The credit incentive to be a maverick

There is a commonly made distinction between two types of scientists: risk-taking, trailblazing mavericks and detail-oriented followers. A number of recent papers have discussed the question what a desirable mixture of mavericks and followers looks like. Answering this question is most useful if a scientific community can be steered toward such a desirable mixture. One attractive route is through credit incentives: manipulating rewards so that reward-seeking scientists are likely to form the desired mixture of their own accord. Here I argue that (even in theory) this idea is less straightforward than it may seem. Interpreting mavericks as scientists who prioritize rewards over speed and risk, I show in a deliberatively simple model that there is a fixed mixture which is not particularly likely to be desirable and which credit incentives cannot alter. I consider a way around this result, but this has some major drawbacks. I conclude that credit incentives are not as promising a way to create a desirable mixture of mavericks and followers as one might have thought.     

The detection of fraud and fakery

Fraud is often found in science, especially in what is termed, 'fringe science'. There are several reasons why scientists should be aware of the fact that they, too, can be deceived, both by subjects in experiments and by themselves. The will to believe is strong even among 'hard-headed' academics, and is often the factor that causes them to publish results that do not stand up to subsequent examination and/or attempts to replicate. In some cases, scientists would be well advised to consult with such experts as conjurors, when skilled frauds are in a position to mislead them.     

Are plants cognitive? A reply to Adams

According to F. Adams [this journal, vol. 68, 2018] cognition cannot be realized in plants or bacteria. In his view, plants and bacteria respond to the here-and-now in a hardwired, inflexible manner, and are therefore incapable of cognitive activity. This article takes issue with the pursuit of plant cognition from the perspective of an empirically informed philosophy of plant neurobiology. As we argue, empirical evidence shows, contra Adams, that plant behavior is in many ways analogous to animal behavior. This renders plants suitable to be described as cognitive agents in a non-metaphorical way. Sections two to four review the arguments offered by Adams in light of scientific evidence on plant adaptive behavior, decision-making, anticipation, as well as learning and memory. Section five introduces the ‘phyto-nervous’ system of plants. To conclude, section six resituates the quest for plant cognition into a broader approach in cognitive science, as represented by enactive and ecological schools of thought. Overall, we aim to motivate the idea that plants may be considered genuine cognitive agents. Our hope is to help propel public awareness and discussion of plant intelligence once appropriately stripped of anthropocentric preconceptions of the sort that Adams' position appears to exemplify.     

Notes on toxinology

Conclusions Some of the papers to follow in the present series of communications on toxinology will show that in the field of chemistry, physiology, pharmacology and immunology, as well as molecular biology, animal venoms provide us with some particularly useful models. Obviously, this is one of the main reasons for the growing interest shown by numerous scientists in animal toxins.With reference to medicine, more research is needed in the field just mentioned with the aim of improving medical care. In addition, however, it is postulated that research on the behaviour of venomous animals towards man, and research into the quantities of venom actually applied to man, be intensified. Also, on the basis of results in this context, people most exposed could be provided with more and better information about prevention.Work of this sort requests the collaboration of biologists, who observe toxic animals in their natural habitat and who investigate in particular when, and under what prerogatives, the animals make use of toxins in their natural surroundings. Thus we end up with what has been said in the introduction to these notes: toxic animals are to be studied as entities and toxicity has to be looked at from all aspects essential for life, possibly including parasite and population control.Should the very last point prove valid, fascinating links could be established between toxinology and ecology and in turn migt become important for nature conservation. Thus, toxinology is but a budding field, the limits of which, can yet only be assumed.     

Evaluating community science

Community science—scientific investigation conducted partly or entirely by non-professional scientists—has many advantages. For example, community science mobilizes large numbers of volunteers who can, at low cost, collect more data than traditional teams of professional scientists. Participation in research can also increase volunteers’ knowledge about and appreciation of science. At the same time, there are worries about the quality of data that community science projects produce. Can the work of non-professionals really deliver trustworthy results? Attempts to answer this question generally compare data collected by volunteers to data collected by professional scientists. When volunteer data is more variable or less accurate than professionally collected data, then the community science project is judged to be inferior to traditional science. I argue that this is not the right standard to use when evaluating community science, because it relies on a false assumption about the aims of science. I show that if we adopt the view that science has diverse aims which are often in tension with one another, then we cannot justify holding community science data to an expert accuracy standard. Instead, we should evaluate the quality of community science data based on its adequacy-for-purpose.     

Classical computationalism and the many problems of cognitive relevance

In this paper I defend the classical computational account of reasoning against a range of highly influential objections, sometimes called relevance problems. Such problems are closely associated with the frame problem in artificial intelligence and, to a first approximation, concern the issue of how humans are able to determine which of a range of representations are relevant to the performance of a given cognitive task. Though many critics maintain that the nature and existence of such problems provide grounds for rejecting classical computationalism, I show that this is not so. Some of these putative problems are a cause for concern only on highly implausible assumptions about the extent of our cognitive capacities, whilst others are a cause for concern only on similarly implausible views about the commitments of classical computationalism. Finally, some versions of the relevance problem are not really objections but hard research issues that any satisfactory account of cognition needs to address. I conclude by considering the diagnostic issue of why accounts of cognition in general—and classical computational accounts, in particular—have faired so poorly in addressing such research issues.     

Scientists as experts: A distinct role?

The role of scientists as experts is crucial to public policymaking. However, the expert role is contested and unsettled in both public and scholarly discourse. In this paper, I provide a systematic account of the role of scientists as experts in policymaking by examining whether there are any normatively relevant differences between this role and the role of scientists as researchers. Two different interpretations can be given of how the two roles relate to each other. The separability view states that there is a normatively relevant difference between the two roles, whereas the inseparability view denies that there is such a difference. Based on a systematic analysis of the central aspects of the role of scientists as experts – that is, its aim, context, mode of output, and standards, I propose a moderate version of the separability view. Whereas the aim of scientific research is typically to produce new knowledge through the use of scientific method for evaluation and dissemination in internal settings, the aim of the expert is to provide policymakers and the public with relevant and applicable knowledge that can premise political reasoning and deliberation.     

Will the real scientists please stand up? dead ends and live issues in the explanation of scientific knowledge

Reflection on the method of science has become increasingly thinner since Kant. If there's any upshot of that part of modern philosophy, it's that the scientists didn't have a secret. There isn't something there that's either effable or ineffable. To understand how they do what they do is pretty much like understanding how any other bunch of skilled craftsmen do what they do. Kuhn's reduction of philosophy of science to sociology of science doesn't point to an ineffable secret of success; it leaves us without the notion of the secret of success.Relativism is the view that every belief on a certain topic, or perhaps, about any topic, is as good as every other. No one holds this view. Except for the occasional co-operative freshman, one cannot find anybody who says that two incompatible opinions on an important topic are equally good. The philosophers who get called ‘relativists’ are those who say that the grounds for choosing between such opinions are less algorithmic than had been thought.Richard Rorty1,2     

Computation vs. information processing: why their difference matters to cognitive science

Since the cognitive revolution, it has become commonplace that cognition involves both computation and information processing. Is this one claim or two? Is computation the same as information processing? The two terms are often used interchangeably, but this usage masks important differences. In this paper, we distinguish information processing from computation and examine some of their mutual relations, shedding light on the role each can play in a theory of cognition. We recommend that theorists of cognition be explicit and careful in choosing notions of computation and information and connecting them together.     

Zur Geschichte des Metermasses

Summary The history of the normal meter shows distinct steps of development. The meter itself was defined by French scientists as a national unit at the beginning of the great French Revolution and realized in 1799 by a platinum rod. A better reproduction of the unit of length was given in 1889 by a 90% Pt-10% Ir platinum bar of special cross section according to an international convention. Every substantial standard, however, has many disadvantages, besides the possibility of an entire loss by an accident. The red cadmium line was therefore used in 1893 to express the meter by the number of its wave lengths in air and a provisional resolution was adopted in 1927 on this basis. Much more suitable, however, is an orange line emitted at 63°K from the isotope⁸⁶Kr, which can be produced in a thermal diffusion column in the state of highest purity. Since 1960, the vacuum wave length of this element has served as the fundamental unit of length.     

The detection of fraud and fakery

Summary Fraud is often found in science, especially in what is termed, fringe science. There are several reasons why scientists should be aware of the fact that they, too, can be deceived, both by subjects in experiments and by themselves. The will to believe is strong even among hard-headed academics, and is often the factor that causes them to publish results that do not stand up to subsequent examination and/or attempts to replicate. In some cases, scientists would be well advised to consult with such experts as conjurors, when skilled frauds are in a position to mislead them.     

Setting up a Discipline: Conflicting Agendas of the Cambridge History of Science Committee, 1936–1950

Traditionally the domain of scientists, the history of science became an independent field of inquiry only in the twentieth century and mostly after the Second World War. This process of emancipation was accompanied by a historiographical departure from previous, ‘scientistic’ practices, a transformation often attributed to influences from sociology, philosophy and history. Similarly, the liberal humanists who controlled the Cambridge History of Science Committee after 1945 emphasized that their contribution lay in the special expertise they, as trained historians, brought to the venture. However, the scientists who had founded the Committee in the 1930s had already advocated a sophisticated contextual approach: innovation in the history of science thus clearly came also from within the ranks of scientists who practised in the field. Moreover, unlike their scientist predecessors on the Cambridge Committee, the liberal humanists supported a positivistic protocol that has since been criticized for its failure to properly contextualize early modern science. Lastly, while celebrating the rise of modern science as an international achievement, the liberal humanists also emphasized the peculiar Englishness of the phenomenon. In this respect, too, their outlook had much in common with the practices from which they attempted to distance their project.     

Models and the dynamics of theory-building in physics. Part I—Modeling strategies

A deeper understanding of models is sought in considering what models do, rather what they are. This distinction emphasizes how two different modeling strategies, as they pursue different purposes, do invest in different options, in particular in regard to rigor and immediate empirical relevance. The analysis focuses therefore on the services expected from models by the scientists who construct them: models are sought for how they contribute to exploring and testing the context in which they operate. In a forthcoming Part II these general considerations will be anchored in the presentation of specific case studies.     

Scientific authorship in the age of collaborative research

I examine two challenges that collaborative research raises for science. First, collaborative research threatens the motivation of scientists. As a result, I argue, collaborative research may have adverse effects on what sorts of things scientists can effectively investigate. Second, collaborative research makes it more difficult to hold scientists accountable. I argue that the authors of multi-authored articles are aptly described as plural subjects, corporate bodies that are more than the sum of the individuals involved. Though journal editors do not currently conceive of the authors of multi-authored articles this way, this conception provides us with the conceptual resources to make sense of how collaborating scientists behave.     

Georg Simmel and naturalist interactivist epistemology of science

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 (2002) 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.     

Vascular stem/progenitor cells: functions and signaling pathways

Vascular stem/progenitor cells (VSCs) are an important source of all types of vascular cells needed to build, maintain, repair, and remodel blood vessels. VSCs, therefore, play critical roles in the development, normal physiology, and pathophysiology of numerous diseases. There are four major types of VSCs, including endothelial progenitor cells (EPCs), smooth muscle progenitor cells (SMPCs), pericytes, and mesenchymal stem cells (MSCs). VSCs can be found in bone marrow, circulating blood, vessel walls, and other extravascular tissues. During the past two decades, considerable progress has been achieved in the understanding of the derivation, surface markers, and differentiation of VSCs. Yet, the mechanisms regulating their functions and maintenance under normal and pathological conditions, such as in eye diseases, remain to be further elucidated. Owing to the essential roles of blood vessels in human tissues and organs, understanding the functional properties and the underlying molecular basis of VSCs is of critical importance for both basic and translational research.     

The theory theory thrice over: the child as scientist, Superscientist or social institution?

Alison Gopnik and Andrew Meltzoff have argued for a view they call the ‘theory theory’: theory change in science and children are similar. While their version of the theory theory has been criticized for depending on a number of disputed claims, we argue that there is a fundamental problem which is much more basic: the theory theory is multiply ambiguous. We show that it might be claiming that a similarity holds between theory change in children and (i) individual scientists, (ii) a rational reconstruction of a Superscientist, or (iii) the scientific community. We argue that (i) is false, (ii) is non-empirical (which is problematic since the theory theory is supposed to be a bold empirical hypothesis), and (iii) is either false or doesn't make enough sense to have a truth-value. We conclude that the theory theory is an interesting failure. Its failure points the way to a full, empirical picture of scientific development, one that marries a concern with the social dynamics of science to a psychological theory of scientific cognition.     

Multifunctional interneurons in behavioral circuits of the medicinal leech

Summary We are using the medicinal leech to study the neuronal basis of behavioral choice. In particular, we are recording from neurons, both extracellularly and intracellularly, in preparations that can express three different behaviors: the shortening reflex, crawling and swimming. We have found that particular mechanosensory neurons can elicit any of the behaviors, and that the movements are produced by just four sets of muscles, each controlled by a small number of motor neurons. Hence, there must be three different pattern-generating neuronal circuits, each of which can be activated by the same set of sensory neurons. We are studying how the choice is made among the three behaviors by recording, while one behavior is being performed, from neurons known to be involved in the initiation of the other two. We have found that an interneuron, cell 204, which is known to initiate and maintain swimming, is also active during shortening and crawling. The activity level in this interneuron can influence whether a mechanosensory stimulus produces shortening or swimming. The neuronal mechanisms by which this choice is normally effected awaits further elucidation of the circuits that elicit and generate shortening and crawling.     

Multifunctional interneurons in behavioral circuits of the medicinal leech

We are using the medicinal leech to study the neuronal basis of behavioral choice. In particular, we are recording from neurons, both extracellularly and intracellularly, in preparations that can express three different behaviors: the shortening reflex, crawling and swimming. We have found that particular mechanosensory neurons can elicit any of the behaviors, and that the movements are produced by just four sets of muscles, each controlled by a small number of motor neurons. Hence, there must be three different pattern-generating neuronal circuits, each of which can be activated by the same set of sensory neurons. We are studying how the choice is made among the three behaviors by recording, while one behavior is being performed, from neurons known to be involved in the initiation of the other two. We have found that an interneuron, cell 204, which is known to initiate and maintain swimming, is also active during shortening and crawling. The activity level in this interneuron can influence whether a mechanosensory stimulus produces shortening or swimming. The neuronal mechanisms by which this choice is normally effected awaits further elucidation of the circuits that elicit and generate shortening and crawling.     

Representing with imaginary models: Formats matter

Models such as the simple pendulum, isolated populations, and perfectly rational agents, play a central role in theorising. It is now widely acknowledged that a study of scientific representation should focus on the role of such imaginary entities in scientists’ reasoning. However, the question is most of the time cast as follows: How can fictional or abstract entities represent the phenomena? In this paper, I show that this question is not well posed. First, I clarify the notion of representation, and I emphasise the importance of what I call the “format” of a representation for the inferences agents can draw from it. Then, I show that the very same model can be presented under different formats, which do not enable scientists to perform the same inferences. Assuming that the main function of a representation is to allow one to draw predictions and explanations of the phenomena by reasoning with it, I conclude that imaginary models in abstracto are not used as representations: scientists always reason with formatted representations. Therefore, the problem of scientific representation does not lie in the relationship of imaginary entities with real systems. One should rather focus on the variety of the formats that are used in scientific practice.