This chapter argues that our self-knowledge is often mediated by our affective self-knowledge. In other words, we often know about ourselves by knowing our own emotions. More precisely, what Cassam has called “substantial self-knowledge” (SSK), such as self-knowledge of one's character, one's values, or one's aptitudes, is mediated by affective forecasting, which is the process of predicting one's emotional responses to possible situations. For instance, a person comes to know that she is courageous by predicting her own emotional reactions to (...) possible risks and dangers. This hypothesis explains why attaining substantive self-knowledge tends to be difficult. Attaining substantive self-knowledge is difficult because, first, SSK is mediated by affective forecasting and, second, we tend to be wrong about predicting the intensity and duration of our own emotional reactions. As a result, we can identify what is common to central cases of SSK: such cases require knowledge about complex dispositions whose manifestations involve affective responses that one is not sufficiently familiar with. One thus needs to resort to the highly fallible method of affective forecasting. (shrink)

REVIEW (1): "Jeff Kochan’s book offers both an original reading of Martin Heidegger’s early writings on science and a powerful defense of the sociology of scientific knowledge (SSK) research program. Science as Social Existence weaves together a compelling argument for the thesis that SSK and Heidegger’s existential phenomenology should be thought of as mutually supporting research programs." (Julian Kiverstein, in Isis) ---- REVIEW (2): "I cannot in the space of this review do justice to the richness and range of Kochan's (...) discussion [...]. There is a great deal in this foundational portion of Kochan's discussion that I find tremendously interesting and engaging [...]." (David R. Cerbone, in Studies in History and Philosophy of Science) ---- REVIEW (3): "Science as Social Existence will be of interest not only to Heidegger scholars but to anyone engaged in science and technology studies. [...] This is an informative and original book. Kochan should be praised for his clear, pleasant-to-read prose." (Michael Butler, in CHOICE). (shrink)

In August 2002, three Indian computer scientists published a paper, ‘PRIMES is in P’, online. It presents a ‘deterministic algorithm’ which determines in ‘polynomial time’ if a given number is a prime number. The story was quickly picked up by the general press, and by this means spread through the scientific community of complexity theorists, where it was hailed as a major theoretical breakthrough. This is although scientists regarded the media reports as vulgar popularizations. When the paper was published in (...) a peer-reviewed journal only two years later, the three scientists had already received wide recognition for their accomplishment. Current sociological theory challenges the ability to clearly distinguish on independent epistemic grounds between distorted and non-distorted scientific knowledge. It views the demarcation lines between such forms of presentation as contextual and unstable. In my paper, I challenge this view. By systematically surveying the popular press coverage of the ‘PRIMES is in P’ affair, I argue--against the prevailing new orthodoxy--that distorted simplifications of scientific knowledge are distinguishable from non-distorted simplifications on independent epistemic grounds. I argue that in the ‘PRIMES is in P’ affair, the three scientists could ride on the wave of the general press-distorted coverage of their algorithm, while counting on their colleagues’ ability to distinguish genuine accounts from distorted ones. Thus, their scientific reputation was unharmed. This suggests that the possibility of the existence of independent epistemic standards must be incorporated into the new SSK model of popularization. (shrink)

We study the representation of sets of desirable gambles by sets of probability mass functions. Sets of desirable gambles are a very general uncertainty model, that may be non-Archimedean, and therefore not representable by a set of probability mass functions. Recently, Cozman (2018) has shown that imposing the additional requirement of even convexity on sets of desirable gambles guarantees that they are representable by a set of probability mass functions. Already more that 20 years earlier, Seidenfeld et al. (1995) gave (...) an axiomatisation of binary preferences—on horse lotteries, rather than on gambles—that also leads to a unique representation in terms of sets of probability mass functions. To reach this goal, they use two devices, which we will call ‘SSK–Archimedeanity’ and ‘SSK–extension’. In this paper, we will make the arguments of Seidenfeld et al. (1995) explicit in the language of gambles, and show how their ideas imply even convexity and allow for conservative reasoning with evenly convex sets of desirable gambles, by deriving an equivalence between the SSK–Archimedean natural extension, the SSK–extension, and the evenly convex natural extension. (shrink)

Author's response to: Raphael Sassower, 'Heidegger and the Sociologists: A Forced Marriage?,' Social Epistemology Review and Reply Collective 7, no. 5 (2018): 30-32. -- Part of a book-review symposium on: Jeff Kochan (2017), Science as Social Existence: Heidegger and the Sociology of Scientific Knowledge (Cambridge UK: Open Book Publishers).

Final instalment of a book-review symposium on: Jeff Kochan (2017), Science as Social Existence: Heidegger and the Sociology of Scientific Knowledge (Cambridge UK: Open Book Publishers). -- Author's response to: Paolo Palladino (2018), 'Heidegger Today: On Jeff Kochan’s Science and Social Existence,' Social Epistemology Review and Reply Collective 7(8): 41-46; and Adam Riggio (2018), 'The Very Being of a Conceptual Scheme: Disciplinary and Conceptual Critiques,' Social Epistemology Review and Reply Collective 7(11): 53-59.

In “A Tension in the Strong Program: The Relation between the Rational and the Social”, Shahram Shahryari (2021) advances the following thesis: In his Strong Program in the sociology of science, David Bloor blames traditional philosophy of science for adopting a dualist strategy in explaining scientific developments, as it employs rational explanation for successful science and social explanation for flawed science. Instead, according to Bloor, all scientific developments should be explained monistically, i.e. in terms of social causes. This is also (...) referred to as the Symmetry Principle, and it is a key tenet in the Strong Program. The author detects a tension here, as Bloor apparently asserts that traditional philosophy of science deploys two kinds of explanation, and simultaneously insists that there is only one kind, i.e. social explanation. (shrink)

Author's response to: Pablo Schyfter, 'Inaccurate Ambitions and Missing Methodologies: Thoughts on Jeff Kochan and the Sociology of Scientific Knowledge,' Social Epistemology Review and Reply Collective 7, no. 8 (2018): 8-14. -- Part of a book-review symposium on: Jeff Kochan (2017), Science as Social Existence: Heidegger and the Sociology of Scientific Knowledge (Cambridge UK: Open Book Publishers).

In his article, “The Strong Program and Asymmetrical Explanation of the History of Science: A Reply to Collin” (Shahryari 2022b), Shahram Shahryari responds to my comments (in Collin 2022) upon his original article, “A Tension in the Strong Program: The Relation between the Rational and the Social” (Shahryari 2022a). I believe that in this new contribution, Shahryari changes the subject as compared to our original discussion. Hence, before I comment upon his recent contribution, I want to recapitulate briefly the content (...) of that discussion. (shrink)

In this article, I provide a historical and philosophical discussion of the so-called “science wars”. The term “science wars” refers to a series of debates which took place in the second half of the 1990s and which centered on the status of science and the nature of scientific knowledge. On the one hand, a group of authors reacted against what they perceived as a “postmodern” attack on science. This in turn led to several reactions from those who were labeled as (...) “postmodernists”. Among these, some authors in turn claimed that it were the scientists and their epigones who were the real aggressors, using the authority of science to attack any form of critical thinking and even democracy itself. I first provide a short historical overview and analysis of the science wars. The aim of this overview is to show how critics of postmodernism ignored differences between different approaches in science studies and in this way constructed the idea of the existence of a homogeneous postmodern attack on science. This resulted in an intellectual trench war, in which more nuanced positions got overlooked, being trapped in the no man’s land between two extreme positions. After this historical overview, I explore this no man’s land. I discuss several scholars and approaches within science studies that had been grouped together by critics of postmodernism. I will focus on the differences between these approaches, thus providing a more nuanced picture of science studies. Finally, I argue for the relevance of revisiting the science wars. Blindly labelling (certain approaches in) science studies as “anti science” disables us from using important insights from these studies, insights which could be relevant in dealing with complex societal issues in which scientific knowledge plays a role such as climate change. (shrink)