We lay groundwork for applying ethnographic methods in philosophy of science. We frame our analysis in terms of two tasks: to identify the benefits of an ethnographic approach in philosophy of science and to structure an ethnographic approach for philosophical investigation best adapted to provide information relevant to philosophical interests and epistemic values. To this end, we advocate for a purpose-guided form of cognitive ethnography that mediates between the explanatory and normative interests of philosophy of science, while maintaining openness and (...) independence when framing such an investigation to achieve robust unbiased results. (shrink)

Tracking technology has been heralded as transformative for animal ecology. In this paper I examine what changes are taking place, showing how current animal movement research is a field ripe for philosophical investigation. I focus first on how the devices alter the limitations and biases of traditional field observation, making observation of animal movement and behaviour possible in more detail, for more varied species, and under a broader variety of conditions, as well as restricting the influence of human presence and (...) observer bias. I reconstruct these as shifts in scope, objectivity, accuracy and fruitfulness. The second transformation is slightly less obvious but equally significant for animal ecology. Tracking devices generate complex data that demands both statistical and biological expertise, which has led to increasingly frequent and intensive collaborations between statisticians and biologists. Based on interviews, I examine how researchers in these interdisciplinary collaborations negotiate the collection, analysis and interpretation of movement data, integrating research interests, methodological constraints, previous field observations, and background theory. Tracking technology is therefore also shifting which disciplinary considerations are brought to bear on research into animal movement and behaviour and how this research is conducted. (shrink)

The standard view in current philosophy of creativity says that being creative has two requirements: being novel and being valuable. The standard view on creativity has recently become an object of critical scrutiny. Hills and Bird have specifically proposed to remove the value requirement from the definition, as it is not clear that creative objects are necessarily valuable or creative people necessarily praiseworthy. In this paper, I argue against Hills and Bird, since eliminating the element of value from the explanation (...) of creativity hinders the understanding of the role that creative products play in actual epistemic practices, which are fundamentally normative. More specifically, I argue that the terms ‘creativity’ and ‘creative’ function as thick epistemic concepts when employed by competent epistemic agents in practice, that is, these concepts have both a descriptive and an evaluative content that cannot be disentangled from one another. Accordingly, I suggest that philosophers should prefer thick accounts over thin accounts of creativity. A thick account of creativity is one that endorses the standard view at its basis, but further develops it in two ways: by stressing the entanglement of the value and novelty requirements; by permitting to encompass a range of domain-specific characterizations of such entanglement for different epistemic situations. In order to take the first steps in the development of such a thick account of creativity, I look at the domain of scientific practices as a case in point, and try to spell out what the thickness of creative instances typically entails here. Namely, I identify the worthy novelty of creative models and methods with their potential to clarify a tradition, with fruitfulness, and with the fulfilment of exploratory aims. (shrink)

The paper frames interdisciplinary research as creating complex, distributed cognitive-cultural systems. It introduces and elaborates on the method of cognitive ethnography as a primary means for investigating interdisciplinary cognitive and learning practices in situ. The analysis draws from findings of nearly 20 years of investigating such practices in research laboratories in pioneering bioengineering sciences. It examines goals and challenges of two quite different kinds of integrative problem-solving practices: biomedical engineering (hybridization) and integrative systems biology (collaborative interdependence). Practical lessons for facilitating (...) research and learning in these specific fields are discussed and a preliminary set of interdisciplinary epistemic virtues are proposed as candidates for cultivation in interdisciplinary practices of these kinds more widely. (shrink)

Modern integrative systems biology defines itself by the complexity of the problems it takes on through computational modeling and simulation. However in integrative systems biology computers do not solve problems alone. Problem solving depends as ever on human cognitive resources. Current philosophical accounts hint at their importance, but it remains to be understood what roles human cognition plays in computational modeling. In this paper we focus on practices through which modelers in systems biology use computational simulation and other tools to (...) handle the cognitive complexity of their modeling problems so as to be able to make significant contributions to understanding, intervening in, and controlling complex biological systems. We thus show how cognition, especially processes of simulative mental modeling, is implicated centrally in processes of model-building. At the same time we suggest how the representational choices of what to model in systems biology are limited or constrained as a result. Such constraints help us both understand and rationalize the restricted form that problem solving takes in the field and why its results do not always measure up to expectations. (shrink)

Prediction and control sufficient for reliable medical and other interventions are prominent aims of modeling in systems biology. The short-term attainment of these goals has played a strong role in projecting the importance and value of the field. In this paper I identify the standard models must meet to achieve these objectives as predictive robustness—predictive reliability over large domains. Drawing on the results of an ethnographic investigation and various studies in the systems biology literature, I explore four current obstacles to (...) achieving predictive robustness; data constraints, parameter uncertainty, collaborative constraints and system-scale requirements. I use a case study and the commentary of systems biologists themselves to show that current practices in the field, rather than pursuing these goals, frequently use models heuristically to investigate and build understanding of biological systems that do not meet standards of predictive robustness but are nonetheless effective uses of computation. A more heuristic conception of modeling allows us to interpret current practices as ways that manage these obstacles more effectively, particularly collaborative constraints, such that modelers can in the long-run at least work towards prediction and control. (shrink)

Metaphors of mind and their elaboration into models serve a crucial explanatory role in psychology. In this article, an attempt is made to describe how biology and engineering provide the predominant metaphors for contemporary psychology. A contrast between the discursive and descriptive functions of metaphor use in theory construction serves as a platform for deliberation upon the pragmatic consequences of models derived therefrom. The conclusion contains reflections upon the possibility of an integrative interdisciplinary psychology.

This paper describes some epistemic cultural considerations which shape the uses of psychology. I argue the study of mind is bound by the metaphysical background of the given locale and era in which it is practiced. The epistemic setting in which psychology takes place will shape what is worth observing, how it is to be studied, how the data is to be interpreted, and the nature of the ultimate explanatory units. To demonstrate conceptual epistemic constraints, I discuss metaphor use in (...) psychology. In addition, epistemic constraints shape the praxes that arise from structural study of the mind. In order to illustrate this cultural constraint, I discuss Soviet Psychology and provide a contrast between practical uses of psychoanalysis in India, Egypt, and rural Ghana. In response to these conceptual and practical epistemic limitations, psychology could adapt methods drawn from history and anthropology. (shrink)