Scientific Practice

Franklin and Pickering agree that scientists in an experimental sequence, like the one to be discussed here, choose to accept certain experiments and their results as crucial, but disagree as to whether such choice can be justified in terms of an on-line estimate of evidential reliability. This paper suggests that it is possible to define a position between Franklin 's Bayesian objectivism and Pickering's social constructivism. This position depends on considering the sequence of improvement in material technique and instrumentation as (...) more important than any measure of reliability determined merely from such factors as evidential spread in relevant sequences, a factor that neither Franklin nor Pickering takes sufficiently into account. (shrink)

Basic research or fundamental research is distinct from both pure and applied research, in that it is pure research with expected useful results. The existence of basic or fundamental research is problematic, at least for both inductivists and instrumentalists, but also for Popper. Assuming scientific research to be the search for explanatory conjectures and for refutations, and assuming technology to be the search of conjectures and some corroborations, we can easily place basic or fundamental research between science and technology as (...) a part of their overlap. As a bonus, the present view of basic or fundamental research as an overlap explains the specific hardship basic research workers encounter. (shrink)

Analogies have been traditionally recognized as a proper part of inductive procedures, akin to generalizations. Seldom, however, have they been presented as superior to generalizations, in the attainability of a higher degree of certitude for their conclusions or in other respects. Though Bacon definitely preferred analogy to generalization1, the tradition seems to me to go the other way-until the recent publication of works by Mary B. Hesse ([2], pp.21-28 and passim) and, perhaps, R. Harr6 ([1], pp.23-28 and passim). The aim (...) of the present note is to argue the following two points. First, generalizations proper are preferable to predictions from past observations to a single future observation, since the latter are ad hoc. Second, analogies are either generalizations proper-perhaps higher-level ones-or ad hoc. In any case, they are not more certain than generalizations, but they are still equally legitimate. (shrink)

Modern philosophy of science was, initially, an epistemology of science based on the logical analysis of the language of science. It was superseded by a “sociological epistemology,” according to which the acceptance of scientific statements and theories depends on conditioningscoming from the social context and powers, and this view has fueled anti-scientific attitudes.This happened because the sociological turn still expressed an epistemology of science. Science, however, is not only a system of knowledge, but also a complex human activity. Hence, ethical, (...) political, social, religious issues appear legitimate if they concern “doing science.”Therefore, we must “rethink” philosophy of science, accepting in it also an axiology of science that could enable us to retain the cognitive value of science and at the same time to make techno-scientific activity compatible with the satisfaction of a great variety of values that inspire our societies. (shrink)

In this paper I argue for a place for logic inscientific methodology, at the same level asthat of computational and historicalapproaches. While it is well known that a awhole generation of philosophers dismissedLogical Positivism (not just for the logicthough), there are at least two reasons toreconsider logical approaches in the philosophyof science. On the one hand, the presentsituation in logical research has gone farbeyond the formal developments that deductivelogic reached last century, and new researchincludes the formalization of several othertypes of (...) reasoning, like induction andabduction. On the other hand, we call for abalanced Philosophy of Science, one inwhich both methods, the formal and thehistorical may be complementary, togetherproviding a pluralistic view of science, inwhich no method is the predominant one. (shrink)

Conflict of interest disclosure has become a routine requirement in communication of scientific information. Its advocates defend COI disclosure as a sensible middle path between the extremes of categorical prohibition on for-profit research and anything-goes acceptance of research regardless of origin. To the extent that COI information is meant to aid reviewer and reader evaluation of research, COIs must be epistemologically significant. While some commentators treat COIs as always relevant to research credibility, others liken the demand for disclosure to an (...) ad hominem attack, impugning integrity when better evidence of research credibility is available. Kevin Elliott has argued for clearer justification of COI relevance to research credibility: some interests may be feared to corrupt research results, while others do not, and Elliott provides criteria to discern which financial COIs are actually relevant to research credibility. In this article, I seek to revise and extend Elliott's proposed criteria to COIs more widely. Specifically, I consider the relevance of financial interests as well as nonfinancial advocacy interests to the credibility of research into environmental equity as funded by industry and community groups, with particular attention to criticism and defence of the 1987 United Church of Christ study on the racial demographics of toxic waste facility siting in the United States. (shrink)

This paper is intended as a critical examination of the question of when the use of computer simulations is beneficial to scientific explanations. This objective is pursued in two steps: First, I try to establish clear criteria that simulations must meet in order to be explanatory. Basically, a simulation has explanatory power only if it includes all causally relevant factors of a given empirical configuration and if the simulation delivers stable results within the measurement inaccuracies of the input parameters. If (...) a simulation is not explanatory, it can still be meaningful for exploratory purposes, but only under very restricted conditions. In the second step, I examine a few examples of Axelrod-style simulations as they have been used to understand the evolution of cooperation (Axelrod, Schüßler) and the evolution of the social contract (Skyrms). These simulations do not meet the criteria for explanatory validity and it can be shown, as I believe, that they lead us astray from the scientific problems they have been addressed to solve and at the same time bar our imagination against more conventional but still better approaches. (shrink)

This paper tries to answer the question why the epistemic value of so many social simulations is questionable. I consider the epistemic value of a social simulation as questionable if it contributes neither directly nor indirectly to the understanding of empirical reality. To examine this question, two classical social simulations are analyzed with respect to their possible epistemic justification: Schelling’s neighborhood segregation model and Axelrod’s reiterated Prisoner’s Dilemma simulations of the evolution of cooperation. It is argued that Schelling’s simulation is (...) useful because it can be related to empirical reality, while Axelrod’s simulations and those of his followers cannot and thus that their scientific value remains doubtful. I relate this findingto the background beliefs of modelers about the superiority of the modeling method as expressed in Joshua Epstein’s keynote address “Why model?”. (shrink)

Phyllis Illari & Federica Russo: Causality: Philosophical Theory Meets Scientific Practice. Oxford: Oxford University Press, 2014, 310pp, £29.99 HB.

Students of the `long' McCarthy period in the United States – fromthe late 1940s through the 1950s – have paid inadequate attentionto the effects of this oppressive time upon science. Visa andpassport denials, loyalty oaths, security investigations, andother problems placed in the paths of scientists no doubthindered science. But they also increased the political maturityof its practitioners, a fact of which recent events make usparticularly aware.

In this paper we elucidate a particular type of instrument. Striking-phenomenon instruments assume their striking profile against the shifting backdrop of theoretical uncertainties. While technologically stable, the phenomena produced by these instruments are linguistically fuzzy, subject to a variety of conceptual representations. But in virtue of their technological stability alone, they can provide a foundation for further technological as well as conceptual development. Sometimes, as in the case of the pulse glass, the phenomenon is taken to confirm conflicting theoretical views; (...) sometimes, as in the case of the Lichtenberg-figures, it holds out the false promise of crucial theoretical importance; sometimes, as in the case of the airpump in the 18th century, it emphatically short-circuits theory and human ingenuity, giving a voice to nature herself; and sometimes, finally, as in the case of the quincunx, the phenomenon stands in for theoretical accounts. We propose and develop the salient features of these instruments demonstrating their importance to our understanding of science. (shrink)

Summary Popular science journalism flourished in the 1860s in England, with many new journals being projected. The time was ripe, Victorian men of science believed, for an ?organ of science? to provide a means of communication between specialties, and between men of science and the public. New formats were tried as new purposes emerged. Popular science journalism became less recreational and educational. Editorial commentary and reviewing the progress of science became more important. The analysis here emphasizes those aspects of popular (...) science which have been identified by Frank Turner as ?public science? and by Thomas Gieryn as ?boundary-work?. The religious, intellectual, and utilitarian values claimed for science by editors and contributors in their tasks of persuading the public to support science and of distinguishing science from what they often called ?applied science? are discussed. These values are shown to vary among editors and, for the editors examined here, Shirley Hibberd, Henry Slack, James Samuelson, William Crookes, and Henry Lawson, to differ significantly from those of T. H. Huxley, John Tyndall, and Norman Lockyer, on whom much study of the popularization of science in the 1860s has focused. (shrink)

Summary Although by the mid-eighteenth century colonial American makers of mathematical instruments were producing many of the scientific instruments required in the British Colonies of North America for surveying and navigation, it was not until after the first quarter of the nineteenth century that American makers had the capability to produce sophisticated precision optical instruments for astronomy and microscopy. Until then, these had to be imported from overseas, chiefly England, at considerable cost and after long delays. Included among them were (...) historically important instruments required for establishing provincial and territorial boundaries, and for making astronomical observations. Although generally treated with the utmost care while in use, eventually one after another was misplaced, lost, destroyed by fire, or, in one instance, carefully hidden away then forgotten until it was discovered more than a century later. (shrink)

It is often claimed that scientists can obtain new knowledge about nature by running computer simulations. How is this possible? I answer this question by arguing that computer simulations are arguments. This view parallels Norton’s argument view about thought experiments. I show that computer simulations can be reconstructed as arguments that fully capture the epistemic power of the simulations. Assuming the extended mind hypothesis, I furthermore argue that running the computer simulation is to execute the reconstructing argument. I discuss some (...) objections and reject the view that computer simulations produce knowledge because they are experiments. I conclude by comparing thought experiments and computer simulations, assuming that both are arguments. (shrink)

Monte Carlo simulations arrive at their results by introducing randomness, sometimes derived from a physical randomizing device. Nonetheless, we argue, they open no new epistemic channels beyond that already employed by traditional simulations: the inference by ordinary argumentation of conclusions from assumptions built into the simulations. We show that Monte Carlo simulations cannot produce knowledge other than by inference, and that they resemble other computer simulations in the manner in which they derive their conclusions. Simple examples of Monte Carlo simulations (...) are analysed to identify the underlying inferences. (shrink)