Economic competitive advantage depends on innovation, which in turn requires pushing back the frontiers of various kinds of knowledge. Although understanding how knowledge grows ought to be a central topic of epistemology, epistemologists and philosophers of science have given it insufficient attention, even deliberately shunning the topic. Traditional confirmation theory and general epistemology offer little help at the frontier, because they are mostly retrospective rather than prospective. Nor have philosophers been highly visible in the science and technology policy realm, despite (...) philosophy’s being a normative discipline. This paper suggests a way to address both deficits. Creative scientists, technologists, business managers, and policy makers face similar problems of decision-making at their respective frontiers of knowledge. These areas should therefore be fertile ground for both epistemologists and philosophers concerned with policy. Here I call attention to the importance of heuristic appraisal for “frontier epistemology” and to policy formation. Evaluation of the comparative promise or expected fertility of available options comprises a cluster of activities that cut across traditional discovery/justification and descriptive/normative distinctions. The study of weak modes of reasoning and evaluation is especially relevant to socio-economic policy. (shrink)

In this paper, I review two related lines of computational research: discovery of scientific knowledge and causal models of scientific phenomena. I also report research on quantitative process models that falls at the intersection of these two themes. This framework represents models as a set of interacting processes, each with associated differential equations that express influences among variables. Simulating such a quantitative process model produces trajectories for variables over time that one can compare to observations. Background knowledge about candidate processes (...) enables search through the space of model structures and associated parameters to find explanations of time-series data. I discuss the representation of such process models, their use for prediction and explanation, and their discovery through heuristic search, along with their interpretation as causal accounts of dynamic behavior. (shrink)

A considerable number of areas of bioscience, including gene and drug discovery, metabolic engineering for the biotechnological improvement of organisms, and the processes of natural and directed evolution, are best viewed in terms of a ‘landscape’ representing a large search space of possible solutions or experiments populated by a considerably smaller number of actual solutions that then emerge. This is what makes these problems ‘hard’, but as such these are to be seen as combinatorial optimisation problems that are best attacked (...) by heuristic methods known from that field. Such landscapes, which may also represent or include multiple objectives, are effectively modelled in silico, with modern active learning algorithms such as those based on Darwinian evolution providing guidance, using existing knowledge, as to what is the ‘best’ experiment to do next. An awareness, and the application, of these methods can thereby enhance the scientific discovery process considerably. This analysis fits comfortably with an emerging epistemology that sees scientific reasoning, the search for solutions, and scientific discovery as Bayesian processes. (shrink)

In recent years questions concerning the impact of public research funding have become the preeminent site at which struggles over the meanings and value of science are played out. In this paper we explore the ‘politics of impact’ in contemporary UK science and research policy and, in particular, detail the ways in which UK research councils have responded to and reframed recent calls for the quantitative measurement of research impacts. Operating as ‘boundary organisations’ research councils are embroiled in what might (...) be characterised as the ‘politics of demarcation’ in which competing understandings of the cultural values of science are traded, exchanged and contested. In this paper we focus on the way the UK’s ‘Engineering and Physical Sciences Research Council’ (EPSRC) has responded to contemporary policy discourses concerning the impacts of public research expenditure. We argue that, in response to the shifting terms of contemporary science policy, the EPSRC has adopted three distinct strategies. Firstly, in collaboration with other research councils the EPSRC have emphasised the intellectual and metrological challenge presented by attempts to quantify the economic impact of public research expenditure, emphasising instead the cumulative impacts of a broad portfolio of ‘basic science’. Secondly, the EPSRC has sought to widen the discursive meaning of research impacts – specifically to include societal and policy impacts in addition to economic ones. Thirdly, the EPSRC has introduced a new framing into the ‘impact agenda’, preferring to talk about ‘pathways to impact’ rather than research impacts per se. In responding to government priority setting, we argue that the EPSRC has sought to exploit both the technical fragility of auditing techniques and the discursive ambiguity of notions of impact. (shrink)

Scientists routinely solve the problem of supplementing one’s store of variables with new theoretical posits that can explain the previously inexplicable. The banality of success at this task obscures a remarkable fact. Generating hypotheses that contain novel variables and accurately project over a limited amount of additional data is so difficult—the space of possibilities so vast—that succeeding through guesswork is overwhelmingly unlikely despite a very large number of attempts. And yet scientists do generate hypotheses of this sort in very few (...) tries. I argue that this poses a dilemma: either the long history of scientific success is a miracle, or there exists at least one method or algorithm for generating novel hypotheses with at least limited projectibility on the basis of what’s available to the scientist at a time, namely a set of observations, the history of past conjectures, and some prior theoretical commitments. In other words, either ordinary scientific success is miraculous or there exists a logic of discovery at the heart of actual scientific method. (shrink)

Considerable demand for academic research and publications is not a new subject of discussion in the academic field. In Indonesia, there is increasing challenge and pressure to conduct scientific publications, making it a very competitive field for academics, particularly for lecturers and postgraduate students. The present study examines Indonesian scholars’ perceptions of academic publishing as a demand from institutions and the government, as well as their understanding of academic misconduct. We conducted a survey with open-ended questions to 55 scholars. The (...) results suggest that Indonesian scholars are knowledgeable about academic publishing and believe that this obligation is inevitable and beneficial for them. To what extent academic misconduct in publications falls under their understanding, though, is still unclear. When presented with information on academic misconduct, in particular using unethical publication services, they show an ambiguous and inconsistent manner, as if the misconduct is understandable. Interestingly, they also reveal other ethically dubious behaviors that appear to be common among Indonesian scholars. The findings indicate that the issue of academic misconduct is still addressed ambiguously by using publication demands as a scapegoat to justify certain unethical publication practices. (shrink)

Extending and expanding Geiger and Feller’s analysis of increasing dispersion in R&D expenditures during the 1980s, the paper analyzes publication and citation counts as well as R&D expenditures for 194 top producers using Web of Science data. We find high and stable levels of inequality in the 1990s and 2000s, combined with robust growth both in the system and on individual campuses, considerable opportunities for short-range mobility and very limited opportunities for long-range mobility. Initial investments in research, private control, and (...) the capacity of wealthy institutions to attract productive faculty are associated with high levels of scientific output. New entrants to the system and those that leave the system are both clustered near the bottom of the hierarchy. (shrink)

There is a social or collective sense of ‘knowledge’, as used, for example, in the phrase ‘the growth of scientific knowledge’. In this paper I show that social knowledge does not supervene on facts about what individuals know, nor even what they believe or intend, or any combination of these or other mental states. Instead I develop the idea that social knowing is an analogue to individual knowing, where the analogy focuses on the functional role of social and individual knowing.