Abstract‘Serendipity’ is a category used to describe discoveries in science that occur at the intersection of chance and wisdom. In this paper, I argue for understanding serendipity in science as an emergent property of scientific discovery, describing an oblique relationship between the outcome of a discovery process and the intentions that drove it forward. The recognition of serendipity is correlated with an acknowledgment of the limits of expectations about potential sources of knowledge. I provide an analysis of serendipity in science (...) as a defense of this definition and its implications, drawing from theoretical and empirical research on experiences of serendipity as they occur in science and elsewhere. I focus on three interrelated features of serendipity in science. First, there are variations of serendipity. The process of serendipitous discovery can be complex. Second, a valuable outcome must be obtained before reflection upon the significance of the unexpected observation or event in respect to that outcome can take place. Therefore, serendipity is retrospectively categorized. Third, the primacy of epistemic expectations is elucidated. Finally, I place this analysis within discussions in philosophy of science regarding the impact of interpersonal competition upon the number and significance of scientific discoveries. Thus, the analysis of serendipity offered in this paper contributes to discussions about the social-epistemological aspects of scientific discovery and has normative implications for the structure of epistemically effective scientific communities. (shrink)

Wagenknecht a récemment introduit une distinction conceptuelle entre dépendance épistémique translucide et dépendance épistémique opaque, dans le but de mieux rendre compte de la diversité des relations de dépendance épistémique au sein des pratiques collaboratives de recherche. Dans la continuité de son travail, mon but est d’expliciter les différents types d’expertise requis lorsque sont employés instruments et ordinateurs dans la production de connaissance, et d’identifier des sources potentielles d’opacité. Mon analyse s’appuie sur un cas contemporain de création de connaissance scientifique, (...) à savoir le traitement de données astrophysiques. (shrink)

Diversity of practice is widely recognized as crucial to scientific progress. If all scientists perform the same tests in their research, they might miss important insights that other tests would yield. If all scientists adhere to the same theories, they might fail to explore other options which, in turn, might be superior. But the mechanisms that lead to this sort of diversity can also generate epistemic harms when scientific communities fail to reach swift consensus on successful theories. In this paper, (...) we draw on extant literature using network models to investigate diversity in science. We evaluate different mechanisms from the modeling literature that can promote transient diversity of practice, keeping in mind ethical and practical constraints posed by real epistemic communities. We ask: what are the best ways to promote an appropriate amount of diversity of practice in scientific communities? (shrink)

​I use network models to simulate social learning situations in which the dominant group ignores or devalues testimony from the marginalized group. I find that the marginalized group ends up with several epistemic advantages due to testimonial ignoration and devaluation. The results provide one possible explanation for a key claim of standpoint epistemology, the inversion thesis, by casting it as a consequence of another key claim of the theory, the unidirectional failure of testimonial reciprocity. Moreover, the results complicate the understanding (...) and application of previously discovered network epistemology effects, notably the Zollman effect (Zollman 2007, 2010). (shrink)

Recent philosophical work has praised the reward structure of science, while recent empirical work has shown that many scientific results may not be reproducible. I argue that the reward structure of science incentivizes scientists to focus on speed and impact at the expense of the reproducibility of their work, thus contributing to the so-called reproducibility crisis. I use a rational choice model to identify a set of sufficient conditions for this problem to arise, and I argue that these conditions plausibly (...) apply to a wide range of research situations. Currently proposed solutions will not fully address this problem. Philosophical commentators should temper their optimism about the reward structure of science. (shrink)

Prepublication peer review should be abolished. We consider the effects that such a change will have on the social structure of science, paying particular attention to the changed incentive structure and the likely effects on the behaviour of individual scientists. We evaluate these changes from the perspective of epistemic consequentialism. We find that where the effects of abolishing prepublication peer review can be evaluated with a reasonable level of confidence based on presently available evidence, they are either positive or neutral. (...) We conclude that on present evidence abolishing peer review weakly dominates the status quo. (shrink)

The communist norm requires that scientists widely share the results of their work. Where did this norm come from, and how does it persist? Michael Strevens provides a partial answer to these questions by showing that scientists should be willing to sign a social contract that mandates sharing. However, he also argues that it is not in an individual credit-maximizing scientist's interest to follow this norm. I argue against Strevens that individual scientists can rationally conform to the communist norm, even (...) in the absence of a social contract or other ways of socially enforcing the norm, by proving results to this effect in a game-theoretic model. This shows that the incentives provided to scientists through the priority rule are sufficient to explain both the origins and the persistence of the communist norm, adding to previous results emphasizing the benefits of the incentive structure created by the priority rule. (shrink)

I present a novel, collaborative, methodology for linguistics: what I call the ‘explanatory economy’. According to this picture, multiple models/theories are evaluated based on the extent to which they complement one another with respect to data coverage. I show how this model can resolve a long-standing worry about the methodology of generative linguistics: that by creating too much distance between data and theory, the empirical credentials of this research program are tarnished. I provide justifications of such methodologically central distinctions as (...) the competence/performance and core/periphery distinction, and then show how we can understand the push for simplicity in the history of generative grammar in this light. (shrink)

Résumé. En trente ans, le rapport d’Internet à l’entreprise scientifique a changé. Nous sommes passés d’un instrument de collaboration scientifique à un dispositif de réseaux sociaux qui assure la plus large diffusion à l’irrationalisme et à l’alt-factualisme. Pour comprendre ce changement, il convient de réexaminer les mécanismes de la convergence des opinions. La première source de cette convergence est l’existence d’un monde commun, qui nous expose aux mêmes faits et qui détermine par révision successive des croyances de chacun, sans que (...) la moindre communication soit requise, une convergence asymptotique des opinions, et ce quelles que soient les croyances de départ. Naturellement, si les faits connus par les uns sont communiqués aux autres, cette convergence s’accélère considérablement, si bien que nous devons considérer la connaissance comme le résultat d’une activité collective, et l’échange d’informations comme l’une de ses sources nécessaires. D’une part, cette coopération épistémique est naturelle et facilement implémentable : en vertu des propriétés caractéristiques de l’information, qui est un bien que nous conservons lorsque nous le donnons, le partage informationnel est exempt des difficultés qui affectent généralement la coopération. D’autre part, cette coopération est intrinsèquement productive : la collaboration entre celui qui sait que φ et celui qui sait que φ implique ψ met chacun des deux agents en possession de la connaissance de ψ, qui n’était pourtant détenue par personne avant l’échange. L’internet des débuts donne à cette coopération informationnelle une ampleur inégalée. La situation actuelle est différente. Un certain nombre de facteurs, dont la porosité croissante entre les scientifiques et le large public, ont mis au premier plan l’échange, non des informations factuelles, mais celui des opinions. Les biais notoires de la psychologie humaine, au premier rang desquels le biais de confirmation, tendent à inverser le rapport entre les faits et les opinions. On cherche les faits confirmant les opinions entretenues, on met en doute les faits récalcitrants et l’on crée des faits corroborants. En bref, on passe d’une problématique de la coopération à une logique de l’affiliation, segmentant l’internet en groupes doxastiques homogènes. (shrink)

W ciągu 30 lat dokonała się głęboka przemiana w relacji między Internetem a aktywnością naukową. Nastąpiło przesunięcie funkcji Internetu, który przestał być jedynie instrumentem współpracy akademickiej, a stał się również narzędziem używanym przez media społecznościowe, zezwalające na maksymalną dyfuzję irracjonalizmu i starego faktualizmu. Aby zrozumieć tę przemianę, należy ponownie zbadać mechanizmy zbieżności opinii. Wynika ona z istnienia wspólnego świata, który ukazuje nam te same fakty i determinuje nieustanną rewizję przekonań każdej osoby. W tym procesie asymptotycznej zbieżności opinii nie wymaga się (...) żadnej komunikacji między jednostkami. Oczywiście, jeśli fakty znane przez jednych są komunikowane innym, konwergencja znacznie przyspiesza, i to tak bardzo, że wiedzę musimy ująć jako rezultat zbiorowej aktywności, w której wymiana informacji jest jednym z jej istotnych źródeł. Z jednej strony takie poznawcze współdziałanie wydaje się naturalne i łatwe do implementacji. Biorąc pod uwagę właściwości informacji, które przechowujemy, nawet jeśli je udostępniamy, to dzielenie się informacją przestaje być przedmiotem zwykłych trudności związanych ze współpracą. Z drugiej strony takie współdziałanie jest produktywne z samej natury: współpraca między kimś, kto zna φ, i kimś, kto wie, że φ implikuje ψ u obydwu jako mających wiedzę ψ, której żaden z nich nie posiadał przed wymianą informacji. Wczesny Internet pozwolił na ekstremalną intensywność tej informacyjnej współpracy. Obecnie mamy do czynienia z odmienną sytuacją. Poszczególne wyznaczniki rosnącej porowatości między naukowcami a opinią publiczną wzmocniły rolę wymiany. Nie jest to już wymiana informacji, lecz wymiana opinii. Stronniczość tkwiąca w naturze ludzkiej, a szczególnie potwierdzenie tej stronniczości, prowadzi do odwrócenia relacji między faktami a opiniami. Szukamy faktów potwierdzających podzielane przez nas opinie, wątpiąc w te, które ich nie określają, i tworzymy fakty do potwierdzenia tego, o czym jesteśmy przekonani. Dlatego przechodzimy od współdziałania do przynależności, dzieląc Internet na homogeniczne grupy wyznawców. (shrink)

‘Serendipity’ is a category used to describe discoveries in science that occur at the intersection of chance and wisdom. In this paper, I argue for understanding serendipity in science as an emergent property of scientific discovery, describing an oblique relationship between the outcome of a discovery process and the intentions that drove it forward. The recognition of serendipity is correlated with an acknowledgment of the limits of expectations about potential sources of knowledge. I provide an analysis of serendipity in science (...) as a defense of this definition and its implications, drawing from theoretical and empirical research on experiences of serendipity as they occur in science and elsewhere. I focus on three interrelated features of serendipity in science. First, there are variations of serendipity. The process of serendipitous discovery can be complex. Second, a valuable outcome must be obtained before reflection upon the significance of the unexpected observation or event in respect to that outcome can take place. Therefore, serendipity is retrospectively categorized. Third, the primacy of epistemic expectations is elucidated. Finally, I place this analysis within discussions in philosophy of science regarding the impact of interpersonal competition upon the number and significance of scientific discoveries. Thus, the analysis of serendipity offered in this paper contributes to discussions about the social-epistemological aspects of scientific discovery and has normative implications for the structure of epistemically effective scientific communities. (shrink)

What differentiates scientific research from non-scientific inquiry? Philosophers addressing this question have typically been inspired by the exalted social place and intellectual achievements of science. They have hence tended to point to some epistemic virtue or methodological feature of science that sets it apart. Our discussion on the other hand is motivated by the case of commercial research, which we argue is distinct from (and often epistemically inferior to) academic research. We consider a deflationary view in which science refers to (...) whatever is regarded as epistemically successful, but find that this does not leave room for the important notion of scientific error and fails to capture distinctive social elements of science. This leads us to the view that a demarcation criterion should be a widely upheld social norm without immediate epistemic connotations. Our tentative answer is the communist norm, which calls on scientists to share their work widely for public scrutiny and evaluation. (shrink)

Recent empirical work has shown that many scientific results may not be reproducible. By itself, this does not entail that there is a problem. However, I argue that there is a problem: the reward structure of science incentivizes scientists to focus on speed and impact at the expense of the reproducibility of their work. I illustrate this using a well-known failure of reproducibility: Fleischmann and Pons' work on cold fusion. I then use a rational choice model to identify a set (...) of sufficient conditions for this problem to arise, and I argue that these conditions plausibly apply to a wide range of research situations. In the conclusion I consider possible solutions and implications for how Fleischmann and Pons' work should be evaluated. (shrink)

I discuss a game-theoretic model in which scientists compete to finish the intermediate stages of some research project. Banerjee et al. have previously shown that if the credit awarded for intermediate results is proportional to their difficulty, then the strategy profile in which scientists share each intermediate stage as soon as they complete it is a Nash equilibrium. I show that the equilibrium is both unique and strict. Thus rational credit-maximizing scientists have an incentive to share their intermediate results, as (...) long as this is sufficiently rewarded. (shrink)