Robustness in Science

I show how omissions lead to robustness and can justify distortions, and I give inferentially relevant explications of abstraction and idealization. Abstraction is explicated as the omission of all and only those claims that use a specific vocabulary; idealization is explicated as the distortion of only those claims that use a specific vocabulary. With these explications, abstraction can justify idealization. As examples of how abstraction justifies idealization and leads to robustness, I discuss Beauchamp and Childress's four principles of biomedical ethics (...) and the qualitative treatment of the Schrödinger equation. (shrink)

This paper concerns the recent revival of entity realism. Having been started with the work of Ian Hacking, Nancy Cartwright and Ronald Giere, the project of entity realism has recently been developed by Matthias Egg, Markus Eronen, and Bence Nanay. The paper opens a dialogue among these recent views on entity realism and integrates them into a more advanced view. The result is an epistemological criterion for reality: the property-tokens of a certain type may be taken as real insofar as (...) only they can be materially inferred from the evidence obtained in a variety of independent ways of detection. (shrink)

This paper draws on the phenomenological-hermeneutical approaches to philosophy of science to develop realist perspectivism, an integration of experimental realism and perspectivism. Specifically, the paper employs the distinction between “manifestation” and “phenomenon” and it advances the view that the evidence of a real entity is “explorable” in order to argue that instrumentally-mediated robust evidence indicates real entities. Furthermore, it underpins the phenomenological notion of the horizonal nature of scientific observation with perspectivism, so accounting for scientific pluralism even in the cases (...) of inconsistent models. Overall, realist perspectivism is proposed as the way to go for (phenomenologically-hermeneutically minded) philosophers of science. (shrink)

Convergence of model projections is often considered by climate scientists to be an important objective in so far as it may indicate the robustness of the models’ core hypotheses. Consequently, the range of climate projections from a multi-model ensemble, called “model spread”, is often expected to reduce as climate research moves forward. However, the successive Assessment Reports of the Intergovernmental Panel on Climate Change indicate no reduction in model spread, whereas it is indisputable that climate science has made improvements in (...) its modelling. In this paper, after providing a detailed explanation of the situation, we describe an epistemological setting in which a steady model spread is not doomed to be seen as negative, and is indeed compatible with a desirable evolution of climate models taken individually. We further argue that, from the perspective of collective progress, as far as the improvement of the products of a multi-model ensemble is concerned, reduction of model spread is of lower priority than model independence. (shrink)

Building on Nozick's invariantism about objectivity, I propose to define scientific objectivity in terms of counterfactual independence. I will argue that such a counterfactual independence account is (a) able to overcome the decisive shortcomings of Nozick's original invariantism and (b) applicable to three paradigmatic kinds of scientific objectivity (that is, objectivity as replication, objectivity as robustness, and objectivity as Mertonian universalism).

Many policy decisions take input from collections of scientific models. Such decisions face significant and often poorly understood uncertainty. We rework the so-called confidence approach to tackle decision-making under severe uncertainty with multiple models, and we illustrate the approach with a case study: insurance pricing using hurricane models. The confidence approach has important consequences for this case and offers a powerful framework for a wide class of problems. We end by discussing different ways in which model ensembles can feed information (...) into the approach, appropriate to different collections of models. (shrink)

When two or more (groups of) researchers independently investigating the same domain arrive at the same result, a multiple discovery occurs. The pervasiveness of multiple discoveries in science suggests the intuition that they are in some sense inevitable—that one should view them as results that force themselves upon us, so to speak. We argue that, despite the intuitive force of such an “inevitabilist insight,” one should reject it. More specifically, we distinguish two facets of the insight and argue that: (a) (...) the profusion of multiple discoveries in scientific practice does not support the inevitabilist side of the inevitability/contingency of science controversy; and (b) the crucial role of background knowledge in scientific inquiry complicates the attempt to interpret the pervasiveness of multiple discoveries in realist terms. (shrink)

There is a widely shared belief that the higher-level sciences can provide better explanations than lower-level sciences. But there is little agreement about exactly why this is so. It is often suggested that higher-level explanations are better because they omit details. I will argue instead that the preference for higher-level explanations is just a special case of our general preference for informative, logically strong, beliefs. I argue that our preference for informative beliefs entirely accounts for why higher-level explanations are sometimes (...) better—and sometimes worse—than lower-level explanations. The result is a step in the direction of the unity of science hypothesis. 1Introduction2Background: Is Omitting Details an Explanatory Virtue? 2.1Anti-reductionist arguments2.2Reductionist argument2.3Logical strength3Bases, Links and Logical Strength4Functionalism and Fodor’s Argument5Two Generalizations6Should the Base Really Be Maximally Strong?7Anti-reductionist Arguments Regarding the Base8Should the Antecedent of the Link Really Be Maximally Weak? (shrink)

The French physicist Jean Baptiste Perrin is widely credited with providing the conclusive argument for atomism. The most well-known part of Perrin’s argument is his description of thirteen different procedures for determining Avogadro’s number (N)–the number of atoms, ions, and molecules contained in a gram-atom, gram-ion, and gram-mole of a substance, respectively. Because of its success in ending the atomism debates Perrin’s argument has been the focus of much philosophical interest. The various philosophers, however, have reached different conclusions, not only (...) about the argument’s general rationale but also the role that the multiple determination of N played in it. This paper emphasizes the historical development of Perrin’s experimental work in order to understand the role that the multiple determination of molecular magnitudes played in his argument for molecular reality. It claims that Perrin used the multiple determination strategy to put forward an exceptionally strong no-coincidence argument to argue for both the correctness of the values for the molecular magnitudes determined and the validity of the auxiliary assumptions upon which the different determinations were based. The historicist approach also allows the identification of the elements responsible for the epistemic strength of Perrin’s no-coincidence argument. (shrink)

This essay proposes a reductive account of robust macro-regularities. On the view proposed, regularities can earn their elite scientific status by featuring in good summaries of restricted regions in the space of physical possibilities: our “modal neighborhoods.” I argue that this view vindicates “nomic foundationalism”, while doing justice to the practice of invoking physically contingent generalizations in higher-level explanations. Moreover, the view suggests an explanation for the particular significance of robust macro-regularities: we rely on summaries of our modal neighborhoods when (...) reasoning hypothetically about “agentially accessible” possibilities. (shrink)

It is commonly thought that Jean Perrin argued for the reality of atoms in the early twentieth century by using what Wesley Salmon calls a “common cause” argument, also known as robustness reasoning. After citing some concerns with this interpretation of Perrin, I offer a different interpretation of Perrin’s work that more closely depicts the details of Perrin’s reasoning in his relevant published writings. I then offer a historical argument that supports this interpretation and discuss the philosophical merits of Perrin’s (...) style of reasoning as I have presented it. I close by showing how my interpretation is distinct from previous interpretations of Perrin’s work. (shrink)

In biomedical measurement, biomarkers are used to achieve reliable prediction of, and useful causal information about patient outcomes while minimizing complexity of measurement, resources, and invasiveness. A biomarker is an assayable metric that discloses the status of a biological process of interest, be it normative, pathophysiological, or in response to intervention. The greatest utility from biomarkers comes from their ability to help clinicians (and researchers) make and evaluate clinical decisions. In this paper we discuss a specific methodological use of clinical (...) biomarkers in pharmacological measurement: Some biomarkers, called ‘surrogate markers’, are used to substitute for a clinically meaningful endpoint corresponding to events and their penultimate risk factors. We confront the reliability of clinical biomarkers that are used to gather information about clinically meaningful endpoints. Our aim is to present a systematic methodology for assessing the reliability of multiple surrogate markers (and biomarkers in general). To do this we draw upon the robustness analysis literature in the philosophy of science and the empirical use of clinical biomarkers. After introducing robustness analysis we present two problems with biomarkers in relation to reliability. Next, we propose an intervention-based robustness methodology for organizing the reliability of biomarkers in general. We propose three relevant conditions for a robust methodology for biomarkers: (R1) Intervention-based demonstration of partial independence of modes: In biomarkers partial independence can be demonstrated through exogenous interventions that modify a process some number of “steps” removed from each of the markers. (R2) Comparison of diverging and converging results across biomarkers: By systematically comparing partially-independent biomarkers we can track under what conditions markers fail to converge in results, and under which conditions they successfully converge. (R3) Information within the context of theory: Through a systematic cross-comparison of the markers we can make causal conclusions as well as eliminate competing theories. We apply our robust methodology to currently developing Alzheimer’s research to show its usefulness for making causal conclusions. (shrink)

La comunidad científica debe acordar cuál es la información esencial que hay que comunicar al retirar un artículo.

Retractions play an important role in research communication by highlighting and explaining how research projects have failed and thereby preventing these mistakes from being repeated. However, the process of retraction and the data it produces is often sparse or incomplete. Drawing on evidence from 2046 retraction records, Quan-Hoang Vuong discusses the emerging trends this data highlights and argues for the need to enforce reporting standards for retractions, as a means of de-stigmatising retraction and rewarding practising integrity in the scholarly record.

Social scientists use many different methods, and there are often substantial disagreements about which method is appropriate for a given research question. In response to this uncertainty about the relative merits of different methods, W. E. B. Du Bois advocated for and applied “methodological triangulation”. This is to use multiple methods simultaneously in the belief that, where one is uncertain about the reliability of any given method, if multiple methods yield the same answer that answer is confirmed more strongly than (...) it could have been by any single method. Against this, methodological purists believe that one should choose a single appropriate method and stick with it. Using tools from voting theory, we show Du Boisian methodological triangulation to be more likely to yield the correct answer than purism, assuming the scientist is subject to some degree of diffidence about the relative merits of the various methods. This holds even when in fact only one of the methods is appropriate for the given research question. (shrink)

Based on a framework that distinguishes several types, roles and functions of values in science, we discuss legitimate applications of values in the validation of computer simulations. We argue that, first, epistemic valuesEpistemic values, such as empirical accuracyAccuracy and coherence with background knowledgeBackground knowledge, have the role to assess the credibilityCredibility of simulation results, whereas, second, cognitive valuesCognitive values, such as comprehensiveness of a conceptual modelConceptual model or easy handling of a numerical model, have the role to assess the usefulness (...) of a model for investigating a hypothesisHypothesis. In both roles, values perform what we call first-order functions. In addition, cognitive values may also serve an auxiliary function by facilitating the assessment of credibility. As for a third type of values, i.e. social valuesSocial values, their legitimate role consists in specifying and weighing epistemic and cognitive values with respect to practical uses of a simulation, which is considered a second-order function. Rational intersubjective agreementAgreement on how to specify and weigh the different values is supposed to ensure objectivity in simulation validation. (shrink)

The aim of this dissertation is to comprehensively study various robustness arguments proposed in the literature from Levins to Lloyd as well as the opposition offered to them and pose enquiry into the degree of epistemic virtue that they provide to the model prediction results with respect to climate science and modeling. Another critical issue that this dissertation strives to examine is that of the actual epistemic notion that is operational when scientists and philosophers appeal to robustness. In attempting to (...) explicate this idea, the discussion turns to arguments provided by Schupbach who completely rejects probabilistic independence in favour of explanatory reasoning, Stegenga and Menon who still see some value in probabilistic independence, and Winsberg who takes applies Schupbach’s to climate science, going beyond models to involve multi-modal evidence. After an exhaustive discussion on these arguments, this dissertation attempts to provide a thorough and updated notion of robustness in climate modeling and climate science. (shrink)

Traditionally, in the literature on robustness analysis objects are classified as genuine phenomena (natural objects, events, and processes) or artifacts (results produced in error). But much of biological measurement requires the manipulation of local experimental conditions in order to produce new effects. These types of intervention-based regularities are neither natural objects nor artifacts; characterizing them as either fails adequately to address key ontological properties as well as their role in scientific practice. It is argued that a new classification, based on (...) methodological considerations, can be useful in order to characterize experimental productions. Experimentally-useful context-sensitive objects are referred to as ‘artefacts’. To show how the new classification works and why it is instructive for scientific practice, two case studies are discussed. First, the puzzle of arsenic-consuming living organisms is analyzed, where under a set of specific experimental conditions a given organism was found to replace phosphorous with arsenic in its DNA. Second, ecological epigenetic measurement is discussed to show the complexity of variant effects in the context of lab, field, and computer measurements. It is argued that the line between artifacts and artefacts is fluid because theoretical, experimental, and practical considerations vary. (shrink)

Roughly, instrumentalism is the view that science is primarily, and should primarily be, an instrument for furthering our practical ends. It has fallen out of favour because historically influential variants of the view, such as logical positivism, suffered from serious defects. -/- In this book, however, Darrell P. Rowbottom develops a new form of instrumentalism, which is more sophisticated and resilient than its predecessors. This position—‘cognitive instrumentalism’—involves three core theses. First, science makes theoretical progress primarily when it furnishes us with (...) more predictive power or understanding concerning observable things. Second, scientific discourse concerning unobservable things should only be taken literally in so far as it involves observable properties or analogies with observable things. Third, scientific claims about unobservable things are probably neither approximately true nor liable to change in such a way as to increase in truthlikeness. -/- There are examples from science throughout the book, and Rowbottom demonstrates at length how cognitive instrumentalism fits with the development of late nineteenth- and early twentieth-century chemistry and physics, and especially atomic theory. Drawing upon this history, Rowbottom also argues that there is a kind of understanding, empirical understanding, which we can achieve without having true, or even approximately true, representations of unobservable things. In closing the book, he sets forth his view on how the distinction between the observable and unobservable may be drawn, and compares cognitive instrumentalism with key contemporary alternatives such as structural realism, constructive empiricism, and semirealism. -/- Overall, this book offers a strong defence of instrumentalism that will be of interest to scholars and students working on the debate about realism in philosophy of science. (shrink)

What are the relevant values to the appraisal of research programs? This question remains hotly debated, as philosophers have recently proposed many lists of values potentially relevant to scientific appraisal. Surprisingly, despite being mentioned in many lists, little attention has been paid to fruitfulness. It is unclear how fruitfulness should be explicated, and whether it has any substantial role in scientific appraisal. In this paper, I argue we should explicate fruitfulness as the capacity to develop of research programs. Moreover, I (...) provide a novel strategy to assess and compare the fruitfulness of programs focused on their research questions and heuristics. To illustrate how this strategy would work, I will discuss a case study, namely the adaptationist program in evolutionary psychology. (shrink)

ABSTRACT There is a new argument form within theoretical biology. This form takes as input competing explanatory models; it yields as output the conclusion that one of these models is more plausible than the others. The driving force for this argument form is an analysis showing that one model exhibits more parametric robustness than its competitors. This article examines these inferences to the more robust explanation, analysing them as variants of inference to the best explanation. The article defines parametric robustness (...) and distinguishes it from more familiar kinds of robustness. The article also argues that parametric robustness is an explanatory virtue not subsumed by more familiar explanatory virtues, and that the plausibility verdicts in the conclusions of inferences to the more robust explanations are best interpreted as guidance for research activity, rather than claims about likely truth. 1Introducing Inference to the More Robust Explanation 2Inference to the More Robust Explanation in the Study of Apoptosis 2.1Regulating apoptosis 2.2Competing models and evidential indecision 2.3Measuring robustness 2.4Robustness as a guide to plausibility 2.5Varieties of robustness 3Inference to the More Robust Explanation as Inference to the Best Explanation 3.1The structure of inference to the best explanation 3.2Parametric robustness as an explanatory virtue rather than an explanandum 3.3Relation of parametric robustness to other explanatory virtues 4Epistemological Significance of Inference to the More Robust Explanation 4.1Plausibility in practice 4.2Plausibility in principle 5Conclusion. (shrink)

There are at least twelve major virtues of good theories: evidential accuracy, causal adequacy, explanatory depth, internal consistency, internal coherence, universal coherence, beauty, simplicity, unification, durability, fruitfulness, and applicability. These virtues are best classified into four classes: evidential, coherential, aesthetic, and diachronic. Each virtue class contains at least three virtues that sequentially follow a repeating pattern of progressive disclosure and expansion. Systematizing the theoretical virtues in this manner clarifies each virtue and suggests how they might have a coordinated and cumulative (...) role in theory formation and evaluation across the disciplines—with allowance for discipline specific modification. An informal and flexible logic of theory choice is in the making here. Evidential accuracy, according to my systematization, is not a largely isolated trait of good theories, as some have made it out to be. Rather, it bears multifaceted relationships, constituting significant epistemic entanglements, with other theoretical virtues. (shrink)

This paper presents a novel fractional-order PID controller tuning strategy based on Bode’s optimal loop shaping which is commonly used for LTI feedback systems. Firstly, the controller parameters are achieved based on flat phase property and Bode’s optimal reference model, so that the controlled system is robust to gain variations and can achieve desirable transient performance according to various control requirements. Then, robustness analysis of the controlled system is carried out to support the results. Furthermore, the parameter setting is analyzed (...) to demonstrate the superiority of the proposed controller. At last, some simulation examples are shown to verify the accuracy and usefulness of the proposed control strategy. The proposed fractional-order PID controller does not have any restriction on the controlled plant, so it can be widely applied on both integer-order and fractional-order systems. (shrink)

Replicability and reproducibility of computational models has been somewhat understudied by “the replication movement.” In this paper, we draw on methodological studies into the replicability of psychological experiments and on the mechanistic account of explanation to analyze the functions of model replications and model reproductions in computational neuroscience. We contend that model replicability, or independent researchers' ability to obtain the same output using original code and data, and model reproducibility, or independent researchers' ability to recreate a model without original code, (...) serve different functions and fail for different reasons. This means that measures designed to improve model replicability may not enhance (and, in some cases, may actually damage) model reproducibility. We claim that although both are undesirable, low model reproducibility poses more of a threat to long-term scientific progress than low model replicability. In our opinion, low model reproducibility stems mostly from authors' omitting to provide crucial information in scientific papers and we stress that sharing all computer code and data is not a solution. Reports of computational studies should remain selective and include all and only relevant bits of code. (shrink)

In the last decade, robustness has been extensively mentioned and discussed in biology as well as in the philosophy of the life sciences. Nevertheless, from both fields, someone has affirmed that this debate has resulted in more semantic confusion than in semantic clearness. Starting from this claim, we wish to offer a sort of prima facie map of the different usages of the term. In this manner we would intend to predispose a sort of “semantic platform” which could be exploited (...) by those who wish to discuss or simply use it. We do this by starting from a core distinction between the robustness of representations, which is a philosophy of science issue, and the representations of robustness, which instead pertains to science. We illustrate our proposal with examples from biology, physics and mathematics. (shrink)

Inference to the Best Explanation (IBE) is widely criticized for being an unreliable form of ampliative inference – partly because the explanatory hypotheses we have considered at a given time may all be false, and partly because there is an asymmetry between the comparative judgment on which an IBE is based and the absolute verdict that IBE is meant to license. In this paper, I present a further reason to doubt the epistemic merits of IBE and argue that it motivates (...) moving to an inferential pattern in which IBE emerges as a degenerate limiting case. Since this inferential pattern is structurally similar to an argumentative strategy known as Inferential Robustness Analysis (IRA), it effectively combines the most attractive features of IBE and IRA into a unified approach to non-deductive inference. (shrink)

In the philosophy of science and epistemology literature, robustness analysis has become an umbrella term that refers to a variety of strategies. One of the main purposes of this paper is to argue that different strategies rely on different criteria for justifications. More specifically, I will claim that: i) robustness analysis differs from de-idealization even though the two concepts have often been conflated in the literature; ii) the comparison of different model frameworks requires different justifications than the comparison of models (...) that differ only for the assumption under test; iii) the replacement of specific assumptions with different ones can encounter specific difficulties in scientific practice. These claims will be supported by a case study in population ecology and a case study in geographical economics. (shrink)

Robustness arguments hold that hypotheses are more likely to be true when they are confirmed by diverse kinds of evidence. Robustness arguments require the confirming evidence to be independent. We identify two kinds of independence appealed to in robustness arguments: ontic independence —when the multiple lines of evidence depend on different materials, assumptions, or theories—and probabilistic independence. Many assume that OI is sufficient for a robustness argument to be warranted. However, we argue that, as typically construed, OI is not a (...) sufficient independence condition for warranting robustness arguments. We show that OI evidence can collectively confirm a hypothesis to a lower degree than individual lines of evidence, contrary to the standard assumption undergirding usual robustness arguments. We employ Bayesian networks to represent the ideal empirical scenario for a robustness argument and a variety of ways in which empirical scenarios can fall short of this ideal. (shrink)

This paper supports the literature which argues that derivational robustness can have epistemic import in highly idealized economic models. The defense is based on a particular example from mathematical economic theory, the dynamic Walrasian general equilibrium model. It is argued that derivational robustness first increased and later decreased the credibility of the Walrasian model. The example demonstrates that derivational robustness correctly describes the practices of a particular group of influential economic theorists and provides support for the arguments of philosophers who (...) have offered a general epistemic justification of such practices. (shrink)

I offer a new argument for the elimination of ‘beliefs’ from cognitive science based on Wimsatt’s concept of robustness and a related concept of fragility. Theoretical entities are robust if multiple independent means of measurement produce invariant results in detecting them. Theoretical entities are fragile when multiple independent means of detecting them produce highly variant results. I argue that sufficiently fragile theoretical entities do not exist. Recent studies in psychology show radical variance between what self-report and non-verbal behaviour indicate about (...) participants’ beliefs. This is evidence that ‘belief’ is fragile, and is thus a strong candidate for elimination. 1 Introduction2 Robustness and Fragility2.1 A historical example of robustness2.2 Fragility and elimination3 The Received View4 Evidence for the Fragility of Belief4.1 Contamination and fragility4.2 Implicit association tests and fragility5 Attempts to Preserve the Belief Category for Cognitive Science5.1 Beliefs and aliefs5.2 Contradictory beliefs5.3 In-between beliefs and the unity assumption5.4 Belief sub-classes5.5 Self-deception6 Alternative Mental States7 Conclusion. (shrink)

Robustness may increase the degree to which the robust result is indirectly confirmed if it is shown to depend on confirmed rather than disconfirmed assumptions. Although increasing the weight with which existing evidence indirectly confirms it in such a case, robustness may also be irrelevant for confirmation, or may even disconfirm. Whether or not it confirms depends on the available data and on what other results have already been established.

It is often argued that inferential role semantics (IRS) entails semantic holism as long as theorists fail to answer the question about which inferences, among the many, are meaning-constitutive. Since analyticity, as truth in virtue of meaning, is a widely dismissed notion in indicating which inferences determine meaning, it seems that holism follows. Semantic holism is often understood as facing problems with the stability of content and many usual explanations of communication. Thus, we should choose between giving up IRS, to (...) avoid these holistic entailments, and defending holism against this charge, to rescue IRS. I try to pursue the second goal by analyzing certain patterns of counterfactual reasoning. Wilfrid Sellars and Robert Brandom claim that, to defend IRS, content-constitutive inferences are those counterfactually robust. While it is difficult to assess the goodness of such a view, it nonetheless entails that counterfactually non-robust inferences (which I call “modally ruled out inferences”) are not content-constitutive. If this is true, and if we take certain remarks about the grasp of concepts on board, there is a way to restrict the scope of the holism entailed by IRS to the extent of reshaping problems with the stability of content. (shrink)

Empirical multiple determination (multiple determination, for short) is the epistemic strategy of establishing the same result by means of multiple and independent procedures. It is an important epistemic strategy praised by both philosophers of science and practicing scientists. Commentators from different contexts have referred to multiple determination as one of the main strategies that researchers use to establish the reliability of their results. Multiple determination has been used to address a variety of problems that arise because of the fallibility of (...) experimental procedures. It is generally believed that being able to establish the same result (or provide evidence for a hypothesis of interest) by means of different and independent procedures is somewhat ‘‘better’’ than doing the same by a single procedure. Despite the heavy appeal to the multiple determination strategy, however, not much philosophical analysis has been provided regarding the grounds on which its epistemic desirability and virtues rest. Not much has been said regarding the structure and rationale underlying arguments which rely on multiple determination, and there is no general agreement regarding the epistemological import of these arguments. In my dissertation, I address these issues. More specifically, my dissertation: a. Provides a conceptual clarification of the epistemic strategy of multiple determination by making evident its differences, in both structure and epistemic import, from other notions and epistemic strategies from which it is often not distinguished in the literature such as robustness, consilience of inductions, variety of evidence, etc. b. Traces the historical and philosophical roots of multiple determination in the 19th century philosophical discussions and scientific developments. Especially, it makes the claim that the emergence of empirical multiple determination as a distinctive epistemic strategy emerged as a response to the scientific and philosophical difficulties facing the atomic and molecular hypotheses of matter and, more generally, the study of unobservable entities, in the end of the 19th century. c. Provides a general conceptual framework for understanding the structure and epistemic import of arguments that rely on the application of the multiple determination strategy in actual scientific research. d. The distinctive feature of my dissertation is that it examines its subject matter from a temporal perspective, by paying close attention to the historical emergence and development of the multiple determination strategy. As such, it also considers the implications of the debates regarding the structure and epistemic import of multiple determination for the relationship between history of science and philosophy of science. (shrink)

Robustness is often presented as a guideline for distinguishing the true or real from mere appearances or artifacts. Most of recent discussions of robustness have focused on the kind of derivational robustness analysis introduced by Levins, while the related but distinct idea of robustness as multiple accessibility, defended by Wimsatt, has received less attention. In this paper, I argue that the latter kind of robustness, when properly understood, can provide justification for ontological commitments. The idea is that we are justified (...) in believing that things studied by science are real insofar as we have robust evidence for them. I develop and analyze this idea in detail, and based on concrete examples show that it plays an important role in science. Finally, I demonstrate how robustness can be used to clarify the debate on scientific realism and to formulate new arguments. (shrink)

Recent literature in philosophy of science has addressed purported notions of explanatory virtues—‘explanatory power’, ‘unification’, and ‘coherence’. In each case, a probabilistic relation between a theory and data is said to measure the power of an explanation, or degree of unification, or degree of coherence. This essay argues that the measures do not capture cases that are paradigms of scientific explanation, that the available psychological evidence indicates that the measures do not capture judgements of explanatory power, and, finally, that the (...) measures do not provide useful methods for selecting hypotheses. 1. Introduction2. Some Proposed Measures of Explanatory Virtues3. Descriptive Inadequacy3.1 Excellent but false explanations3.2 Causal explanation4. Psychological Inadequacy5. Finding the Truth6. Conclusion. (shrink)

The concordance of results that are “robust” across multiple scientific modalities is widely considered to play a critical role in the epistemology of science. But what should we make of those cases where such multimodal evidence is discordant? Jacob Stegenga has recently argued that robustness is “worse than useless” in these cases, suggesting that “different kinds of evidence cannot be combined in a coherent way.” In this article I respond to this critique and illustrate the critical methodological role that robustness (...) plays as an aim of scientific inquiry. (shrink)

Robert Hudson’s book is a contribution to the recent debate on robustness analysis in scientific practice, with a specific focus on the empirical sciences. In this context, robustness analysis is defined as a way to increase the probability of a certain hypothesis by showing that the same result is obtained from several, alternative methods. The rationale underlying this practice is that it would be highly unlikely if different, independent means of observation provided the same wrong outcome.We do not believe in (...) miracles; hence, the probability of the initial hypothesis being true increases if the same result occurs across conditions.Simple as this notion sounds, according to Hudson, the various attempts that have been offered in the literature to formalize it have proved to be unsuccessful. Hudson’s skeptical argument is formulated at the outset of the book and illustrated throughout by means of several episodes from the recent history of science, mainly from physics and biology. Met .. (shrink)

Proponents of evidence-based medicine have argued convincingly for applying this scientific method to medicine. However, the current methodological framework of the EBM movement has recently been called into question, especially in epidemiology and the philosophy of science. The debate has focused on whether the methodology of randomized controlled trials provides the best evidence available. This paper attempts to shift the focus of the debate by arguing that clinical reasoning involves a patchwork of evidential approaches and that the emphasis on evidence (...) hierarchies of methodology fails to lend credence to the common practice of corroboration in medicine. I argue that the strength of evidence lies in the evidence itself, and not the methodology used to obtain that evidence. Ultimately, when it comes to evaluating the effectiveness of medical interventions, it is the evidence obtained from the methodology rather than the methodology that should establish the strength of the evidence. (shrink)

This paper summarizes (in German) recent tendencies in the philosophy of the life sciences.

In Seeing Things, Robert Hudson assesses a common way of arguing about observation reports called "robustness reasoning." Robustness reasoning claims that an observation report is more likely to be true if the report is produced by multiple, independent sources. Seeing Things argues that robustness reasoning lacks the special value it is often claimed to have. Hudson exposes key flaws in various popular philosophical defenses of robustness reasoning. This philosophical critique of robustness is extended by recounting five episodes in the history (...) of science (from experimental microbiology, atomic theory, astrophysics, and astronomy) where robustness reasoning is — or could be claimed to have been — used. Hudson goes on to show that none of these episodes do in fact exhibit robustness reasoning. In this way, the significance of robustness reasoning is rebutted on both philosophical and historical grounds. But the book does more than critique robustness reasoning. It also develops a better defense of the informative value of observation reports. The book concludes by relating insights into the failure of robustness reasoning to a popular approach to scientific realism called "(theoretical) preservationism." Hudson argues that those who defend this approach to realism commit similar errors to those who advocate robustness reasoning. In turn, a new form of realism is formulated and defended. Called "methodological preservationism," it recognizes the fundamental value of naked-eye observation to scientists — and the rest of us. (shrink)

The issue of common method variance and bias in Indonesia still has not gained much attention; even the terminology is less popular, except among psychometric enthusiasts and experts. In fact, the potential for common method variance and bias infiltrating in research results is very high, especially in studies that use a single method, a single source, and concurrent design, which are highly favored by psychological lecturers and researchers in Indonesia. This paper is a critical review, exposing the debate and serious (...) impact regarding common method variance and bias, as well as procedures for detecting, addressing and correcting its effects. The author hoped this paper contributes in filling the gap in the literature, especially in Psychology Research Methodology text books in the Indonesian language, so that psychological researches in Indonesia continue to increase their quality and to have their better place in international publications. (shrink)

The aim of this paper is to develop ideas about robustness analyses. I introduce a form of robustness analysis that I call sufficient parameter robustness, which has been neglected in the literature. I claim that sufficient parameter robustness is different from derivational robustness, the focus of previous research. My purpose is not only to suggest a new taxonomy of robustness, but also to argue that previous authors have concentrated on a narrow sense of robustness analysis, which they have inadequately distinguished (...) from other investigations of models such as sensitivity analysis. (shrink)

Robustness concepts are often invoked to manage two obstacles confronting models of ecological systems: complexity and uncertainty. The intuitive idea is that any result derived from many idealized but credible models is thereby made more reliable or is better confirmed. An appropriate basis for this inference has proven elusive. Here, several representations of robustness analysis are vetted, paying particular attention to complex models of ecosystems and the global climate. The claim that robustness is itself confirmatory because robustness analysis employs a (...) Bayesian variety-of-evidence argument is criticized, but recent overwhelming pessimism about robustness may have a silver lining. (shrink)

Odenbaugh and Alexandrova provide a challenging critique of the epistemic benefits of robustness analysis, singling out for particular criticism the account we articulated in Kuorikoski et al.. Odenbaugh and Alexandrova offer two arguments against the confirmatory value of robustness analysis: robust theorems cannot specify causal mechanisms and models are rarely independent in the way required by robustness analysis. We address Odenbaugh and Alexandrova’s criticisms in order to clarify some of our original arguments and to shed further light on the properties (...) of robustness analysis and its epistemic rationale. (shrink)