In an Isis 2008 review of research in History and Philosophy of Science (HPS), Galison opened discussion on ten on-going HPS problems. It is however unclear to what extent these problems, and constraints on their solutions, are of HPS’s own making. Recent research provides a basic resolution of these issues. In a recent paper Hooker (Perspect Sci 26(2): 266–291, 2018b) proposed that the discipline(s) of HPS should themselves also be understood to employ paradigms in HPS to understand science, analogously to (...) those employed in science to understand scientific domains. The paper argued for recognising at least two paradigms, one based on logic, and analytic forms more generally, the other based on deliberative judgement making. The present paper aims to use paradigmatic responses to Galison’s problems to explore the differing natures, merits and limitations of these two paradigms. This exploration also reveals the basic inadequacy of the analytic paradigm to illuminate the conduct of science, thereby permitting many of his problems to be dissolved rather than solved. (shrink)

Complex systems are used, studied and instantiated in science, with what con-sequences? To be clear and systematic in response it is necessary to distin-guish the consequences, for science, of science using and studying complex systems, for philosophy of science, of science using and studying complex systems, for philosophy of science, of philosophy of science modelling sci-ence as a complex system. Each of these is explored in turn, especially. While has been least studied, it will be shown how modelling science as (...) a complex process may change our conception of science and thereby query what a philosophy of science adequate to this complexity might look like. (shrink)

The point of this paper is to provide a principled framework for a naturalistic, interactivist-constructivist model of rational capacity and a sketch of the model itself, indicating its merits. Being naturalistic, it takes its orientation from scientific understanding. In particular, it adopts the developing interactivist-constructivist understanding of the functional capacities of biological organisms as a useful naturalistic platform for constructing such higher order capacities as reason and cognition. Further, both the framework and model are marked by the finitude and fallibility (...) that science attributes to organisms, with their radical consequences, and also by the individual and collective capacities to improve their performances that learning organisms display. Part A prepares the ground for the exposition through a critique of the dominant Western analytic tradition in rationalising science, followed by a brief exposition of the naturalist framework that will be employed to frame the construction. This results in two sets of guidelines for constructing an alternative. Part B provides the new conception of reason as a rich complex of processes of improvement against epistemic values, and argues its merits. It closes with an account of normativity and our similarly developing rational knowledge of it, including (reflexively) of reason itself. (shrink)

Complexity arises from interaction dynamics, but its forms are co-determined by the operative constraints within which the dynamics are expressed. The basic interaction dynamics underlying complex systems is mostly well understood. The formation and operation of constraints is often not, and oftener under appreciated. The attempt to reduce constraints to basic interaction fails in key cases. The overall aim of this paper is to highlight the key role played by constraints in shaping the field of complex systems. Following an introduction (...) to constraints, the paper develops the roles of constraints in specifying forms of complexity and illustrates the roles of constraints in formulating the fundamental challenges to understanding posed by complex systems. (shrink)

In 1895 sociologist and philosopher Georg Simmel published a paper: ‘On a connection of selection theory to epistemology’. It was focussed on the question of how behavioural success and the evolution of the cognitive capacities that underlie it are to be related to knowing and truth. Subsequently, Simmel’s ideas were largely lost, but recently an English translation was published by Coleman in this journal. While Coleman’s contextual remarks are solely concerned with a preceding evolutionary epistemology, it will be argued here (...) that Simmel pursues a more unorthodox, more radically biologically based and pragmatist, approach to epistemology in which the presumption of a wholly interests-independent truth is abandoned, concepts are accepted as species-specific and truth tied intimately to practical success. Moreover, Simmel’s position, shorn of one too-radical commitment, shares its key commitments with the recently developed interactivist–constructivist framework for understanding biological cognition and naturalistic epistemology. There Simmel’s position can be given a natural, integrated, three-fold elaboration in interactivist re-analysis, unified evolutionary epistemology and learnable normativity. (shrink)

The role of interaction in learning is essential and profound: it must provide the means to solve open problems (those only vaguely specified in advance), but cannot be captured using our familiar formal cognitive tools. This presents an impasse to those confined to present formalisms; but interaction is fundamentally dynamical, not formal, and with its importance thus underlined it invites the development of a distinctively interactivist account of life and mind. This account is provided, from its roots in the interactivist (...) biological constitution of life, through the evolution of the dual internal regulatory capacities expressed as intentionality and intelligence, to its expression in self-directed anticipative learning in persons and in science. (shrink)

A paradigm instructs in how to do research successfully. Analytic philosophy of science, currently dominant, models paradigmatic rational science as a system of logical inferences. It is, however, an abundantly inadequate paradigm. This paper presents an alternative paradigm: science as an organized collection of problem solving processes. This position is backed, on the one side, by a cognitive model of problem solving process applicable to all problem solving circumstances and, on the other, by a non-formal conception of rationality that provides (...) a wider enriched notion of rational research process than is available to the analytic paradigm. The result is a very different way of looking at science and of doing history and philosophy of science. The position is developed sufficiently to display its nature and merits. (shrink)

Error is protean, ubiquitous and crucial in scientific process. In this paper it is argued that understanding scientific process requires what is currently absent: an adaptable, context-sensitive functional role for error in science that naturally harnesses error identification and avoidance to positive, success-driven, science. This paper develops a new account of scientific process of this sort, error and success driving Self-Directed Anticipative Learning (SDAL) cycling, using a recent re-analysis of ape-language research as test example. The example shows the limitations of (...) other accounts of error, in particular Mayo’s (Error and the growth of experimental knowledge, 1996) error-statistical approach, and SDAL cycling shows how they can be fruitfully contextualised. (shrink)

: The purpose of this paper and its sister paper I (Farrell and Hooker, a) is to present, evaluate and elaborate a proposed new model for the process of scientific development: self-directed anticipative learning. The vehicle for its evaluation is a new analysis of a well-known historical episode: the development of ape language research. Paper I examined the basic features of SDAL in relation to the early history of ape-language research. In this second paper we examine the reconceptualization of ape-language (...) research following what many conceived to be Terrace's refutation of ape-language. We show that the apparent 'revolution' in our understanding of ape linguistic capacities was not based upon 'revolutionary' research different in kind from 'normal' research. The same processes of self-directed interactive exploration of possibility space, that enables a homing-in upon both error and success, is present in all phases of productive science. Moreover, conceiving science as an SDAL process explains how scientists learn how to learn about their research domain. (shrink)