Classifying is a fundamental operation in the acquisition of knowledge. Taxonomic theory can help students of cognition, evolutionary psychology, ethology, anatomy, and sociobiology to avoid serious mistakes, both practical and theoretical. More positively, it helps in generating hypotheses useful to a wide range of disciplines. Composite wholes, such as species and societies, are “individuals” in the logical sense, and should not be treated as if they were classes. A group of analogous features is a natural kind, but a group of (...) homologous features is not. Imposing hypotheses justified only on the basis of nominalist, realist, phenomenalist, or conceptualist metaphysics upon the neurophysiology of organisms or upon the causes of behavior exemplifies the “psychologist's fallacy” of William James. Levels should be distinguished from their members and from classes of levels, and the ontological status of entities ranked at levels should be made clear. It is important not to confuse such categories as substance and process with one another. Several genetical terms, such as “gene” and chromosome,” are even more equivocal than has been realized. Discussions about units of selection, behavior, and thinking suffer from the ambiguity of a “unit of” an entity. An important source of misunderstanding about natural selection is the habit of treating it as an “agent”: in an important sense, natural selection does not “act” at all. (shrink)

The aim of this paper is to clarify the role of category theory in the foundations of mathematics. There is a good deal of confusion surrounding this issue. A standard philosophical strategy in the face of a situation of this kind is to draw various distinctions and in this way show that the confusion rests on divergent conceptions of what the foundations of mathematics ought to be. This is the strategy adopted in the present paper. It is divided into 5 (...) sections. We first show that already in the set theoretical framework, there are different dimensions to the expression foundations of. We then explore these dimensions more thoroughly. After a very short discussion of the links between these dimensions, we move to some of the arguments presented for and against category theory in the foundational landscape. We end up on a more speculative note by examining the relationships between category theory and set theory. (shrink)

The holism-reductionism debate, one of the classic subjects of study in the philosopy of science, is currently at the heart of epistemological concerns in ecology. Yet the division between holism and reductionism does not always stand out clearly in this field. In particular, almost all work in ecosystem ecology and landscape ecology presents itself as holistic and emergentist. Nonetheless, the operational approaches used rely on conventional reductionist methodology.From an emergentist epistemological perspective, a set of general 'transactional' principles inspired by the (...) work of J. Dewey and J.K. Feibleman are proposed in an effort to develop a coherent ontological and methodological semantics. (shrink)

This paper presents a novel research model - Contextual Constructs Model and the theory that underpins it - Contextual Constructs Theory. First developed as part of a complex project investigating user perceptions of information quality during Web-based information re-trieval, the CCM is not a single research method per se, but is a modelled research framework providing an over-arching perspective of scientific inquiry, by which a researcher is able to iden-tify multiple possible methods of study and analysis according to the identified (...) research con-structs and their contexts. Central to CCM/CCT is that all research involves the fusion of two key elements: 1) context; and 2) cognitively-driven constructs; and that the co-dependent nature of the relationship between these two research components inform the research process and eventual outcomes. The resulting CCM is one that frames research as a contextual process of phases, in-dentifying the conceptual, philosophical, implementation, and evaluation tasks associated with a research investigation. The value of framing research within a CCM comes from its capacity to frame complex, real world phenomena since its epistemology is a blend of a critical-real world view - where reality can be both constructed and constant; within a systems-science paradigm - where constructs are not reduced to isolated parts, but investigated in terms of multiple co-constructions and the contextual relationships between them. (shrink)

The paper examines some of the significant new developments in the epistemological framing of systems theory, and their application within the information and management sciences. Specifically, the article argues that Information Systems – at its heart a systems-science – requires an ongoing discourse into how the metaphors of ‘living systems’, ‘complex systems’, and ‘complexity’ apply to the theoretical foundations of the IS discipline at large. Pragmatically, the implications of developing a complex and living systems framework to investigate IS phenomena has (...) the capacity to synthesise the very way information systems researchers consider their discipline, and the scientific inquiry of it. The “information system” becomes a decentralised, complex and evolving entity, where notions of chaos theory; system self-organisation; autopoietic and dissipative networks; emergence; entropy; and nonlinear dynamics; provide a rich and novel way to investigate system behaviours, human cognitive behaviours, and the management and business contexts in which those behaviours occur. (shrink)

Philosophers of information, according to Luciano Floridi (The philosophy of information. Oxford University Press, Oxford, 2010, p 32), study how information should be “adequately created, processed, managed, and used.” A small number of epistemologists have employed the concept of information as a cornerstone of their theoretical framework. How this concept can be used to make sense of seemingly intractable epistemological problems, however, has not been widely explored. This paper examines Fred Dretske’s information-based epistemology, in particular his response to radical epistemological (...) skepticism. We discuss the relationship between information, evidence and knowledge in relation to the problem of skepticism and the options available to an information-based epistemology for dealing with it. (shrink)

Whenever an adequate theory is found in science, we will still be left with two questions: why this theory rather than some other theory, and how should this theory be interpreted? I argue that these questions can be answered by a theory of system relations. The basic idea is that fundamental characteristics of systems, viz. those arising from the general systemic nature of those systems, cannot be comprehended with the aid of discipline-specific methods. The systems theory required should commence with (...) an analysis of the qualitatively different relations possible between systems, because it is precisely the nature of those relations that determines the basic structures of systems. That the theory of the fundamental system relations and their ontological and epistemological implications is indeed able to provide the answers sought is demonstrated in theoretical physics and Plessner's analysis of the basic structures of plant, animal and human being. (shrink)

The Recursive Bayesian Net formalism was originally developed for modelling nested causal relationships. In this paper we argue that the formalism can also be applied to modelling the hierarchical structure of mechanisms. The resulting network contains quantitative information about probabilities, as well as qualitative information about mechanistic structure and causal relations. Since information about probabilities, mechanisms and causal relations is vital for prediction, explanation and control respectively, an RBN can be applied to all these tasks. We show in particular how (...) a simple two-level RBN can be used to model a mechanism in cancer science. The higher level of our model contains variables at the clinical level, while the lower level maps the structure of the cell's mechanism for apoptosis. (shrink)

This paper seeks to contribute to the sociology of nations, a literature that is only starting to carve out its place in the social sciences. The paper offers a reconceptualization of “nations” as “national cultures”, employing an evolutionary perspective and a systemic framework in which “nations” are understood as cultural systems of a special kind. National cultures are intimately tied to natural languages, and the acquisition of a national culture occurs as part and parcel of the acquisition of a natural (...) language. Acquiring a natural language is a prerequisite for learning other cultural systems (artefactual languages as well as other natural languages). National cultures function as metacultures. They are also the reference cultures for modern states and their citizens, a political dimension of nations that is of paramount importance, though it will only be touched on in this paper. National cultures should be considered as the most fundamental type of cultural system today. (shrink)

In social science, one objection to causal analysis is that the assumption of the closure of the system makes the analysis too narrow in scope, that is, it considers only 'closed' and 'hermetic' systems thus neglecting many other external influences. On the contrary, system analysis deals with complex structures where every element is interrelated with everything else in the system. The question arises as to whether the two approaches can be compatible and whether causal analysis can be integrated into the (...) broader framework of system analysis. This article attempts a negative answer on the grounds of fundamental differences in their assumptions and suggests using system analysis as a post-hoc comparative tool. (shrink)

The anti-causal prophecies of last century have been disproved. Causality is neither a ‘relic of a bygone’ nor ‘another fetish of modern science’; it still occupies a large part of the current debate in philosophy and the sciences. This investigation into causal modelling presents the rationale of causality, i.e. the notion that guides causal reasoning in causal modelling. It is argued that causal models are regimented by a rationale of variation, nor of regularity neither invariance, thus breaking down the dominant (...) Human paradigm. The notion of variation is shown to be embedded in the scheme of reasoning behind various causal models: e.g. Rubin’s model, contingency tables, and multilevel analysis. It is also shown to be latent – yet fundamental – in many philosophical accounts. Moreover, it has significant consequences for methodological issues: the warranty of the causal interpretation of causal models, the levels of causation, the characterisation of mechanisms, and the interpretation of probability. This book offers a novel philosophical and methodological approach to causal reasoning in causal modelling and provides the reader with the tools to be up to date about various issues causality rises in social science. (shrink)