The department of philosophy at National Chung Cheng University in Taiwan will host the Taiwan-Belgium Philosophy of Science Workshop on 12-13 September. Scholars from Université Catholique de Louvain (UCL) and several universities in Taiwan will present their recent works in the philosophy of science. The topics include three major categories: Causation in biology, models in science, and the scientific realism debate.
The event will be hold online, and is open to register before 24:00, Sep. 07. More information about the event and registration, please check here.
Three of the scholars from our institute, professor Jonathan Kricko and graduate student Ming-Jung Cheng and Yun-Ying Kuo, have the privilege to present a talk on the workshop. The topic and abstract of their talks is shown down below.
Theories that are more successful than their rivals are not more likely to contain approximately true parts if the evidence is misleading
Selective scientific realists infer from the success of scientific theories to the claim that those theories contain parts that are at least approximately true. This paper argues against a particular version of this sort of success-to-truth inference. It does so on the grounds that, in situations in which the overall evidential situation was misleading, theories were successful due to the fact that they contain parts that are not even approximately true.
The particular version of the success-to-truth inference that I’ll argue against is due to David Harker (2013). Harker develops a selective realist position in terms of a comparative notion of success that requires examining the ways in which theories achieved progress over their rivals. According to Harker’s comparative notion of success, a theory is more empirically successful than a rival, and thereby makes progress over its rival, if that theory predicts phenomena that are inexplicable or anomalous according to its rival. His form of selective realism is based on the idea
that we should regard as approximately true those parts of theories that make them comparatively more successful than their rivals.
One of the virtues of Harker’s defense of his position is that he clearly explains how his position ought to be assessed and what would count as a counterexample to his position. Harker identifies one historical counterexample to his position, which centers on Priestley’s successful prediction that heating a calx in hydrogen, which Priestley identified as pure phlogiston, would transform the calx into a metal. Harker (2013, p. 101) labels this case a “genuine counterexample” on the grounds that “empirical progress was achieved in a manner that relied on a theoretical
assumption that can no longer be regarded as approximately true,” namely, the assumption that the process by which a calx is transformed into a metal is a process of absorption. However, Harker states that, so long as his position can accommodate most historical cases, a single counterexample
doesn’t pose a problem. Harker closes his discussion of this counterexample by posing a challenge: “Antirealists who doubt my proposal on historical grounds are challenged to provide further examples that resemble Priestley’s” (2013, p. 101).
I aim to take up this challenge, and in order to identify some additional counterexamples to Harker’s position, I make use of Greg Frost-Arnold’s (2019) Problem of Misleading Evidence. The problem is that past scientists were often faced with a total body of evidence that misleadingly confirmed theories that, by current lights, we cannot regard as even approximately true. I argue that counterexamples to Harker’s position are, in general, cases in which the total evidence available at the time misleadingly confirmed a part of a theory that is not even approximately true. Frost-Arnold uses a number of historical cases to motivate the Problem of Misleading Evidence. In particular, he claims that misleading evidence confirmed Ptolemy’s geostatic model of the universe in the second century, the theory of spontaneous generation in the late eighteenth century, the caloric theory of heat in the early nineteenth century, and the theory that denies that the continents move in the early twentieth century. I argue that these four misleading evidence cases are counterexamples to Harker’s position. In each of these four cases, a theory made empirical progress over its rivals in virtue of a theoretical assumption that can no longer be regarded as even approximately true. I conclude that these counterexamples provide us with a strong reason to doubt Harker’s position and the kind of success-to-truth inference that he defends.
The more general upshot of my argument concerns cases in which theories are comparatively more successful than their rivals in the sense that they make progress over their rivals by successfully predicting phenomena that their rivals do not predict. Even if this sort of progress is due to specific parts of theories that we can identify, such progress may not be good evidence for the approximate truth of those parts of theories in virtue of which they make progress over their rivals. After all, the overall evidential situation may be misleading, and in such cases, the progress that theories make over their rivals may be due to parts of those theories that are not even approximately true.
Frost-Arnold, G. (2019). How to be a historically motivated antirealist: The problem of misleading evidence. Philosophy of Science, 86(5): 906-917. https://doi.org/10.1086/705453.
Harker, D. (2013). How to split a theory: Defending selective realism and convergence without proximity. The British Journal for the Philosophy of Science, 64(1), 79-106. https://doi.org/10.1093/bjps/axr059.
Idealized patient models in patient-centered care
Cheng, Min-Jung (speaker), Yong Alison Wang, Rong-San Jiang, Karen Yan
Patient-centered care (PCC) has become a prominent healthcare trend in the 21st century (Institute of Medicine, 2001). Many researchers have articulated various PCC concepts to inform clinical practice better (Mead & Bower, 2000; Tanenbaum, 2015). Some have offered further in-depth analyses of the nature of patients in PCC (Dahlberg et al., 2009; Entwistle & Watt, 2013). However, most researchers aim to give a general account of PCC or the nature of patients by stripping away the details regarding disease types and care contexts. For example, caring for stroke patients involves at least neuro-vascular knowledge and acute care context, but caring for cancer patients involves at least oncological knowledge and chronic care context. The general accounts of patients typically do not include these contextual details. But it is possible that being a patient in an acute care context is entirely different from being a patient in a chronic care context. The general accounts conceal this possibility.
We will use our clinical case studies to show how intuitively the same person becomes different types of patients by entering different care contexts. Our clinical case studies are about Taiwanese cancer patients receiving medical care in a cancer center. We will borrow the resources from Potochnik (2020) to examine how clinical professionals idealize the nature of patients when they construct “idealized patient models” for care practice. Our analysis goes beyond the literature on idealization by showing how idealized patient models socially instruct clinical encounters, specifically how people interact with each other in a clinical setting. From the perspective of the so-called distributed cognition (Nersessian, 2022), idealized patient models play critical roles in shaping the cognitive processes of clinical professionals and those encounters with clinical professionals.
Dahlberg, K., Todres, L., & Galvin, K. (2009). Lifeworld-led healthcare is more than patient-led care: An existential view of well-being. Medicine, Health Care and Philosophy, 12(3), 265–271. https://doi.org/10.1007/s11019-008-9174-7
Entwistle, V. A., & Watt, I. S. (2013). Treating Patients as Persons: A Capabilities Approach to Support Delivery of Person-Centered Care. The American Journal of Bioethics, 13(8), 29–39. https://doi.org/10.1080/15265161.2013.802060
Institute of Medicine. (2001). Crossing the Quality Chasm: A New Health System for the 21st Century. National Academies Press (US).
Mead, N., & Bower, P. (2000). Patient-centredness: A conceptual framework and review of the empirical literature. Social Science & Medicine, 51(7), 1087–1110. https://doi.org/10.1016/S0277-9536(00)00098-8
Nersessian, N. J. (2022). Interdisciplinarity in the Making: Models and Methods in Frontier Science. MIT Press.
Potochnik, A. (2020). Idealization and the Aims of Science. University of Chicago Press. https://press.uchicago.edu/ucp/books/book/chicago/I/bo27128726.html
Tanenbaum, S. J. (2015). What is Patient-Centered Care? A Typology of Models and Missions. Health Care Analysis, 23(3), 272–287. https://doi.org/10.1007/s10728-013-0257-0
Epistemic injustice in shared decision-making
Kuo, Yun-Ying (speaker), Yong Alison Wang, Rong-San Jiang, Karen Yan
Shared decision-making (SDM) refers to an ideal decision-making model for clinical encounters since 1972. This model emphasizes the joint participation of both practitioners and patients in making treatment or care plans during their decision-making process, especially factoring into the preferences and values of patients.
In this paper, we will focus on SDM in the cancer-care context and use our clinical case studies as supporting evidence for our arguments. Charles, Gafni, and Whelan’s (1997) (CGW, for short) definition of SDM in the cancer-care context was the most adopted one in various cancer guidelines (Carmona, Crutwell, Burnham, Polak, 2021). Their definition involves the following three conditions: (1) exchange of information between practitioners and patients, (2) both parties share their preferences toward treatment options, and (3) decide on a treatment plan with the agreement of both parties.
However, when the SDM guidelines adopt CGW’s definition, the three conditions are usually modified as the following: (1’) practitioners supply knowledge, including expertise and their experience, (2’) patients disclose their preferences and values in clinical conversation, and (3’) both parties reach an agreement on a treatment decision together. 
By comparing CGW’s definition and the SDM guidelines, we can see that (1) and (1’) are significantly different because (1’) takes away the patients’ role as information, knowledge, or experience providers. (2) and (2’) are also different because (2’) does not allow clinical professionals to express or share their preferences and values or neglect how their preferences and values affect the decision-making processes.
In this article, we will argue that the two modifications made by the guideline versions are epistemically unjust (Fricker, 2007). (1’) is epistemically unjust because it commits to what Fricker called testimonial injustice, a kind of wrong done to patients’ capacity as knowers of their illness experience and daily care practice. (2’) is epistemically unjust because it also commits to testimonial injustice, a kind of wrong done to clinical professionals’ capacity as knowers of what practice will work for a patient in a specific care context. This knowledge involves what Joyce and Cartwright (2019) called “local effectiveness prediction” in their criticism of the evidence-based practice.
To rectify the epistemically unjust modifications of CGW’s SDM definition, we propose to restore CGW’s original formulations of (1) and (2) and expand them to accommodate current cancer care practice. We will illustrate our proposed SDM definition with two clinical case studies to show how to respect patients’ capacity as knowers of their illness experience and daily care practice and clinical professionals’ capacity as knowers of what practice will work for a patient in a specific care context.
Carmona, C., Crutwell, J., Burnham, M., & Polak, L. (2021). Shared decision-making: Summary of NICE guidance. BMJ, 373, n1430. https://doi.org/10.1136/bmj.n1430
Charles, C., Gafni, A., & Whelan, T. (1997). Shared decision-making in the medical encounter: What does it mean? (or it takes at least two to tango). Social Science & Medicine, 44(5), 681–692. https://doi.org/10.1016/S0277-9536(96)00221-3
Fricker, M. (2007). Epistemic Injustice: Power and the Ethics of Knowing. Oxford University Press.
Joyce, K. E., & Cartwright, N. (2020). Bridging the Gap Between Research and Practice: Predicting What Will Work Locally. American Educational Research Journal, 57(3), 1045–1082. https://doi.org/10.3102/0002831219866687
Shared decision-making: Summary of NICE guidance | The BMJ. https://www.bmj.com/content/373/bmj.n1430
Veatch, R. M. (1972). Models for ethical medicine in a revolutionary age. What physician-patient roles foster the most ethical relationship? The Hastings Center Report, 2(3), 5–7