Riana Betzler

In 1949, the social psychologists Leonard S. Cottrell, Jr. and Rosalind Dymond wrote a paper calling for increased attention to the empathic responses in empirical social psychology. The empathic responses, they wrote, “occupy a crucial position in human interaction and adjustment” (Psychiatry 12(4):355–359, 1949, https://doi.org/10.1080/00332747.1949.11022747 ). Not only practically important for therapy and communication, the empathic responses were considered to be foundational for the very development of the self. In this paper, I examine challenges that arose in the 1940s and 1950s, when researchers attempted to subject empathy to scientific scrutiny. I focus specifically on conceptual and methodological problems that Dymond faced in developing her measures of empathy, which are typically considered to be the first in existence. This foray into the history of empathy measures offers a case study for considering questions about validity and coherence in the philosophy of psychological measurement.

We have noticed a worrying trend of students receiving failing grades because they disappear. They stop showing up to class and stop submitting work. They become unresponsive to email and do not take up offers of help. In a real sense, these students fail but have not taken the class. In this essay, we attempt to address this issue by examining systemic and structural features of higher education that contribute to this phenomenon, using our home institution, San José State University, as an example. We look at add/drop policies and argue that they create an environment that is hostile for the student population our university serves—primarily first-generation students of color with low socioeconomic status. We argue that these policies constitute an instance of structural injustice that becomes systemic when combined with other sources of injustice in our students’ lives. We situate these structural and systemic injustices within larger discussions of the hidden curriculum and decolonial approaches to pedagogy. Finally, we conclude with a call to action. We urge others to consider university-level policy as a source of structural injustice that interacts with wider systems of injustice. The details of how this works, however, will differ depending on contextual details particular to individual systems.

Contemporary healthcare environments are becoming increasingly informationally demanding. This requires patients, and those supporting them, to engage with a broad range of expert knowledge. At the same time, patients must find ways to make sense of this information in the context of their own values and needs. In this article, we confront the problem of communication in our current age of complexity. We do this by focusing on a field that has already had to grapple with these issues directly: genetic counseling. We articulate an empathy-based framework that provides a way to integrate the teaching and counseling models of genetic counseling. As well as being useful for those providing genetic counseling in the era of genomic medicine, this framework has the potential to address challenges of communication in healthcare settings beyond genetic counseling. Furthermore, it has important ramifications for ethical debates about autonomy and decision-making.

Many people think of empathy as a powerful force for good within society and as a crucial component of moral cognition. Recently, prominent theorists in psychology and philosophy have challenged this viewpoint and mounted a case against empathy. The most compelling versions of this case rely heavily on empirical evidence from psychology and neuroscience. They contend that the inherent partiality and parochialism of empathy undermines its potential to serve moral ends. This paper argues that the argument against empathy overreaches; it makes an unwarranted inference from descriptive evidence about our empathic capacities to normative claims about the proper role of empathy in culture, society, and ethics. The paper concludes with suggestions about how to use insights from the empirical literature to build a more nuanced and contextually sensitive account of the role of empathy in our ethical lives.

Questions about how empathy should be conceptualized have long been a preoccupation of the field of empathy research. There are numerous definitions of empathy that have been proposed and that often overlap with other concepts such as sympathy and compassion. This makes communication between research groups or across disciplines difficult. Many researchers seem to see the diversity of definitions as a problem rather than a form of benign pluralism. Within this debate about conceptualization, researchers sometimes suggest that more neuroscientific evidence will make the problem go away – that uncovering the processes underlying empathy will thereby also sort out conceptual difficulties. In this paper, I challenge this assumption by examining how neuroscientists studying empathy use concepts in practice – both in the development of their measures and in the interpretation of their data. I argue that this neuroscientific literature demonstrates that continuity and stability comes from the use of cert...

This paper argues that enthusiasm for empathy has grown to the point at which empathy has taken on the status of an “ideal” in modern medicine. We need to pause and scrutinize this ideal before moving forward with empathy training programs for medical students. Taking empathy as an ideal obscures the distinction between the multiple aims that calls for empathy seek to achieve. While these aims may work together, they also come apart and yield different recommendations about the sort of behavior physicians should cultivate in a given situation. I begin by demonstrating how enthusiasm for empathy has increased dramatically. I then specify precisely what I mean in calling empathy an “ideal.” I then describe some dangers associated with taking empathy to be an ideal unreflectively. I discuss the merits of works that provide conceptualizations of empathy that are specifically tailored for the medical domain and conclude that although these works move discussions about empathy in medical care forward, they could do more to foreground the goals and aims underlying calls for increased empathy. I provide specific suggestions as to how exactly we might foreground these goals and aims to further avoid conceptual confusion about empathy in medical education.

Philosophers of science have offered several definitions of mechanism, most of which have biological or neuroscientific roots. In this paper, I consider whether these definitions apply equally well to cognitive science. I examine this question by looking at the case of statistical learning, which has been called a domain-general learning mechanism in the cognitive scientific literature. I argue that statistical learning does not constitute a mechanism in the philosophical sense of the term. This conclusion points to significant limitations in the scope of the mechanist philosophy when it comes to accounting for explanation in cognitive science.

Recent trends in the debate about natural kinds tend towards increasingly permissive and practice-oriented views. I argue that while these accounts—which I characterize using Boyd’s ([1991]) term ‘enthusiasm’—offer several helpful insights, they often lack the normative force that they want to have; that is, they cannot provide an account of what makes something a good or bad, better or worse, kind for scientific pursuits. I argue that such accounts can regain a minimal sense of normativity in two ways. The first, which has already been widely embraced by theorists, is to index the appropriateness of a scientific kind to the domain within which it is situated. While this is a good solution, it is not clear how it can be applied in interdisciplinary and cross-domain research pursuits, which are increasingly common. The second way of regaining normativity—which is especially, but not exclusively, effective for such cross-domain pursuits—is to attend to the stage at which scientific research is occurring.