This essay attempts to distinguish and discuss the importance and limitations of different ways of being wrong. At first it is argued that strictly falsifiable knowledge is concerned with simple (instrumental) mistakes only, and thus is incapable of understanding more complex errors (and truths). In order to gain a deeper understanding of mistakes (and to understand a deeper kind of mistake), it is argued that communicative aspects have to be taken into account. This is done in the theory of communicative (...) action, which adds to our knowledge of errors the notion of communicative mistakes: mistakes as obstacles for sincere communication. However, to overcome this still purely negative judgement of errors, two processes are examined in which mistakes are best regarded as developmental steps, that is, steps not only meaningful in their own right (as containing some truth), but also as necessary preconditions for further progress. This would suggest that truth is born out of errors. But if so, one has to understand the wrongness of such errors; how is it that they are erroneous if they (somehow) contain the truth? At the end of this essay, a tentative answer to this question is given. (shrink)

Each type of learning is proposed as being a three-stage process, composed of: (i) recognition of a perceptual situation and performance of an action corresponding thereto; (ii) observation of a deviation of the action result from an expected outcome; (iii) re-arrangement of the conceptual framework of reasoning to meaningfully assimilate the observed deviation. In order to evaluate a general, systemic significance of the concept of learning proposed hereby, the latter is assessed from perspectives that correspond to diverse levels of organizational (...) complexity of Nature. Thermodynamic concepts, constructivist and autopoietic frameworks of analysis of cognitive phenomena, and the aspects of social sciences are intertwined so as to support the all-encompassing meaning of the general pathways of learning proposed herein. Numerous ethical consequences, with a particular emphasis on educational approaches, are derived from accepting such a general nature of learning and development. Naturally implied dialectical form of evolution, according to which prosperous and favorable features of human creativity arise solely from problem-solving situations, is further discussed. (shrink)

Some accounts of evidence regard it as an objective relationship holding between data and hypotheses, perhaps mediated by a testing procedure. Mayo’s error-statistical theory of evidence is an example of such an approach. Such a view leaves open the question of when an epistemic agent is justified in drawing an inference from such data to a hypothesis. Using Mayo’s account as an illustration, I propose a framework for addressing the justification question via a relativized notion, which I designate security , (...) meant to conceptualize practices aimed at the justification of inferences from evidence. I then show how the notion of security can be put to use by showing how two quite different theoretical approaches to model criticism in statistics can both be viewed as strategies for securing claims about statistical evidence. (shrink)

In silicio design plays a fundamental role in the endeavour to synthesise biological systems. In particular, computer-aided design software enables users to manage the complexity of biological entities that is connected to their construction and reconfiguration. The software’s graphical user interface bridges the gap between the machine-readable data on the algorithmic subface of the computer and its human-amenable surface represented by standardised diagrammatic elements. Notations like the Systems Biology Graphical Notation , together with interactive operations such as drag & drop, (...) allow the user to visually design and simulate synthetic systems as ‘bio-algorithmic signs’. Finally, the digital programming process should be extended to the wet lab to manufacture the designed synthetic biological systems. By exploring the different ‘faces’ of synthetic biology, I argue that in particular computer-aided design is pushing the idea to automatically produce de novo objects. Multifaceted software processes serve mutually aesthetic, epistemic and performative purposes by simultaneously black-boxing and bridging different data sources, experimental operations and community-wide standards. So far, synthetic biology is mainly a product of digital media technologies that structurally mimic the epistemological challenge to take both qualitative as well as quantitative aspects of biological systems into account in order to understand and produce new and functional entities. (shrink)

While the term “reactivity” has come to be associated with specific phenomena in the social sciences, having to do with subjects’ awareness of being studied, this paper takes a broader stance on this concept. I argue that reactivity is a ubiquitous feature of the psychological subject matter and that this fact is a precondition of experimental research, while also posing potential problems for the experimenter. The latter are connected to the worry about distorted data and experimental artifacts. But what are (...) experimental artifacts and what is the most productive way of dealing with them? In this paper, I approach these questions by exploring the ways in which experimenters in psychology simultaneously exploit and suppress the reactivity of their subject matter in order to produce experimental data that speak to the question or subject matter at hand. Highlighting the artificiality of experimental data, I raise the question of what distinguishes a genuine experimental result from an experimental artifact. My analysis construes experimental results as the outcomes of inferences from the data that take material background assumptions as auxiliary premises. Artifacts occur when one or more of these background assumptions are false, such that the data do not reliably serve the purposes they were generated for. I conclude by laying out the ways in which my analysis of data quality is relevant to, and informed by, recent debates about the replicability of experimental results. (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)

At the turn of the twentieth century, so-called “glass diseases” seriously affected the use of scientific and technical glassware. It had become apparent by 1900 that glass, a supposedly neutral and inert material, not only interacted with its environment but also interfered with anything it contained—chemically, physically, and biologically. Starting from the assumption that modern laboratory research depends on containers that regulate the spatial, material, and epistemic enclosure of its experimental milieus and objects, this essay argues that the standardization of (...) glass quality from the 1900s to the 1930s must be understood as a reconfiguration of a “marginal” but nonetheless constitutive element of modern laboratory environments. The aim here is thus to weave various threads together into an (un)natural history of a modern material, one that considers epistemology, technology, and ontology—or, more specifically, the changing requirements and functions of glassware in the modern laboratory, the invention of specifically adapted glass substances, and the parallel advancement of glass science and its theories of what glass actually is. (shrink)

ArgumentGlass vessels such as flasks and test tubes play an ambiguous role in the historiography of modern laboratory research. In spite of the strong focus on the role of materiality in the last decades, the scientific glass vessel – while being symbolically omnipresent – has remained curiously neglected in regard to its materiality. The popular image ortoposof the transparent, neutral, and quasi-immaterial glass container obstructs the view of the physico-chemical functionality of this constitutive inner boundary in modern laboratory environments and (...) its material historicity. In order to understand how glass vessels were able to provide a stable epistemic containment of spatially enclosed experimental phenomena in the new laboratory ecologies emerging in the nineteenth and early twentieth century, I will focus on the history of thematerialstandardization of laboratory glassware. I will follow the rise of a new awareness for measurement errors due to the chemical agency of experimental glass vessels, then I will sketch the emergence of a whole techno-scientific infrastructure for the improvement of glass container quality in late nineteenth-century Germany. In the last part of my argument, I will return to the laboratory by looking at the implementation of this glass reform that created a newoikosfor the inner experimental milieus of modern laboratory research. (shrink)

I contrast two modes of error-elimination relevant to evaluating evidence in accounts that emphasize frequentist reliability. The contrast corresponds to that between the use of of a reliable inference procedure and the critical scrutiny of a procedure with regard to its reliability, in light of what is and is not known about the setting in which the procedure is used. I propose a notion of security as a category of evidential assessment for the latter. In statistical settings, robustness theory and (...) misspecification testing exemplify two distinct strategies for securing statistical inferences. (shrink)