In recent discussions, there is wide agreement that philosophy of science should be rooted in actual scientific practice. This trend is, perhaps, particularly evident in discussions around scientific explanations, where philosophers are moving away from idealized textbook examples to scrutinize real-world scientific explanations through an in-depth engagement with case studies from various fields. However, the use of case studies has elicited concerns regarding the risk of bias and overgeneralization. This paper addresses such concerns and underscores how case studies can play a role in philosophical examinations of science.

Building on a proposal by Hasok Chang, I suggest that rather than as starting points for inductive generalizations, one way in which case studies can figure in philosophical examinations is as resources for abstraction. Discussing a concrete example from molecular biology, I further spell out this idea and demonstrate how detailed analyses of patterns of scientific reasoning can offer nuanced insights into explanatory practices. I conclude by outlining how the suggested perspective on case studies also contributes to a more comprehensive understanding of normativity within the philosophy of science in practice.

In the Call for Abstracts (CfA) for the Workshop of the GDWP questions are raised concerning the notion of scientific practices as there is still no common definition. Mostly, the notion of scientific practices is still linked to laboratories, in which the works of Bruno Latour or Karin Knorr-Cetina took place and thrived in the 1970s and 1980s. (Concerning the special institutional frame of the works of Bruno Latour see, e.g., Lars GERTENBACH / Henning LAUX, Zur Aktualität von Bruno Latour. Einführung in sein Werk (Wiesbaden 2019), 87-88 and Matthias WIESER, Das Netzwerk von Bruno Latour. Die Akteur-Netzwerk-Theorie zwischen Science & Technology Studies und poststrukturalistischer Soziologie (Bielefeld 2012), 5. And concerning the notion of laboratories as primary places of early practice studies see for example WIESER, Das Netzwerk von Bruno Latour, 22 or 24.) But as such institutions are only one of many, where scientific practices emerge and are at work, it becomes evident that practices in other places are seldom acknowledged. One of them is universities – scientific institutions combined with an emphasis on higher education at the same time. If we think of universities as scientific institutions, what are scientific practices that we come across there? I would argue that teaching would be one answer, next to doing research, writing books and essays, etc., which already shows that scientific practices are different from those applied in laboratories.

However, it seems, that there is still no sufficient theoretical background for research on scientific practices in universities, such as, e.g., teaching, although this practice is often (but not always) shaped by the newest state of research and researchers themselves. At universities (ideally) knowledge is discussed and exchanged (mostly with a hierarchical stance between lecturer and students). So, if discussions on the newest research do take place in classes or lectures, science can be debated and enhanced in those very moments, which is, as I would argue, part of scientific practices as well.

Also, adding the historical perspective as another argumentative layer, in the case of, e.g., Austria it becomes even more evident that universities and most of all, university teaching, were both a big part of “science”. For example, especially since the Student Revolution of 1848/49, “science” was embedded in Austrian lecture halls and textbooks and embedded into universities. (See for example Thomas MAISEL, Lehr- und Lernfreiheit und die ersten Schritte zu einer Universitäts- und Studienreform im Revolutionsjahr 1848, in: Christof AICHNER, Brigitte MAZOHL (Hg.), Die Thun-Hohenstein’schen Universitätsreformen 1849-1860 (Wien / Köln / Weimar 2017), 99-117, 105-106.) Consequently, in terms of pre-20th-Century science, it becomes evident that the term “scientific practices” only linked to non-university institutions, such as laboratories, becomes narrow, and thus, scientific practices at universities (e.g., university teaching) and their specific mechanisms (1) should be included when we think of “scientific practices” and (2) should be investigated further in the context of the “practice turn”.

In ecology, behavioral biology, and evolutionary biology a common scientific practice is to do research on a group-, a population-, and even on a species-level. This is done by collecting data of those groupings and calculating averages, standard deviations, growth rates, and other traits. However, a new trend seems to be taking root as scientists are becoming more and more interested in the individual differences and how these influence the groups, populations, and species (Bouchard and Huneman, 2013; Trappes, 2021, p. 5f; Uriarte and Menge, 2018). For example, if you want to know whether there are morphological size differences between two sexes of a population, you have to measure a number of individuals of both sexes and then group the results. By the end you have two groups of data based on individual measurements. You can now calculate the average sizes for both groups which may or may not reveal a significant size difference. With IBR, however, the information that can be gained, provides more insights into the individual and the intra-specific variation without losing any information about the group, population, or species.

Our research group is part of a larger collaborative research center (CRC) that includes biologists from ecology, behavioral, and evolutionary biology as well as two groups of philosophers of science. Within this CRC we have observed a shift from focusing on groups to focusing on individuals. To support our observations, we created a questionnaire, conducted interviews, and held a discussion round. Most of the participants claimed they were doing individual based research and described their methods and processes in detail. However, when asked to explain what IBR is, most answered with “doing research on individuals” in one variation or another. This explanation is rather unsatisfying as it would allow almost anything to pass as individual based research including the example given earlier. Also, this explanation clashes with the methods and processes the biologists described. We found that IBR has at least three main characteristics: identifiability, multiple measurements, and individual-based analysis. All individuals should be identifiable. This can be done by spatial separation (placing individual fruit flies into test boxes), phenotypic traits (individual markings of fire salamanders), tagging (ringing birds), or tracking (GPS trackers on sea lion, e.g.: Schwarz et al., n.d.). Multiple measurements means that there has to be more than one piece of information. This can be done with an ongoing test that takes place over a longer period of time, tests that are repeated in a certain interval, or measurements of multiple traits without repetition. Lastly,

the analysis of the data should be individual based. While the data can be grouped to calculate averages or variation within the groups, it is also analyzed in a way that allows a clear depiction of the individual. This makes the final results traceable and individually distinguishable.

This list of features is not exhaustive further analysis of IBR is taking place with the focus being on the epistemic consequences of conducting IBR.

Despite its central epistemic role, the nature of the standards by which an observational claim is accepted has received little philosophical and historical attention. Chalmers (1985, 2013) has noted the transition from an Aristotelian doctrine of observation based on perception to the acceptance of telescopic observations promoted by Galileo’s demonstrations. Franklin (2013) has discussed the rise of a discovery standard in particle physics based on statistical significance and its subsequent transitions. More recently, Dawid (2021) has noted the need to integrate meta-empirical assessments into the concept of empirical confirmation in the period of the acceptance of atomism that led to a justified observation of microphysical objects. However, these authors have focused on specific historical periods without intending to provide a broader understanding of the implications of these transformations. In this talk, I defend the claim that an atemporal set of standards that can be used as necessary and sufficient conditions for evaluating observational claims is alien to the nature of scientific practice.

The liberal attitude regarding the concept of observation in scientific practice is governed by the dynamical nature of standards of acceptability for observations. I argue that the historically influential empiricist view of observation, which sees perception as a static central standard for an observation, has overshadowed the long-standing dynamic nature of the concept of observation in scientific practice, which is governed by transformations in its standards.

Advances in science and technology have increasingly provided us with new observational methods and means to extend our senses and observe aspects of the world that are inaccessible to our optical instruments of observation. This has influenced our understanding of the concept of observation and allowed scientists to adopt a permissive attitude toward the concept. As a result, what qualifies as a standard for accepting a proper observational claim has become relative to the socio-historical context in which the observation is made. Thus, there do not seem to be universally fixed and static standards for evaluating scientific observations. Instead, the scientific community adheres to a specific set of standards in each context.

For the purposes of this talk, I will draw on the examples provided by the aforementioned authors to argue that, in general, at each stage, the community manages to accept an update to the standards by appealing to the common scientific and conceptual toolkit available in that context. The common toolkit may include, for example, background knowledge, basic shared assumptions, coincidence and robustness arguments, eliminative reasoning and technical skills. The introduction of new means of observation does not result in abrupt changes in standards. Instead, specific standards may persist or be layered through stages of theoretical and methodological changes. This suggests the need for a contextual understanding of observation. The above consideration further suggests that the community’s acceptance of the dynamic nature of observational standards in practice is not inconsistent with a rational understanding of scientific change.

References

• Chalmers, Alan. “Galileo’s Telescopic Observations of Venus and Mars.” The British Journal for the Philosophy of Science 36, no. 2 (1985): 175–84.
• Chalmers, Alan. What Is This Thing Called Science? The University of Queensland Press/The Humanities Press, 2013, 4th edition.
• Dawid, R. “The role of meta-empirical theory assessment in the acceptance of atomism.” Stud Hist Philos Sci. 2021 Dec; 90:50-60.
• Franklin, Allan. “Is Seeing Believing? Observation in Physics”. Phys. Perspect. 19 (2017): 321–423.
• Franklin, Allan. Shifting Standards: Experiments in Particle Physics in the Twentieth Century. University of Pittsburgh Press, 2013.

In particle physics practice, individual or subgroups of Feynman diagrams are often taken to be representative of particle interactions. In papers relating to the discovery of a Higgs candidate in 2012, the CMS Collaboration at the LHC used individual Feynman diagrams to illustrate different decay channels that produce a Higgs particle (see, e.g., The CMS Collaboration 2013). In quantum many-particle physics, so-called ladder diagrams appear, for example, in the Hartree-Fock method of approximating the energy of a quantum many-body system in its ground state. Only specific, ladder-looking types of Feynman diagrams are considered and summed over (see Broadhurst 1993, Ablinger et al. 2012).

It thus seems apparent that physicists use Feynman diagrams to visualize the content of the debate, illustrate their argumentations, and further the readers’ understanding of their paper – they use Feynman diagrams to represent the physical situation.

This conflicts with the general perception of Feynman diagrams in philosophy of science, where they are commonly considered mathematical artifacts of a perturbative approach to calculating cross sections. Only all infinite possibilities of some particles to interact, corresponding each to a Feynman diagram, are linked to one interaction. Therefore, it has been previously argued that, given the most common accounts of representation, individual diagrams do not represent (see Dorato and Rossanese 2018; Brown 2018).

In this talk, I present a revised account of representation suitable for areas where we have little knowledge of the target system. Returning to the most fundamental question of representation – in virtue of what does a model represent a target? – I develop an agent-centred account of representation in which Feynman diagrams, considered as a model of the corresponding particle interaction, represent the interaction in virtue of providing understanding of it. This aim is the justification for using the model to represent the target. It is thus a functionalist account of representation, aiming at understanding the target with the model, rather than at making causal inferences about the target system through model inferences. It allows the accommodation of models, in our case Feynman diagrams, to represent a target without having to make claims about the reality of the model ingredients, and without requiring isomorphic mapping or literal truthfulness. Hence, it is suitable for highly speculative areas of science, and reconciles scientific practice in particle physics with philosophy of science.

References

• Ablinger, Jakob et al. (2012). ‘Massive 3-loop ladder diagrams for quarkonic local operator matrix elements’. In: Nuclear Physics B 864.1, pp. 52–84.
• Broadhurst, D. J. (1993). ‘Summation of an infinite series of ladder diagrams’. In: Physics Letters B 307.1, pp. 132–139.
• Brown, James Robert (2018). ‘How Do Feynman Diagrams Work?’ In: Perspectives on Science 26.4, pp. 423–442.
• Dorato, Mauro and Emanuele Rossanese (2018). ‘The Nature of Representation in Feynman Diagrams’. In: Perspectives on Science 26.4, pp. 443–458.
• The CMS Collaboration (2013). ‘Evidence for the 125 GeV Higgs boson decaying to a pair of leptons’. In: Journal of High Energy Physics 2014.5, pp. 587–609.