriptive accounts of the nature of explanation in neuroscience and the global goals of such explanation have recently proliferated in the philosophy of neuroscience and with them new understandings of the experimental practices of neuroscientists have emerged. In this paper, I consider two models of such practices; one that takes them to be reductive; another that takes them to be integrative. I investigate those areas of the neuroscience of learning and memory from which the examples used to substantiate these models (...) are culled, and argue that the multiplicity of experimental protocols used in these research areas presents specific challenges for both models. In my view, these challenges have been overlooked largely because philosophers have hitherto failed to pay sufficient attention to fundamental features of experimental practice. I demonstrate that when we do pay attention to such features, evidence for reduction and integrative unity in neuroscience is simply not borne out. I end by suggesting some new directions for the philosophy of neuroscience that pertain to taking a closer look at the nature of neuroscientific experiments. (shrink)

In recent debates about the replication crisis, two positions have been dominant: one that focuses on methodological reforms and one that focuses on theory building. This paper takes up the suggestion that there might be a deeper difference in play, concerning the ways the very subject matter of psychology is construed by opposing camps, i.e., in terms of stable effects versus in terms of complexity. I argue that each gets something right, but neither is sufficient. My analysis suggests that the (...) context sensitivity of the psychological subject matter needs to be front and center of methodological and theoretical efforts. (shrink)

Scientists aim to remediate artifacts in their experimental datasets. However, the remediation of one artifact can result in another. Why might this happen, and what does this consequence tell us about how we should account for artifacts and their control? In this paper, I explore a case in functional neuroimaging where remediation appears to have caused this problem. I argue that remediation amounts to a change to an experimental arrangement. These changes need not be surgical, and the arrangement need not (...) satisfy the criterion of causal modularity. Thus, remediation can affect more than just the factor responsible for the artifact. However, if researchers can determine the consequences of their remediation, they can make adjustments that control for the present artifact as well as for previously controlled ones. Current philosophical accounts of artifacts and the factors responsible for them cannot adequately address this issue, as they do not account for what is needed for artifact remediation (and specifically correction). I support my argument by paralleling it with ongoing concerns regarding the transparency of complex computational systems, as near future remediation across the experimental life sciences will likely make greater use of AI tools to correct for artifacts. (shrink)

Cultural phylogenetics has made remarkable progress by relying on methods originally developed in biology. But biological and cultural evolution do not always proceed according to the same principles. So what, if anything, could justify the use of phylogenetic methods to reconstruct the evolutionary history of culture? In this paper, we describe models used to assess the reliability of inference methods and show how these models play an underappreciated role in addressing that question. The notion of reliability is of course central (...) to these models. As we explain, a common way of understanding reliability is in terms of low error rates. A careful look at case studies in cultural phylogenetics suggests that reliability models partly corroborate this understanding of reliability but also raises points of tension. We conclude by hinting at a few ways forward. (shrink)

This essay attempts to provide additional motivation for the data/phenomena framework advocated in Bogen and Woodward, “Saving the Phenomena”.

This paper provides a restatement and defense of the data/ phenomena distinction introduced by Jim Bogen and me several decades ago (e.g., Bogen and Woodward, The Philosophical Review, 303–352, 1988). Additional motivation for the distinction is introduced, ideas surrounding the distinction are clarified, and an attempt is made to respond to several criticisms.

Going back at least to Duhem, there is a tradition of thinking that crucial experiments are impossible in science. I analyse Duhem's arguments and show that they are based on the excessively strong assumption that only deductive reasoning is permissible in experimental science. This opens the possibility that some principle of inductive inference could provide a sufficient reason for preferring one among a group of hypotheses on the basis of an appropriately controlled experiment. To be sure, there are analogues to (...) Duhem's problems that pertain to inductive inference. Using a famous experiment from the history of molecular biology as an example, I show that an experimentalist version of inference to the best explanation (IBE) does a better job in handling these problems than other accounts of scientific inference. Furthermore, I introduce a concept of experimental mechanism and show that it can guide inferences from data within an IBE-based framework for induction. 1. Introduction2. Duhem on the Logic of Crucial Experiments3. ‘The Most Beautiful Experiment in Biology’4. Why Not Simple Elimination?5. Severe Testing6. An Experimentalist Version of IBE 6.1. Physiological and experimental mechanisms6.2. Explaining the data6.3. IBE and the problem of untested auxiliaries6.4. IBE-turtles all the way down7. Van Fraassen's ‘Bad Lot’ Argument8. IBE and Bayesianism9. Conclusions. (shrink)

It is assumed that scientific models contain no superfluous model elements in scientific representation. A representational model is constructed with all the model elements serving the representational purpose. The received view has it that there are no redundant model elements which are non-representational. Contrary to this received view, I argue that there exist some non-representational model elements which are essential in scientific representation. I call them representation-supporting model elements in virtue of the fact that they play the role to support (...) the representational role of representational model elements. Representation-supporting model elements, which have a characteristic of dependability, are not to be eliminated in the process of modeling although they are playing second fiddle to representational model elements in scientific representation. (shrink)

This paper draws attention to an increasingly common method of using computer simulations to establish evidential standards in physics. By simulating an actual detection procedure on a computer, physicists produce patterns of data (‘signatures’) that are expected to be observed if a sought-after phenomenon is present. Claims to detect the phenomenon are evaluated by comparing such simulated signatures with actual data. Here I provide a justification for this practice by showing how computer simulations establish the reliability of detection procedures. I (...) argue that this use of computer simulation undermines two fundamental tenets of the Bogen–Woodward account of evidential reasoning. Contrary to Bogen and Woodward’s view, computer-simulated signatures rely on ‘downward’ inferences from phenomena to data. Furthermore, these simulations establish the reliability of experimental setups without physically interacting with the apparatus. I illustrate my claims with a study of the recent detection of the superfluid-to-Mott-insulator phase transition in ultracold atomic gases. (shrink)

Influential classical and recent approaches to explicate confirmation, explanation, or explanatory power define these relations or degrees between hypotheses and evidence. This holds for both deductive and Bayesian approaches. However, this neglects the role of data, which for many everyday and scientific examples cannot simply be classified as evidence. I present arguments to sharply distinguish data from evidence in Bayesian approaches. Taking into account this distinction, we can rewrite Schupbach and Sprenger’s measure of explanatory power and show the strengths of (...) this adaptation by applying it to the example of the detection of gravitational waves in physics. (shrink)

While epistemic justification is a central concern for both contemporary epistemology and philosophy of science, debates in contemporary epistemology about the nature of epistemic justification have not been discussed extensively by philosophers of science. As a step toward a coherent account of scientific justification that is informed by, and sheds light on, justificatory practices in the sciences, this paper examines one of these debates—the internalist-externalist debate—from the perspective of objective accounts of scientific evidence. In particular, we focus on Deborah Mayo’s (...) error-statistical theory of evidence because it is a paradigmatically objective theory of evidence that is strongly informed by methodological practice. We contend that from the standpoint of such an objective theory of evidence, justification in science has both externalist and internalist characteristics. In reaching this conclusion, however, we find that the terms of the contemporary debate between internalists and externalists have to be redefined to be applicable to scientific contexts. (shrink)

Some twenty years ago, Bogen and Woodward challenged one of the fundamental assumptions of the received view, namely the theory-observation dichotomy and argued for the introduction of the further category of scientific phenomena. The latter, Bogen and Woodward stressed, are usually unobservable and inferred from what is indeed observable, namely scientific data. Crucially, Bogen and Woodward claimed that theories predict and explain phenomena, but not data. But then, of course, the thesis of theory-ladenness, which has it that our observations are (...) influenced by the theories we hold, cannot apply. On the basis of two case studies, I want to show that this consequence of Bogen and Woodward’s account is rather unrealistic. More importantly, I also object against Bogen and Woodward’s view that the reliability of data, which constitutes the precondition for data-to-phenomena inferences, can be secured without the theory one seeks to test. The case studies I revisit have figured heavily in the publications of Bogen and Woodward and others: the discovery of weak neutral currents and the discovery of the zebra pattern of magnetic anomalies. I show that, in the latter case, data can be ignored if they appear to be irrelevant from a particular theoretical perspective (TLI) and that, in the former case, the tested theory can be critical for the assessment of the reliability of the data (TLA). I argue that both TLI and TLA are much stronger senses of theory-ladenness than the classical thesis and that neither TLI nor TLA can be accommodated within Bogen and Woodward’s account. (shrink)

The paper proposes a practical answer to Duhem's problem within the framework of experimental psychology. First, this problem is briefly discussed; second, two studies in psychology are presented illustrating how theories are tested. Thirdly, based on the foregoing, an approach called the “Empirical Reasoning” is developed and justified. It is shown that the ER approach can successfully cope with Duhem's problem. Finally, the ER approach and the Error Statistics approach of Mayo are critically compared with regard to Duhem's problem.

El presente escrito se propone presentar el modelo de tres niveles del conocimiento científico (datos, fenómenos y teorías) desde los recientes resultados de la filosofía de la ciencia obtenidos por dos perspectivas filosóficas particulares: el nuevo experimentalismo y el enfoque semántico de las teorías. Para ello contrasta los planteamientos principales de estas dos perspectivas con el modelo de dos niveles del conocimiento científico (observación y teoría) del positivismo lógico, que dominó el panorama de la filosofía de la ciencia en las (...) primeras seis décadas del siglo XX. (shrink)

This chapter contains sections titled: Highlights of Past Literature Current Work Future Work.

We argue that the logical outcome of the cladistics revolution in biological systematics, and the move towards rankless phylogenetic classification of nested monophyletic groups as formalized in the PhyloCode, is to eliminate the species rank along with all the others and simply name clades. We propose that the lowest level of formally named clade be the SNaRC, the Smallest Named and Registered Clade. The SNaRC is an epistemic level in the classification, not an ontic one. Naming stops at that level (...) because there is no currently acceptable evidence for clades within it, not because no smaller clades exist. Later, included clades may be named. They would then become the SNaRCs, while the original SNaRC would keep its original name. We argue that all theoretical tasks of biology, in evolution and ecology, as well as practical tasks such as conservation assessment, are better approached using this rankless phylogenetic approach. (shrink)

In seeking general accounts of evidence, confirmation, or inference, philosophers have looked to logical relationships between evidence and hypotheses. Such logics of evidential relationship, whether hypothetico-deductive, Bayesian, or instantiationist fail to capture or be relevant to scientific practice. They require information that scientists do not generally have (e.g., an exhaustive set of hypotheses), while lacking slots within which to include considerations to which scientists regularly appeal (e.g., error probabilities). Building on my co-symposiasts contributions, I suggest some directions in which a (...) new and more adequate philosophy of evidence can move. (shrink)

This paper proposes an account of accurate scientific representation in terms of techniques that produce data from a target phenomenon. I consider an approach to accurate representation that abstracts from such epistemic factors, justified by a thesis I call Ontic Priority. This holds that criteria for representational accuracy depend on a pre-established account of the nature of the relation between a model and its target phenomenon. I challenge Ontic Priority, drawing on the observation that many working scientists do not have (...) access to information allowing them to describe this relation between model and target or compare them accordingly. I critique the ability of an ontic-first approach to provide accuracy criteria in such cases and present historical support for an alternative according to which a model is accurate if and only if integrating the model into a theory of the data acquisition process yields well-fitting predictions of patterns in the data. (shrink)

This paper investigates some metaphysical and epistemological assumptions behind Bogen and Woodward’s data-to-phenomena inferences. I raise a series of points and suggest an alternative possible Kantian stance about data-to-phenomena inferences. I clarify the nature of the suggested Kantian stance by contrasting it with McAllister’s view about phenomena as patterns in data sets.

Observation and experiment as categories for analysing scientific practice have a long pedigree in writings on science. There has, however, been little attempt to delineate observation and experiment with respect to analysing scientific practice; in particular, scientific experimentation, in a systematic manner. Someone who has presented a systematic account of observation and experiment as categories for analysing scientific experimentation is Ian Hacking. In this paper, I present a detailed analysis of Hacking’s observation versus experiment account. Using a range of cases (...) from various fields of scientific enquiry, I argue that the observation versus experiment account is not an adequate framework for delineating scientific experimentation in a systematic manner. (shrink)

The papers collected here are the result of an INTERNATIONAL SYMPOSIUM: Data · Phenomena · Theories: What’s the notion of a scientific phenomenon good for? held in Heidelberg in September 2008. The event was organized by the research group Causality, Cognition, and the Constitution of Scientific Phenomena in cooperation with Philosophy Department at the University of Heidelberg (Peter McLaughlin and Andreas Kemmerling) and the IWH Heidelberg. The symposium was supported by the Emmy-Noether-Programm der Deutschen Forschungsgemeinschaft and by Stiftung Universitat Heidelebrg (...) . The workshop was held in honor of Daniela Bailer-Jones, who died on 13 November 2006 at the age of 37 (cf. my 2007 Daniela Bailer-Jones ). Bailer-Jones was an Emmy Noether fellow, and the symposium was arranged and run by those who were working in her research group at the time of her death: Monika Dullstein, Jochen Apel, and Pavel Radchencko. To them goes the credit for the conception, planning, and carrying out of the symposium. (shrink)

Three decades ago, James Bogen and James Woodward argued against the possibility and usefulness of scientific explanations of data. They developed a picture of scientific reasoning where stable phenomena were identified via data without much input from theory. Rather than explain data, theories ‘save the phenomena’. In contrast, I argue that there are good reasons to explain data, and the practice of science reveals attempts to do so. I demonstrate that algorithms employed to address inverse problems in remote-sensing applications should (...) be understood as attempts to identify phenomena by explaining the data. Thus, this paper furthers understanding of data-to-phenomena reasoning in science, and demonstrates theory may play a more central role in phenomena identification than previously recognized. (shrink)

The aim of this article is to contribute to the discussion about the so-called “empirical claim” and “empirical basis” of theory testing. First, the proposals of reconceptualization of the standard notions of partial potential model, intended application and empirical claim of a theory made by Balzer (1982, 1988, 1997a, 1997b, 2006, Balzer, Lauth & Zoubek 1993) and Gähde (1996, 2002, 2008) will be first discussed. Then, the distinction between “global” and “local empirical basis” will be introduced, linking it with that (...) of “global” and “local or particular empirical claim”. After that, following Balzer (1997a), along the lines of Suppes (1962), I will present a way in which what count as ‘data’ for a theory can be modeltheoretically represented and conceptualized. Finally, the proposed analysis will be exemplified with the case of classical genetics (reconstructed in Balzer & Lorenzano 2000, Lorenzano, 1995, 2000, 2002). (shrink)

I propose a framework that explicates and distinguishes the epistemic roles of data and models within empirical inquiry through consideration of their use in scientific practice. After arguing that Suppes’ characterization of data models falls short in this respect, I discuss a case of data processing within exploratory research in plant phenotyping and use it to highlight the difference between practices aimed to make data usable as evidence and practices aimed to use data to represent a specific phenomenon. I then (...) argue that whether a set of objects functions as data or models does not depend on intrinsic differences in their physical properties, level of abstraction or the degree of human intervention involved in generating them, but rather on their distinctive roles towards identifying and characterizing the targets of investigation. The paper thus proposes a characterization of data models that builds on Suppes’ attention to data practices, without however needing to posit a fixed hierarchy of data and models or a highly exclusionary definition of data models as statistical constructs. (shrink)

I propose a framework that explicates and distinguishes the epistemic roles of data and models within empirical inquiry through consideration of their use in scientific practice. After arguing that Suppes’ characterization of data models falls short in this respect, I discuss a case of data processing within exploratory research in plant phenotyping and use it to highlight the difference between practices aimed to make data usable as evidence and practices aimed to use data to represent a specific phenomenon. I then (...) argue that whether a set of objects functions as data or models does not depend on intrinsic differences in their physical properties, level of abstraction or the degree of human intervention involved in generating them, but rather on their distinctive roles towards identifying and characterizing the targets of investigation. The paper thus proposes a characterization of data models that builds on Suppes’ attention to data practices, without however needing to posit a fixed hierarchy of data and models or a highly exclusionary definition of data models as statistical constructs. (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)

Advanced medical imaging, such as CT, fMRI and PET, has undergone enormous progress in recent years, both in accuracy and utilization. Such techniques often bring with them an illusion of immediacy, the idea that the body and its diseases can be directly inspected. In this paper we target this illusion and address the issue of the reliability of advanced imaging tests as knowledge procedures, taking positron emission tomography in oncology as paradigmatic case study. After individuating a suitable notion of reliability, (...) we argue that PET is a highly theory-laden and non-immediate knowledge procedure, in spite of the photographic-like quality of the images it delivers; the diagnostic conclusions based on the interpretation of PET images are population-dependent; PET images require interpretation, which is inherently observer-dependent and therefore variable. We conclude with a three-step methodological proposal for enhancing the reliability of advanced medical imaging. (shrink)

The article argues for the epistemic rationale of triangulation, namely, the use of multiple and independent sources of evidence. It claims that triangulation is to be understood as causal reasoning from data to phenomenon, and it rationalizes its epistemic value in terms of controlling for likely errors and biases of particular data-generating procedures. This perspective is employed to address objections against triangulation concerning the fallibility and scope of the inference, as well as problems of independence, incomparability, and discordance of evidence. (...) The debate on the existence of social preferences is used as an illustrative case. (shrink)

The 2011 Nobel Prize in Physics was awarded to researchers from the Supernova Cosmology Project and the High-z Supernova Search Team for the discovery of the accelerating expansion of the universe. In this paper, I provide a historical analysis of the supernova cosmology evidence put forward by these teams for the accelerating universe, in terms of an iterative model of scientific progress developed by Hasok Chang in the context of his study of the development of measurement standards. I argue, using (...) the key concept of epistemic iteration, that the iterative model adequately accounts for evidence production in experimental science as well. In order to apply Chang’s model to the experimental evidence for the accelerating universe, I introduce the concept of endorsement as a particular mode of progress, and argue that supernova scientists produced an endorsed measurement system to claim evidence for their discovery. Furthermore, I show that the credibility of the evidence was not based on a particular measurement, rather, what proved to be decisive was the “robust consistency” of many individual results. (shrink)

El presente escrito se propone presentar el modelo de tres niveles del conocimiento científico (datos, fenómenos y teorías) desde los recientes resultados de la filosofía de la ciencia obtenidos por dos perspectivas filosóficas particulares: el nuevo experimentalismo y el enfoque semántico de las teorías. Para ello contrasta los planteamientos principales de estas dos perspectivas con el modelo de dos niveles del conocimiento científico (observación y teoría) del positivismo lógico, que dominó el panorama de la filosofía de la ciencia en las (...) primeras seis décadas del siglo XX. (shrink)

The Ultimatum Game is one of the most successful experimental designs in the history of the social sciences. In this article I try to explain this success—what makes it a “paradigmatic experiment”—stressing in particular its versatility. Despite the intentions of its inventors, the Ultimatum Game was never a good design to test economic theory, and it is now mostly used as a heuristic tool for the observation of nonstandard preferences or as a “social thermometer” for the observation of culture‐specific norms. (...) †To contact the author, please write to: Department of Sociology and Philosophy, University of Exeter, Amory Building, Exeter EX4 4DT, UK; e‐mail: [email protected]. (shrink)

South Korean high school students are being taught Einstein’s Special Theory of Relativity. In this article, I examine the portrayal of this theory in South Korean high school physics textbooks and discuss an alternative method used to solve the analyzed problems. This examination of how these South Korean textbooks present this theory has revealed two main flaws: First, the textbooks’ contents present historically fallacious backgrounds regarding the origin of this theory because of a blind dependence on popular undergraduate textbooks, which (...) ignore the revolutionary aspects of the theory in physics. And second, the current ingredients of teaching this theory are so simply enumerated and conceptually confused that students are not provided with good opportunities to develop critical capacities for evaluating scientific theories. Reviewing textbooks used in South Korea, I will, first, claim that the history of science contributes to understand not merely the origins but also two principles of this theory. Second, in addition to this claim, I argue that we should distinguish not only hypotheses from principles but also phenomena from theoretical consequences and evidence. Finally, I suggest an alternative way in which theory testing occurs in the process of evaluation among competitive theories on the basis of data, not in the simple relation between a hypothesis and evidence. (shrink)

This essay presents a unified account of safety, sensitivity, and severe testing. S’s belief is safe iff, roughly, S could not easily have falsely believed p, and S’s belief is sensitive iff were p false S would not believe p. These two conditions are typically viewed as rivals but, we argue, they instead play symbiotic roles. Safety and sensitivity are both valuable epistemic conditions, and the relevant alternatives framework provides the scaffolding for their mutually supportive roles. The relevant alternatives condition (...) holds that a belief is warranted only if the evidence rules out relevant error possibilities. The safety condition helps categorise relevant from irrelevant possibilities. The sensitivity condition captures ‘ruling out’. Safety, sensitivity, and the relevant alternatives condition are typically presented as conditions on warranted belief or knowledge. But these properties, once generalised, help characterise other epistemic phenomena, including warranted inference, legal verdicts, scientific claims, reaching conclusions, addressing questions, warranted assertion, and the epistemic force of corroborating evidence. We introduce and explain Mayo’s severe testing account of statistical inference. A hypothesis is severely tested to the extent it passes tests that probably would have found errors, were they present. We argue Mayo’s account is fruitfully understood using the resulting relevant alternatives framework. Recasting Mayo’s condition using the conceptual framework of contemporary epistemology helps forge fruitful connections between two research areas—philosophy of statistics and the analysis of knowledge—not currently in sufficient dialogue. The resulting union benefits both research areas. (shrink)

Critics who are concerned over the epistemological status of psychiatric diagnoses often describe them as being constructed. In contrast, those critics usually see symptoms as relatively epistemologically unproblematic. In this paper I show that symptoms are also constructed. To do this I draw upon the demarcation between data and phenomena. I relate this distinction to psychiatry by portraying behaviour of individuals as data and symptoms as phenomena. I then draw upon philosophers who consider phenomena to be constructed to argue that (...) symptoms are also constructed. Rather than being ready made in the world I show how symptoms are constructs we apply to the world. I highlight this with a historical example and describe methodological constraints on symptom construction. I show the epistemic problems with psychiatric diagnoses are also applicable to symptoms. Following this, I suggest that critics of psychiatric diagnoses should extend their criticism to symptoms or, if they still believe symptoms are relatively epistemologically unproblematic, should rethink their concerns over psychiatric diagnoses. (shrink)

While the term “reactivity” has come to be associated with specific phenomena in the social sciences, having to do with subjects’ awareness of being studied, this paper takes a broader stance on this concept. I argue that reactivity is a ubiquitous feature of the psychological subject matter and that this fact is a precondition of experimental research, while also posing potential problems for the experimenter. The latter are connected to the worry about distorted data and experimental artifacts. But what are (...) experimental artifacts and what is the most productive way of dealing with them? In this paper, I approach these questions by exploring the ways in which experimenters in psychology simultaneously exploit and suppress the reactivity of their subject matter in order to produce experimental data that speak to the question or subject matter at hand. Highlighting the artificiality of experimental data, I raise the question of what distinguishes a genuine experimental result from an experimental artifact. My analysis construes experimental results as the outcomes of inferences from the data that take material background assumptions as auxiliary premises. Artifacts occur when one or more of these background assumptions are false, such that the data do not reliably serve the purposes they were generated for. I conclude by laying out the ways in which my analysis of data quality is relevant to, and informed by, recent debates about the replicability of experimental results. (shrink)

Error is protean, ubiquitous and crucial in scientific process. In this paper it is argued that understanding scientific process requires what is currently absent: an adaptable, context-sensitive functional role for error in science that naturally harnesses error identification and avoidance to positive, success-driven, science. This paper develops a new account of scientific process of this sort, error and success driving Self-Directed Anticipative Learning (SDAL) cycling, using a recent re-analysis of ape-language research as test example. The example shows the limitations of (...) other accounts of error, in particular Mayo’s (Error and the growth of experimental knowledge, 1996) error-statistical approach, and SDAL cycling shows how they can be fruitfully contextualised. (shrink)

The biological effects of low doses of toxic and carcinogenic chemicals are currently a matter of significant scientific controversy. This paper argues that philosophers of science can contribute to alleviating this controversy by examining it with the aid of a novel account of scientific anomaly. Specifically, analysis of contemporary research on chemical hormesis (i.e., alleged beneficial biological effects produced by low doses of substances that are harmful at higher doses) suggests that scientists may initially describe anomalous phenomena in terms of (...) multiple distinct "characterizations," each of which is compatible with current empirical evidence. By focusing attention on this feature of scientific anomalies, philosophers of science can alleviate the controversy over low-dose chemical effects in at least two ways: (1) they can pinpoint the significant ways in which particular characterizations frame the controversy, and (2) they can identify the methodological value judgments at stake in researchers' choice of characterizations. (shrink)

This paper discusses features of an epistemically valuable form of evidence that raise troubles for received and new epistemological treatments of experimental evidence.

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)

The paper rebuts a currently popular criticism against a certain take on the referential role of discontinuities and singularities in the physics of first-order phase transitions. It also elaborates on a proposal I made previously on how to understand this role within the framework provided by the distinction between data and phenomena.

Bogen and Woodward’s distinction between data and phenomena raises the need to understand the structure of the data-to-phenomena and theory-to-phenomena inferences. I suggest that one way to study the structure of these inferences is to analyze the role of the assumptions involved in the inferences: What kind of assumptions are they? How do these assumptions contribute to the practice of identifying phenomena? In this paper, using examples from atmospheric dynamics, I develop an account of the practice of identifying the target (...) in the data-to-phenomena and theory-to-phenomena inferences in which assumptions about spatiotemporal scales play a central role in the identification of parameters that describe the target system. I also argue that these assumptions are not only empirical but they are also idealizing and abstracting. I conclude the paper with a reflection on the role of idealizations in modeling. (shrink)

This paper proposes an extended version of the interventionist account for causal inference in the practical context of biological mechanism research. This paper studies the details of biological mechanism researchers’ practices of assessing the evidential legitimacy of experimental data, arguing why quantity and variety are two important criteria for this assessment. Because of the nature of biological mechanism research, the epistemic values of these two criteria result from the independence both between the causation of data generation and the causation in (...) question and between different interventions, not techniques. The former independence ensures that the interventions in the causation in question are not affected by the causation that is responsible for data generation. The latter independence ensures the reliability of the final mechanisms not only in the empirical but also the formal aspects. This paper first explores how the researchers use quantity to check the effectiveness of interventions, where they at the same time determine the validity of the difference-making revealed by the results of interventions. Then, this paper draws a distinction between experimental interventions and experimental techniques, so that the reliability of mechanisms, as supported by the variety of evidence, can be safely ensured in the probabilistic sense. The latter process is where the researchers establish evidence of the mechanisms connecting the events of interest. By using case studies, this paper proposes to use ‘intervention’ as the fruitful connecting point of literature between evidence and mechanisms. (shrink)

In this paper I offer an appraisal of James Bogen and James Woodward’s distinction between data and phenomena which pursues two objectives. First, I aim to clarify the notion of a scientific phenomenon. Such a clarification is required because despite its intuitive plausibility it is not exactly clear how Bogen and Woodward’s distinction has to be understood. I reject one common interpretation of the distinction, endorsed for example by James McAllister and Bruce Glymour, which identifies phenomena with patterns in data (...) sets. Furthermore, I point out that other interpretations of Bogen and Woodward’s distinction do not specify the relationship between phenomena and theories in a satisfying manner. In order to avoid this problem I propose a contextual understanding of scientific phenomena according to which phenomena are states of affairs which play specific roles in scientific practice and to which we adopt a special epistemic attitude. Second, I evaluate the epistemological significance of Bogen and Woodward’s distinction with respect to the debate between scientific realists and constructive empiricists. Contrary to what Bogen and Woodward claim, I argue that the distinction does not provide a convincing argument against constructive empiricism. (shrink)

Economists use the term ‘stylized fact’ in many contexts, though the meaning of this phrase and the motivation for using such a concept is unclear. In this paper, we provide a philosophical analysis of stylized facts, which aims to be methodologically interesting and useful. While our framework applies to all principled uses of stylized facts, we illustrate its core features by applying it to Nicholas Kaldor's initial and exemplary use of stylized facts in growth economics.

The objective of this dissertation is to write the first pages of the biography of paleobiological data. I will focus on i) the genesis of this kind of data as it emerged in German stratigraphy and paleontology between the mid 19th and the early 20th centuries and ii) how the conceptualization of the paleontological data was reformulated and taken as the starting point for studying the patterns of the diversity of life in deep time between the 1940s and 70s. This (...) is the turning point that marks the ‘coming into being’ of specifically paleobiological data. I will reconstruct in detail how it was possible to transform an incomplete and misleading material object — the fossil record that can be admired in a museum —into a no longer misleading source of knowledge. I will namely describe the genesis of the paleobiological practice by retracing the encounter of two different approaches to the fossil record between the mid 19th and early 20th centuries in German academia and their later diffusion into English-speaking countries. (shrink)