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Robustness Analysis

Philosophy of Science 73 (5):730-742 (2006)

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  1. Convergence strategies for theory assessment.Elena Castellani - 2024 - Studies in History and Philosophy of Science Part A 104 (C):78-87.
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  • How to Express Implicit Attitudes.Elmar Unnsteinsson - 2024 - Philosophical Quarterly 74 (1):251-272.
    I argue that what speakers mean or express can be determined by their implicit or unconscious states, rather than explicit or conscious states. Further, on this basis, I show that the sincerity conditions for utterances can also be fixed by implicit states. This is a surprising result which goes against common assumptions about speech acts and sincerity. Roughly, I argue that the result is implied by two plausible and independent theories of the metaphysics of speaker meaning and, further, that this (...)
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  • Multi-model approaches to phylogenetics: Implications for idealization.Aja Watkins - 2021 - Studies in History and Philosophy of Science Part A 90 (C):285-297.
    Phylogenetic models traditionally represent the history of life as having a strictly-branching tree structure. However, it is becoming increasingly clear that the history of life is often not strictly-branching; lateral gene transfer, endosymbiosis, and hybridization, for example, can all produce lateral branching events. There is thus motivation to allow phylogenetic models to have a reticulate structure. One proposal involves the reconciliation of genealogical discordance. Briefly, this method uses patterns of disagreement – discordance – between trees of different genes to add (...)
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  • The epistemic value of independent lies: false analogies and equivocations.Margherita Harris - 2021 - Synthese 199 (5-6):14577-14597.
    Here I critically assess an argument put forward by Kuorikoski et al. (Br J Philos Sci, 61(3):541–567, 2010) for the epistemic import of model-based robustness analysis. I show that this argument is not sound since the sort of probabilistic independence on which it relies is unfeasible. By revising the notion of probabilistic independence imposed on the models’ results, I introduce a prima-facie more plausible argument. However, despite this prima-facie plausibility, I show that even this new argument is unsound in most (...)
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  • Robustness and Modularity.Trey Boone - forthcoming - British Journal for the Philosophy of Science.
    Functional robustness refers to a system’s ability to maintain a function in the face of perturbations to the causal structures that support performance of that function. Modularity, a crucial element of standard methods of causal inference and difference-making accounts of causation, refers to the independent manipulability of causal relationships within a system. Functional robustness appears to be at odds with modularity. If a function is maintained despite manipulation of some causal structure that supports that function, then the relationship between that (...)
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  • On the Exploratory Function of Agent-Based Modeling.Meinard Kuhlmann - 2021 - Perspectives on Science 29 (4):510-536.
    Agent-based models derive the behavior of artificial socio-economic entities computationally from the actions of a large number of agents. One objection is that highly idealized ABMs fail to represent the real world in any reasonable sense. Another objection is that they at best show how observed patterns may have come about, because simulations are easy to produce and there is no evidence that this is really what happens. Moreover, different models may well yield the same result. I will rebut these (...)
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  • Robustness, Reliability, and Overdetermination (1981).William C. Wimsatt - 2012 - In Lena Soler (ed.), Characterizing the robustness of science: after the practice turn in philosophy of science. New York: Springer Verlag. pp. 61-78.
    The use of multiple means of determination to “triangulate” on the existence and character of a common phenomenon, object, or result has had a long tradition in science but has seldom been a matter of primary focus. As with many traditions, it is traceable to Aristotle, who valued having multiple explanations of a phenomenon, and it may also be involved in his distinction between special objects of sense and common sensibles. It is implicit though not emphasized in the distinction between (...)
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  • Multiple-Models Juxtaposition and Trade-Offs among Modeling Desiderata.Yoshinari Yoshida - 2021 - Philosophy of Science 88 (1):103-123.
    This article offers a characterization of what I call multiple-models juxtaposition, a strategy for managing trade-offs among modeling desiderata. MMJ displays models of distinct phenomena to...
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  • Argumentative landscapes: the function of models in social epistemology.N. Emrah Aydinonat, Samuli Reijula & Petri Ylikoski - 2021 - Synthese 199 (1-2):369-395.
    We argue that the appraisal of models in social epistemology requires conceiving of them as argumentative devices, taking into account the argumentative context and adopting a family-of-models perspective. We draw up such an account and show how it makes it easier to see the value and limits of the use of models in social epistemology. To illustrate our points, we document and explicate the argumentative role of epistemic landscape models in social epistemology and highlight their limitations. We also claim that (...)
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  • Modeling in Biology: looking backward and looking forward.Steven Hecht Orzack & Brian McLoone - 2019 - Studia Metodologiczne 39.
    Understanding modeling in biology requires understanding how biology is organized as a discipline and how this organization influences the research practices of biologists. Biology includes a wide range of sub-disciplines, such as cell biology, population biology, evolutionary biology, molecular biology, and systems biology among others. Biologists in sub-disciplines such as cell, molecular, and systems biology believe that the use of a few experimental models allows them to discover biological universals, whereas biologists in sub-disciplines such as ecology and evolutionary biology believe (...)
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  • (1 other version)Theory-choice, transient diversity and the efficiency of scientific inquiry.AnneMarie Borg, Daniel Frey, Dunja Šešelja & Christian Straßer - 2019 - European Journal for Philosophy of Science 9 (2):26.
    Recent studies of scientific interaction based on agent-based models suggest that a crucial factor conducive to efficient inquiry is what Zollman has dubbed ‘transient diversity’. It signifies a process in which a community engages in parallel exploration of rivaling theories lasting sufficiently long for the community to identify the best theory and to converge on it. But what exactly generates transient diversity? And is transient diversity a decisive factor when it comes to the efficiency of inquiry? In this paper we (...)
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  • Evolutionary Explanations of Simple Communication: Signalling Games and Their Models.Travis LaCroix - 2020 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 51 (1):19-43.
    This paper applies the theoretical criteria laid out by D’Arms et al. to various aspects of evolutionary models of signalling. The question that D’Arms et al. seek to answer can be formulated as follows: Are the models that we use to explain the phenomena in question conceptually adequate? The conceptual adequacy question relates the formal aspects of the model to those aspects of the natural world that the model is supposed to capture. Moreover, this paper extends the analysis of D’Arms (...)
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  • Evidence amalgamation in the sciences: an introduction.Roland Poellinger, Jürgen Landes & Samuel C. Fletcher - 2019 - Synthese 196 (8):3163-3188.
    Amalgamating evidence from heterogeneous sources and across levels of inquiry is becoming increasingly important in many pure and applied sciences. This special issue provides a forum for researchers from diverse scientific and philosophical perspectives to discuss evidence amalgamation, its methodologies, its history, its pitfalls, and its potential. We situate the contributions therein within six themes from the broad literature on this subject: the variety-of-evidence thesis, the philosophy of meta-analysis, the role of robustness/sensitivity analysis for evidence amalgamation, its bearing on questions (...)
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  • Linguistics and the explanatory economy.Gabe Dupre - 2019 - Synthese 199 (Suppl 1):177-219.
    I present a novel, collaborative, methodology for linguistics: what I call the ‘explanatory economy’. According to this picture, multiple models/theories are evaluated based on the extent to which they complement one another with respect to data coverage. I show how this model can resolve a long-standing worry about the methodology of generative linguistics: that by creating too much distance between data and theory, the empirical credentials of this research program are tarnished. I provide justifications of such methodologically central distinctions as (...)
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  • Robust realism for the life sciences.Markus I. Eronen - 2019 - Synthese 196 (6):2341-2354.
    Although scientific realism is the default position in the life sciences, philosophical accounts of realism are geared towards physics and run into trouble when applied to fields such as biology or neuroscience. In this paper, I formulate a new robustness-based version of entity realism, and show that it provides a plausible account of realism for the life sciences that is also continuous with scientific practice. It is based on the idea that if there are several independent ways of measuring, detecting (...)
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  • To Assist or Not to Assist? Assessing the Potential Moral Costs of Humanitarian Intervention in Nature.Kyle Johannsen - 2020 - Environmental Values 29 (1):29-45.
    In light of the extent of wild animal suffering, some philosophers have adopted the view that we should cautiously assist wild animals on a large scale. Recently, their view has come under criticism. According to one objection, even cautious intervention is unjustified because fallibility is allegedly intractable. By contrast, a second objection states that we should abandon caution and intentionally destroy habitat in order to prevent wild animals from reproducing. In my paper, I argue that intentional habitat destruction is wrong (...)
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  • (1 other version)Theory-choice, transient diversity and the efficiency of scientific inquiry.AnneMarie Borg, Daniel Frey, Dunja Šešelja & Christian Straßer - 2019 - European Journal for Philosophy of Science 9 (2):26.
    Recent studies of scientific interaction based on agent-based models suggest that a crucial factor conducive to efficient inquiry is what Zollman has dubbed ‘transient diversity’. It signifies a process in which a community engages in parallel exploration of rivaling theories lasting sufficiently long for the community to identify the best theory and to converge on it. But what exactly generates transient diversity? And is transient diversity a decisive factor when it comes to the efficiency of inquiry? In this paper we (...)
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  • Evaluating Formal Models of Science.Michael Thicke - 2020 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 51 (2):315-335.
    This paper presents an account of how to evaluate formal models of science: models and simulations in social epistemology designed to draw normative conclusions about the social structure of scientific research. I argue that such models should be evaluated according to their representational and predictive accuracy. Using these criteria and comparisons with familiar models from science, I argue that most formal models of science are incapable of supporting normative conclusions.
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  • Microbes, mathematics, and models.Maureen A. O'Malley & Emily C. Parke - 2018 - Studies in History and Philosophy of Science Part A 72:1-10.
    Microbial model systems have a long history of fruitful use in fields that include evolution and ecology. In order to develop further insight into modelling practice, we examine how the competitive exclusion and coexistence of competing species have been modelled mathematically and materially over the course of a long research history. In particular, we investigate how microbial models of these dynamics interact with mathematical or computational models of the same phenomena. Our cases illuminate the ways in which microbial systems and (...)
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  • Two Senses of Experimental Robustness: Result Robustness and Procedure Robustness.Koray Karaca - 2022 - British Journal for the Philosophy of Science 73 (1):279-298.
    In the philosophical literature concerning scientific experimentation, the notion of robustness has been solely discussed in relation to experimental results. In this paper, I propose a novel sense of experimental robustness that applies to experimental procedures. I call the foregoing sense of robustness procedure robustness and characterize it as the capacity of an experimental procedure to maintain its intended function invariant during the experimental process despite possible variations in its inputs. I argue that PR is a precondition for what I (...)
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  • Systematizing the theoretical virtues.Michael N. Keas - 2017 - Synthese 1 (6):1-33.
    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 (...)
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  • Wild Animal Suffering is Intractable.Nicolas Delon & Duncan Purves - 2018 - Journal of Agricultural and Environmental Ethics 31 (2):239-260.
    Most people believe that suffering is intrinsically bad. In conjunction with facts about our world and plausible moral principles, this yields a pro tanto obligation to reduce suffering. This is the intuitive starting point for the moral argument in favor of interventions to prevent wild animal suffering. If we accept the moral principle that we ought, pro tanto, to reduce the suffering of all sentient creatures, and we recognize the prevalence of suffering in the wild, then we seem committed to (...)
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  • Models in the Geosciences.Alisa Bokulich & Naomi Oreskes - 2017 - In Magnani Lorenzo & Bertolotti Tommaso Wayne (eds.), Springer Handbook of Model-Based Science. Springer. pp. 891-911.
    The geosciences include a wide spectrum of disciplines ranging from paleontology to climate science, and involve studies of a vast range of spatial and temporal scales, from the deep-time history of microbial life to the future of a system no less immense and complex than the entire Earth. Modeling is thus a central and indispensable tool across the geosciences. Here, we review both the history and current state of model-based inquiry in the geosciences. Research in these fields makes use of (...)
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  • Modeling complexity: cognitive constraints and computational model-building in integrative systems biology.Miles MacLeod & Nancy J. Nersessian - 2018 - History and Philosophy of the Life Sciences 40 (1):17.
    Modern integrative systems biology defines itself by the complexity of the problems it takes on through computational modeling and simulation. However in integrative systems biology computers do not solve problems alone. Problem solving depends as ever on human cognitive resources. Current philosophical accounts hint at their importance, but it remains to be understood what roles human cognition plays in computational modeling. In this paper we focus on practices through which modelers in systems biology use computational simulation and other tools to (...)
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  • Robustness and Independent Evidence.Jacob Stegenga & Tarun Menon - 2017 - Philosophy of Science 84 (3):414-435.
    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 (...)
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  • Unification Strategies in Cognitive Science.Marcin Miłkowski - 2016 - Studies in Logic, Grammar and Rhetoric 48 (1):13–33.
    Cognitive science is an interdisciplinary conglomerate of various research fields and disciplines, which increases the risk of fragmentation of cognitive theories. However, while most previous work has focused on theoretical integration, some kinds of integration may turn out to be monstrous, or result in superficially lumped and unrelated bodies of knowledge. In this paper, I distinguish theoretical integration from theoretical unification, and propose some analyses of theoretical unification dimensions. Moreover, two research strategies that are supposed to lead to unification are (...)
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  • When Expert Disagreement Supports the Consensus.Finnur Dellsén - 2017 - Australasian Journal of Philosophy 96 (1):142-156.
    It is often suggested that disagreement among scientific experts is a reason not to trust those experts, even about matters on which they are in agreement. In direct opposition to this view, I argue here that the very fact that there is disagreement among experts on a given issue provides a positive reason for non-experts to trust that the experts really are justified in their attitudes towards consensus theories. I show how this line of thought can be spelled out in (...)
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  • (1 other version)Computer models and the evidence of anthropogenic climate change: An epistemology of variety-of-evidence inferences and robustness analysis.Martin Vezer - 2016 - Computer Models and the Evidence of Anthropogenic Climate Change: An Epistemology of Variety-of-Evidence Inferences and Robustness Analysis MA Vezér Studies in History and Philosophy of Science 56:95-102.
    To study climate change, scientists employ computer models, which approximate target systems with various levels of skill. Given the imperfection of climate models, how do scientists use simulations to generate knowledge about the causes of observed climate change? Addressing a similar question in the context of biological modelling, Levins (1966) proposed an account grounded in robustness analysis. Recent philosophical discussions dispute the confirmatory power of robustness, raising the question of how the results of computer modelling studies contribute to the body (...)
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  • Who is a Modeler?Michael Weisberg - 2007 - British Journal for the Philosophy of Science 58 (2):207-233.
    Many standard philosophical accounts of scientific practice fail to distinguish between modeling and other types of theory construction. This failure is unfortunate because there are important contrasts among the goals, procedures, and representations employed by modelers and other kinds of theorists. We can see some of these differences intuitively when we reflect on the methods of theorists such as Vito Volterra and Linus Pauling on the one hand, and Charles Darwin and Dimitri Mendeleev on the other. Much of Volterra's and (...)
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  • Robustness Analysis as Explanatory Reasoning.Jonah N. Schupbach - 2018 - British Journal for the Philosophy of Science 69 (1):275-300.
    When scientists seek further confirmation of their results, they often attempt to duplicate the results using diverse means. To the extent that they are successful in doing so, their results are said to be robust. This paper investigates the logic of such "robustness analysis" [RA]. The most important and challenging question an account of RA can answer is what sense of evidential diversity is involved in RAs. I argue that prevailing formal explications of such diversity are unsatisfactory. I propose a (...)
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  • What good are abstract and what-if models? Lessons from the Gaïa hypothesis.Sébastien Dutreuil - 2014 - History and Philosophy of the Life Sciences 36 (1):16-41.
    This article on the epistemology of computational models stems from an analysis of the Gaia hypothesis (GH). It begins with James Kirchner’s criticisms of the central computational model of GH: Daisyworld. Among other things, the model has been criticized for being too abstract, describing fictional entities (fictive daisies on an imaginary planet) and trying to answer counterfactual (what-if) questions (how would a planet look like if life had no influence on it?). For these reasons the model has been considered not (...)
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  • Robustness and reality.Markus I. Eronen - 2015 - Synthese 192 (12):3961-3977.
    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 (...)
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  • I modelli in economia.Alessandra Basso & Caterina Marchionni - 2015 - Aphex 11.
    The paper reviews the philosophical literature on the epistemology of modelling in contemporary economics. In particular, it focuses on open questions concerning the epistemic role of models, the validity of inferences from the models to the world, and the legitimacy of their use for purposes of explanation, prediction and intervention.
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  • External representations and scientific understanding.Jaakko Kuorikoski & Petri Ylikoski - 2015 - Synthese 192 (12):3817-3837.
    This paper provides an inferentialist account of model-based understanding by combining a counterfactual account of explanation and an inferentialist account of representation with a view of modeling as extended cognition. This account makes it understandable how the manipulation of surrogate systems like models can provide genuinely new empirical understanding about the world. Similarly, the account provides an answer to the question how models, that always incorporate assumptions that are literally untrue of the model target, can still provide factive explanations. Finally, (...)
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  • Using Multiple Means of Determination.Jutta Schickore & Klodian Coko - 2013 - International Studies in the Philosophy of Science 27 (3):295-313.
    This article examines a metaphilosophical issue, namely existing disagreements in philosophy of science about the significance of using multiple means of determination in scientific practice. We argue that this disagreement can, in part, be resolved by separating different questions that can be asked about the use of multiple means of determination, including the following: what can be concluded from the convergence of data or the convergence of claims about phenomena? Are the conclusions drawn from the convergence of data and of (...)
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  • Reengineering the Darwinian Sciences in Social Context.William C. Wimsatt - 2006 - Biological Theory 1 (4):341-342.
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  • Robustness and sensitivity of biological models.Jani Raerinne - 2013 - Philosophical Studies 166 (2):285-303.
    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 (...)
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  • Feminist implications of model-based science.Angela Potochnik - 2012 - Studies in History and Philosophy of Science Part A 43 (2):383-389.
    Recent philosophy of science has witnessed a shift in focus, in that significantly more consideration is given to how scientists employ models. Attending to the role of models in scientific practice leads to new questions about the representational roles of models, the purpose of idealizations, why multiple models are used for the same phenomenon, and many more besides. In this paper, I suggest that these themes resonate with central topics in feminist epistemology, in particular prominent versions of feminist empiricism, and (...)
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  • Robust! -- Handle with care.Wybo Houkes & Krist Vaesen - 2012 - Philosophy of Science 79 (3):1-20.
    Michael Weisberg has argued that robustness analysis is useful in evaluating both scientific models and their implications and that robustness analysis comes in three types that share their form and aim. We argue for three cautionary claims regarding Weisberg's reconstruction: robustness analysis may be of limited or no value in evaluating models and their implications; the unificatory reconstruction conceals that the three types of robustness differ in form and role; there is no confluence of types of robustness. We illustrate our (...)
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  • Pluralistic physicalism and the causal exclusion argument.Markus I. Eronen - 2012 - European Journal for Philosophy of Science 2 (2):219-232.
    There is a growing consensus among philosophers of science that scientific endeavors of understanding the human mind or the brain exhibit explanatory pluralism. Relatedly, several philosophers have in recent years defended an interventionist approach to causation that leads to a kind of causal pluralism. In this paper, I explore the consequences of these recent developments in philosophy of science for some of the central debates in philosophy of mind. First, I argue that if we adopt explanatory pluralism and the interventionist (...)
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  • Confirmation and Robustness of Climate Models.Elisabeth A. Lloyd - 2010 - Philosophy of Science 77 (5):971–984.
    Recent philosophical attention to climate models has highlighted their weaknesses and uncertainties. Here I address the ways that models gain support through observational data. I review examples of model fit, variety of evidence, and independent support for aspects of the models, contrasting my analysis with that of other philosophers. I also investigate model robustness, which often emerges when comparing climate models simulating the same time period or set of conditions. Starting from Michael Weisberg’s analysis of robustness, I conclude that his (...)
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  • Three Kinds of Idealization.Michael Weisberg - 2007 - Journal of Philosophy 104 (12):639-659.
    Philosophers of science increasingly recognize the importance of idealization: the intentional introduction of distortion into scientific theories. Yet this recognition has not yielded consensus about the nature of idealization. e literature of the past thirty years contains disparate characterizations and justifications, but little evidence of convergence towards a common position.
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  • Going Outside the Model: Robustness Analysis and Experimental Science.Michael Trevor Bycroft - 2009 - Spontaneous Generations 3 (1):123-141.
    In 1966 the population biologist Richard Levins gave a forceful and in?uential defence of a method called “robustness analysis” (RA). RA is a way of assessing the result of a model by showing that different but related models give the same result. As Levins put it, “our truth is the intersection of independent lies” (1966, 423). Steven Orzack and Elliott Sober (1993) responded with an equally forceful critique of this method, concluding that the idea of robustness “lacks proper de?nition and (...)
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  • Determinism, predictability and open-ended evolution: lessons from computational emergence.Philippe Huneman - 2012 - Synthese 185 (2):195-214.
    Among many properties distinguishing emergence, such as novelty, irreducibility and unpredictability, computational accounts of emergence in terms of computational incompressibility aim first at making sense of such unpredictability. Those accounts prove to be more objective than usual accounts in terms of levels of mereology, which often face objections of being too epistemic. The present paper defends computational accounts against some objections, and develops what such notions bring to the usual idea of unpredictability. I distinguish the objective unpredictability, compatible with determinism (...)
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  • (1 other version)Prediction in selectionist evolutionary theory.Rasmus Gr⊘Nfeldt Winther - 2009 - Philosophy of Science 76 (5):889-901.
    Selectionist evolutionary theory has often been faulted for not making novel predictions that are surprising, risky, and correct. I argue that it in fact exhibits the theoretical virtue of predictive capacity in addition to two other virtues: explanatory unification and model fitting. Two case studies show the predictive capacity of selectionist evolutionary theory: parallel evolutionary change in E. coli, and the origin of eukaryotic cells through endosymbiosis.
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  • On the dangers of making scientific models ontologically independent: Taking Richard Levins' warnings seriously.Rasmus Grønfeldt Winther - 2006 - Biology and Philosophy 21 (5):703-724.
    Levins and Lewontin have contributed significantly to our philosophical understanding of the structures, processes, and purposes of biological mathematical theorizing and modeling. Here I explore their separate and joint pleas to avoid making abstract and ideal scientific models ontologically independent by confusing or conflating our scientific models and the world. I differentiate two views of theorizing and modeling, orthodox and dialectical, in order to examine Levins and Lewontin’s, among others, advocacy of the latter view. I compare the positions of these (...)
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  • Aggregate, composed, and evolved systems: Reductionistic heuristics as means to more holistic theories. [REVIEW]William C. Wimsatt - 2006 - Biology and Philosophy 21 (5):667-702.
    Richard Levins’ distinction between aggregate, composed and evolved systems acquires new significance as we recognize the importance of mechanistic explanation. Criteria for aggregativity provide limiting cases for absence of organization, so through their failure, can provide rich detectors for organizational properties. I explore the use of failures of aggregativity for the analysis of mechanistic systems in diverse contexts. Aggregativity appears theoretically desireable, but we are easily fooled. It may be exaggerated through approximation, conditions of derivation, and extrapolating from some conditions (...)
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  • Robustness Analysis and Hubble Tension.Marco Forgione - manuscript
    The paper presents and discusses the Hubble tension with respect to recent results in cosmology. I shall argue that the measurements from the James Webb Space Telescope and TRGB stars calibrations allow us to infer that the estimates of H0 with late universe methods are robust. Building on from robustness analysis, I conclude that the resolution of the tension cannot be expected to come from new systematics, but rather from new physics.
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  • Independent evidence in multi-messenger astrophysics.Jamee Elder - 2024 - Studies in History and Philosophy of Science Part A 104 (C):119-129.
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  • Pluralizing measurement: Physical geodesy's measurement problem and its resolution.Miguel Ohnesorge - 2022 - Studies in History and Philosophy of Science Part A 96 (C):51-67.
    Derived measurements involve problems of coordination. Conducting them often requires detailed theoretical assumptions about their target, while such assumptions can lack sources of evidence that are independent from these very measurements. In this paper, I defend two claims about problems of coordination. I motivate both by a novel case study on a central measurement problem in the history of physical geodesy: the determination of the earth's ellipticity. First, I argue that the severity of problems of coordination varies according to scientists' (...)
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