In this paper we propose an informal exposition of the structure approach in the philosophy of science. Scientific knowledge is here considered as a collection of scientific theories. Each scientific theory has logico-linguistic, model-representing, pragmatic-procedural, and problem-heuristical subsystems and a subsystem of ties. The pivotal methodological concept for the exact description of these subsystems is the named set. We also outline the possibility of applying the structure-nominative approach to certain problems in the philosophy of science.

This thesis presents a proof theoretical investigation of some constructive set theories with restricted set induction. The set theories considered are various systems of Constructive Zermelo Fraenkel set theory, CZF ([1]), in which the schema of $\in$ - Induction is either removed or weakened. We shall examine the theories $CZF^\Sigma_\omega$ and $CZF_\omega$, in which the $\in$ - Induction scheme is replaced by a scheme of induction on the natural numbers (only for  formulas in the case of the first theory, (...) for arbitrary formulas in the second theory). Of particular interest is the system CZF− + INAC, which is obtained by removing $\in$ - Induction and by adding an axiom, INAC, for inaccessible sets. The main outcome is that CZF− + INAC is a predicative set theory with inaccessible sets, its proof theoretic ordinal being $\Gamma_0$. The proof theoretic strength of these theories, has been determined by means of proof theoretical reductions. The upper bounds have been obtained by interpreting the set theories in classical theories of (iterated) inductive definitions with ordinals. A significant feature of these interpretations is that they are realizability interpretations, which make an indirect use of Aczel’s interpretation of CZF in Martin Löf type theory, and, in the case of CZF− + INAC, also employ a maximum bisimulation relation to represent equality between sets. The lower bounds are obtained by interpreting appropriate subsystems of intuitionistic second order arithmetic in the set theories. At the conclusion of the thesis we present work unrelated to the previous chapters. It is a preliminary study of the constructible hierarchy in CZF. We begin by formalizing the notion of definability in constructive set theory and then introduce Gödel’s L in CZF. We prove that intuitionistic L is a model of a subsystem of CZF strong enough to include intuitionistic Kripke-Platek set theory, and also that L is a model of the axiom of constructibility, provably in CZF. (shrink)

The paper explicates the stages of the author’s philosophical evolution in the light of Kopnin’s ideas and heritage. Starting from Kopnin’s understanding of dialectical materialism, the author has stated that category transformations of physics has opened from conceptualization of immutability to mutability and then to interaction, evolvement and emergence. He has connected the problem of physical cognition universals with an elaboration of the specific system of tools and methods of identifying, individuating and distinguishing objects from a scientific theory domain. The (...) role of vacuum conception and the idea of existence (actual and potential, observable and nonobservable, virtual and hidden) types were analyzed. In collaboration with S.Crymski heuristic and regulative functions of categories of substance, world as a whole as well as postulates of relativity and absoluteness, and anthropic and self-development principles were singled out. Elaborating Kopnin’s view of scientific theories as a practically effective and relatively true mapping of their domains, the author in collaboration with M. Burgin have originated the unified structure-nominative reconstruction (model) of scientific theory as a knowledge system. According to it, every scientific knowledge system includes hierarchically organized and complex subsystems that partially and separately have been studied by standard, structuralist, operationalist, problem-solving, axiological and other directions of the current philosophy of science. 1) The logico-linguistic subsystem represents and normalizes by means of different, including mathematical, languages and normalizes and logical calculi the knowledge available on objects under study. 2) The model-representing subsystem comprises peculiar to the knowledge system ways of their modeling and understanding. 3) The pragmatic-procedural subsystem contains general and unique to the knowledge system operations, methods, procedures, algorithms and programs. 4) From the viewpoint of the problem-heuristic subsystem, the knowledge system is a unique way of setting and resolving questions, problems, puzzles and tasks of cognition of objects into question. It also includes various heuristics and estimations (truth, consistency, beauty, efficacy, adequacy, heuristicity etc) of components and structures of the knowledge system. 5) The subsystem of links fixes interrelations between above-mentioned components, structures and subsystems of the knowledge system. The structure-nominative reconstruction has been used in the philosophical and comparative case-studies of mathematical, physical, economic, legal, political, pedagogical, social, and sociological theories. It has enlarged the collection of knowledge structures, connected, for instance, with a multitude of theoreticity levels and with an application of numerous mathematical languages. It has deepened the comprehension of relations between the main directions of current philosophy of science. They are interpreted as dealing mainly with isolated subsystems of scientific theory. This reconstruction has disclosed a variety of undetected knowledge structures, associated also, for instance, with principles of symmetry and supersymmetry and with laws of various levels and degrees. In cooperation with the physicist Olexander Gabovich the modified structure-nominative reconstruction is in the processes of development and justification. Ideas and concepts were also in the center of Kopnin’s cognitive activity. The author has suggested and elaborated the triplet model of concepts. According to it, any scientific concept is a dependent on cognitive situation, dynamical, multifunctional state of scientist’s thinking, and available knowledge system. A concept is modeled as being consisted from three interrelated structures. 1) The concept base characterizes objects falling under a concept as well as their properties and relations. In terms of volume and content the logical modeling reveals partially only the concept base. 2) The concept representing part includes structures and means (names, statements, abstract properties, quantitative values of object properties and relations, mathematical equations and their systems, theoretical models etc.) of object representation in the appropriate knowledge system. 3) The linkage unites a structures and procedures that connect components from the abovementioned structures. The partial cases of the triplet model are logical, information, two-tired, standard, exemplar, prototype, knowledge-dependent and other concept models. It has introduced the triplet classification that comprises several hundreds of concept types. Different kinds of fuzziness are distinguished. Even the most precise and exact concepts are fuzzy in some triplet aspect. The notions of relations between real scientific concepts are essentially extended. For example, the definition and strict analysis of such relations between concepts as formalization, quantification, mathematization, generalization, fuzzification, and various kinds of identity are proposed. The concepts «PLANET» and «ELEMENTARY PARTICLE» and some of their metamorphoses were analyzed in triplet terms. The Kopnin’s methodology and epistemology of cognition was being used for creating conception of the philosophy of law as elaborating of understanding, justification, estimating and criticizing legal system. The basic information on the major directions in current Western philosophy of law (legal realism, feminism, criticism, postmodernism, economical analysis of law etc.) is firstly introduced to the Ukrainian audience. The classification of more than fifty directions in modern legal philosophy is suggested. Some results of historical, linguistic, scientometric and philosophic-legal studies of the present state of Ukrainian academic science are given. (shrink)

This paper continues investigations of the monotone fixed point principle in the context of Feferman's explicit mathematics begun in [14]. Explicit mathematics is a versatile formal framework for representing Bishop-style constructive mathematics and generalized recursion theory. The object of investigation here is the theory of explicit mathematics augmented by the monotone fixed point principle, which asserts that any monotone operation on classifications (Feferman's notion of set) possesses a least fixed point. To be more precise, the new axiom not merely (...) postulates the existence of a least solution, but, by adjoining a new constant to the language, it is ensured that a fixed point is uniformly presentable as a function of the monotone operation. Let T 0 + UMID denote this extension of explicit mathematics. [14] gave lower bounds for the strength of two subtheories of T 0 + UMID in relating them to fragments of second order arithmetic based on Π 1 2 comprehension. [14] showed that T $_0 \upharpoonright$ + UMID and T $_0 \upharpoonright$ + IND N + UMID have at least the strength of (Π 1 2 - CA) $\upharpoonright$ and (Π 1 2 - CA), respectively. Here we are concerned with the exact reversals. Let UMID N be the monotone fixed-point principle for subclassifications of the natural numbers. Among other results, it is shown that T $_0 \upharpoonright$ + UMID N and T $_0 \upharpoonright$ + IND N + UMID N have the same strength as (Π 1 2 - CA) $\upharpoonright$ and (Π 1 2 - CA), respectively. The results are achieved by constructing set-theoretic models for the aforementioned systems of explicit mathematics in certain extensions of Kripke-Platek set theory and subsequently relating these set theories to subsystems of second arithmetic. (shrink)

Economics prefers complete explanations: general over partial equilibrium, microfoundational over aggregate. Similarly, probabilistic accounts of causation frequently prefer greater detail to less as in typical resolutions of Simpson’s paradox. Strategies of causal refinement equally aim to distinguish direct from indirect causes. Yet, there are countervailing practices in economics. Representative-agent models aim to capture economic motivation but not to reduce the level of aggregation. Small structural vector-autoregression and dynamic stochastic general-equilibrium models are practically preferred to larger ones. The distinction between exogenous (...) and endogenous variables suggests partitioning the world into distinct subsystems. The tension in these practices is addressed within a structural account of causation inspired by the work of Herbert Simon’s, which defines cause with reference to complete systems adapted to deal with incomplete systems and piecemeal evidence. The focus is on understanding the constraints that a structural account of causation places on the freedom to model complex or lower-order systems as simpler or higher-order systems and on to what degree piecemeal evidence can be incorporated into a structural account. (shrink)

Why are quantum correlations so puzzling? A standard answer is that they seem to require either nonlocal influences or conspiratorial coincidences. This suggests that by embracing nonlocal influences we can avoid conspiratorial fine-tuning. But that’s not entirely true. Recent work, leveraging the framework of graphical causal models, shows that even with nonlocal influences, a kind of fine-tuning is needed to recover quantum correlations. This fine-tuning arises because the world has to be just so as to disable the use of nonlocal (...) influences to signal, as required by the no-signaling theorem. This places an extra burden on theories that posit nonlocal influences, such as Bohmian mechanics, of explaining why such influences are inaccessible to causal control. I argue that Everettian Quantum Mechanics suffers no such burden. Not only does it not posit nonlocal influences, it operates outside the causal models framework that was presupposed in raising the fine-tuning worry. Specifically, it represents subsystems with density matrices instead of random variables. This allows it to sidestep all the results (including EPR and Bell) that put quantum correlations in tension with causal models. However, this doesn’t mean one must abandon causal reasoning altogether in a quantum world. When decoherence is rampant and there’s no controlled entanglement, Everettian Quantum Mechanics licenses our continued use of standard causal models. When controlled entanglement is present---such as in Bell-type experiments---we can employ recently-proposed quantum causal models that are consistent with Everettian Quantum Mechanics. We never need invoke any kind of non-local influence or any kind of fine-tuning. (shrink)

When parties and interest groups interact, they can do so in several ways which could be on an informal level, lobbying for a party candidate, or group representatives approach party leaders in the parliament to lobby them on an issue. There is a plethora of studies on the extent to which major political parties and major interests have related in the past and continue to relate or interact at the organizational level. Researchers have investigated to what extent parties and groups (...) had formal organizational ties, cooperated in elections, or worked in concert on developing and implementing policies. Factors that for decades have determined the relationship between political parties and interest groups in liberal democracies are political system and subsystem development, political culture and political ideology, centralization of government and policymaking, nature of the party system, political party dependence on interest groups, encompassing characteristics of the interest group system, interest group development, ideology, and leadership. However, the pandemic has influenced to a great extend the relationship between interest groups and politics. While Covid-19 crisis has consolidated power within governments, leaving opposition parties in a bind, on the other hand it has galvanized interest groups and businesses to mobilize. The pandemic has opened up the lobbying playing field to many new players. The paper aims to investigate to what extend the pandemic has influenced the relationship between political parties, government and interest groups and what strategies have these last ones used to get heard in a time when social distancing has reduced the opportunities for face-to-face lobbying. (shrink)

Scientific models are important, if not the sole, units of science. This thesis addresses the following question: in virtue of what do scientific models represent their target systems? In Part i I motivate the question, and lay out some important desiderata that any successful answer must meet. This provides a novel conceptual framework in which to think about the question of scientific representation. I then argue against Callender and Cohen’s attempt to diffuse the question. In Part ii I investigate the (...) ideas that scientific models are ‘similar’, or structurally morphic, to their target systems. I argue that these approaches are misguided, and that at best these relationships concern the accuracy of a pre-existing representational relationship. I also pay particular attention to the sense in which target systems can be appropriately taken to exhibit a ‘structure’, and van Fraassen’s recent argument concerning the pragmatic equivalence between representing phenomena and data. My next target is the idea that models should not be seen as objects in their own right, but rather what look like descriptions of them are actually direct descriptions of target systems, albeit not ones that should be understood literally. I argue that these approaches fail to do justice to the practice of scientific modelling. Finally I turn to the idea that how models represent is grounded, in some sense, in their inferential capacity. I compare this approach to anti-representationalism in the philosophy of language and argue that analogous issues arise in the context of scientific representation. Part iii contains my positive proposal. I provide an account of scientific representation based on Goodman and Elgin’s notion of representation-as. The result is a highly conventional account which is the appropriate level of generality to capture all of its instances, whilst remaining informative about the notion. I illustrate it with reference to the Phillips-Newlyn machine, models of proteins, and the Lotka-Volterra model of predator-prey systems. These examples demonstrate how the account must be understood, and how it sheds light on our understanding of how models are used. I finally demonstrate how the account meets the desiderata laid out at the beginning of the thesis, and outline its implications for further questions from the philosophy of science; not limited to issues surrounding the applicability of mathematics, idealisation, and what it takes for a model to be ‘true’. (shrink)

We pursue a model-oriented rather than axiomatic approach to the foundations of Quantum Mechanics, with the idea that new models can often suggest new axioms. This approach has often been fruitful in Logic and Theoretical Computer Science. Rather than seeking to construct a simplified toy model, we aim for a 'big toy model', in which both quantum and classical systems can be faithfully represented—as well as, possibly, more exotic kinds of systems. To this end, we show how (...) Chu spaces can be used to represent physical systems of various kinds. In particular, we show how quantum systems can be represented as Chu spaces over the unit interval in such a way that the Chu morphisms correspond exactly to the physically meaningful symmetries of the systems—the unitaries and antiunitaries. In this way we obtain a full and faithful functor from the groupoid of Hubert spaces and their symmetries to Chu spaces. We also consider whether it is possible to use a finite value set rather than the unit interval; we show that three values suffice, while the two standard possibilistic reductions to two values both fail to preserve fullness. (shrink)

Scientific models represent aspects of the empirical world. I explore to what extent this representational relationship, given the specific properties of models, can be analysed in terms of propositions to which truth or falsity can be attributed. For example, models frequently entail false propositions despite the fact that they are intended to say something "truthful" about phenomena. I argue that the representational relationship is constituted by model users "agreeing" on the function of a model, on the fit with (...) data and on the aspects of a phenomenon that are modelled. Model users weigh the propositions entailed by a model and from this decide which of these propositions are crucial to the acceptance and continued use of the model. Thus, models represent phenomena when certain propositions they entail are true, but this alone does not exhaust the representational relationship. Therefore, the constraints that produce the choice of the relevant propositions in a model must also be examined and their analysis contributes to understanding the relationship between models and phenomena. (shrink)

One of the main results of Gödel [4] and [5] is that, if M is a transitive set such that $\langle M, \epsilon \rangle$ is a model of ZF (Zermelo-Fraenkel set theory) and α is the least ordinal not in M, then $\langle L_\alpha, \epsilon \rangle$ is also a model of ZF. In this note we shall use the Jensen uniformisation theorem to show that results analogous to the above hold for certain subsystems of ZF. The subsystems we (...) have in mind are those that are formed by restricting the formulas in the separation and replacement axioms to various levels of the Levy hierarchy. This is all done in § 1. In § 2 we proceed to establish the exact order relationships which hold among the ordinals of the minimal models of some of the systems discussed in § 1. Although the proofs of these latter results will not require any use of the uniformisation theorem, we will find it convenient to use some of the more elementary results and techniques from Jensen's fine-structural theory of L. We thus provide a brief review of the pertinent parts of Jensen's works in § 0, where a list of general preliminaries is also furnished. We remark that some of the techniques which we use in the present paper have been used by us previously in [6] to prove various results about β-models of analysis. Since β-models for analysis are analogous to transitive models for set theory, this is not surprising. (shrink)

I argue that ML models used in science function as highly idealized toy models. If we treat ML models as a type of highly idealized toy model, then we can deploy standard representational and epistemic strategies from the toy model literature to explain why ML models can still provide epistemic success despite their lack of similarity to their targets.

Peter Spirtes. Conditional Independence in Directed Cyclical Graphical Models Representing Feedback or Mixtures.

In order to modelize the reasoning of intelligent agents represented by a poset T, H. Rasiowa introduced logic systems called “Approximation Logics”. In these systems the use of a set of constants constitutes a fundamental tool. We have introduced in [8] a logic system called equation image without this kind of constants but limited to the case that T is a finite poset. We have proved a completeness result for this system w.r.t. an algebraic semantics. We introduce in this paper (...) a Kripke-style semantics for a subsystem equation image of equation image for which there existes a deduction theorem. The set of “possible worldsr is enriched by a family of functions indexed by the elements of T and satisfying some conditions. We prove a completeness result for system equation image with respect to this Kripke semantics and define a finite Kripke structure that characterizes the propositional fragment of logic equation image. We introduce a reational semantics which has the advantage to allow an interpretation of the propositionnal logic equation image using only binary relations. We treat also the computational complexity of the satisfiability problem of the propositional fragment of logic equation image. (shrink)

A new explanation of kurtosis in asset price behavior is proposed involving flare attractors. Such attractors depend on chaotic fundamentals driving subsystems which trigger nonlinearly response functions each with a switching mechanism representing the changing of agents from stabilizing to destabilizing behavior. Heterogeneous agent types are shown by a set of these response functions that are interlinked. With a larger number of agent types system behavior resembles that of many financial markets. Such a model is consistent with newer (...) approaches relying upon evolutionary learning mechanisms with heterogeneous agents as well as models depending on fractal characteristics. (shrink)

The field of “BERTology” aims to locate linguistic representations in large language models (LLMs). These have commonly been interpreted as representing structural descriptions (SDs) familiar from theoretical linguistics, such as abstract phrase-structures. However, it is unclear how such claims should be interpreted in the first place. This paper identifies six possible readings of “linguistic representation” from philosophical and linguistic literature, concluding that none has a straight-forward application to BERTology. In philosophy, representations are typically analyzed as cognitive vehicles individuated by (...) intentional content. This clashes with a prevalent mentalist interpretation of linguistics, which treats SDs as (narrow) properties of cognitive vehicles themselves. I further distinguish between three readings of both kinds, and discuss challenges each brings for BERTology. In particular, some readings would make it trivially false to assign representations of SDs to LLMs, while others would make it trivially true. I illustrate this with the concrete case study of structural probing: a dominant model-interpretation technique. To improve the present situation, I propose that BERTology should adopt a more “LLM-first” approach instead of relying on pre-existing linguistic theories developed for orthogonal purposes. (shrink)

The representation of a quantum system as the spatial configuration of its constituents evolving in time as a trajectory under the action of the wave-function, is the main objective of the de Broglie–Bohm theory. However, its standard formulation is referred to the statistical ensemble of its possible trajectories. The statistical ensemble is introduced in order to establish the exact correspondence between the probability density on the spatial configurations and the quantum distribution, that is the squared modulus of the wave-function. In (...) this work we explore the possibility of using the pilot wave theory at the level of a single Bohm’s trajectory, that is a single realization of the time dependent configuration which should be representative of a single realization of the quantum system. The pilot wave theory allows a formally self-consistent representation of quantum systems as a single Bohm’s trajectory, but in this case there is no room for the Born’s rule at least in its standard form. We will show that a correspondence exists between the statistical distribution of configurations along the single Bohm’s trajectory and the quantum distribution for a subsystem interacting with the environment in a multicomponent system. To this aim, we present the numerical results of the single Bohm’s trajectory description of the model system of six confined planar rotors with random interactions. We find a rather close correspondence between the coordinate distribution of one rotor, the others representing the environment, along its trajectory and the time averaged marginal quantum distribution for the same rotor. This might be considered as the counterpart of the standard Born’s rule when the pilot wave theory is applied at the level of single Bohm’s trajectory. Furthermore a strongly fluctuating behavior with a fast loss of correlation is found for the evolution of each rotor coordinate. This suggests that a Markov process might well approximate the evolution of the Bohm’s coordinate of a single rotor and, under this condition, it is shown that the correspondence between coordinate distribution and quantum distribution of the rotor is exactly verified. (shrink)

RESUMEN Introducción: La dimensión ambiental constituye un proceso esencial en la formación de profesionales, de modo que en el desempeño de su profesión puedan educar hacia el desarrollo sostenible a las futuras generaciones. Objetivo: Representar en un modelo pedagógico la lógica de la dimensión ambiental en la formación laboral investigativa de los profesionales en la universidad. Materiales y métodos: Se utilizaron métodos teóricos, empíricos y matemáticos-estadísticos. Resultados: Elaboración del modelo pedagógico de dimensión ambiental en la formación laboral investigativa de los (...) profesionales en formación. El modelo está estructurado en tres subsistemas: uno teórico, se centra en la integración de saberes pedagógico ambientales a partir de las relaciones que se establecen entre sus componentes, otro metodológico, el cual resume la proyección ambiental de la formación laboral investigativa y un subsistema procedimental, que manifiesta la instrumentación transformadora ambiental que debe ocurrir en los estudiantes. El modelo aporta una cualidad sinérgica que le imprime identidad, totalidad y contribuye a su autodesarrollo. Conclusiones: Con la elaboración del modelo se revelan nuevas interpretaciones que se manifiestan como relaciones teóricas funcionales surgidas entre los componentes de los subsistemas que lo integran y a la vez, entre los subsistemas como macro componentes. La validación del modelo resultó estadísticamente significativa, mediante la instrumentación de una estrategia pedagógica para la dimensión ambiental en la formación laboral investigativa. ABSTRACT Introduction: The environmental component is an essential process in the training of professionals, that enables them to educate future generations towards sustainable development. Objective: To represent in a pedagogical model the logic of the environmental dimension in the research training of professionals. Materials and methods: Theoretical, empirical and mathematical-statistical methods were used. Findings: The development of the pedagogical model of environmental dimension in research and labor training of professionals. The model is structured in three subsystems: the first focuses on the integration of environmental pedagogical knowledge from the relationships established between its components; the second is of a methodological character and summarizes the environmental projection of research training; whereas the third one is procedural, expressing the environmental transformative instrumentation that must occur in students. The model provides a synergistic quality that consolidates identity, totality and contributes to its self-development. Conclusions: With the elaboration of the model new interpretations are revealed that are manifested as functional theoretical relations arising between the components of the subsystems that integrate it and at the same time, between the subsystems as macro components. The evaluation of the model was statistically significant, through the instrumentation of a pedagogical strategy for the environmental dimension in the research and labor training. (shrink)

The disavowal of positivist science by many educational researchers has resulted in a deepening polarization of research agendas and an epistemological divide that appears increasingly difficult to span. Despite a turning away from science altogether by some, and thus toward various forms of poststructuralist inquiry, this has not held back the renewed entrenchment of more narrow definitions by policy elites of what constitutes scientific educational research. The new sciences of complexity signal the emergence of a new scientific paradigm that challenges (...) some of the core assumptions of positivism, while offering the potential to develop a new kind of social science that demands both rigour and imagination in coming to understand the emergence and behaviours of social systems and the subsystems that comprise them. The language, concepts and principles of complexity are central to the development of a new science of qualities to complement the science of quantities that has shaped our understanding of the physical and social worlds. Accomplishing this task promises to 1) open up new investigations that have thus far been beyond the purview of scientific study, 2) allow the study of social phenomena as fully embodied, or at least as more robust models than those represented in the abstracted empiricism upon which the sciences of quantities are predicated, and 3) allow for more coarse‐grained explanations and predictions of social phenomena to be legitimated as scientific. Both educational research and educational practice stand to gain from this expansion of the scientific repertoire to include rigorous and imaginative investigations of phenomena characterized by change and transformation. (shrink)

A common strategy for simplifying complex systems involves partitioning them into subsystems whose behaviors are roughly independent of one another at shorter timescales. Dynamic causal models clarify how doing so reveals a system’s nonequilibrium causal relationships. Here I use these models to elucidate the idealizations and abstractions involved in representing a system at a timescale. The models reveal that key features of causal representations—such as which variables are exogenous—may vary with the timescale at which a system is considered. This (...) has implications for debates regarding which systems can be represented causally. (shrink)

This study attempts to extend the literature in ethics research by developing and testing a model of an individual's ethical system which identifies the sources of influence on the decision process. The model is developed from an interdisciplinary literature review and includes six subsystems or spheres that exert influence on an individual: the workplace, family, religion, legal system, community, and profession. The study also examines the role of materiality in the decision-making process. Using this model, empirical tests (...) identify the spheres that exert the most influence on the decision-maker facing an ethical dilemma. In addition, the relative importance of the spheres and the interaction among the spheres is examined. Findings show that: (1) individuals rate variables at different levels of importance as the materiality of the breach changes and (2) the spheres that are considered most important for minor ethical breaches are different than the spheres considered most influential in a major ethical situation. Exploratory factor analysis suggests that the variables representing the spheres can be summarized by three factors. Further, it indicates that these factors change with materiality. (shrink)

Physical models have long been used to represent a great many things. By and large, however, the representational powers of physical models have been taken for granted in recent philosophy of science. Interest has focused on more ubiquitous and seemingly more important theoretical models, particularly those found in mathematical physics. In this paper, I focus on physical models, comparing them with theoretical models and finally with recently popular computational models. My aim is to show that the representational aspects of models (...) used in science are fundamentally the same across all three categories of models. (shrink)

The basic Bayesian model of credence states, where each individual’s belief state is represented by a single probability measure, has been criticized as psychologically implausible, unable to represent the intuitive distinction between precise and imprecise probabilities, and normatively unjustifiable due to a need to adopt arbitrary, unmotivated priors. These arguments are often used to motivate a model on which imprecise credal states are represented by sets of probability measures. I connect this debate with recent work in Bayesian cognitive (...) science, where probabilistic models are typically provided with explicit hierarchical structure. Hierarchical Bayesian models are immune to many classic arguments against single-measure models. They represent grades of imprecision in probability assignments automatically, have strong psychological motivation, and can be normatively justified even when certain arbitrary decisions are required. In addition, hierarchical models show much more plausible learning behavior than flat representations in terms of sets of measures, which—on standard assumptions about update—rule out simple cases of learning from a starting point of total ignorance. (shrink)

The concepts of the innateness, universality, species-specificity, and autonomy of the human language capacity have had an extreme impact on the psycholinguistic debate for over thirty years. These concepts are evaluated from several neurobiological perspectives, with an emphasis on the emergence of language and its decay due to brain lesion and progressive brain disease.Evidence of perceptuomotor homologies and preadaptations for human language in nonhuman primates suggests a gradual emergence of language during hominid evolution. Regarding ontogeny, the innate component of language (...) capacity is likely to be polygenic and shared with other developmental domains. Dissociations between verbal and nonverbal development are probably rooted in the perceptuomotor specializations of neural substrates rather than the autonomy of a grammar module. Aphasiologicaldata often assumed to suggest modular linguistic subsystems can be accounted for in terms of a neurofunctional model incorporating perceptuomotor-based regional specializationsand distributivity of representations. Thus, dissociations between grammatical functors and content words are due to different conditions of acquisition and resulting differences in neural representation. Human brains are characterized by multifactorial interindividual variability, and strict universality of functional organization is biologically unrealistic.A theoretical alternative is proposed according to which (1) linguistic specialization of brain areas is due to epigenetic and probabilistic maturational events, not to genetic ”hard-wiring,” and (2) linguistic knowledge is neurally represented in distributed cell assemblies whose topography reflects the perceptuomotor modalities involved in the acquisition and use of a given item of knowledge. (shrink)

Different researchers use "the philosophy of automated theorem p r o v i n g " t o cover d i f f e r e n t concepts, indeed, different levels of concepts. Some w o u l d count such issues as h o w to e f f i c i e n t l y i n d e x databases as part of the philosophy of automated theorem p r o v i n g . (...) Others wonder about whether f o r m u l a s should be represented as strings or as trees or as lists, and call this part of the philosophy of automated theorem p r o v i n g . Yet others concern themselves w i t h what k i n d o f search should b e embodied i n a n y automated theorem prover, or to what degree any automated theorem prover should resemble Prolog. Still others debate whether natural deduction or semantic tableaux or resolution is " b e t t e r " , a n d c a l l t h i s a part of the p h i l o s o p h y of automated theorem p r o v i n g . Some people wonder whether automated theorem p r o v i n g should be " h u m a n oriented" or "machine o r i e n t e d " — sometimes arguing about whether the internal p r o o f methods should be " h u m a n - I i k e " or not, sometimes arguing about whether the generated proof should be output in a f o r m u n d e r s t a n d a b l e by p e o p l e , and sometimes a r g u i n g a b o u t the d e s i r a b i l i t y o f h u m a n intervention in the process of constructing a proof. There are also those w h o ask such questions as whether we s h o u l d even be concerned w i t h completeness or w i t h soundness of a system, or perhaps we should instead look at very efficient (but i n c o m p l e t e ) subsystems or look at methods of generating models w h i c h might nevertheless validate invalid arguments. A n d a l l of these have been v i e w e d as issues in the philosophy of automated theorem proving. Here, I w o u l d l i k e to step back from such i m p l e m e n t - ation issues and ask: " W h a t do we really think we are doing when we w r i t e an automated theorem prover?" My reflections are perhaps idiosyncratic, but I do think that they put the different researchers* efforts into a broader perspective, and give us some k i n d of handle on w h i c h directions we ourselves m i g h t w i s h to pursue when constructing (or extending) an automated theorem proving system. A logic is defined to be (i) a vocabulary and formation rules ( w h i c h tells us w h a t strings of symbols are w e l l - formed formulas in the logic), and ( i i ) a definition of ' p r o o f in that system ( w h i c h tells us the conditions under which an arrangement of formulas in the system constitutes a proof). Historically speaking, definitions of ' p r o o f have been given in various different manners: the most c o m m o n have been H i l b e r t - s t y l e ( a x i o m a t i c ) , Gentzen-style (consecution, or sequent), F i t c h - s t y l e (natural deduction), and Beth-style (tableaux).. (shrink)

The recent discussion on scientific representation has focused on models and their relationship to the real world. It has been assumed that models give us knowledge because they represent their supposed real target systems. However, here agreement among philosophers of science has tended to end as they have presented widely different views on how representation should be understood. I will argue that the traditional representational approach is too limiting as regards the epistemic value of modelling given the focus on the (...) relationship between a single model and its supposed target system, and the neglect of the actual representational means with which scientists construct models. I therefore suggest an alternative account of models as epistemic tools. This amounts to regarding them as concrete artefacts that are built by specific representational means and are constrained by their design in such a way that they facilitate the study of certain scientific questions, and learning from them by means of construction and manipulation. (shrink)

Models such as the simple pendulum, isolated populations, and perfectly rational agents, play a central role in theorising. It is now widely acknowledged that a study of scientific representation should focus on the role of such imaginary entities in scientists’ reasoning. However, the question is most of the time cast as follows: How can fictional or abstract entities represent the phenomena? In this paper, I show that this question is not well posed. First, I clarify the notion of representation, and (...) I emphasise the importance of what I call the “format” of a representation for the inferences agents can draw from it. Then, I show that the very same model can be presented under different formats, which do not enable scientists to perform the same inferences. Assuming that the main function of a representation is to allow one to draw predictions and explanations of the phenomena by reasoning with it, I conclude that imaginary models in abstracto are not used as representations: scientists always reason with formatted representations. Therefore, the problem of scientific representation does not lie in the relationship of imaginary entities with real systems. One should rather focus on the variety of the formats that are used in scientific practice. (shrink)

Dynamic engineering models have yet to be evaluated in the context of feminist engineering ethics. Decision-making concerning gender in dynamic modeling design is a gender and ethical issue that is important to address regardless of the system in which the dynamic modeling is applied. There are many dynamic modeling tools that operationally include the female population, however, there is an important distinction between females and women; it is the difference between biological sex and the social construct of gender, which is (...) fluid and changes over time and geography. The ethical oversight in failing to represent or misrepresenting gender in model design when it is relevant to the model purpose can have implications for model validity and policy model development. This paper highlights this gender issue in the context of feminist engineering ethics using a dynamic population model. Women are often represented in this type of model only in their biological capacity, while lacking their gender identity. This illustrative example also highlights how language, including the naming of variables and communication with decision-makers, plays a role in this gender issue. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Diacritics 31.4 (2001) 85-102 [Access article in PDF] Culture in the Disk Drive Computationalism, Memetics, and the Rise of Posthumanism Stephen Dougherty Ever since Descartes argued that there are striking similarities between a man and a clock, humanism has been in a state of crisis. To put it more pointedly, humanism has always been in a state of crisis, ever since it emerged in the sixteenth and seventeenth centuries (...) as a constellation of beliefs that made man rather than God the measure of all things. Thus, since we are arguably witnesses now to the eclipse of the humanist tradition, we might take some comfort (if any is desired) in considering that if we have failed the ideal of humanism, it has also failed us. From the beginning its borders were too porous, its boundaries too ill defined. For even as man turned himself into a god, he increasingly began to resemble a machine.In terms of bodily representation, our machinic evolution through the last four centuries culminates in the figure of the cyborg; and if we have already become posthuman, as N. Katherine Hayles suggests, then the cyborg stands as the iconic pop culture figure of our epochal transformation. But you don't need electronic prosthetic devices attached to your body or silicon chips implanted in your head to be posthuman. As Hayles argues, "[w]hether or not interventions have been made on the body, new models of subjectivity emerging from such fields as cognitive science and artificial life imply that even a biologically unaltered Homo sapiens counts as posthuman" [4]. What counts especially, according to Hayles, is not the body/machine interface but how we conceptualize the workings of the mind/brain.In the humanist tradition signalled by Descartes, the subject is an I, an ego that is master of itself, a unified consciousness thinking itself. Before it is anything else, the Cartesian subject is a function of thought—ineffable and immaterial, and partaking in its nature of the divine and ineffable spirit that guarantees its communication with the material world. Thus, even though God has always been in the process of disappearing through the centuries since the Renaissance, spirit hasn't. Humanism never abandoned the concept of a spiritualized man, registering at the least a dissatisfaction with science's conventional claim to the possession of special and superior knowledge, and until quite recently dualism of one variety or another has been the normative philosophical attitude.But in posthumanism matters are different. To begin with, as Hayles puts it, "computation rather than possessive individualism is taken as the ground of being" [34]. Human consciousness is no longer that which thinks itself into its own unity, a mysterious phenomenon of infinite reflexivity that would become the central subject of, and the central problem for, modern philosophy. In fact, in the posthumanist regime human consciousness is no longer primarily a matter for philosophy, since questions regarding ontology and epistemology are displaced by the question of functionality. Cognitive processes are turned into syntactical operations similar to those that computers perform, 1 [End Page 85] and consciousness is reduced to mere epiphenomena of those machinic operations. 2Further, the cognitive functions of posthuman subjectivity are dispersed among a complex network of interrelated systems and subsystems (modules) responsible for receiving and interpreting data. 3 Consciousness thus loses the holistic unity it had possessed with a considerable degree of consensus from Descartes up to the behavioralists. Just as significantly, it loses its ineffability. The computationalists do not interrogate the mind as something beyond the grasp of scientific rationality because they do not approach thought as immaterial. Insofar as the brain has become a machine, mind is reduced to matter. In the new posthuman dispensation, then, philosophical dualism gives way to monism.Such an outcome would seem to suggest that the onset of posthumanism represents the ultimate victory for positivism and scientific rationalism in explaining human behavior. As Francis Crick explains in The Astonishing Hypothesis: The Scientific Search for the Soul, "the aim of science is to explain all aspects of the behavior of our brains, including... (shrink)

Over the past half-century, modelling has come to play an increasingly important role in cancer research. These representational tools frame perceptions of malignant disease, guide public health responses, and help determine which interventions are necessary. But what makes a cancer model a model? What authority do they have? What stories do they tell? And how do they shape our understanding of disease and bodies? To shed light on these questions, this article explores the long history of cancer modelling (...) in sub-Saharan Africa: a place where malignant disease has often been imagined as different, and where experimentation and improvisation in cancer research and treatment has been rife. Drawing on archival and ethnographic sources, we examine modelling strategies that health professionals have used to generate information about cancer in Africa from the mid 20th century to the present day. Focusing on three different case studies – anatomical models of Burkitt's lymphoma patients, diagnostic models for Kaposi sarcoma, and statistical models of the African smoking and lung cancer epidemic – we meditate on the multiplicity of models and modelling by identifying the epistemic strands that hold these representations together, as well as what sets them apart. In addition to contributing to discussions of how cancer research has taken shape beyond the Anglo-American realm, our article helps expand and complicate our understandings of what a disease model is. (shrink)

Most recent philosophical thought about the scientific representation of the world has focused on dyadic relationships between language-like entities and the world, particularly the semantic relationships of reference and truth. Drawing inspiration from diverse sources, I argue that we should focus on the pragmatic activity of representing, so that the basic representational relationship has the form: Scientists use models to represent aspects of the world for specific purposes. Leaving aside the terms "law" and "theory," I distinguish principles, specific conditions, (...) models, hypotheses, and generalizations. I argue that scientists use designated similarities between models and aspects of the world to form both hypotheses and generalizations. (shrink)

© Springer-Verlag Berlin Heidelberg 2015. When reasoning about knowledge of procedures under imperfect information, the explicit representation of epistemic possibilities blows up the S5like models of standard epistemic logic. To overcome this drawback, in this paper, we propose a new logical framework based on compact models without epistemic accessibility relations for reasoning about knowledge of procedures. Inspired by the 3-valued abstraction method in model checking, we introduce hyper models which encode the imperfect procedural information. We give a highly non-trivial (...) 2-valued semantics of epistemic dynamic logic on such models while validating all the usual S5 axioms. Our approach is suitable for applications where procedural information is ‘learned’ incrementally, as demonstrated by various examples. (shrink)

We examine two very different approaches to formalising real computation, commonly referred to as “Computable Analysis” and “the BSS approach”. The main models of computation underlying these approaches—bit computation and BSS, respectively—have also been put forward as appropriate foundations for scientific computing. The two frameworks offer useful computability and complexity results about problems whose underlying domain is an uncountable space. Since typically the problems dealt with in physical sciences, applied mathematics, economics, and engineering are also defined in uncountable domains, it (...) is fitting that we choose between these two approaches a foundational framework for scientific computing. However, the models are incompatible as to their results. What is more, the BSS model is highly idealised and unrealistic; yet, it is the de facto implicit model in various areas of computational mathematics, with virtually no problems for the everyday practice. This paper serves three purposes. First, we attempt to delineate what the goal of developing foundations for scientific computing exactly is. We distinguish between two very different interpretations of that goal, and on the separate basis of each one, we put forward answers about the appropriateness of each framework. Second, we provide an account of the fruitfulness and wide use of BSS, despite its unrealistic assumptions. Third, according to one of our proposed interpretations of the scope of foundations, the target domain of both models is a certain mathematical structure. In a clear sense, then, we are using idealised models to study a purely mathematical structure. The third purpose is to point out and explain this intriguing phenomenon and attempt to make connections with the typical case of idealised models of empirical domains. (shrink)

Neuroconstructivism (Mareschal et al. 2007a) provides a useful framework for how to integrate research from different levels of analysis to model the multidimensional dynamics of development. However, the authors overlook the topic of meaning, a fundamental feature of cognition and subjective experience and also downplay the nonlinear nature of developmental causality. Neuroconstructivism is overly optimistic on the point of how well current computational models can address the challenge of complexity in developmental science.

This paper gives an account of dimensions in the reason model found in Horty : 1–33, 2011), Horty and Bench-Capon and Rigoni :133–160, 2015. doi: 10.1007/s10506-015-9166-x). The account is constructed with the purpose of rectifying problems with the approach to incorporating dimensions in Horty, namely, the problems arising from the collapse of the distinction between the reason model and the result model on that approach. Examination of the newly constructed theory revealed that the importance of dimensions in (...) the reason model lies in their ability to establish weighings between reasons/factors of the same polarity. This permits past cases to constrain future cases in ways they could not on the reason model with just factors. The paper then discusses how dimensions might be established from a case base and how dimensions that are incomplete in various aspects might be dealt with in the theory. It closes with comparisons to other work in the literature on AI and Law and suggestions for further improvement of the reason model. (shrink)

This article discusses the desirability and feasibility of modeling precedents with multiple interpretations within factor-based models of precedential constraint. The main idea is that allowing multiple reasonable interpretations of cases and modeling precedential constraint as a function of what all reasonable interpretations compel may be advantageous. The article explains the potential benefits of extending the models in this way with a focus on incorporating a theory of vertical precedent in U.S. federal appellate courts. It also considers the costs of extending (...) the models in this way, such as the significant increase in the functional size of the case base and the need to provide some kind of ordering on interpretations to select a “best” interpretation. Finally, the article suggests partially incorporating multiple interpretations of dimensions as a realistic starting point for incorporating interpretations generally, and shows how doing so can help address difficulties with dimensions. The conclusion remarks on the use of interpretations to deal with inconsistent precedents. (shrink)

Representation and models have been the focus of considerable interest in philosophy of science for several decades. But the publication in 2008 of Bas van Fraassen’s important book Scientific representation: Paradoxes of perspective gave a novel and strong impetus to the study of their role in the dynamic of scientific knowledge, as attested by the growing quantity of papers and conferences related to representation. In science, knowing necessarily involves representing—phenomena at least and perhaps more for the scientific realist—by means (...) of mathematical structures. Even if these structures are not, as van Fraassen aptly insists, mental ideas, scientific activity is still evolving within the modern Cartesian “épistèmè de la representation” as Michel Foucault famously put it.This book is a welcome collection of exciting papers which grew out of a Workshop on representation and models organized on 11–12 March in Ferrol, at the University of A Coruña . Most papers are devoted to .. (shrink)

People use commonsense science knowledge to flexibly explain, predict, and manipulate the world around them, yet we lack computational models of how this commonsense science knowledge is represented, acquired, utilized, and revised. This is an important challenge for cognitive science: Building higher order computational models in this area will help characterize one of the hallmarks of human reasoning, and it will allow us to build more robust reasoning systems. This paper presents a novel assembled coherence theory of human conceptual change, (...) whereby people revise beliefs and mental models by constructing and evaluating explanations using fragmentary, globally inconsistent knowledge. We implement AC theory with Timber, a computational model of conceptual change that revises its beliefs and generates human-like explanations in commonsense science. Timber represents domain knowledge using predicate calculus and qualitative model fragments, and uses an abductive model formulation algorithm to construct competing explanations for phenomena. Timber then scores competing explanations with respect to previously accepted beliefs, using a cost function based on simplicity and credibility, identifies a low-cost, preferred explanation and accepts its constituent beliefs, and then greedily alters previous explanation preferences to reduce global cost and thereby revise beliefs. Consistency is a soft constraint in Timber; it is biased to select explanations that share consistent beliefs, assumptions, and causal structure with its other, preferred explanations. In this paper, we use Timber to simulate the belief changes of students during clinical interviews about how the seasons change. We show that Timber produces and revises a sequence of explanations similar to those of the students, which supports the psychological plausibility of AC theory. (shrink)

The idea that quantum randomness can be reduced to randomness of classical fields (fluctuating at time and space scales which are essentially finer than scales approachable in modern quantum experiments) is rather old. Various models have been proposed, e.g., stochastic electrodynamics or the semiclassical model. Recently a new model, so called prequantum classical statistical field theory (PCSFT), was developed. By this model a “quantum system” is just a label for (so to say “prequantum”) classical random field. Quantum (...) averages can be represented as classical field averages. Correlations between observables on subsystems of a composite system can be as well represented as classical correlations. In particular, it can be done for entangled systems. Creation of such classical field representation demystifies quantum entanglement. In this paper we show that quantum dynamics (given by Schrödinger’s equation) of entangled systems can be represented as the stochastic dynamics of classical random fields. The “effect of entanglement” is produced by classical correlations which were present at the initial moment of time, cf. views of Albert Einstein. (shrink)

Boyer's minimal model of ownership psychology suggests that joint possession triggers representations of collective agency. However, many forms of co-ownership based on cooperation or competition can be represented as a set of P() or L() tags without inferring a unifying collective entity. Moreover, representations of partible ownership are required to engage in cooperative production and distribution of resources.

We show that certain model-theoretic forcing arguments involving subsystems of second-order arithmetic can be formalized in the base theory, thereby converting them to effective proof-theoretic arguments. We use this method to sharpen the conservation theorems of Harrington and Brown-Simpson, giving an effective proof that WKL+0 is conservative over RCA0 with no significant increase in the lengths of proofs.

Thought is the primary force of humans for their survival, it consists in the use of knowledge and beliefs to determine the most appropriate action in the current situation according to a rationally inspired treatment. The usual knowledge used in practical life is based on models that are representative of reality, such as descriptions and pairs of opposites. We discuss here our thesis that these types of representations of knowledge induce restrictive effects on thought. Indeed, in particular, these two types (...) have specific characteristics that lead to binding effects on thinking such as limitation and influence. The result is a decrease in the capacity of being a rational autonomous agent harmful to one's own interests, which is characterized by deleterious behaviors: lack of reflection (resulting in), inaction, submission, imitation, being just a follower, persuasion by one's group, confusion, handing over to others... However, types of representations that are hardly more complex allow for a better consideration of one's preferences, including a type of representation that enables to move away from couples of opposites by adding neutrality, which produces a distancing from the immediacy of choices (and contrary binary alternatives) while facilitating personal appreciation. This type is in line with the mechanism for finding an optimal solution based on preferential weighting, which is one of the most widely used cognitive operations in human life. We indicate here that this type of representation is typical of neutrosophy, which is an extension of the dialectical thinking of Western philosophy. (shrink)

Today most philosophers of science believe that models play a central role in science and that one of the main functions of scientific models is to represent systems in the world. Despite much talk of models and representation, however, it is not yet clear what representation in this context amounts to nor what conditions a certain model needs to meet in order to be a representation of a certain system. In this thesis, I address these two questions. First, I (...) will distinguish three senses in which something, a vehicle, can be said to be a representation of something else, a target—which I will call respectively denotation, epistemic representation, and faithful epistemic representation—and I will argue that the last two senses are the most important in this context. I will then outline a general account of what makes a vehicle an epistemic representation of a certain target for a certain user—which, according to the account I defend, is the fact that a user adopts what I call an interpretation of the vehicle in terms of the target—and of what makes an epistemic representation of a certain target a faithful epistemic representation of it—which, according to the account I defend, is a specific sort of structural similarity between the vehicle and the target. (shrink)

A model representing isotope separation during water evaporation in plants was constructed. The model accounts for substance diffusion, convective transfer and evaporation from the surface of the leaves. The dependence of the system’s separation and enrichment coefficients on various parameters was determined. A comparison was made between the enrichment coefficients calculated from experimental data from different plants and those based on the model. Qualitative agreement between the experimental and theoretical values was obtained for the case of (...) $$\frac{uh}{D} {\gg} 1$$ uh D ≫ 1, where u is the average velocity of water in the plant, h is the height of the plant, and D is the diffusion coefficient of the substance. (shrink)

Biologists, climate scientists, and economists all rely on models to move their work forward. In this book, I explore the use of models in these and other fields to introduce readers to the various philosophical issues that arise in scientific modeling. I show that paying attention to models plays a crucial role in appraising scientific work. -/- After surveying a wide range of models from a number of different scientific disciplines, I demonstrate how focusing on models sheds light on many (...) perennial issues in philosophy of science and in philosophy in general. For example, reviewing the range of views on how models represent their targets introduces readers to the key issues in debates on representation, not only in science but in the arts as well. Also, standard epistemological questions are cast in new and interesting ways when we confront the question, "What makes for a good (or bad) model?". (shrink)