Model Pluralism

2019 ◽  
Vol 50 (2) ◽  
pp. 91-114 ◽  
Author(s):  
Walter Veit

This paper introduces and defends an account of model-based science that I dub model pluralism. I argue that despite a growing awareness in the philosophy of science literature of the multiplicity, diversity, and richness of models and modeling practices, more radical conclusions follow from this recognition than have previously been inferred. Going against the tendency within the literature to generalize from single models, I explicate and defend the following two core theses: (i) any successful analysis of models must target sets of models, their multiplicity of functions within science, and their scientific context and history and (ii) for almost any aspect x of phenomenon y, scientists require multiple models to achieve scientific goal z.

Author(s):  
Lauri Koskela ◽  
Ehud Kroll

AbstractThe original ideas on design abduction, inspired by treatments in philosophy of science, had a narrow conception on how novelty emerges in design, when looked at in terms of logic. The authors have previously presented a re-proposed notion of abduction in design, taking the differences between science and design into account. Now, in this article, the invention of the airplane by the Wright brothers is analyzed as a retrospective case study. Key parts of the re-proposed notion of design abduction are demonstrated, and two new types of design abduction are identified, namely strategic abduction and dynamic abduction. Perhaps even more importantly, a new hypothesis on the cognitive basis of design abduction is reached. While the importance of model-based abduction (and reasoning) is confirmed, the case also pinpoints the central role of verbalization and discussion in supporting design reasoning in general and especially abduction. All in all, it seems that an improved understanding of design abduction and its cognitive basis would be instrumental in promoting more effective and efficient designing.


Erkenntnis ◽  
2021 ◽  
Author(s):  
Nicholas Emmerson

AbstractRecent years have seen growing interest in modifying interventionist accounts of causal explanation in order to characterise noncausal explanation. However, one surprising element of such accounts is that they have typically jettisoned the core feature of interventionism: interventions. Indeed, the prevailing opinion within the philosophy of science literature suggests that interventions exclusively demarcate causal relationships. This position is so prevalent that, until now, no one has even thought to name it. We call it “intervention puritanism”. In this paper, we mount the first sustained defence of the idea that there are distinctively noncausal explanations which can be characterized in terms of possible interventions; and thus, argue that I-puritanism is false. We call the resultant position “intervention liberalism” (I-liberalism, for short). While many have followed Woodward (Making Things Happen: A Theory of Causal Explanation, Oxford University Press, Oxford, 2003) in committing to I-pluralism, we trace support for I-liberalism back to the work of Kim (in: Kim (ed) Supervenience and mind, Cambridge University Press, Cambridge, 1974/1993). Furthermore, we analyse two recent sources of scepticism regarding I-liberalism: debate surrounding mechanistic constitution; and attempts to provide a monistic account of explanation. We show that neither literature provides compelling reasons for adopting I-puritanism. Finally, we present a novel taxonomy of available positions upon the role of possible interventions in explanation: weak causal imperialism; strong causal imperialism; monist intervention puritanism; pluralist intervention puritanism; monist intervention liberalism; and finally, the specific position defended in this paper, pluralist intervention liberalism.


Author(s):  
Douglas W. Heinrichs

Current thinking in medical ethics posits that treatment decisions should result from negotiation between clinician and patient as autonomous agents. However the view of science that underlies most thinking about evidence in medicine encourages the belief that in principle optimal evi-dence-based judgment as to best treatments can be reached by the clinician apart from such ne-gotiation, reducing negotiation to a sham process. A model-based notion of science, derived from a naturalistic philosophy of science, argues that the process of predicting optimal treatment re-quires consideration of a patient’s goals, and thus requires ongoing negotiations with the patient. Hence values are integral to the scientific process, not something extra-scientific that must be reconciled with it. From this perspective the clinician’s activity becomes one with scientific method rather than an ill-defined, and typically undervalued, art.


Author(s):  
David Herman

This chapter considers formal models of narrative and the nature of the theory of narrative. After discussing the diachronic and synchronic approaches to investigating the role of formal models in narrative analysis, the chapter looks at those ideas about models and modeling as a kind of bridge between humanistic and technoscientific discourse. It then evaluates descriptive and functional classifications of models, along with a range of perspectives on mathematical models and modeling. It also presents a case study in metanarratology, with a particular focus on modeling practices that have been brought to bear on focalization. It also analyzes some instances of the confluence of the formal study of narrative and mathematics, including the use of permutation groups, as well as the synergy between mathematically based theories of structural linguistics and early work on story grammars.


Author(s):  
Inmaculada de Melo-Martín ◽  
Kristen Intemann

This chapter assesses whether focusing on rules of engagement for fruitful discussions about competing scientific views provides a good strategy for reliably identifying normatively inappropriate dissent (NID). It discusses some of the rules for effective criticism dominant in the philosophy of science literature: shared standards, uptake, and expertise. It shows that although all these criteria appear eminently reasonable as requirements for transformative criticism, what they actually involve is not straightforward. Some of the interpretations of these criteria are likely to identify as inappropriate dissent that is actually epistemically valuable, while other interpretations of these criteria would fail to pinpoint the very cases of dissent that some consider paradigm cases of NID.


2019 ◽  
Vol 9 (2) ◽  
pp. 115 ◽  
Author(s):  
Julia Mierdel ◽  
Franz X. Bogner

As effective methods to foster students’ understanding of scientific models in science education are needed, increased reflection on thinking about models is regarded as a relevant competence associated with scientific literacy. Our study focuses on the influence of model-based approaches (modeling vs. model viewing) in an out-of-school laboratory module on the students’ understanding of scientific models. A mixed method design examines three subsections of the construct: (1) students’ reasoning about multiple models in science, (2) students’ understanding of models as exact replicas, and (3) students’ understanding of the changing nature of models. There were 293 ninth graders from Bavarian grammar schools that participated in our hands-on module using creative model-based tasks. An open-ended test item evaluated the students’ understanding of “multiple models” (MM). We defined five categories with a majority of students arguing that the individuality of DNA structure leads to various DNA models (modelers = 36.3%, model viewers = 41.1%). Additionally, when applying two subscales of the quantitative instrument Students’ Understanding of Models in Science (SUMS) at three testing points (before, after, and delayed-after participation), a short- and mid-term decrease for the subscale “models as exact replicas” (ER) appeared, while mean scores increased short- and mid-term for the subscale “the changing nature of models” (CNM). Despite the lack of differences between the two approaches, a positive impact of model-based learning on students’ understanding of scientific models was observed.


Conceptus ◽  
2009 ◽  
Vol 38 (93) ◽  
Author(s):  
Jan Radler

SummaryErnst Topitsch’s analysis of world views is presented. His explanatory model consists of an elaborated projection-reflection-scheme. It is argued that the projection is an abductive inference. As a consequence Topitsch’s analysis of world views can be linked to recent developments in the philosophy of science. Finally the question is considered whether the projection can be interpreted as an inference to the best explanation. This is denied because an inference to the best explanation roots in a scientific context, whereas Topitsch’s (abductive) projection obviously does not.


2019 ◽  
Author(s):  
Jonas M B Haslbeck ◽  
Oisín Ryan ◽  
Donald Robinaugh ◽  
Lourens Waldorp ◽  
Denny Borsboom

Over the past decade there has been a surge of empirical research investigating mental disorders as complex systems. In this paper, we investigate how to best make use of this growing body of empirical research and move the field toward its fundamental aims of explaining, predicting, and controlling psychopathology. We first review the contemporary philosophy of science literature on scientific theories and argue that fully achieving the aims of explanation, prediction, and control requires that we construct formal theories of mental disorders: theories expressed in the language of mathematics or a computational programming language. We then investigate three routes by which one can use empirical findings (i.e., data models) to construct formal theories: (a) using data models themselves as formal theories, (b) using data models to infer formal theories, and (c) comparing empirical data models to theory-implied data models in order to evaluate and refine an existing formal theory. We argue that the third approach is the most promising path forward. We conclude by introducing the Abductive Formal Theory Construction (AFTC) framework, informed by both our review of philosophy of science and our methodological investigation. We argue that this approach provides a clear and promising way forward for using empirical research to inform the generation, development, and testing of formal theories both in the domain of psychopathology and in the broader field of psychological science.


Author(s):  
Ronald N. Giere

Naturalized philosophy of science is part of a general programme of naturalism in philosophy. Naturalists reject all forms of supernaturalism, holding that reality, including human life and culture, is exhausted by what exists in the causal order of nature. Naturalists also reject any claims to a priori knowledge, including that of principles of inference, holding instead that all knowledge derives from human interactions with the natural world. Philosophically, naturalists identify most closely with empiricism or pragmatism. David Hume was a naturalist. So was John Dewey. The logical empiricists were naturalists regarding fundamental ontological categories such as space, time and causality, but non-naturalists about scientific inference, which they came to regard as a branch of logic. Most naturalists now dismiss searches for ’philosophical foundations’ of the special sciences, treating the basic principles of any science as part of scientific theory itself. The main objection to naturalism has been at the level of general methodological principles, particularly those regarding scientific inference. Here non-naturalists object that, being limited to ’describing’ how science is in fact practised, naturalists cannot provide norms for legitimate scientific inferences. And providing such norms is held to be one of the main goals of the philosophy of science. Naturalists reply that the only norms required for science are those connecting specific means with the assumed goals of research. These connections can be established only through further scientific research. And the choice of goals is, for naturalists, not a scientific question but a matter of practical choice guided by an empirical understanding of what can in fact be achieved. Among naturalists, the main differences concern the relative importance of various aspects of the practice of science. These aspects exist at different levels: neurological, biological, psychological, personal, computational, methodological, social and cultural. Each of these levels has its champions among contemporary naturalists, some insisting that everything ultimately be reduced to their favourite level. Perhaps the wisest approach is to allow that influences at all levels are operative in any scientific context, while admitting that some influences may be more important than others in particular cases, depending on what one seeks to understand. There may be no simple, one-level, naturalistic theory of science.


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