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)

Biological sciences have strived to adopt the conceptual framework of physics and have become increasingly quantitatively oriented, aiming to refute the assertion that biology appears unquantifiable, unpredictable, and messy. But despite all effort, biology is characterized by a paucity of quantitative statements with universal applications. Nonetheless, many biological disciplines—most notably molecular biology—have experienced an ascendancy over the last 50 years. The underlying core concepts and ideas permeate and inform many neighboring disciplines. This surprising success is probably not so much attributable (...) to mathematical and statistical approaches in molecular biology, but rather to the preponderance of qualitative approaches, especially visualization. Visualizations can be afforded by quantitative research, but usually they rely on both, quantitative and qualitative research. I claim the following three features to be responsible for the unceasing zeal for using visualizations: visual representations facilitate reasoning, images can be cognitively processed in a “fast” manner, and abstractions of visual representations prompt conceptual advances. In summary, visualizations have largely contributed to the success of molecular biology by conveying its concepts to other disciplines, and at the same time, eclipsing mere quantitative approaches. However, visualizations also bear the risk of misinterpretation when traversing neighboring disciplines and even more so when pervading nonscientific domains. (shrink)

The discovery and ongoing investigation of microRNAs suggest important conceptual and methodological lessons for philosophers and historians of biology. This paper provides an account of miRNA research and the shift from viewing these tiny regulatory entities as minor curiosities to seeing them as major players in the post-transcriptional regulation of genes. Conceptually, the study of miRNAs is part of a broader change in understandings of genetic regulation, in which simple switch-like mechanisms were reinterpreted as aspects of complex cellular and genome-wide (...) processes. Among them are the activities of small RNAs, previously regarded as non-functional. Methodologically, the miRNA story suggests new ways of characterizing biological research that should prove helpful to philosophers of science who seek to develop more pluralistic, pragmatic models of scientific inquiry. miRNA research displays iterative movements between multiple modes of investigation that include not only the proposal and testing of hypotheses but also exploratory, technology-oriented and question-driven modes of research. As an exemplary story of scientific discovery and development, the miRNA case illustrates transitions from genetics to genomics and systems biology, and it shows how diverse configurations of research practice are related to major scientific advances. (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)

Philosophers of science readily acknowledge that nonepistemic values influence the discovery and pursuit of scientific theories, but many tend to regard these influences as epistemically uninteresting. The present paper challenges this position by identifying three avenues through which nonepistemic values associated with discovery and pursuit in contemporary pollution research influence theory appraisal: (1) by guiding the choice of questions and research projects, (2) by altering experimental design, and (3) by affecting the creation and further investigation of theories or hypotheses. This (...) analysis indicates that the effects of these values are sufficiently complex and epistemically significant to merit further attention. †To contact the authors, please write to: Kevin Elliott, Department of Philosophy, University of South Carolina, Columbia, SC 29208; e‐mail: [email protected] . Daniel McKaughan, Department of Philosophy, Boston College, Chestnut Hill, MA 02467; e‐mail: [email protected]. (shrink)

A number of scholars have recently drawn attention to the importance of iteration in scientific research. This paper builds on these previous discussions by drawing a distinction between epistemic and methodological forms of iteration and by clarifying the relationships between them. As defined here, epistemic iteration involves progressive alterations to scientific knowledge claims, whereas methodological iteration refers to an interplay between different modes of research practice. While distinct, these two forms of iteration are related in important ways. Contemporary research on (...) the biological effects of nanomaterials illustrates that methodological iteration can help to “initiate,” “equip,” and “stimulate” epistemic iteration. (shrink)

The biological effects of low doses of toxic and carcinogenic chemicals are currently a matter of significant scientific controversy. This paper argues that philosophers of science can contribute to alleviating this controversy by examining it with the aid of a novel account of scientific anomaly. Specifically, analysis of contemporary research on chemical hormesis (i.e., alleged beneficial biological effects produced by low doses of substances that are harmful at higher doses) suggests that scientists may initially describe anomalous phenomena in terms of (...) multiple distinct "characterizations," each of which is compatible with current empirical evidence. By focusing attention on this feature of scientific anomalies, philosophers of science can alleviate the controversy over low-dose chemical effects in at least two ways: (1) they can pinpoint the significant ways in which particular characterizations frame the controversy, and (2) they can identify the methodological value judgments at stake in researchers' choice of characterizations. (shrink)

There has been relatively little effort to provide a systematic overview of different forms of exploratory experimentation (EE). The present paper examines the growing subdiscipline of nanotoxicology and suggests that it illustrates at least four ways that researchers can engage in EE: searching for regularities; developing new techniques, simulation models, and instrumentation; collecting and analyzing large swaths of data using new experimental strategies (e.g., computer-based simulation and "high-throughput" instrumentation); and structuring an entire disciplinary field around exploratory research agendas. In order (...) to distinguish these and other activities more effectively, the paper proposes a taxonomy that includes three dimensions along which types of EE vary: (1) the aim of the experimental activity, (2) the role of theory in the activity, and (3) the methods or strategies employed for varying experimental parameters. (shrink)