In this dissertation I achieve the following: (1) I present motivating criteria for a general comprehensive theory of scientific explanation. I review historical approaches to modeling explanation in light of these criteria. (2) I present New Mechanist Explanation ("NME") as the leading candidate for a contemporary, complete theory of scientific explanation. (3) I present constraints on the applicability of New Mechanism in modeling biology, chemistry, and physics. I argue for the unsuitability of NME as a candidate for (...) a general theory of explanation due to its significant omissions of explanatory content and subsequent incompleteness. (4) I present arguments for the indispensable explanatory power of mathematics in science, noting that much of NME's failures are owed to its poor integration of mathematical explanation as applied to science. (5) I propose a Rational-Relational theory of explanation(“RRE”). I present RRE in detail and demonstrate it as a true working general theory of explanation which best meets the motivating criteria presented in (1). I disambiguate RRE from structural explanation ("SE"). I show that historical models of explanation, including the deductive nomological (DNE) model, statistical relevance ("SRE") model, structural model (SE) and unification model ("UE") may be successfully treated as sub-classes of explanation within the scope of RRE. I provide a rubric for selecting amongst sub-theories of explanation under RRE in the purpose of highlighting particular features of relational explanations. (6) In conclusion, I argue that philosophers of science should move forward using RRE as a general model of scientific explanation as a working alternative to the incomplete model of NME. (shrink)

"Rationality: Contexts and Constraints" is an interdisciplinary reappraisal of the nature of rationality. In method, it is pluralistic, drawing upon the analytic approaches of philosophy, linguistics, neuroscience, and more. These methods guide exploration of the intersection between traditional scholarship and cutting-edge philosophical or scientific research. In this way, the book contributes to development of a suitably revised, comprehensive understanding of rationality, one that befits the 21st century, one that is adequately informed by recent investigations of science, pathology, non-human (...) thought, emotion, and even enigmatic Chinese texts that might previously have seemed to be expressions of irrationalism. Addresses recent challenges and Identifies a direction for future research on rationalityInvestigates the relationship between rationality and mental disorders, such as delusion and depressionAssesses reasoning in artificial intelligence and nonhuman animalsReflects on ancient Chinese Philosophy and possible cultural differences in human psychology Employs philosophical reflection, along with linguistic, probabilistic, and logical techniques. (shrink)

It is often thought that metaphysical grounding underwrites a distinctive sort of metaphysical explanation. However, it would be a mistake to think that all metaphysical explanations are underwritten by metaphysical grounding. In service of this claim, I offer a novel kind of metaphysical explanation called metaphysical explanation by constraint, examples of which have been neglected in the literature. I argue that metaphysical explanations by constraint are not well understood as grounding explanations.

This paper analyzes the historical context and systematic importance of Kant's hypothetical use of reason. It does so by investigating the role of hypotheses in Kant's philosophy of science. We first situate Kant’s account of hypotheses in the context of eighteenth-century German philosophy of science, focusing on the works of Wolff, Meier, and Crusius. We contrast different conceptions of hypotheses of these authors and elucidate the different theories of probability informing them. We then adopt a more systematic perspective to discuss (...) Kant's idea that scientific hypotheses must articulate real possibilities. We argue that Kant's views on the intelligibility of scientific hypotheses constitute a valuable perspective on scientific understanding and the constraints it imposes on scientific rationality. (shrink)

The study examined constraints to accessing micro credit loan scheme of Bank of Agriculture BOA among farmers in Enugu State, Nigeria Implications for extension service delivery. Purposive and simple random sampling techniques were used in selecting one hundred 100 respondents for the study. Data were collected using structured interview schedule questionnaire and analyzed using frequency, percentage, mean scores and standard deviation. The study revealed that micro credit loan scheme 88.6 were the most patronized among the rural farmers. Others such (...) as ECOWAS, IFAD project and ATHP programme were not patronized at all, probably because the type of projects sponsored by these credit loan scheme are not important to the respondents. The respondents farmers were highly constrained by late release of funds M= 1.27 , grace period too short M= 1. 17 , excessive bureaucracy M= 1. 14 , too short payback period M= 1. 13 , services not regular M= 1. 13 , among others. The Bank of Agriculture staff also noted that they were constrained by late release of approved funds by head quarters of the Bank of Agriculture M= 1.43 , loan diversion M= 1.27 , poor funding of field officers M= 1.20 , lack of awareness by borrowers M= 1.10 and insufficient staff M= 0.93 . The study recommends that adequate awareness campaign on the availability of micro credit loan scheme by Bank of Agriculture should be created in order for the beneficiaries to be knowledgeable about it. It highlights the need for approval of more funds under the scheme and timely release of funds when needed especially during planting season in order to enable the farmers to make judicious use of it for optimum productivity. Mbah Evangeline N | Jiriko, R | Agada, M.O. "Constraints to Accessing Micro-Credit and Loan Scheme of Bank of Agriculture among Farmers in Enugu State, Nigeria: Implications for Extension Service Delivery" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-4 , June 2017 . (shrink)

A naturalistic impulse has taken speculative analytic metaphysics in its critical sights. Importantly, the claim that it is desirable or requisite to give metaphysics scientific moorings rests on underlying epistemological assumptions or principles. If the naturalistic impulse toward metaphysics is to be well-founded and its prescriptions to have normative force, those assumptions or principles should be spelled out and justified. In short, advocates of naturalized or scientific metaphysics require epistemic infrastructure. This paper begins to supply it. The author (...) first sketches her conception of suitably naturalized or scientific metaphysics. She then lays out a number of candidate epistemic principles centring around the notion of theoretical constraint. The author offers several arguments for the principles, based on statistical likeliness, agreement, falsity avoidance, and methodological efficiency and inefficiency. Finally, she shows how scientific metaphysics satisfies the epistemic principles and is therefore preferable to its traditional rivals. (shrink)

This paper outlines the methodological and empirical limitations of analysing the potential relationship between complex social phenomena such as democracy and inequality. It shows that the means to assess how they may be related is much more limited than recognised in the existing literature that is laden with contradictory hypotheses and findings. Better understanding our scientific limitations in studying this potential relationship is important for research and policy because many leading economists and other social scientists such as Acemoglu and (...) Robinson mistakenly claim to identify causal linkages between inequality and democracy but at times still inform policy. In contrast to the existing literature, the paper argues that ‘structural’ or ‘causal’ mechanisms that may potentially link the distribution of economic wealth and different political regimes will remain unknown given reasons such as their highly complex and idiosyncratic characteristics, fundamental econometric constraints and analysis at the macro-level. Neither new data sources, different analysed time periods nor new data analysis techniques can resolve this question and provide robust, general conclusions about this potential relationship across countries. Researchers are thus restricted to exploring rough correlations over specific time periods and geographic contexts with imperfect data that are very limited for cross-country comparisons. (shrink)

Theoretical models are widely held as sources of knowledge of reality. Imagination is vital to their development and to the generation of plausible hypotheses about reality. But how can imagination, which is typically held to be completely free, effectively instruct us about reality? In this paper I argue that the key to answering this question is in constrained uses of imagination. More specifically, I identify make-believe as the right notion of imagination at work in modelling. I propose the first overarching (...) taxonomy of types of constraints on scientific imagination that enables knowledge of reality. And I identify two main kinds of knowledge enabled by models, knowledge of the imaginary scenario specified by models and knowledge of reality. (shrink)

This paper critiques the new mechanistic explanatory program on grounds that, even when applied to the kinds of examples that it was originally designed to treat, it does not distinguish correct explanations from those that blunder. First, I offer a systematization of the explanatory account, one according to which explanations are mechanistic models that satisfy three desiderata: they must 1) represent causal relations, 2) describe the proper parts, and 3) depict the system at the right ‘level.’ Second, I argue that (...) even the most developed attempts to fulfill these desiderata fall short by failing to appropriately constrain explanatorily apt mechanistic models. -/- *This paper used to be called "The Emperor's New Mechanisms". (shrink)

The ontic conception of explanation, according to which explanations are "full-bodied things in the world," is fundamentally misguided. I argue instead for what I call the eikonic conception, according to which explanations are the product of an epistemic activity involving representations of the phenomena to be explained. What is explained in the first instance is a particular conceptualization of the explanandum phenomenon, contextualized within a given research program or explanatory project. I conclude that this eikonic conception has a number of (...) benefits, including making better sense of scientific practice and allowing for the full range of normative constraints on explanation. (shrink)

Mechanisms play a crucial role in scientific research across various disciplines, and philosophers of science have devoted significant effort into understanding their ontology and epistemology. This paper examines the relationship between mechanisms and phenomena, highlighting the inherent dependence of mechanistic delineation on the characterization of phenomena. By acknowledging that characterizing phenomena is influenced by pragmatic considerations and research interests, the paper argues that mechanistic inquiry is inherently shaped by researchers’ perspectives. This dependence raises concerns about the possibility of a (...) realist view of mechanisms. To address these concerns, the paper explores how top-down constraints, rooted in researchers’ interests and pragmatic concerns, can be balanced by bottom-up constraints derived from empirical considerations. In conclusion, I argue that the interplay between these constraints forms an empirical and realist counterweight to the perspectival nature of top-down constraints. (shrink)

Understanding computation as “a process of the dynamic change of information” brings to look at the different types of computation and information. Computation of information does not exist alone by itself but is to be considered as part of a system that uses it for some given purpose. Information can be meaningless like a thunderstorm noise, it can be meaningful like an alert signal, or like the representation of a desired food. A thunderstorm noise participates to the generation of meaningful (...) information about coming rain. An alert signal has a meaning as allowing a safety constraint to be satisfied. The representation of a desired food participates to the satisfaction of some metabolic constraints for the organism. Computations on information and representations will be different in nature and in complexity as the systems that link them have different constraints to satisfy. Animals have survival constraints to satisfy. Humans have many specific constraints coming in addition. And computers will compute what the designer and programmer ask for. We propose to analyze the different relations between information, meaning and representation by taking an evolutionary approach on the systems that link them. Such a bottom-up approach allows starting with simple organisms and avoids an implicit focus on humans, which is the most complex and difficult case. To make available a common background usable for the many different cases, we use a systemic tool that defines the generation of meaningful information by and for a system submitted to a constraint [Menant, 2003]. This systemic tool allows to position information, meaning and representations for systems relatively to environmental entities in an evolutionary perspective. We begin by positioning the notions of information, meaning and representation and recall the characteristics of the Meaning Generator System (MGS) that link a system submitted to a constraint to its environment. We then use the MGS for animals and highlight the network nature of the interrelated meanings about an entity of the environment. This brings us to define the representation of an item for an agent as being the network of meanings relative to the item for the agent. Such meaningful representations embed the agents in their environments and are far from the Good Old Fashion Artificial Intelligence type ones. The MGS approach is then used for humans with a limitation resulting of the unknown nature of human consciousness. Application of the MGS to artificial systems brings to look for compatibilities with different levels of Artificial Intelligence (AI) like embodied-situated AI, the Guidance Theory of Representations, and enactive AI. Concerns relative to different types of autonomy and organic or artificial constraints are highlighted. We finish by summarizing the points addressed and by proposing some continuations. (shrink)

Operations research science is defined as the science that is concerned with applying scientific methods to complex problems in managing and directing large systems of people, including resources and tools in various fields, private and governmental work, peace and war, politics, administration, economics, planning and implementation in various domains. It uses scientific methods that take the language of mathematics as a basis for it and uses computer, without which it would not have been possible to achieve numerical solutions (...) to the raised problems, those that need correct solutions, when the solutions abound and the options are multiple, so we need a decision based on correct scientific foundations and takes into account all the circumstances and changes that you can encounter the decision-maker during the course of work, and nothing is left to chance or luck, but rather everything that enters into the account and plays its role in decision-making, and we get that when we use the concepts of neutrosophic science to reformulate what the science of operations research presented in terms of methods and methods to solve many practical problems, so we will present in this research a study aimed at shedding light on the most important methods used to solve nonlinear models, which is the Lagrangian multiplier method for nonlinear models constrained by equality and then reformulated using the concepts of neutrosophic science. (shrink)

The God Experiment – Let there be Light -/- The question “What is real?” can be traced back to the shadows in Plato’s cave. Two thousand years later, Rene Descartes lacked knowledge about arguing against an evil´ deceiver feeding us the illusion of sensation. Descartes’ epistemological concept later led to various theories of what our sensory experiences actually are. The concept of ”illusionism”, proposing that even the very conscious experience we have – our qualia – is an illusion, is not (...) only a red-pill scenario found in the 1999 science fiction movie ”The Matrix” but is also a philosophical concept promoted by modern tinkers, most prominently by Daniel Dennett. He describes his argument against qualia as materialistic and scientific. Reflection upon a possible simulation and our perceived reality was beautifully visualized in “The Matrix”, bringing the old ideas of Descartes to coffee houses around the world. Irish philosopher Bishop Berkeley was the father of what has later been coined as “subjective idealism”, basically stating that “what you perceive is real” (e.g., ”The Matrix” is real because its population perceives it). Berkeley then argued against Isaac Newton’s absolutism of space, time, and motion in 1721, ultimately leading to Ernst Mach and Albert Einstein’s respective views. Several neuroscientists have rejected Dennetts’ perspective on the illusion of consciousness, and idealism is often dismissed as the notion that people want to pick and choose the tenets of reality. Even Einstein ended his life on a philosophical note, pondering the very foundations of reality. With the advent of quantum technologies based on the control of individual fundamental particles, the question of whether our universe is a simulation isn’t just intriguing. Our ever-advancing understanding of fundamental physical processes will likely lead us to build quantum computers utilizing quantum effects for simulating nature quantum-mechanically in all complexity, as famously envisioned by Richard Feynman. Finding an answer to the simulation question will potentially alter our very definition and understanding of life, reshape theories on the evolution and fate of the universe, and impact theology. No direct observations provide evidence in favor or against the simulation hypothesis, and experiments are needed to verify or refute it. In this paper, we outline several constraints on the limits of computability and predictability in/of the universe, which we then use to design experiments allowing for first conclusions as to whether we participate in a simulation chain. We elaborate on how the currently understood laws of physics in both complete and small-scale universe simulations prevent us from making predictions relating to the future states of a universe, as well as how every physically accurate simulation will increase in complexity and exhaust computational resources as global thermodynamic entropy increases. Eventually, in a simulation in which the computer simulating a universe is governed by the same physical laws as the simulation and is smaller than the universe it simulates, the exhaustion of computational resources will halt all simulations down the simulation chain unless an external programmer intervenes or isn’t limited by the simulation’s physical laws, which we may be able to observe. By creating a simulation chain and observing the evolution of simulation behavior throughout the hierarchy taking stock of statistical relevance, as well as comparing various least complex simulations under computability and predictability constraints, we can gain insight into whether our universe is part of a simulation chain. -/- Index Terms—Simulation, simulation hypothesis, quantum computing, universe, life, intelligence. (shrink)

Historically left to the margins, the topics of imagination and creativity have gained prominence in philosophy of science, challenging the once dominant distinction between ‘context of discovery’ and ‘context of justification’. The aim of this chapter is to explore imagination and creativity starting from issues within contemporary philosophy of science, making connections to these topics in other domains along the way. It discusses the recent literature on the role of imagination in models and thought experiments, and their comparison with fictions. (...) It then turns to the importance of constraints on imaginings in the scientific domain, as well as whether constraints can hinder creativity. The second part of the paper focuses on the social dimensions of science. It considers imagination and creativity of scientific communities, asks whether the institution of science promotes creativity (and whether we want it to) or if it encourages conservativeness, and ends with a reflection on the politics of imagination and creativity in science. (shrink)

In the last decades, many changes have occurred in scientific publishing, including online publication, data repositories, file formats and standards. The role played by computers in this process rekindled the argument on forms of technical determinism. This paper addresses this old debate by exploring the case of publishing processes in prehistoric archaeology during the second part of the twentieth century, prior to the wide-scale adoption of computers. It investigates the case of a collective and international attempt to standardize the (...) typological analysis of prehistoric lithic objects, coined typologie analytique by Georges Laplace and developed by a group of French, Italian, and Spanish researchers. The aim of this paper is to: 1) present a general bibliometric scenario of prehistoric archaeology publishing in continental Europe; 2) report on the little-known typologie analytique method in archaeology, using publications, archives, and interviews; 3) show how the publication of scientific production was shaped by social (editorial policies, support networks) and material (typography features and publication formats) constraints; and 4) highlight how actors founded resources to control and counterbalance these effects, namely by changing and improving publishing formats. (shrink)

This dissertation explores the influence of time constraints on different research practices. The first two parts present case studies, which serve as a basis for discussing the epistemological and ethical implications of temporal limitations in scientific research. Part I is a case study on gravitational wave research, conducted by the LIGO Scientific Collaboration. This exemplifies fundamental research – without immediate societal applications, open-ended in terms of timeline and in terms of research goals. It is based, in part, (...) on qualitative interviews conducted with gravitational wave physicists. I show that considerations about time and speed play a role in every stage of research: goal setting, method design, and the evaluation and communication of results. Part II provides a case study on translational medicine, an approach explicitly dedicated to accelerating research in order to develop and implement new therapies. This epitomizes applied research with high social stakes, motivated by non-epistemic goals. Here, epistemic trade-offs between speed and reliability intersect with ethical trade-offs between different types of harms. In Part III, the insights from both of these case studies are used as the basis for a more general discussion concerning the pragmatic aspects of epistemic practices, especially in relation to current debates centered on the role of values in science. A particular focus is on the value of speed and the ability to generate reliable results, either via choice of methods, or via decisions about which goals to set, as well as decisions about when to stop further testing. The primary thesis of the dissertation is that pragmatic considerations stemming from limitations of resources are a necessary feature of the pursuit of epistemic aims, and that the epistemic is thus inherently pragmatic. (shrink)

After two centuries, the Diltheyan idea of the incommensurability of the natural and social sciences remains hegemonic. Alternative visions have since been overlooked; in this regard, the Baden neo-Kantian school showed that any divergence concerns implied method and not the phenomenal object of studies. W. Windelband coined the terms “nomological” and “idiographic” to underline how each discipline can be explained as a science of both law and events. To begin, I will show how complex thinking can expand and institute a (...) general integrative frame that overcomes the assumed incommensurability. By “complex,” I mean an anti-reductionist approach to understanding and a consequent ability to reveal the phenomenal world in terms of nested self-organized systems. Social and natural systems are persistent coalescences of individual entities showing series of interduality such as unicity and multiplicity, top-down conservation and bottom-up inno- vation, constraint of law and freedom of agencies. The two instances are maintained together by the rejection of abstracted and isolated concepts and the embrace of a general principle of indeterminacy resolving the apparent contradiction within the parallelization of the extremes as two different moments of analyses rooted in the social and natural classical methods. This paper considers both a) the Positivist attempt in the XIX century to approach the study of social phenomena in terms of law and b) the emergence of a general social science embracing the principle of acasuality, adapted from the study of the subatomic phenomenal world in quantum theory. Finally, this paper sketches how complex methodology can address historical and social studies with system theory in order to overcome classical dualities such as determinism vs. freedom, social vs. individual, and top down conservation vs. bottom up innovation in the form of an integrative parallelization. (shrink)

Dissertation Prospectus. Exploring the limits of New Mechanism as a general theory of scientific explanation, limiting its scope and proposing constraints.

Tracking technology has been heralded as transformative for animal ecology. In this paper I examine what changes are taking place, showing how current animal movement research is a field ripe for philosophical investigation. I focus first on how the devices alter the limitations and biases of traditional field observation, making observation of animal movement and behaviour possible in more detail, for more varied species, and under a broader variety of conditions, as well as restricting the influence of human presence and (...) observer bias. I reconstruct these as shifts in scope, objectivity, accuracy and fruitfulness. The second transformation is slightly less obvious but equally significant for animal ecology. Tracking devices generate complex data that demands both statistical and biological expertise, which has led to increasingly frequent and intensive collaborations between statisticians and biologists. Based on interviews, I examine how researchers in these interdisciplinary collaborations negotiate the collection, analysis and interpretation of movement data, integrating research interests, methodological constraints, previous field observations, and background theory. Tracking technology is therefore also shifting which disciplinary considerations are brought to bear on research into animal movement and behaviour and how this research is conducted. (shrink)

Social scientists appeal to various “structures” in their explanations including public policies, economic systems, and social hierarchies. Significant debate surrounds the explanatory relevance of these factors for various outcomes such as health, behavioral, and economic patterns. This paper provides a causal account of social structural explanation that is motivated by Haslanger (2016). This account suggests that social structure can be explanatory in virtue of operating as a causal constraint, which is a causal factor with unique characteristics. A novel causal framework (...) is provided for understanding these explanations–this framework addresses puzzles regarding the mysterious causal influence of social structure, how to understand its relation to individual choice, and what makes it the main explanatory (and causally responsible) factor for various outcomes. (shrink)

Scientific research is constrained by limited resources, so it is imperative that it be conducted efficiently. This paper introduces the notion of epistemic expression, a kind of representation that expedites the solution of research problems. Epistemic expressions are representations that (i) contain information in a way that enables more reliable information to place the most stringent constraints on possible solutions and (ii) make new information readily extractible by biasing the search through that space. I illustrate these conditions using (...) historical and contemporary examples of biomolecular structure determination. Then, I argue that the notion of epistemic expression parts ways with pragmatic accounts of scientific representation and an understanding of models as artifacts, neither of which require models to accurately represent. Explicating epistemic expression thus fills a gap in our understanding of scientific practice, extending Morrison and Morgan's (1999) conception of models as investigative instruments. (shrink)

In this essay we collect and put together a number of ideas relevant to the under- standing of the phenomenon of creativity, confining our considerations mostly to the domain of cognitive psychology while we will, on a few occasions, hint at neuropsy- chological underpinnings as well. In this, we will mostly focus on creativity in science, since creativity in other domains of human endeavor have common links with scientific creativity while differing in numerous other specific respects. We begin by (...) briefly introducing a few basic notions relating to cognition, among which the notion of ‘concepts’ is of basic relevance. The myriads of concepts lodged in our mind constitute a ‘conceptual space’ of an enormously complex structure, where con- cepts are correlated by beliefs that are themselves made up of concepts and are as- sociated with emotions. The conceptual space, moreover, is perpetually in a state of dynamic evolution that is once again of a complex nature. A major component of the dynamic evolution is made up of incessant acts of inference, where an inference occurs essentially by means of a succession of correlations among concepts set up with beliefs and heuristics, the latter being beliefs of a special kind, namely, ones relatively free of emotional associations and possessed of a relatively greater degree of justification. Beliefs, along with heuristics, have been described as the ‘mind’s software’, and con- stitute important cognitive components of the self-linked psychological resources of an individual. The self is the psychological engine driving all our mental and physical activity, and is in a state of ceaseless dynamics resulting from one’s most intimate ex- periences of the world accumulating in the course of one’s journey through life. Many of our psychological resources are of a dual character, having both a self-linked and a shared character, the latter being held in common with larger groups of people and imbibed from cultural inputs. We focus on the privately held self-linked beliefs of an individual, since these are presumably of central relevance in making possible inductive inferences – ones in which there arises a fundamental need of adopting a choice or making a decision. Beliefs, decisions, and inferences, all have the common link to the self of an individual and, in this, are fundamentally analogous to free will, where all of these have an aspect of non-determinism inherent in them. Creativity involves a major restructuring of the conceptual space where a sustained inferential process eventually links remote conceptual domains, thereby opening up the possibility of a large number of new correlations between remote concepts by a cascading process. Since the process of inductive inference depends crucially on de- cisions at critical junctures of the inferential chain, it becomes necessary to examine the basic mechanism underlying the making of decisions. In the framework that we attempt to build up for the understanding of scientific creativity, this role of decision making in the inferential process assumes central relevance. With this background in place, we briefly sketch the affect theory of decisions. Affect is an innate system of response to perceptual inputs received either from the exter- nal world or from the internal physiological and psychological environment whereby a positive or negative valence gets associated with a perceptual input. Almost every sit- uation faced by an individual, even one experienced tacitly, i.e., without overt aware-ness, elicits an affective response from him, carrying a positive or negative valence that underlies all sorts of decision making, including ones carried out unconsciously in inferential processes. Referring to the process of inferential exploration of the conceptual space that gener- ates the possibility of correlations being established between remote conceptual do- mains, such exploration is guided and steered at every stage by the affect system, analogous to the way a complex computer program proceeds through junctures where the program ascertains whether specified conditions are met with by way of generating appropriate numerical values – for instance, the program takes different routes, depending on whether some particular numerical value turns out to be positive or negative. The valence generated by the affect system in the process of adoption of a choice plays a similar role which therefore is of crucial relevance in inferential processes, especially in the exploration of the conceptual space where remote domains need to be linked up – the affect system produces a response along a single value dimension, resembling a number with a sign and a magnitude. While the affect system plays a guiding role in the exploration of the conceptual space, the process of exploration itself consists of the establishment of correlations between concepts by means of beliefs and heuristics, the self-linked ones among the latter having a special role in making possible the inferential journey along alternative routes whenever the shared rules of inference become inadequate. A successful access to a remote conceptual domain, necessary for the creative solution of a standing problem or anomaly – one that could not be solved within the limited domain hitherto accessed – requires a phase of relatively slow cumulative search and then, at some stage, a rapid cascading process when a solution is in sight. Representing the conceptual space in the form of a complex network, the overall process can be likened to one of self-organized criticality commonly observed in the dynamical evolution of complex systems. In order that inferential access to remote domains may actually be possible, it is necessary that restrictions on the exploration process – necessary for setting the context in ordinary instances of inductive inference – be relaxed and a relatively free exploration in a larger conceptual terrain be made possible. This is achieved by the mind going into the default mode, where external constraints – ones imposed by shared beliefs and modes of exploration – are made inoperative. While explaining all these various aspects of the creative process, we underline the supremely important role that analogy plays in it. Broadly speaking, analogy is in the nature of a heuristic, establishing correlations between concepts. However, analo- gies are very special in that these are particularly effective in establishing correlations among remote concepts, since analogy works without regard to the contiguity of the concepts in the conceptual space. In establishing links between concepts, analogies have the power to light up entire terrains in the conceptual space when a rapid cas- cading of fresh correlations becomes possible. The creative process occurs within the mind of a single individual or of a few closely collaborating individuals, but is then continued by an entire epistemic community, eventually resulting in a conceptual revolution. Such conceptual revolutions make pos- sible the radical revision of scientific theories whereby the scope of an extant theory is broadened and a new theoretical framework makes its appearance. The emerging theory is characterized by a certain degree of incommensurability when compared with the earlier one – a feature that may appear strange at first sight. But incommen- surability does not mean incompatibility and the apparently contrary features of the relation between the successive theories may be traced to the multi-layered structureof the conceptual space where concepts are correlated not by means of single links but by multiple ones, thereby generating multiple layers of correlation, among which some are retained and some created afresh in a conceptual restructuring. We conclude with the observation that creativity occurs on all scales. Analogous to correlations being set up across domains in the conceptual space and new domains being generated, processes with similar features can occur within the confines of a domain where a new layer of inferential links may be generated, connecting up sub- domains. In this context, insight can be looked upon as an instance of creativity within the confines of a domain of a relatively limited extent. (shrink)

This paper aims 1) to introduce the notion of theoretical story as a resource and source of constraint for the construction and assessment of models of phenomena; 2) to show the relevance of this notion for a better understanding of the role and nature of values in scientific activity. The reflection on the role of values and value judgments in scientific activity should be attentive, I will argue, to the distinction between models and the theoretical story that guides (...) and constrains their construction. The aim of scientific activity is to develop understanding of phenomena, and something that serves this aim and contributes to the development of understanding has a cognitive value. Cognitive values are the features that something that plays a role in scientific activity should have so that it can serve its aim. I will focus my attention on the features of the theoretical story and of the models. (shrink)

This article explores the usefulness of interdisciplinarity as method of enquiry by proposing an investigation of the concept of information in the light of semiotics. This is because, as Kull, Deacon, Emmeche, Hoffmeyer and Stjernfelt state, information is an implicitly semiotic term (Biological Theory 4(2):167–173, 2009: 169), but the logical relation between semiosis and information has not been sufficiently clarified yet. Across the history of cybernetics, the concept of information undergoes an uneven development; that is, information is an ‘objective’ entity (...) in first order cybernetics, and becomes a ‘subjective’ entity in second order cybernetics. This contradiction relegates the status of information to that of a ‘true’ or ‘false’ formal logic problem. The present study proposes that a solution to this contradiction can be found in Deely’s reconfiguration of Peirce’s ‘object’ (as found in his triadic model of semiosis) into ‘thing’ and ‘object’ (Deely 1981). This ontology allows one to argue that information is neither ‘true’ nor ‘false’, and to suggest that, when considered in light of its workability, information can be both true and false, and as such it constitutes an organism’s purely objective reality (Deely 2009b). It is stated that in the process of building such a reality, information is ‘motivated’ by environmental, physiological, emotional (including past feelings and expectations) constraints which are, in turn, framed by observership. Information is therefore found in the irreducible cybersemiotic process that links at once all these conditions and that is simultaneously constrained by them. The integration of cybernetics’ and semiotics’ understanding of information shows that history is the analytical principle that grants scientific rigour to interdisciplinary investigations. As such, in any attempt to clarify its epistemological stance (e.g. the semiotic aspect of information), it is argued that biosemiotics does not need only to acknowledge semiotics (as it does), but also cybernetics in its interdisciplinary heritage. (shrink)

Humean accounts of chance have a problem with undermining futures: they have to accept that some series of events are physically possible and have a nonzero chance but are inconsistent with the chances being what they are. This contradicts basic platitudes about chances (such as those given by Bigelow et al. (1993) and Schaffer (2007)) and leads to inconsistency between plausible constraints on credences. We show how Humeans can avoid these contradictions by drawing on metaphysically impossible worlds that are, (...) nevertheless, scientifically possible. One major advantage of our approach is that one single move deals with these both problems, whereas previous Humean approaches to undermining (such as that given by Lewis (1994), Thau (1994), and Hall (1994)) have only addressed the connection between credence and chance. Furthermore, our approach connects more closely with the way we employ stochastic scientific theories. And it’s part of a unified solution to other challenges that the Humean faces. (shrink)

In this paper, an account of theoretical integration in cognitive (neuro)science from the mechanistic perspective is defended. It is argued that mechanistic patterns of integration can be better understood in terms of constraints on representations of mechanisms, not just on the space of possible mechanisms, as previous accounts of integration had it. This way, integration can be analyzed in more detail with the help of constraintsatisfaction account of coherence between scientific representations. In particular, the account has resources to (...) talk of idealizations and research heuristics employed by researchers to combine separate results and theoretical frameworks. The account is subsequently applied to an example of successful integration in the research on hippocampus and memory, and to a failure of integration in the research on mirror neurons as purportedly explanatory of sexual orientation. (shrink)

Few things have impacted our lives as much as science and technology, but how we developed science and civilisation is one of the most challenging questions that has not yet been well explained. Attempting to identify the central driver, leading scientists have highlighted the role of culture, cooperation and geography. They focus thus on broad factors that are important basic preconditions but that we cannot directly influence. To better address the question, this paper integrates evidence from evolutionary biology, cognitive science, (...) methodology, archaeology and anthropology. The paper identifies 9 main preconditions necessary for contemporary science, which include 6 main preconditions for civilisation. Using a kind of quasi-experimental research design we observe that some cultures (experimental groups) met the preconditions while other cultures (control groups) did not. Among the preconditions, we explain how our mind's evolved methodological abilities (to observe, solve problems and experiment) have directly enabled acquiring knowledge about the world and collectively developing increasingly sophisticated methods (such as mathematics and more systematic experimentation) that have enabled science and civilisation. We have driven the major revolutions throughout our history – the palaeolithic technological and agricultural revolutions and later the so-called scientific, industrial and digital revolutions – by using our methodological abilities in new ways and developing new methods and tools, i.e. through methodological revolutions. Viewing our methods as the main mechanism through which we have directly developed scientific and technological knowledge, and thus science and civilisation, provides a new framework for understanding science and the history of science. Viewing humans as homo methodologicus, using an expanding methodological toolbox, provides a nuanced explanation of how we have been directly able to meet our needs, solve problems and develop vast bodies of technological and scientific knowledge. By better understanding the origin and foundations of science, we can better understand their limits and, most importantly, how to push those limits. We can do so especially by addressing the evolved cognitive constraints and biases we face and improving the methods we use. (shrink)

⦿ In my dissertation I introduce, motivate and take the first steps in the implementation of, the project of naturalising modal metaphysics: the transformation of the field into a chapter of the philosophy of science rather than speculative, autonomous metaphysics. -/- ⦿ In the introduction, I explain the concept of naturalisation that I apply throughout the dissertation, which I argue to be an improvement on Ladyman and Ross' proposal for naturalised metaphysics. I also object to Williamson's proposal that modal metaphysics (...) --- or some view in the area --- is already a quasi-scientific discipline. -/- ⦿ Recently, some philosophers have argued that the notion of metaphysical modality is as ill defined as to be of little theoretical utility. In the second chapter I intend to contribute to such skepticism. First, I observe that each of the proposed marks of the concept, except for factivity, is highly controversial; thus, its logical structure is deeply obscure. With the failure of the "first principles" approach, I examine the paradigmatic intended applications of the concept, and argue that each makes it a device for a very specific and controversial project: a device, therefore, for which a naturalist will find no use for. I conclude that there is no well-defined or theoretically useful notion of objective necessity other than logical or physical necessity, and I suggest that naturalising modal metaphysics can provide more stable methodological foundations. -/- ⦿ In the third chapter I answer a possible objection against the in-principle viability of the project: that the concept of metaphysical modality cannot be understood through the philosophical analysis of any scientific theory, since metaphysical necessity "transcends'' natural necessity, and science only deals with the latter. I argue that the most important arguments for this transcendence thesis fail or face problems that, as of today, remain unsolved. -/- ⦿ Call the idea that science doesn't need modality, "demodalism''. Demodalism is a first step in a naturalistic argument for modal antirealism. In the fourth chapter I examine six versions of demodalism to explain why a family of formalisms, that I call "spaces of possibility'', are (i) used in a quasi-ubiquitous way in mathematised sciences (I provide examples from theoretical computer science to microeconomics), (ii) scientifically interpreted in modal terms, and (iii) used for at least six important tasks: (1) defining laws and theories; (2) defining important concepts from different sciences (I give several examples); (3) making essential classifications; (4) providing different types of explanations; (5) providing the connection between theory and statistics, and (6) understanding the transition between a theory and its successor (as is the case with quantisation). -/- ⦿ In fifth chapter I propose and defend a naturalised modal ontology. This is a realism about modal structure: my realism about constraints. The modal structure of a system are the relationships between its possible states and between its possible states and those of other systems. It is given by the plurality of restrictions to which said system is subject. A constraint is a factor that explains the impossibility of a class of states; I explain this concept further. First, I defend my point of view by rejecting some of its main rivals: constructive empiricism, Humean conventionalism, and wave function realism, as they fail to make sense of quantum chaos. This is because the field requires the notion of objective modal structure, and the mentioned views have trouble explaining the modal facts of quantum dynamics. Then, I argue that constraint realism supersedes these views in the context of Bohm's standard theory and mechanics, and underpins the study of quantum chaos. Finally, I consider and reject two possible problems for my point of view. -/- ⦿ A central concern of modal metaphysicians has been to understand the logical system that best characterises necessity. In the sixth chapter I intend to recover the logical project applied to my naturalistic modal metaphysics. Scientists and philosophers of science accept different degrees of physical necessity, ranging from purely mathematically necessary facts that restrict physical behaviour, to kinetic principles, to particular dynamical constraints. I argue that this motivates a multimodal approach to modal logic, and that the time dependence of dynamics motivates a logic of historical necessity. I propose multimodal propositional (classical) logics for Bohmian mechanics and the Everettian theory of many divergent worlds, and I close with a criticism of Williamson's approach to the logic of state spaces of dynamic systems. (shrink)

Inspired by Bas van Fraassen’s Stance Empiricism, Anjan Chakravartty has developed a pluralistic account of what he calls epistemic stances towards scientific ontology. In this paper, I examine whether Chakravartty’s stance pluralism can exclude epistemic stances that licence pseudo-scientific practices like those found in Scientology. I argue that it cannot. Chakravartty’s stance pluralism is therefore prone to a form of debilitating relativism. I consequently argue that we need (1) some ground or constraint in relation to which epistemic stances (...) can be ranked by degrees, and (2) some way to demarcate science from pseudo-science so that we know what epistemic stances are about. Regarding (1), I argue that empirical detectability can serve as the ground in relation to which epistemic stances are ranked by degrees. Regarding (2), I argue for ranking sciences on a continuum according to established institutional criteria, rather than attempting to draw a strict demarcation. (shrink)

When do objects at different times compose a further object? This is the question of diachronic composition. The universalist answers, ‘under any conditions whatsoever’. Others argue for restrictions on diachronic composition: composition occurs only when certain conditions are met. Recently, some philosophers have argued that restrictions on diachronic compositions are motivated by our best physical theories. In Persistence and Spacetime and elsewhere, Yuri Balashov argues that diachronic compositions are restricted in terms of causal connections between object stages. In a recent (...) article, Nikk Effingham argues that the standard objections to views that endorse restrictions on composition do not apply to a view that restricts composition according to compliance with the laws of nature. On the face of it, such restrictions on diachronic composition preserve our common-sense ontology while eliminating from it scientifically revisionary objects that travel faster than the speed of light. I argue that these attempts to restrict diachronic composition by appealing to either causal or nomological constraints face insurmountable difficulties within the context of special relativity. I discuss how the universalist should best respond to Hudson’s argument for superluminal objects, and in doing so, I present and defend a new sufficient condition for motion that does not entail that such objects are in superluminal motion. 1 Introduction2 Diachronic Composition3 Diachronic Composition and Superluminal Objects4 Restricting Diachronic Composition5 Causal and Nomological Restrictions on Composition in a Relativistic Context6 Superluminal Objects and Motion7 Conclusion. (shrink)

Biosemiotics and Semiotics have similarities and differences. Both deal with signal and meaning. One difference is that Biosemiotics covers a domain (life) that is less complex that the one addressed by Semiotics (human). We believe that this difference can be used to have Biosemiotics bringing added value to Semiotics. This belief is based on the fact that a theory of meaning is easier to build up for living elements than for humans, and that the results obtained for life can make (...) available some tools for a higher level of complexity. Semiotic has been encountering some difficulties to deliver a scientific theory of meaning that can be efficient at the level of human mind. The obstacles come from our ignorance on the nature of human. As it is true that we do not understand the nature of human mind on a scientific basis. On the other hand, the nature and properties of life are better understood. And we can propose a modelization for a generation of meaningful information in the field of elementary life. Once such a modelization is established, it is possible to look at extending it to the domain of human life. Such an approach on a theory of meaning (begininig in Biosemiotics and aiming at Semiotics), is what we present in this paper. Taking an elementary living element as reference, we introduce the bases of a systemic theory of meaning. Using a simple living system submitted to a constraint, we define a meaningful information, a meaning generator system and some elements related to meaningful information transmission. We then try to identify the hypothesis that need to be taken into account so the results obtained for living elements can be extended to human. (shrink)

Human freedom is in tension with nomological determinism and with statistical determinism. The goal of this paper is to answer both challenges. Four contributions are made to the free-will debate. First, we propose a classification of scientific theories based on how much freedom they allow. We take into account that indeterminism comes in different degrees and that both the laws and the auxiliary conditions can place constraints. A scientific worldview pulls towards one end of this classification, while (...) libertarianism pulls towards the other end of the spectrum. Second, inspired by Hoefer, we argue that an interval of auxiliary conditions corresponds to a region in phase space, and to a bundle of possible block universes. We thus make room for a form of non-nomological indeterminism. Third, we combine crucial elements from the works of Hoefer and List; we attempt to give a libertarian reading of this combination. On our proposal, throughout spacetime, there is a certain amount of freedom that can be interpreted as the result of agential choices. Fourth, we focus on the principle of alternative possibilities throughout and propose three ways of strengthening it. (shrink)

This paper aims to better motivate the naturalization of metaphysics by identifying and criticizing a class of theories I call ’free range metaphysics’. I argue that free range metaphysics is epistemically inadequate because the constraints on its content—consistency, simplicity, intuitive plausibility, and explanatory power—are insufficiently robust and justificatory. However, since free range metaphysics yields clarity-conducive techniques, incubates science, and produces conceptual and formal tools useful for scientifically engaged philosophy, I do not recommend its discontinuation. I do recommend, however, ending (...) the discipline’s bad faith. That is, I urge that free range metaphysics not be taken to have fully satisfactory epistemic credentials over and above its pragmatic ones. (shrink)

The aim of this study is to justify the belief that there are biological normative mechanisms that fulfill non-trivial causal roles in the explanations (as formulated by researchers) of actions and behaviors present in specific systems. One example of such mechanisms is the predictive mechanisms described and explained by predictive processing (hereinafter PP), which (1) guide actions and (2) shape causal transitions between states that have specific content and fulfillment conditions (e.g. mental states). Therefore, I am guided by a specific (...) theoretical goal associated with the need to indicate those conditions that should be met by the non-trivial theory of normative mechanisms and the specific models proposed by PP supporters. In this work, I use classical philosophical methods, such as conceptual analysis and critical reflection. I also analyze selected studies in the field of cognitive science, cognitive psychology, neurology, information theory and biology in terms of the methodology, argumentation and language used, in accordance with their theoretical importance for the issues discussed in this study. In this sense, the research presented here is interdisciplinary. My research framework is informed by the mechanistic model of explanation, which defines the necessary and sufficient conditions for explaining a given phenomenon. The research methods I chose are therefore related to the problems that I intend to solve. In the introductory chapter, “The concept of predictive processing”, I discuss the nature of PP as well as its main assumptions and theses. I also highlight the key concepts and distinctions for this research framework. Many authors argue that PP is a contemporary version of Kantianism and is exposed to objections similar to those made against the approach of Immanuel Kant. I discuss this thesis and show that it is only in a very general sense that the PP framework is neo-Kantian. Here we are not dealing with transcendental deduction nor with the application of transcendental arguments. I argue that PP is based on reverse engineering and abduction inferences. In the second part of this chapter, I respond to the objection formulated by Dan Zahavi, who directly accuses this research framework of anti-realistic consequences. I demonstrate that the position of internalism, present in the so-called conservative PP, does not imply anti-realism, and that, due to the explanatory role played in it by structural representations directed at real patterns, it is justified to claim that PP is realistic. In this way, I show that PP is a non-trivial research framework, having its subject, specific methods and its own epistemic status. Finally, I discuss positions classified as the socalled radical PP. In the chapter “Predictive processing as a Bayesian explanatory model” I justify the thesis according to which PP offers Bayesian modeling. Many researchers claim that the brain is an implemented statistical probabilistic network that is an approximation of the Bayesian 7 rule. In practice, this means that all cognitive processes are to apply Bayes' rule and can be described in terms of probability distributions. Such a solution arouses objections among many researchers and is the subject of wide criticism. The purpose of this chapter is to justify the thesis that Bayesian PP is a non-trivial research framework. For this purpose, I argue that it explains certain phenomena not only at the computational level described by David Marr, but also at the level of algorithms and implementation. Later in this chapter I demonstrate that PP is normative modeling. Proponents of the use of Bayesian models in psychology or decision theory argue that they are normative because they allow the formulation of formal rules of action that show what needs to be done to make a given action optimal. Critics of this approach emphasize that such thinking about the normativity of Bayesian modeling is unjustified and that science should shift from prescriptive to descriptive positions. In a polemic with Shira Elqayam and Jonathan Evans (2011), I show that the division they propose into prescriptivism and Bayesian descriptivism is apparent, because, as I argue, there are two forms of prescriptivism, i.e. the weak and the strong. I argue that the weak version is epistemic and can lead to anti-realism, while the strong version is ontic and allows one to justify realism in relation to Bayesian models. I argue that a weak version of prescriptivism is valid for PP. It allows us to adopt anti-realism in relation to PP. In practice, this means that you can explain phenomena using Bayes' rule. This does not, however, imply that they are Bayesian in nature. However, the full justification of realism in relation to the Bayesian PP presupposes the adoption of strong prescriptivism. This position assumes that phenomena are explained by Bayesian rule because they are Bayesian as such. If they are Bayesian in nature, then they should be explained using Bayesian modeling. This thesis will be substantiated in the chapters “Normative functions and mechanisms in the context of predictive processing” and “Normative mechanisms and actions in predictive processing”. In the chapter “The Free Energy Principle in predictive processing”, I discuss the Free Energy Principle (hereinafter FEP) formulated by Karl Friston and some of its implications. According to this principle, all biological systems (defined in terms of Markov blankets) minimize the free energy of their internal states in order to maintain homeostasis. Some researchers believe that PP is a special case of applying this principle to cognition, and that predictive mechanisms are homeostatic mechanisms that minimize free energy. The discussion of FEP is important due to the fact that some authors consider it to be important for explanatory purposes and normative. If this is the case, then FEP turns out to be crucial in explaining normative predictive mechanisms and, in general, any normative biological mechanisms. To define the explanatory possibilities of this principle, I refer to the discussion of its supporters on the issue they define as the problem of continuity and discontinuity between life and mind. A critical analysis of this discussion and the additional arguments I have formulated have allowed me to revise the explanatory ambitions of FEP. I also reject the belief that this principle is necessary to explain the nature of predictive mechanisms. I argue that the principle formulated and defended by Friston is an important research heuristic for PP analysis. 8 In the chapter “Normative functions and mechanisms in predictive processing”, I start my analyzes by formulating an answer to the question about the normative nature of homeostatic mechanisms. I demonstrate that predictive mechanisms are not homeostatic. I defend the view that a full explanation of normative mechanisms presupposes an explanation of normative functions. I discuss the most important proposals for understanding the normativity of a function, both from a systemic and teleosemantic perspective. I conclude that the non-trivial concept of a function must meet two requirements which I define as explanatory and normative. I show that none of the theories I have invoked satisfactorily meets both of these requirements. Instead, I propose a model of normativity based on Bickhard's account, but supplemented by a mechanistic perspective. I argue that a function is normative when: (1) it allows one to explain the dysfunction of a given mechanism; (2) it contributes to the maintenance of the organism's stability by shaping and limiting possible relations, processes and behaviors of a given system; and when (3) (according to the representational and predictive functions) it enables explaining the attribution of logical values of certain representations / predictions. In such an approach, a mechanism is normative when it performs certain normative functions and when it is constitutive for a specific action or behavior, despite the fact that for some reason it cannot realize it either currently or in the long-term. Such an understanding of the normativity of mechanisms presupposes the acceptance of the epistemic hypothesis. I argue that this hypothesis is not cognitively satisfactory, and therefore the ontic hypothesis should be justified, which is directly related to adopting the position of ontic prescriptivism. For this reason, referring to the mechanistic theory of scientific explanations, I formulate an ontical interpretation of the concept of a normative mechanism. According to this approach, a mechanism or a function is normative when they perform such and such causal roles in explaining certain actions and behaviors. With regard to the normative properties of predictive mechanisms and functions, this means that they are the causes of specific actions an organism carries out in the environment. In this way, I justify the necessity of accepting the ontic hypothesis and rejecting the epistemic hypothesis. The fifth chapter, “Normative mechanisms and actions in predictive processing”, is devoted to the dark room problem and the related exploration-exploitation trade-off. A dark room is the state that an agent could be in if it minimized the sum of all potential prediction errors. I demonstrate that, in accordance with the basic assumption of PP about the need for continuous and long-term minimization of prediction errors, such a state should be desirable for the agent. Is it really so? Many authors believe it is not. I argue that the test of the value of PP is the possibility of a non-trivial solution of this problem, which can be reduced to the choice between active and uncertainty-increasing exploration and safe and easily predictable exploitation. I show that the solution proposed by PP supporters present in the literature does not enable a fully satisfactory explanation of this dilemma. Then I defend the position according to which the full explanation of the normative mechanisms, and, subsequently, the solution to the dilemma of exploration and exploitation, involves reference to the existence of constraints present in the environment. The constraints 9 include elements of the environment that make a given mechanism not only causal but also normative. They are therefore key to explaining the predictive mechanisms. They do not only play the role of the context in which the mechanism is implemented, but, above all, are its constitutive component. I argue that the full explanation of the role of constraints in normative predictive mechanisms presupposes the integration of individual models of specific cognitive phenomena, because only the mechanistic integration of PP with other models allows for a non-trivial explanation of the nature of normative predictive mechanisms that would have a strong explanatory value. The explanatory monism present in many approaches to PP makes it impossible to solve the problem of the dark room. Later in this chapter, I argue that the Bayesian PP is normative not because it enables the formulation of such and such rules of action, but because the predictive mechanisms themselves are normative. They are normative because they condition the choice of such and such actions by agents. In this way, I justify the hypothesis that normative mechanisms make it possible to explain the phenomenon of agent motivation, which is crucial for solving the dark room problem. In the last part of the chapter, I formulate the hypothesis of distributed normativity, which assumes that the normative nature of certain mechanisms, functions or objects is determined by the relations into which these mechanisms, functions or objects enter. This means that what is normative (in the primary sense) is the relational structure that constitutes the normativity of specific items included in it. I suggest that this hypothesis opens up many areas of research and makes it possible to rethink many problems. In the “Conclusion”, I summarize the results of my research and indicate further research perspectives. (shrink)

A model of metaphysics associated with EJ Lowe and Tuomas Tahko sees metaphysics as involving a priori knowledge of possible essences, or at least modal facts, and delimiting the actual ‘ontological categories,’ the ultimate and essential divisions of what exists, based on the results of a posteriori scientific investigation. Their approach to metaphysics has been criticized by those who argue that such metaphysics is unsuitably a priori, disconnected with empirical research in natural science, and ends up failing to provide (...) meaningful constraints on metaphysical theorization. I present different epistemological and semantic worries about these accounts to motivate an alternative perspective on which metaphysics centers on form, rather than possibility. This scholastic perspective is shown to incorporate the skeptical insights as constitutive of its approach to existence, by way of the position that ‘being’ is not a genus. Rather, ‘being’ is a determinable. The scholastic approach can thus provide responses to the skeptics, since it denies that ontological categories – in the Lowe/Tahko sense – are what metaphysicians investigate and proposes a different view of ontological categories as classes of forms. (shrink)

Acknowledging that Nature is one unified whole, we expect that physics and biology are intimately related. Keeping in mind that physics became an exact science with which we are already familiar with, while, apparently, we do not have at present a similar knowledge about biology, we consider how can we make useful the clarity of physics to shed light to biology. The next question will be what are the most basic categories of physics and biology. If we do not want (...) to cut laws of Nature into different parts, we obtain a constraint, and the remaining part of physics will be the input data to the equations of physics. In these terms, our question will be: if we keep biological laws intact, as indivisible units, what remains in case of biology? This approach, just because it is more fundamental, has significant consequences for philosophy, and obviously offers a new conceptual framework considering the relation between the ontopoietic principle of Anna-Teresa Tymieniecka and the biological principle. The quintessence of science, namely, the first essentially complete scientific world picture is presented in a detailed form. (shrink)

Reasoning from a naturalistic perspective, viewing the mind as an evolved biological organ with a particular structure and function, a number of influential philosophers and cognitive scientists claim that science is constrained by human nature. How exactly our genetic constitution constrains scientific representations of the world remains unclear. This is problematic for two reasons. Firstly, it often leads to the unwarranted conclusion that we are cognitively closed to certain aspects or properties of the world. Secondly, it stands in the (...) way of a nuanced account of the relationship between our cognitive and perceptual wiring and scientific theory. In response, I propose a typology or classification of the different kinds of biological constraints and their sources on science. Using Boden’s notion of a conceptual space, I distinguish between constraints relating to the ease with which we can reach representations within our conceptual space and constraints causing possible representations to fall outside of our conceptual space. This last kind of constraints does not entail that some aspects or properties of the world cannot be represented by us – as argued by advocates of ‘cognitive closure’ – merely that some ways of representing the world are inaccessible to us. It relates to what Clark and Rescher have framed as ‘the alien scientist hypothesis’. The purpose of this typology is to provide some much needed clarity and structure to the debate about biological constraints on science. (shrink)

Even if the “value-free ideal of science” (VFI) were an unattainable goal, one could ask: can it be a useful fiction, one that is beneficial for the research community and society? This question is particularly crucial for scholars and institutions concerned with research integrity (RI), as one cannot offer normative guidance to researchers without making some assumptions about what ideal scientific research looks like. Despite the insofar little interaction between scholars studying RI and those working on values in science, (...) the overlap of topics and interests make collaboration between the two fields promising for understanding research and its ethics. Here, we identify—for the use of RI scholars—the non-epistemic reasons (societal, political, professional) for and against the VFI considered in the literature. All of these are concerned with the beneficial or detrimental consequences that endorsing the VFI would have on society, policy-making, or the scientific community, with some authors appealing to the same principles to argue for opposite positions. Though most of the reviewed articles do not endorse the VFI, it is generally agreed that some constraints have to be put on the use of non-epistemic values. Disagreement on the utility of the VFI lies both on the different epistemic-descriptive positions taken by different authors, and on the scarcity of relevant empirical studies. Engaging critically with the reasons here identified and more in general with the values in science debate will help the RI community decide whether the VFI should be included in future codes of conduct. (shrink)

The physiological constraints of our neuro-sensory instrumentation limit the information we receive and from which we fashion our impressions. These limitations precede the psychological issues of data generation and analysis described by Ioannidis [1]. Scientific models widely accepted for at least 50 years [2,3] suggest that the peripheral and central nervous systems do not provide direct information about phenomena as they exist in nature. Instead, perceptible phenomena stimulate sense organs to produce nerve impulses. Sensory nerve impulses are not (...) replicas of the phenomena stimulating their production. The brain, by obscure mechanisms, then fabricates personal experience from the sensory nerve impulses. The relationship of phenomena to the brain's experiential construct is unknown. Since evidence is produced by sense organs and the brain (neither of which incorporates bona fide replicas of phenomena), all scientific conclusions are likely false in the sense that they are not based on direct knowledge of phenomena as they exist in nature. (shrink)

The aim of this study was to identify the obstacles facing the application of knowledge management and its impact on performance at Palestine Technical University-Kadoorei from the point of view of employees and to detect the differences between the average views of the study sample on the subject of the study according to some variables such as (gender, nature of work, Education Level, specialization, years of experience). The study followed the descriptive analytical method and the questionnaire as a tool for (...) study. It was distributed to 74 employees. After the questionnaire was distributed, the data was collected and coded and entered into the computer and processed statistically using the SPSS program. The study found that the percentage of approval of the obstacles to the application of knowledge management at Palestine Technical University-Kadoorei differed between few and large, and the relative weight of the axis was complete (68.2). The degree of awareness of the workers of the reality of performance excellence at the University of Palestine Technical-Kadoorei was between medium and very large. There is an impact of the constraints of the application of knowledge management on performance excellence at Palestine Technical University-Kadoorei. In light of the results of the previous study, the researchers recommended that the importance of knowledge management should be taken into account in order to raise the university's reputation and reputation at home and abroad and improve its services to students and the local community. And to promote the exchange of experiences and knowledge with local, regional and international universities in order to enhance the knowledge and preserve it and provide modern and sophisticated scientific techniques and use them in administrative and academic work at the university. (shrink)

This chapter critically analyzes evolutionary epistemology as a theoretical framework for the study of science as a historical and cultural phenomenon. As spelled out by Campbell in the 1970s, evolutionary epistemology has an ambitious goal: it aims at understanding the complex relations between bio- logical evolution, especially the biological evolution of human cognition, and the cultural evolution of scientific knowledge. It eventually aims at forming an integrated causal theory of the evolution of science, starting with the evo- lution of (...) human cognition. In this chapter, the author considers Campbell’s project and specifies why it is still today a worthwhile project for explain- ing the evolution of science as a specific case of cultural evolution. But he also criticizes Campbell’s evolutionary epistemology for assuming that blind variation and selective retention are the processes through which science evolves. This assumption, the author argues, is at odds with much of what we know about scientific cognition and the history of science. He advocates (1) dropping the methodological constraint of looking for processes of blind variation and selective retention at the expense of other constructive processes and mechanisms of knowledge production; but (2) retaining the integrative point of evolutionary epistemology, which implies taking seriously the results of evolutionary psychology; and (3) retaining the populational framework for explaining the history of science, which means questioning why some scientific beliefs and practices eventually spread and stabilize in a scientific community. We end up with an updated research program for evolutionary epistemology, which faces new challenges. (shrink)

This paper examines the following three questions: (1) In The Rose Garden of Mystery (Golshan-e Rāz), how does the prominent 7-8th-century Iranian Sufi, Maḥmūd Shabistarī, distinguish the mystical “contemplation” and “rational reflection” in pursuing divine knowledge? (2) Was Shabistarī an anti-rationalist (strict fideist)? (3) How does Shabistarī’s position fit into the ancient Greek, Neoplatonist, and medieval Islamic and Christian metaphysics? This paper examines Golshan-e Rāz in the context of Shabistarī’s other works, commentaries, secondary sources, and Islamic thought—Sufism and philosophy. Existing (...) literature on Golshan-e Rāz primarily focuses on its literary aspects, neglecting its philosophical and mystical concepts. However, a thorough understanding requires examining these concepts in a broad context, which will inspire further research. The rationale behind this research is rooted in the religious obligation for believers to know God, with “thinking” as the means to acquire such knowledge. This is why the first question Herawī poses to Shabistarī pertains to the nature of thought—justifying this paper’s focus. Contemporary opposition to religion often stems from its perceived incongruity with the rational frameworks offered by positivism, materialism, or scientific inquiry. By differentiating between mystical and rational modes of thought that Shabistarī presents, this study shows the contemporary person that intellectual inquiry extends beyond rationalism and encompasses mysticism. Consequently, rational and mystical perspectives should be pursued in the quest for the divine. Furthermore, this study contends that Shabistarī should not be regarded as a strict fideist; instead, his criticism is directed toward the constraints inherent in rational thinking. (shrink)

Kant’s notorious remark about the impossibility of there ever being a Newton of a blade of grass has often been interpreted as a misguided pre-emptive strike against Darwin and evolutionary theories in general: 'It would be absurd for humans even to make such an attempt or to hope that there may yet arise a Newton who could make comprehensible even the generation of a blade of grass according to natural laws that no intention has ordered; rather, we must absolutely deny (...) this insight to human beings. (CPJ 5:400) My aim in this chapter is to re-evaluate this claim in the context of Kant’s account of organic generation and argue that, contrary to what is usually thought, it does leave room for the possibility of evolution. After spelling out the constraints Kant identifies for any scientific study of the history of living beings, I examine his theory of generation and draw its implications for biological heredity, species diversity, and the role played by environmental factors in organic development. On this basis, I conclude that first, evolution is a possible albeit far-fetched hypothesis for Kant; second, Darwin’s theory of natural selection would have turned a far-fetched possibility into a plausible candidate; and third, it would not have disposed of the need for teleology. This is why, I argue, Darwin could never have been a Newton of a blade of grass. (shrink)

There is broad agreement among social researchers and social ontologists that the project of dividing humans into social kinds should be guided by at least two methodological commitments. First, a commitment to what best serves moral and political interests, and second, a commitment to describing accurately the causal structures of social reality. However, researchers have not sufficiently analyzed how these two commitments interact and constrain one another. In the absence of that analysis, several confusions have set in, threatening to undermine (...) shared goals for the responsible modeling of social kinds of humans. This essay first explains the source and substance of these confusions. Then, by distinguishing different value-laden investigative questions into the classification of social kinds of humans, it sets out specific relations of dependence and constraint between empirically-driven investigations and value-driven investigations into social kinds of humans. The result is a more detailed and fruitful framework for thinking about the classification of social kinds that respects both normative interests and mind-independent causal regularities. (shrink)

Our moral convictions cannot, on the face of it, count in evidence against scientific claims with which they happen to conflict. Moral anti-realists of whatever stripe can explain this easily: science is immune to moral refutation because moral discourse is defective as a trustworthy source of true and objective judgments. Moral realists, they can add, are unable to explain this immunity. After describing how anti-realists might implement this reasoning, the paper argues that the only plausible realist comeback turns on (...) the practical nature of moral reasoning. This comeback, however, places significant constraints on the structure of evidence for moral judgments. These constraints cannot be met by coherentist defenders of reflective-equilibrium methodology or by anyone sympathetic to bottom-up, case-driven foundationalism, including those who claim we have perceptual or perception-like access to moral truths. Unfortunately for realists in these categories, alternative realism-friendly accounts of science’s apparent moral immunity are unpromising. These neither explain nor explain away our unwillingness to infer an is from an ought, as Hume might have put it. Science’s apparent immunity to moral refutation therefore poses a serious problem for any realist unhappy with top-down, theory-driven conceptions of the structure of moral evidence. (shrink)

My aim in this paper is to give a philosophical analysis of the relationship between contingently available technology and the knowledge that it makes possible. My concern is with what specific subjects can know in practice, given their particular conditions, especially available technology, rather than what can be known “in principle” by a hypothetical entity like Laplace’s Demon. The argument has two parts. In the first, I’ll construct a novel account of epistemic possibility that incorporates two pragmatic conditions: responsibility and (...) practicability. For example, whether subjects can gain knowledge depends in some circumstances on whether they have the capability of gathering relevant evidence. In turn, the possibility of undertaking such investigative activities depends in part on factors like ethical constraints, economical realities, and available technology. In the second part of the paper, I’ll introduce “technological possibility” to analyze the set of actions made possible by available technology. To help motivate the problem and later test my proposal, I’ll focus on a specific historical case, one of the earliest uses of digital electronic computers in a scientific investigation. I conclude that the epistemic possibility of gaining access to scientific knowledge about certain subjects depends (in some cases) on the technological possibility for making responsible investigations. (shrink)

A natural suggestion and increasingly popular account of how to revise our logical beliefs treats revision of logic analogously to the revision of scientific theories. I investigate this approach and argue that simple applications of abductive methodology to logic result in revision-cycles, developing a detailed case study of an actual dispute with this property. This is problematic if we take abductive methodology to provide justification for revising our logical framework. I then generalize the case study, pointing to similarities with (...) more recent and popular heterodox logics such as naïve logics of truth. I use this discussion to motivate a constraint—logical partisanhood—on the uses of such methodology: roughly: both the proposed alternative and our actual background logic must be able to agree that moving to the alternative logic is no worse than staying put. (shrink)

Reasoning from inconclusive evidence, or ‘induction’, is central to science and any applications we make of it. For that reason alone it demands the attention of philosophers of science. This Element explores the prospects of using probability theory to provide an inductive logic, a framework for representing evidential support. Constraints on the ideal evaluation of hypotheses suggest that overall support for a hypothesis is represented by its probability in light of the total evidence, and incremental support, or confirmation, indicated (...) by an increased probability given the evidence than otherwise. This proposal is shown to have the capacity to reconstruct many canons of the scientific method and inductive inference. Along the way, significant objections are discussed, such as the challenge from inductive scepticism and the objection that the probabilistic approach makes evidential support arbitrary. (shrink)

In this paper, I consider the relationship between Inference to the Best Explanation and Bayesianism, both of which are well-known accounts of the nature of scientific inference. In Sect. 2, I give a brief overview of Bayesianism and IBE. In Sect. 3, I argue that IBE in its most prominently defended forms is difficult to reconcile with Bayesianism because not all of the items that feature on popular lists of “explanatory virtues”—by means of which IBE ranks competing explanations—have confirmational (...) import. Rather, some of the items that feature on these lists are “informational virtues”—properties that do not make a hypothesis \ more probable than some competitor \ given evidence E, but that, roughly-speaking, give that hypothesis greater informative content. In Sect. 4, I consider as a response to my argument a recent version of compatibilism which argues that IBE can provide further normative constraints on the objectively correct probability function. I argue that this response does not succeed, owing to the difficulty of defending with any generality such further normative constraints. Lastly, in Sect. 5, I propose that IBE should be regarded, not as a theory of scientific inference, but rather as a theory of when we ought to “accept” H, where the acceptability of H is fixed by the goals of science and concerns whether H is worthy of commitment as research program. In this way, IBE and Bayesianism, as I will show, can be made compatible, and thus the Bayesian and the proponent of IBE can be friends. (shrink)