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Representing with model organisms: A refined DEKI account
Get PDFIn this article, we mobilize and refine the DEKI account of scientific representation to show that model organisms are not models but model ‘carriers,’ only abstracted and selected ‘parts’ of which are included in biological models. These parts correspond to phenomena of interest that are interpreted as mechanisms or other kinds of causal processes within certain theoretical domains. The models can then be used to represent similar target phenomena in other organisms. Our proposal paves the way to reconcile opposing positions apropos the representational status of model organisms and build a more robust epistemology of model organism-based research
How is a relational formal ontology relational? A introduction to the semiotic logic of agency in physics, mathematics, and natural philosophy
Get PDFA speculative exploration of the distinction between a relational formal ontology and a classical formal ontology for modelling phenomena in nature that exhibit relationally-mediated wholism, such as phenomena from quantum physics and biosemiotics. Whereas a classical formal ontology is based on mathematical objects and classes, a relational formal ontology is based on mathematical signs and categories. A relational formal ontology involves nodal networks (systems of constrained iterative processes) that are dynamically sustained through signalling. The nodal networks are hierarchically ordered and exhibit characteristics of deep learning. Clarifying the distinction between classical and relational formal ontologies may help to clarify the role of interpretative context in physics (eg. the role of the observer in quantum theory)
"They Had It Coming!" The Effect of Moral Character on Somatic and Mental Health Judgments
Get PDFPrior research has unveiled a pathologization effect where individuals perceived as having bad moral character are more likely to have their conditions labeled as diseases and are less often considered healthy compared to those viewed as having a good moral character. Moreover, these individuals are perceived as less unlucky in their affliction and more deserving of it. This study explores the broader impacts of moral character on such judgments, hypothesizing that these effects reach deeper and extend to both negative and positive moral evaluations. The pathologization effect also raises concerns about potential discrimination and the overmedicalization of normal health variations, so we also examine whether providing more detailed descriptions of conditions mitigates the influence of judgments of moral character. The methodology and broader implications of our findings are discussed, emphasizing the need for a deeper understanding of how moral judgments might influence patient care
Unification and Surprise: On the Confirmatory Reach of Unification
Get PDFThere is no doubt that a theory that is unified has a certain appeal. Scientific practice in fundamental physics relies heavily on it. But is a unified theory more likely to be empirically adequate than a non-unified theory? Myrvold has pointed out that, on a Bayesian account, only a specific form of unification, which he calls mutual information unification, can have confirmatory value. In this paper, we argue that Myrvold’s analysis suffers from an overly narrow understanding of what counts as evidence. If one frames evidence in a way that includes observations beyond the theory’s intended domain, one finds a much richer and more interesting perspective on the connection between unification and theory confirmation. By adopting this strategy, we give a Bayesian account of unification that (i) goes beyond mutual information unification to include other cases of unification, and (ii) gives a crucial role to the element of surprise in the discovery of a unified theory. We illus- trate the explanatory strength of this account with some cases from fundamental physics and other disciplines
The contemporary scientific progress debate in philosophy of science and empirical evidence on Knowledge That versus Knowledge How in scientific practice
Get PDFIn his comprehensive survey of the contemporary debate over scientific progress in philosophy of science, Rowbottom observes that philosophers of science have mostly relied on interpretations of historical cases from the history of science and intuitions elicited by hypothetical cases as evidence for or against philosophical accounts of scientific progress. Only a few have tried to introduce empirical evidence into this debate, whereas most others have resisted the introduction of empirical evidence by claiming that doing so would reduce the debate to empirical studies of science. In this paper, I set out to show how empirical evidence can be introduced into the scientific progress debate. I conduct a corpus-based, quantitative study whose results suggest that there is a positive linear relationship between knowledge that talk and knowledge how talk in scientific articles. These results are contrary to Niiniluoto’s view according to which there is a clear distinction between scientific progress and technological progress such that knowledge that belongs to the former, whereas knowledge how belongs to the latter
Fully Self-Consistent Semiclassical Gravity
Get PDFA theory of quantum gravity consists of a gravitational framework which, unlike general relativity, takes into account the quantum character of matter. In spite of impressive advances, no fully satisfactory, self-consistent and empirically viable theory with those characteristics has ever been constructed. A successful semiclassical gravity model, in which the classical Einstein tensor couples to the expectation value of the energy-momentum tensor of quantum matter fields, would, at the very least, constitute a useful stepping stone towards quantum gravity. However, not only no empirically viable semiclassical theory has ever been proposed, but the self-consistency of semiclassical gravity itself has been called into question repeatedly over the years. Here, we put forward a fully self-consistent, empirically viable semiclassical gravity framework, in which the expectation value of the energy-momentum tensor of a quantum field, evolving via a relativistic objective collapse dynamics, couples to a fully classical Einstein tensor. We present the general framework, a concrete example, and briefly explore possible empirical consequences of our model
From Computation to Coherence: Toward a Structural Symbolic Theory of General Intelligence
Get PDFWhat distinguishes genuine intelligence from sophisticated simulation? This paper argues that the answer lies in symbolic coherence—the structural capacity to interpret information, revise commitments, and maintain continuity of reasoning across contradiction. Current AI systems generate fluent outputs while lacking mechanisms to track their own symbolic commitments or resolve contradictions through norm-guided revision. This theory proposes F(S), a structural identity condition requiring interpretive embedding, reflexive situatedness, and internal normativity. This condition is substrate-neutral and applies to both biological and artificial systems. Unlike behavioral benchmarks, F(S) offers criteria for participation in symbolic reasoning rather than surface-level imitation. To demonstrate implementability, the paper presents a justification graph architecture that supports recursive coherence and transparent revision. A diagnostic scalar, symbolic density, tracks alignment over symbolic time. By uniting philosophical insights with concrete system design, this framework outlines foundations for machines that may one day understand rather than simulate understanding
Maxwell, Peirce, and Planck: The Quest for Absolute Measurement and Absolute Reality
Get PDFPeople are often interested in physics due to its purported objectivity. It aims to truly be a study of nature (φύσεις) in itself. On the other hand, physics is a human construct, a language we use to describe the world as we experience it. In our quest for absolute reality, then, it seems that we must rid our description of the world of all subjectivity. This lecture concerns part of a story of such an attempt: the quest for absolute measurement. We will consider physical and philosophical aspects of the attempts of Maxwell, Peirce, and Planck to rid our language of physical measurement of undue subjectivity. This will shed some light on the possibility of knowing absolute reality---and the possibility of communication with aliens
Digging deeper with deep learning? Explanatory understanding and deep neural networks
Get PDFDespite their successes at prediction and classification, deep neural networks (DNNs) are often claimed to fail when it comes to providing any understanding of real-world phenomena. However, recently, some authors have argued that DNNs can provide such understanding. To resolve this controversy, I first examine under which conditions DNNs provide humans with explanatory understanding in a clearly defined sense that refers to a simple setting. I adopt a systematic approach that draws on theories of explanation and explanatory understanding, but avoid dependence on any specific account by developing broad conditions of explanatory understanding that leave space for filling in the details in several alternative ways. I argue that the conditions are difficult to satisfy however these details are filled in. The main problem is that, to provide explanatory understanding in the sense I have defined, a DNN has to contain an explanation, and scientists typically do not know whether it does. Accordingly, they cannot feel committed to the explanation or use it, which means that other conditions of explanatory understanding are not satisfied. Still, in some attenuated senses, the conditions can be fulfilled. To complete my conciliatory project, I further show that my results so far are compatible with using DNNs to infer explanatorily relevant information in a thorough investigation. This is what the more optimistic literature on DNNs has focused on. In sum, then, the significance of DNNs for understanding real-world systems depends on what it means to say that they provide understanding, and on how humans use them
Patient values and inductive risk in disorders of consciousness
Get PDFDiagnosing patients with disorders of consciousness involves inductive risk: the risk of false negative and false positive results when gathering and interpreting evidence of consciousness. A recent proposal suggests mitigating that risk by incorporating patient values into methodological choices at the level of individual diagnostic techniques: when using machine-learning algorithms to detect neural evidence of responsiveness to commands, clinicians should consider the patient’s own preferences about whether avoiding false positives or false negatives takes priority (Birch, 2023). In this paper, I argue that this proposal raises concerns about how to ensure that inevitable non-epistemic value judgments do not outweigh epistemic considerations. Additionally, it comes with challenges related to the predictive accuracy of surrogate decision-makers and the decisional burden imposed on them. Hence, I argue that patient values should not be incorporated at the level of gathering evidence of consciousness, but that they should play the leading role when considering how to respond to that evidence