Matching Items (7)
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- All Subjects: Science--Philosophy
- All Subjects: developmental evolution
- Creators: Creath, Richard
Description
This is a study of scientific realism, and of the extent to which it is undermined by objections that have been raised by advocates of various forms of antirealism. I seek to develop and present a version of scientific realism that improves on past formulations, and then to show that standard antirealist arguments against it do not succeed. In this paper, I will first present my formulation of scientific realism, which conceives of theories as model-based and as fundamentally non-linguistic. I advocate an epistemic position that accords with indirect realism, and I review and assess the threat posed by theses of underdetermination. Next, I review and discuss three important views: the antirealist constructivist view of Thomas Kuhn, the realist view of Norwood Hanson, and the antirealist constructive empiricist view of Bas van Fraassen. I find merits and flaws in all three views. In the course of those discussions, I develop the theme that antirealists' arguments generally depend on assumptions that are open to question, especially from the perspective of the version of realism I advocate. I further argue that these antirealist views are undermined by their own tacit appeals to realism.
ContributorsNovack, Alexander Dion (Author) / Armendt, Brad (Thesis advisor) / Creath, Richard (Committee member) / French, Peter (Committee member) / Arizona State University (Publisher)
Created2013
Description
The present essay addresses the epistemic difficulties involved in achieving consensus with respect to the Hayek-Keynes debate. In particular, it is argued that the debate cannot be settled on the basis of the observable evidence; or, more precisely, that the empirical implications of the theories of Hayek and Keynes are such that, regardless of what is observed, both of the theories can be interpreted as true, or at least, not falsified. Regardless of the evidence, both Hayek and Keynes can be interpreted as right. The underdetermination of theories by evidence is an old and ubiquitous problem in science. The present essay makes explicit the respects in which the empirical evidence underdetermines the choice between the theories of Hayek and Keynes. In particular, it is argued both that there are convenient responses one can offer that protect each theory from what appears to be threatening evidence (i.e., that the choice between the two theories is underdetermined in the holist sense) and that, for particular kinds of evidence, the two theories are empirically equivalent (i.e., with respect to certain kinds of evidence, the choice between the two theories is underdetermined in the contrastive sense).
ContributorsScheall, Scott (Author) / Creath, Richard (Thesis advisor) / Armendt, Brad (Committee member) / French, Peter (Committee member) / Arizona State University (Publisher)
Created2012
Description
The Modern Synthesis embodies a theory of natural selection where selection is to be fundamentally understood in terms of measures of fitness and the covariance of reproductive success and trait or character variables. Whether made explicit or left implicit, the notion that selection requires that some trait variable cause reproductive success has been deemphasized in our modern understanding of exactly what selection amounts to. The dissertation seeks to advance a theory of natural selection that is fundamentally causal. By focusing on the causal nature of natural selection (rather than on fitness or statistical formulae), certain conceptual and methodological problems are seen in a new, clarifying light and avenues toward new, interesting solutions to those problems are illustrated. First, the dissertation offers an update to explicitly causal theories of when exactly a trait counts as an adaptation upon fixation in a population and draws out theoretical and practical implications for evolutionary biology. Second, I examine a case of a novel character that evolves by niche construction and argue that it evolves by selection for it and consider implications for understanding adaptations and drift. The third contribution of the dissertation is an argument for the importance of defining group selection causally and an argument against model pluralism in the levels of selection debate. Fourth, the dissertation makes a methodological contribution. I offer the first steps toward an explicitly causal methodology for inferring the causes of selection—something often required in addition to inferring the causes of reproductive success. The concluding chapter summarizes the work and discusses potential paths for future work.
ContributorsAnderson, Wesley (Author) / Armendt, Brad (Thesis advisor) / Creath, Richard (Committee member) / Glymour, Bruce (Committee member) / Kinzig, Ann (Committee member) / Perrings, Charles (Committee member) / Arizona State University (Publisher)
Created2016
Description
Systems biology studies complex biological systems. It is an interdisciplinary field, with biologists working with non-biologists such as computer scientists, engineers, chemists, and mathematicians to address research problems applying systems’ perspectives. How these different researchers and their disciplines differently contributed to the advancement of this field over time is a question worth examining. Did systems biology become a systems-oriented science or a biology-oriented science from 1992 to 2013?
This project utilized computational tools to analyze large data sets and interpreted the results from historical and philosophical perspectives. Tools deployed were derived from scientometrics, corpus linguistics, text-based analysis, network analysis, and GIS analysis to analyze more than 9000 articles (metadata and text) on systems biology. The application of these tools to a HPS project represents a novel approach.
The dissertation shows that systems biology has transitioned from a more mathematical, computational, and engineering-oriented discipline focusing on modeling to a more biology-oriented discipline that uses modeling as a means to address real biological problems. Also, the results show that bioengineering and medical research has increased within systems biology. This is reflected in the increase of the centrality of biology-related concepts such as cancer, over time. The dissertation also compares the development of systems biology in China with some other parts of the world, and reveals regional differences, such as a unique trajectory of systems biology in China related to a focus on traditional Chinese medicine.
This dissertation adds to the historiography of modern biology where few studies have focused on systems biology compared with the history of molecular biology and evolutionary biology.
This project utilized computational tools to analyze large data sets and interpreted the results from historical and philosophical perspectives. Tools deployed were derived from scientometrics, corpus linguistics, text-based analysis, network analysis, and GIS analysis to analyze more than 9000 articles (metadata and text) on systems biology. The application of these tools to a HPS project represents a novel approach.
The dissertation shows that systems biology has transitioned from a more mathematical, computational, and engineering-oriented discipline focusing on modeling to a more biology-oriented discipline that uses modeling as a means to address real biological problems. Also, the results show that bioengineering and medical research has increased within systems biology. This is reflected in the increase of the centrality of biology-related concepts such as cancer, over time. The dissertation also compares the development of systems biology in China with some other parts of the world, and reveals regional differences, such as a unique trajectory of systems biology in China related to a focus on traditional Chinese medicine.
This dissertation adds to the historiography of modern biology where few studies have focused on systems biology compared with the history of molecular biology and evolutionary biology.
ContributorsZou, Yawen (Author) / Laubichler, Manfred (Thesis advisor) / Maienschein, Jane (Thesis advisor) / Creath, Richard (Committee member) / Ellison, Karin (Committee member) / Newfeld, Stuart (Committee member) / Arizona State University (Publisher)
Created2016
Description
A central task for historians and philosophers of science is to characterize and analyze the epistemic practices in a given science. The epistemic practice of a science includes its explanatory goals as well as the methods used to achieve these goals. This dissertation addresses the epistemic practices in gene expression research spanning the mid-twentieth century to the twenty-first century. The critical evaluation of the standard historical narratives of the molecular life sciences clarifies certain philosophical problems with respect to reduction, emergence, and representation, and offers new ways with which to think about the development of scientific research and the nature of scientific change.
The first chapter revisits some of the key experiments that contributed to the development of the repression model of genetic regulation in the lac operon and concludes that the early research on gene expression and genetic regulation depict an iterative and integrative process, which was neither reductionist nor holist. In doing so, it challenges a common application of a conceptual framework in the history of biology and offers an alternative framework. The second chapter argues that the concept of emergence in the history and philosophy of biology is too ambiguous to account for the current research in post-genomic molecular biology and it is often erroneously used to argue against some reductionist theses. The third chapter investigates the use of network representations of gene expression in developmental evolution research and takes up some of the conceptual and methodological problems it has generated. The concluding comments present potential avenues for future research arising from each substantial chapter.
In sum, this dissertation argues that the epistemic practices of gene expression research are an iterative and integrative process, which produces theoretical representations of the complex interactions in gene expression as networks. Moreover, conceptualizing these interactions as networks constrains empirical research strategies by the limited number of ways in which gene expression can be controlled through general rules of network interactions. Making these strategies explicit helps to clarify how they can explain the dynamic and adaptive features of genomes.
The first chapter revisits some of the key experiments that contributed to the development of the repression model of genetic regulation in the lac operon and concludes that the early research on gene expression and genetic regulation depict an iterative and integrative process, which was neither reductionist nor holist. In doing so, it challenges a common application of a conceptual framework in the history of biology and offers an alternative framework. The second chapter argues that the concept of emergence in the history and philosophy of biology is too ambiguous to account for the current research in post-genomic molecular biology and it is often erroneously used to argue against some reductionist theses. The third chapter investigates the use of network representations of gene expression in developmental evolution research and takes up some of the conceptual and methodological problems it has generated. The concluding comments present potential avenues for future research arising from each substantial chapter.
In sum, this dissertation argues that the epistemic practices of gene expression research are an iterative and integrative process, which produces theoretical representations of the complex interactions in gene expression as networks. Moreover, conceptualizing these interactions as networks constrains empirical research strategies by the limited number of ways in which gene expression can be controlled through general rules of network interactions. Making these strategies explicit helps to clarify how they can explain the dynamic and adaptive features of genomes.
ContributorsRacine, Valerie (Author) / Maienschein, Jane (Thesis advisor) / Laubichler, Manfred D (Thesis advisor) / Creath, Richard (Committee member) / Newfeld, Stuart (Committee member) / Morange, Michel (Committee member) / Arizona State University (Publisher)
Created2016
Description
This dissertation begins to lay out a small slice of the history of morphological research, and how it has changed, from the late 19th through the close of the 20th century. Investigators using different methods, addressing different questions, holding different assumptions, and coming from different research fields have pursued morphological research programs, i.e. research programs that explore the process of changing form. Subsequently, the way in which investigators have pursued and understood morphology has witnessed significant changes from the 19th century to modern day research. In order to trace this shifting history of morphology, I have selected a particular organ, teeth, and traced a tendril of research on the dentition beginning in the late 19th century and ending at the year 2000. But even focusing on teeth would be impossible; the scope of research on this organ is far too vast. Instead, I narrow this dissertation to investigation of research on a particular problem: explaining mammalian tooth morphology. How researchers have investigated mammalian tooth morphology and what counts as an explanation changed dramatically during this period.
ContributorsMacCord, Katherine (Author) / Maienschein, Jane (Thesis advisor) / Laubichler, Manfred (Thesis advisor) / Laplane, Lucie (Committee member) / Kimbel, William (Committee member) / Creath, Richard (Committee member) / Hurlbut, Benjamin (Committee member) / Arizona State University (Publisher)
Created2017
Description
At the interface of developmental biology and evolutionary biology, the very
criteria of scientific knowledge are up for grabs. A central issue is the status of evolutionary genetics models, which some argue cannot coherently be used with complex gene regulatory network (GRN) models to explain the same evolutionary phenomena. Despite those claims, many researchers use evolutionary genetics models jointly with GRN models to study evolutionary phenomena.
How do those researchers deploy those two kinds of models so that they are consistent and compatible with each other? To address that question, this dissertation closely examines, dissects, and compares two recent research projects in which researchers jointly use the two kinds of models. To identify, select, reconstruct, describe, and compare those cases, I use methods from the empirical social sciences, such as digital corpus analysis, content analysis, and structured case analysis.
From those analyses, I infer three primary conclusions about projects of the kind studied. First, they employ an implicit concept of gene that enables the joint use of both kinds of models. Second, they pursue more epistemic aims besides mechanistic explanation of phenomena. Third, they don’t work to create and export broad synthesized theories. Rather, they focus on phenomena too complex to be understood by a common general theory, they distinguish parts of the phenomena, and they apply models from different theories to the different parts. For such projects, seemingly incompatible models are synthesized largely through mediated representations of complex phenomena.
The dissertation closes by proposing how developmental evolution, a field traditionally focused on macroevolution, might fruitfully expand its research agenda to include projects that study microevolution.
criteria of scientific knowledge are up for grabs. A central issue is the status of evolutionary genetics models, which some argue cannot coherently be used with complex gene regulatory network (GRN) models to explain the same evolutionary phenomena. Despite those claims, many researchers use evolutionary genetics models jointly with GRN models to study evolutionary phenomena.
How do those researchers deploy those two kinds of models so that they are consistent and compatible with each other? To address that question, this dissertation closely examines, dissects, and compares two recent research projects in which researchers jointly use the two kinds of models. To identify, select, reconstruct, describe, and compare those cases, I use methods from the empirical social sciences, such as digital corpus analysis, content analysis, and structured case analysis.
From those analyses, I infer three primary conclusions about projects of the kind studied. First, they employ an implicit concept of gene that enables the joint use of both kinds of models. Second, they pursue more epistemic aims besides mechanistic explanation of phenomena. Third, they don’t work to create and export broad synthesized theories. Rather, they focus on phenomena too complex to be understood by a common general theory, they distinguish parts of the phenomena, and they apply models from different theories to the different parts. For such projects, seemingly incompatible models are synthesized largely through mediated representations of complex phenomena.
The dissertation closes by proposing how developmental evolution, a field traditionally focused on macroevolution, might fruitfully expand its research agenda to include projects that study microevolution.
ContributorsElliott, Steve (Author) / Creath, Richard (Thesis advisor) / Laubichler, Manfred D. (Thesis advisor) / Armendt, Brad (Committee member) / Forber, Patrick (Committee member) / Pratt, Stephen (Committee member) / Arizona State University (Publisher)
Created2017