There has been increased attention on how scientific communities should respond to spurious dissent. One proposed method is to hide such dissent by preventing its publication. To investigate this, I computationally model the epistemic effects of hiding dissenting evidence on scientific communities. I find that it is typically epistemically harmful to hide dissent, even when there exists an agent purposefully producing biased dissent. However, hiding dissent also allows for quicker correct epistemic consensus among scientists. Quicker consensus may be important when (...) policy decisions must be made quickly, such as during a pandemic, suggesting times when hiding dissent may be useful. (shrink)

Here I look to some work in the historical sciences in order to draw out some of the epistemic benefits of “speculative narratives,” which bears on some more general epistemic benefits of speculative reasoning. Due to the contingent nature of much historical evidence, some degree of speculative reasoning is necessary to get the epistemological ball rolling in the historical sciences, and I argue that speculative narratives provide the necessary sort of frameworking apparatus for doing precisely this. I use contemporary work (...) on the first peopling of the Americas (the “Clovis First Debate”) for illustration. (shrink)

Imagination is extremely important for science, yet very little is known about how scientists actually use it. Are scientists taught to imagine? What do they value imagination for? How do social and disciplinary factors shape it? How is the labor of imagining distributed? These questions should be high priority for anyone who studies or practices science, and this paper argues that the best methods for addressing them are qualitative. I summarize a few preliminary findings derived from recent interview-based and observational (...) qualitative studies that I have performed. These finding include: (i) imagination is only valued for use in addressing maximally specific problems, and only when all else fails; (ii) younger scientists and scientists who are members of underrepresented groups express less positive views about imagination in general, and have less confidence in their own imaginations; (iii) while scientists seem to employ various epistemological frameworks to evaluate imaginings, overall they appear to be epistemic consequentialists about imagination, and this holds also for their evaluations of the tools they use to extend the power of their imaginations. I close by discussing the epistemic and ethical consequences of these findings, and then suggesting a few research avenues that could be explored next as we move forward in the study of scientific imagination. (shrink)

There is a growing concern for the proper role of science within democratic societies, which has led to the development of new science policies for the implementation of social responsibility in research. Although the very expression ‘social responsibility of science’ may be interpreted in different ways, many of these emerging policy frameworks define it, at least in part, as a form of anticipative reflection about the potential impacts of research in society. What remains a rather under-discussed issue is the definition (...) of the bearer of the social responsibility of science. In other words, it is not clear who is supposed to engage in such an anticipative reflection, whether individual researchers or research groups. In the past few years, philosophers of science have begun to use qualitative research methods to fill the gaps between normative models of the organisation of ideal scientific communities and the reality of actual scientific practices. In this article, I follow this approach to discuss the issue of the collective dimension of the social responsibility of science. I rely on a qualitative study conducted on an interdisciplinary research group and I describe how group dynamics position individuals and distribute duties and roles, including social responsibility. Qualitative descriptions of the distribution of duties within actual research groups should inform the formulation of general prescriptive theories on the collective responsibility of science. (shrink)

Scientists recognize the necessity of imagination for solving tough problems. But how does the cognitive faculty responsible for daydreaming help in solving scientific problems? Philosophers claim that imagination is informative only when it is constrained to be maximally realistic. However, using a case study from space science, we show that scientists use imagination intentionally to break reality-oriented constraints. To do this well, they first target low-confidence constraints, and then higher-confidence constraints, until a plausible solution is found. This paper exemplifies a (...) new approach to epistemology of imagination that focuses on sets of imaginings (rather than individual imaginings), and responsible (rather than reliable) imaginings. (shrink)

Citation metrics are statistical measures of scientific output that draw on citation indexes. They purport to capture the impact of scientific articles and the journals in which they appear. As evaluative tools they are mostly used in the natural sciences, but they are also acquiring an important role in the humanities. While the strengths and weaknesses of citation metrics are extensively debated in a variety of fields, they have only recently started attracting attention in the philosophy of science. This paper (...) takes a further step in this direction and presents an analysis of citation metrics from the perspective of a Kuhnian model for the development of science. To do so, it assesses the argument made against the use of citation metrics for scientific research by Gillies (2008). According to Gillies, citations metrics tend to over-protect normal science at the expenses of revolutionary science–in other words, reinforce the status quo rather than supporting innovations and breakthroughs. Unlike Gillies, this paper focuses on the context of normal science and shows that citation metrics can in fact arbitrarily hinder its development when they do not take field-specific differences into account. In light of this, the paper cautions against their use for evaluative purposes. To argue for this conclusion, the paper shows that citation metrics fail to “carve science at its joints” and thus cannot be relied upon as indicators of scientific quality that can support the development of normal science. (shrink)

People with bad beliefs — roughly beliefs that conflict with those of the relevant experts and are maintained regardless of counter-evidence — are often cast as bad believers. Such beliefs are seen to be the result of, e.g., motivated or biased cognition and believers are judged to be epistemically irrational and blameworthy in holding them. Here I develop a novel framework to explain why people form bad beliefs. People with bad beliefs follow the social epistemic norms guiding how agents are (...) supposed to form and share beliefs within their respective communities. Beliefs go bad because these norms aren’t reliably knowledge-conducive. In other words, bad beliefs aren’t due to bad believers but due bad social epistemic norms. The framework also unifies different explanations of bad beliefs, is testable and provides distinct interventions to combat such beliefs. The framework also helps to capture the complex and often contextual normative landscape surrounding bad beliefs more adequately. On this picture, it’s primarily groups that are to be blamed for bad beliefs. I also suggest that some individuals will be blameless for forming their beliefs in line with their group’s norms, whereas others won’t be. And I draw attention to the factors that influence blameworthiness-judgements in these contexts. (shrink)

General epistemic polarization arises when the beliefs of a population grow further apart, in particular when all agents update on the same evidence. Epistemic factionalization arises when the beliefs grow further apart, but different beliefs also become correlated across the population. I present a model of how factionalization can emerge in a population of ideally rational agents. This kind of factionalization is driven by probabilistic relations between beliefs, with background beliefs shaping how the agents’ beliefs evolve in the light of (...) new evidence. Moreover, I show that in such a model, the only possible outcomes from updating on identical evidence are general convergence or factionalization. Beliefs cannot spread out in all directions: if the beliefs overall polarize, then it must result in factionalization. (shrink)

In the social epistemology of scientific knowledge, it is largely accepted that relationships of trust, not just reliance, are necessary in contemporary collaborative science characterised by relationships of opaque epistemic dependence. Such relationships of trust are taken to be possible only between agents who can be held accountable for their actions. But today, knowledge production in many fields makes use of AI applications that are epistemically opaque in an essential manner. This creates a problem for the social epistemology of scientific (...) knowledge, as scientists are now epistemically dependent on AI applications that are not agents, and therefore not appropriate candidates for trust. (shrink)

While the debate on values in science focuses on normative questions on the level of the individual (e.g. should researchers try to make their work as value free as possible?), comparatively little attention has been paid to the institutional and professional norms that researchers are expected to follow. To address this knowledge gap, we conduct a content analysis of leading national codes of conduct for research integrity of European countries, and structure our analysis around the question: do these documents allow (...) for researchers to be influenced by “non-epistemic” (moral, cultural, commercial, political, etc.) values or do they prohibit such influence in compliance with the value-free ideal (VFI) of science? Our results return a complex picture. On the one hand, codes of conduct consider many non-epistemic values to be a legitimate influence on the decision-making of researchers. On the other, most of these documents include what we call _VFI-like positions_: passages claiming that researchers should be free and independent from any external influence. This shows that while many research integrity documents do not fully endorse the VFI, they do not reject it and continue to be implicitly influenced by it. This results in internal tensions and underdetermined guidance on non-epistemic values that may limit some of the uses of research integrity codes, especially for purposes of ethical self-regulation. While codes of conduct cannot be expected to decide how researchers should act in every instance, we do suggest that they acknowledge the challenges of how to integrate non-epistemic values in research in a more explicit fashion. (shrink)

Microaggressions are hypothesized to play a causal role in undesirable population effects such as racial health gaps, but the mechanisms through which this occurs are not yet well understood. I call inquiry about these mechanisms the “explanatory project.” I suggest that the explanatory project has been hindered by microaggression concepts tailored to be applicable under conditions of lived uncertainty, rather than to facilitate understanding of structural causes. I defend a pluralist, structural account of microaggressions from arguments by Regina Rini that, (...) while appropriate for ethical projects, do not apply to the explanatory project. (shrink)

We review several topics of philosophical interest connected to misleading online content. First we consider proposed definitions of different types of misleading content. Then we consider the epistemology of misinformation, focusing on approaches from virtue epistemology and social epistemology. Finally we discuss how misinformation is related to belief polarization, and argue that models of rational polarization present special challenges for conceptualizing fake news and misinformation.

Biomedical deployments of data science capitalise on vast, heterogeneous data sources. This promotes a diversified understanding of what counts as evidence for health-related interventions, beyond the strictures associated with evidence-based medicine. Focusing on COVID-19 transmission and prevention research, I consider the epistemic implications of this diversification of evidence in relation to: (1) experimental design, especially the revival of natural experiments as sources of reliable epidemiological knowledge; and (2) modelling practices, particularly the recognition of transdisciplinary expertise as crucial to developing and (...) interpreting data models. Acknowledging such shifts in evidential, experimental and modelling practices helps avoid harmful applications of data-intensive methods. (shrink)

Correspondence in Nature Human Behaviour.

The concept of moralisation of health behaviours was introduced in social psychology to describe the attribution of moral properties to habits and conditions like smoking or being a vegetarian. Moral properties are powerful motivators for people and institutions, as they may trigger blame, stigma, and appraisal, as well as the polarisation of interest and scientific hype. Here I extend the concept and illustrate how medicines and treatments can be seen as if they had moral properties, too, when they come to (...) be regarded as good or bad in the moral sense, and not just in the instrumental sense of benefiting or harming health. I propose the hydroxychloroquine (HCQ) controversy of 2020 as an example of moralisation of a medicine. HCQ and chloroquine are anti-malarial drugs, whose off-label use for Covid-19 was hotly discussed in the early months of the pandemic, both in the media and within the scientific community, and eventually dismissed when robust evidence came out. The point of the paper is to show that moralisation of health products and treatments may influence individual and institutional decisions in significant ways, and also affect research. For these reasons, it should be carefully monitored and critically assessed. (shrink)

Given that values influence the scientific process, including when doing economics, we should be asking under what conditions this influence is justifiable. In this paper, I argue that citizen engagement could be the best way to scrutinize and justify value influences in economics. To do so, I analyze a number of citizen engagement initiatives in economics and discuss how they contribute to value scrutiny. Next, I look at the rationales that have been formulated for such a citizen economics, like, e.g., (...) increasing economic literacy, democratization, and, strengthening the legitimacy of economics, and I evaluate their benefits for the scrutiny of values. Overall, the paper concludes that citizen engagement is a promising way to address value judgments in economics and to make economics epistemically more robust even though there are still some challenges to be addressed for it to become part of a broadened economic methodology. (shrink)

Assumptions about obesity—e.g., its connection to ill health, its causes, etc.—are still prevalent today, and they make up what I call the medical model of fatness. In this paper, I argue that the medical model was established on the basis of insufficient evidence and has nevertheless continued to be relied upon to justify methodological choices that further entrench the assumptions of the medical model. These choices are illegitimate in so far as they conflict with both the epistemic and social aims (...) of obesity research. I conclude the paper with a partial solution to these epistemic and social shortcomings. (shrink)

Enlightenment science and medicine achieved different levels of accuracy and precision as both sought rationality, empiricism, and the spread of human happiness. Animal magnetism was a unique medical phenomenon of late Enlightenment Paris that established trust with the public and had a significant cultural impact. Yet this method was not reproducible, involved limited rule-following, and lacked a coherent theoretical framework. Lessons from this phenomenon have included the first use of the placebo and the first design and implementation of careful, controlled (...) experimentation in the medical context. Another lesson can be the power of demonstration and spectacle in communicating medical innovations. In fact, the underpinnings of science – the reproducibility of a certain scientific experiment and the rules, know-hows, and theories it assures – can be so conveyed to the public. (shrink)

When solving a complex problem in a group, should group members always choose the best available solution that they are aware of? In this paper, I build simulation models to show that, perhaps surprisingly, a group of agents who individually randomly follow a better available solution than their own can end up outperforming a group of agents who individually always follow the best available solution. This result has implications for the feminist philosophy of science and social epistemology.

Scientific disagreements sometimes persist even if scientists fully share results of their research. In this paper we develop an agent-based model to study the impact of diverging diagnostic values scientists may assign to the evidence, given their different background assumptions, on the emergence of polarization in the scientific community. Scientists are represented as Bayesian updaters for whom the diagnosticity of evidence is given by the Bayes factor. Our results suggest that an initial disagreement on the diagnostic value of evidence can, (...) but does not necessarily, lead to polarization, depending on the sample size of the performed studies and the confidence interval within which scientists share their opinions. In particular, the more data scientists share,the more likely it is that the community will end up polarized. (shrink)

In response to broad transformations brought about by the digitalization, globalization, and commodification of research processes, the Open Science [OS] movement aims to foster the wide dissemination, scrutiny and re-use of research components for the good of science and society. This Element examines the role played by OS principles and practices within contemporary research and how this relates to the epistemology of science. After reviewing some of the concerns that have prompted calls for more openness, I highlight how the interpretation (...) of openness as the sharing of resources, so often encountered in OS initiatives and policies, may have the unwanted effect of constraining epistemic diversity and worsening epistemic injustice, resulting in unreliable and unethical scientific knowledge. By contrast, I propose to frame openness as the effort to establish judicious connections among systems of practice, predicated on a process-oriented view of research as a tool for effective and responsible agency. (shrink)

I examine error diagnosis (model-model disagreement) in climate model intercomparisons including its difficulties, fruitful examples, and prospects for streamlining error diagnosis. I suggest that features of climate model intercomparisons pose a more significant challenge for error diagnosis than do features of individual model construction and complexity. Such features of intercomparisons include, e.g., the number of models involved, how models from different institutions interrelate, and what scientists know about each model. By considering numerous examples in the climate modeling literature, I distill (...) general strategies (e.g., employing physical reasoning and using dimension reduction techniques) used to diagnose model error. Based on these examples, I argue that an error repertoire could be beneficial for improving error diagnosis in climate modeling, although constructing one faces several difficulties. Finally, I suggest that the practice of error diagnosis demonstrates that scientists have a tacit-yet-working understanding of their models which has been under-appreciated by some philosophers. (shrink)

There remains no consensus among social scientists as to how to measure and understand forms of information deprivation such as misinformation. Machine learning and statistical analyses of information deprivation typically contain problematic operationalizations which are too often biased towards epistemic elites’ conceptions that can undermine their empirical adequacy. A mature science of information deprivation should include considerable citizen involvement that is sensitive to the value-ladenness of information quality and that doing so may improve the predictive and explanatory power of extant (...) models. (shrink)

This white paper outlines the plans of the History Philosophy Culture Working Group of the Next Generation Event Horizon Telescope Collaboration.

This paper shows how institutional values influence the design and evaluation of arguments in funding proposals for research. We characterize a general argument made within proposals and several kinds of subarguments that contribute to it. We indicate that funders’ values inform the kinds of proposal documents funders require and their relative weighting of them. We illustrate these points by showing how a program office in the U.S. federal agency NOAA uses its public service mission to require and heavily weigh arguments (...) to transition new knowledge to NOAA service providers. We suggest conceptual questions raised by the use of transition knowledge. (shrink)

Scientists imagine constantly. They do this when generating research problems, designing experiments, interpreting data, troubleshooting, drafting papers and presentations, and giving feedback. But when and how do scientists learn how to use imagination? Across 6 years of ethnographic research, it has been found that advanced career scientists feel comfortable using and discussing imagination, while graduate and undergraduate students of science often do not. In addition, members of marginalized and vulnerable groups tend to express negative views about the strength of their (...) imaginations and the general usefulness of imagination in science. After introducing these findings and discussing the typical relationship between a scientist and their imagination across a career, we argue that reducing the number or power of active imaginations in science is epistemically counterproductive. We suggest several ways to bring imagination back into science in a more inclusive way, especially through courses on imagination for scientists, good role models, and exemplar-based learning. (shrink)

Cancer biology features the ascription of normal functions to parts of cancers. At least some ascriptions of function in cancer biology track local normality of parts within the global abnormality of the aberration to which those parts belong. That is, cancer biologists identify as functions activities that, in some sense, parts of cancers are supposed to perform, despite cancers themselves having no purpose. The present paper provides a theory to accommodate these normal function ascriptions—I call it the Modeling Account of (...) Normal Function (MA). MA comprises two claims. First, normal functions are activities whose performance by the function-bearing part contributes to the self-maintenance of the whole system and, thereby, results in the continued presence of that part. Second, MA holds that models of system-level activities that are (partly) constitutive of self-maintenance are improved by including a representation of the relevant function-bearing part and by making reference to the activity/activities that part performs which contribute(s) to those system-level activities. I contrast MA with two other accounts that seek to explicate the ascription of normal functions in biology, namely, the organizational account and the selected effects account. Both struggle to extend to cancer biology. However, I offer ecumenical readings which allow them to recover some ascriptions of normal function to parts of cancers. So, though I contend that MA excels in this respect, the purpose of this paper is served if it provides materials for bridging the gap between cancer biology, philosophy of cancer, and the literature on function. (shrink)

Scientific curation, where scientific evidence is selected and shared, is essential to public belief formation about science. Yet common curation practices can distort the body of evidence the public sees. Focusing on science journalism, we employ computational models to investigate how such distortions influence public belief. We consider these effects for agents with and without confirmation bias. We find that standard journalistic practices can lead to significant distortions in public belief; that preexisting errors in public belief can drive further distortions (...) in reporting; that practices that appear relatively unobjectionable can produce serious epistemic harm; and that, in some cases, common curation practices related to fairness and extreme reporting can lead to polarization. (shrink)

This chapter gives an overview of the various themes and issues discussed in the volume. It includes summaries of all chapters and places the contributions, some of which are part of a critical conversation format, in the context of the larger literature and debates.

Scientific activities strongly depend on concepts and classifications to represent the world in an orderly and workable manner. This creates a trade-off. On the one hand, it is important to leave space for conceptual and classificatory criticism. On the other hand, agreement on which concepts and classifications to use, is often crucial for communication and the integration of research and ideas. In this paper, we show that this trade-off can sometimes be best resolved through conceptual governance, in which scientific institutions (...) set a collective conceptual standard, and that voting can be a reasonable way to implement that governance. Voting is a means to simultaneously aggregate among conflicting values, preferences and priorities that often underpin conceptual or classificatory debates, all while signaling ongoing disagreement. We also discuss how the legitimacy of the voting process and its outcome can be ensured. (shrink)

Citation metrics are statistical measures of scientific outputs that draw on citation indexes. They purport to capture the impact of scientific articles and the journals in which they appear. As evaluative tools, citation metrics are mostly used in the natural sciences, but they are also acquiring an important role in the humanities, thereby affecting the development of research programs and institutions. While the strengths and weaknesses of citation metrics are extensively debated in a variety of fields, they have only recently (...) started attracting attention in the philosophy of science. This paper takes a further step in this direction and presents an analysis of citation metrics from the perspective of a Kuhnian model for the development of science. To do that, it starts with an overview of citation metrics both at the general level and at the level of specific metrics, such as Impact Factor, h-index, and field-specific indicators. After that, it engages with Gillies’ argument against the use of citation metrics for scientific research. According to Gillies (2008), citation metrics tend to over-protect normal science at the expenses of revolutionary science. This paper shows that, under certain conditions, citation metrics can in fact arbitrarily hinder the development of normal science and, in light of this, it cautions against using them for evaluative purposes. (shrink)

Biodiversity science is in a pivotal period when diverse groups of actors—including researchers, businesses, national governments, and Indigenous Peoples—are negotiating wide-ranging norms for governing and managing biodiversity data in digital repositories. These repositories, often called biodiversity data portals, are a type of organization for which governance can address or perpetuate the colonial history of biodiversity science and current inequities. Researchers and Indigenous Peoples are developing and implementing new strategies to examine and change assumptions about which agents should count as salient (...) participants in scientific projects, especially in projects that build and manage large digital data portals. Two notable efforts are the FAIR (Findable, Accessible, Interoperable, Reusable) and CARE (Collective benefit, Authority, Responsibility, Ethics) Principles for scientific data management and governance. To characterize how these principles influence the governance of biodiversity data portals, we develop an account of fit-for-use data that makes explicit its social as well as technical conditions in relation to agents and purposes. The FAIR Principles, already widely adopted by biodiversity researchers, prioritize machine agents and efficient computation, while the CARE Principles prioritize Indigenous Peoples and their data sovereignty. Both illustrate the potency of an emerging general strategy by which groups of actors craft and implement governance principles for data fitness-of-use to change assumptions about who are salient participants in data science. (shrink)

We investigate the explanatory role of epistemic virtue in accounting for the success of science as a social institution that is characterized by predominantly epistemic ends. Several structural explanations of the epistemic success of science that commonly rule out virtue attributions to scientists are explored in reference to a case of collective epistemic vice; namely, the credibility crisis in the social and behavioral sciences. These accounts underline the social structure of science as the chief explanatory factor in its collective success, (...) and endorse a common conclusion, namely that individual virtue is neither necessary nor sufficient for science to be successful. While acknowledging that divergent motivations and behaviors might also serve the collective goals of science, our analysis of the credibility crisis shows that the presence of a significant proportion of epistemically virtuous scientists in a scientific community is a necessary condition for collective epistemic success in a scientific community. (shrink)

The persistent pervasiveness of inappropriately small studies in empirical fields is regu-larly deplored in scientific discussions. Consensually, taken individually, higher-powered studies are more likely to be truth-conducive. However, are they also beneficial for the wider performance of truth-seeking communities? We study the impact of sample sizes on collective exploration dynamics under ordinary conditions of resource limita-tion. We find that large collaborative studies, because they decrease diversity, can have detrimental effects in certain realistic circumstances that we characterize precisely. We show how (...) limited inertia mechanisms may partially solve this pooling dilemma and dis-cuss our findings briefly in terms of editorial policies. (shrink)

Biodiversity scientists often describe their field as aiming to save life and humanity, but the field has yet to reckon with the history and contemporary practices of colonialism and systematic racism inherited from natural history. The online data portals scientists use to store and share biodiversity data are a growing class of organizations whose governance can address or perpetuate and further institutionalize the implicit assumptions and inequitable social impacts from this extensive history. In this context, researchers and Indigenous Peoples are (...) developing and implementing new strategies to examine and change assumptions about which agents should count as salient participants to scientific projects, especially projects that build and manage large digital data portals. Two notable efforts are the FAIR and CARE Principles for scientific data management and governance. To characterize how these influence the governance of biodiversity data portals, we develop an account of fitness-for-use that makes explicit its social as well as technical conditions in relation to agents and purposes. The FAIR Principles, already widely adopted by biodiversity data projects, prioritize machine agents and efficient computation, while the CARE Principles prioritize Indigenous Peoples and their data sovereignty. Both illustrate the potency of an emerging general strategy by which groups of actors craft and implement governance principles for data fitness-of-use to change assumptions about salient participants to data science. (shrink)

This essay presents a unified account of safety, sensitivity, and severe testing. S’s belief is safe iff, roughly, S could not easily have falsely believed p, and S’s belief is sensitive iff were p false S would not believe p. These two conditions are typically viewed as rivals but, we argue, they instead play symbiotic roles. Safety and sensitivity are both valuable epistemic conditions, and the relevant alternatives framework provides the scaffolding for their mutually supportive roles. The relevant alternatives condition (...) holds that a belief is warranted only if the evidence rules out relevant error possibilities. The safety condition helps categorise relevant from irrelevant possibilities. The sensitivity condition captures ‘ruling out’. Safety, sensitivity, and the relevant alternatives condition are typically presented as conditions on warranted belief or knowledge. But these properties, once generalised, help characterise other epistemic phenomena, including warranted inference, legal verdicts, scientific claims, reaching conclusions, addressing questions, warranted assertion, and the epistemic force of corroborating evidence. We introduce and explain Mayo’s severe testing account of statistical inference. A hypothesis is severely tested to the extent it passes tests that probably would have found errors, were they present. We argue Mayo’s account is fruitfully understood using the resulting relevant alternatives framework. Recasting Mayo’s condition using the conceptual framework of contemporary epistemology helps forge fruitful connections between two research areas—philosophy of statistics and the analysis of knowledge—not currently in sufficient dialogue. The resulting union benefits both research areas. (shrink)

Using the examples of physics, mathematics and psychology, traditionally used by philosophers and historians of science to demonstrate different levels of “maturity” and “accuracy” of science, the article shows that at the present stage the differences between “mature” and “immature” sciences fade out. General trends of modern sciences are highlighted: growing disunity and fractionation, a split between different levels of science, as well as the difficulty in defining a criterion for the demarcation of scientific and non-scientific knowledge. Therefore, the stigmatization (...) of the social sciences is inadequate, and the crises of identity of psychologists and sociologists are unfounded. In connection with the fractionation of science, it is possible to predict, along with interdisciplinary research, a greater number of multi-paradigm or multi-approach studies, which, to a certain extent, make it possible to reconcile various scientific worldviews within one science. (shrink)

Extant accounts of trust in science focus on reconciling scientific and public value judgments, but neglect the challenge of learning audience values. I argue that for scientific experts to be epistemically trustworthy, they should adopt a cooperative approach to learning about the values of their audience. A cooperative approach, in which expert and non-expert inquirers iteratively refine value judgments, better achieves important second-order epistemic dimensions of trustworthiness. I suggest that strong objectivity in the feminist standpoint theoretic sense is sometimes a (...) prerequisite for trustworthiness. (shrink)

We examine arguments for and against the use of mechanistic evidence in assessing treatment efficacy and find that advocates of EBM+ and their critics have largely been talking past each other due to difference in focus. We explore aducanumab for the treatment of Alzheimer’s disease as a case which may speak to the role of EBM+ in pharmaceutical regulation. The case suggests the debate may be more fruitful if philosophers confine debates to particular domains of medical science and weigh in (...) prospectively instead of relying on historical cases where outcomes are known and which are susceptible to hindsight bias. (shrink)

The social epistemology of science would benefit from paying more attention to the nature of argumentative exchanges. Argumentation is not only a cognitive activity but a collaborative social activity whose functioning needs to be understood from a psychological and communicative perspective. Thus far, social and organizational psychology has been used to discuss how social diversity affects group deliberation by changing the mindset of the participants. Argumentative exchanges have comparable effects, but they depend on cognitive diversity and emerge through critical interaction. (...) An example of a cognitive psychological theory is discussed that explains how mutual reasoning affects how we think, make decisions, and solve problems, as well as how cognitive biases may facilitate an efficient division of cognitive labor. These observations are compared with the existing results in the social epistemology of science. Moreover, I explicate the conceptual differences between the distributed and social processing of information. While argumentative exchanges belong to the latter domain, most existing simulations model distributed processing, which may compromise their real-world relevance and proper conceptual interpretation. However, I aim not to criticize the existing simulation methods but to promote an approach from the cognitive psychology of reasoning that complements the current use of organizational psychology and computer simulations by investigating a different set of mechanisms relating to similar phenomena of interest in the social epistemology of science. (shrink)

Agent-based modelling has become a well-established method in social epistemology and philosophy of science but the question of what kind of explanations these models provide remains largely open. This paper is dedicated to this issue. It starts by distinguishing between real-world phenomena, real-world possibilities, and logical possibilities as different kinds of targets which agent-based models can represent. I argue that models representing the former two kinds provide how-actually explanations or causal how-possibly explanations. In contrast, models that represent logical possibilities provide (...) epistemically opaque how-possibly explanations. While highly idealised ABMs in the form in which they are initially proposed typically fall into the last category, the epistemic opaqueness of explanations they provide can be reduced by validation procedures. To this purpose, an examination of results of simulations in terms of classes of models can be particularly helpful. I illustrate this point by discussing a class of ABMs of scientific interaction and the claim that a high degree of interaction can impede scientific inquiry. (shrink)

Diversity of social identities can improve the performance of groups through varied cognitive and communicative pathways. Recently, research efforts have focused on identifying when we should expect to see these potential benefits in real-world settings. While most research to date has studied this topic at individual and interpersonal levels, in this paper, we develop an agent-based model to explore how various aspects of homophily, the tendency of individuals to associate with similar others, affects performance at a larger scale. Study 1 (...) examines how two types of homophily---identity-driven and opinion-driven---impact collective performance on a sequential decision-making task via modulating network formation and trust relations. Study 2 considers how the presence of identity-based conformity pressure can affect the findings from the first study. Overall, we find that the effect of homophily on performance is complex, depending on the operative dimensions of similarity, mediating pathways, and the specific outcome of interest. Finally, we discuss the implications of our results for policy interventions aiming to improve group performance. (shrink)

Confirmation bias has been widely studied for its role in failures of reasoning. Individuals exhibiting confirmation bias fail to engage with information that contradicts their current beliefs, and, as a result, can fail to abandon inaccurate beliefs. But although most investigations of confirmation bias focus on individual learning, human knowledge is typically developed within a social structure. We use network models to show that moderate confirmation bias often improves group learning. However, a downside is that a stronger form of confirmation (...) bias can hurt the knowledge producing capacity of the community. (shrink)

Is science getting at the truth? The sceptics – those who spread doubt about science – often employ a simple argument: scientists were sure in the past, and then they ended up being wrong. Such sceptics draw on dramatic quotes from eminent scientists such as Lord Kelvin, who reportedly stated at the turn of the 20th century “There is nothing new to be discovered in physics now,” shortly before physics was dramatically transformed. They ask: given the history of science, wouldn’t (...) it be naïve to think that current scientific theories reveal ‘the truth’, and will never be discarded in favour of other theories? Through a combination of historical investigation and philosophical-sociological analysis, Identifying Future-Proof Science defends science against such potentially dangerous scepticism. It is argued that we can confidently identify many scientific claims that are future-proof: they will last forever, so long as science continues. How do we identify future-proof claims? This appears to be a new question for science scholars, and not an unimportant one. It is argued that the best way to identify future-proof science is to avoid any attempt to analyse the relevant first-order scientific evidence, instead focusing purely on second-order evidence. Specifically, a scientific claim is future-proof when the relevant scientific community is large, international, and diverse, and at least 95% of that community would describe the claim as a ‘scientific fact’. In the entire history of science, no claim meeting these criteria has ever been overturned, despite enormous opportunity. (shrink)

Envy is pervasive in academia. What are its epistemic effects? I present a characterization of envy that captures some of its essential features according to the philosophical literature. I use this characterization to illustrate a classic argument that views envy as collectively disadvantageous. Then, based on insights from the social epistemology of science, I evaluate this argument in the context of academic research. I argue that given the nature of epistemic goods, the best strategies available to the envious academic typically (...) lead to collective epistemic benefits. I conclude by presenting a challenge for the design of epistemic institutions: it is difficult to restructure institutions to reduce envy without severe epistemic drawbacks. (shrink)

An expert is commonly considered to be somebody who possesses the right kind of knowledge and skills to find out true answers for questions in a domain. However, this common conception that focuses only on an individual’s knowledge and skills is not very useful to understand the epistemically interdependent nature of contemporary scientific expertise, which becomes increasingly more relevant due to the rise of large interdisciplinary research collaborations. The typical scientific expert today relies substantially on complex scientific instruments and numerous (...) other experts in forming expert judgment. Moreover, we have research collaborations where multiple scientists interact in a way that gives rise to distributed cognitive systems, which can act as a single informant. Accordingly, our concept of scientific expertise should not consist only in individual knowledge and skills, but also accommodate epistemic dependence and collective knowledge production. To this aim, this paper proposes a reconstruction of the concept of scientific expertise as informant reliability by building on the virtue-epistemological account of epistemic competences and theories of extended and distributed cognition. Considered in reference to the social epistemic function of expertise, a scientific expert should be conceived as a reliable informant in a scientific domain, which implies that when consulted on matters in that domain they assert competently, honestly, and completely. Competent expert assertion involves the epistemic responsibility to draw on nothing but the highest degree of epistemic competence relevant to the given context. Thus, being a reliable informant may require one to draw on an extended epistemic competence that goes beyond one’s individual competence, or to form supra-individual or group-informants that manifest collectively the kind of complex epistemic competence required for the investigation of certain research questions. (shrink)

The epistemic subject of collective scientific knowledge has been a matter of dispute in recent philosophy of science and epistemology. Following the distributed cognition framework, both collective-subject accounts (most notably by Knorr-Cetina, in _Epistemic Cultures_, Harvard University Press, 1999) as well as no-subject accounts of collective scientific knowledge (most notably by Giere, Social Epistemology 21:313–320, 2007; in Carruthers, Stich, Siegal (eds), _The Cognitive Basis of Science_, Cambridge University Press, 2002a) have been offered. Both strategies of accounting for collective knowledge are (...) problematic from the perspective of mainstream epistemology. Postulating genuinely collective epistemic subjects is a high-commitment strategy with little clear benefit. On the other hand, eliminating the epistemic subject radically severs the link between knowledge and knowers. Most importantly, both strategies lead to the undesirable outcome that in some cases of scientific knowledge there might be no individual knower that we can identify. I argue that distributed cognition offers us a fertile framework for analyzing complex socio-technical processes of contemporary scientific knowledge production, but scientific knowledge should nonetheless be located in individual knowers. I distinguish between the production and possession of knowledge, and argue that collective knowledge is collectively produced knowledge, not collectively possessed knowledge. I then propose an account of non-testimonial, expert scientific knowledge which allows for collectively produced knowledge to be known by individuals. (shrink)

There are different varieties of conservatism concerning belief formation and revision. We assesses the veritistic effects of a particular kind of conservatism commonly attributed to Quine: the so-called maxim of minimum mutiliation, which states that agents should give up as few beliefs as possible when facing recalcitrant evidence. Based on a formal bounded rationality model of belief revision, which parametrizes degree of conservatism, and corresponding multi-agent simulations, we eventually argue against doxastic conservatism from the vantage point of veritistic social epistemology.

This article emphasises the academic possibilities of autoethnography using a philosophical and theoretical framework to underpin it. The author uses a proposed research project to illustrate how and why autoethnography should be considered an academic methodology appropriate for a Doctor of Philosophy study. Crotty’s research paradigm model informs the author’s theoretical framework with a focus on Social Constructionism and Symbolic Interactionism as it’s foundations. The intention of the article is to encourage other doctoral candidates to consider the scholarly attributes of (...) autoethnography for their own research endeavours through the utilisation of an interpretivist research paradigm. (shrink)

Criticism is a staple of the scientific enterprise and of the social epistemology of science. Philosophical discussions of criticism have traditionally focused on its roles in relation to objectivity, confirmation, and theory choice. However, attention to criticism and to criticizability should also inform our thinking about scientific pursuits: the allocation of resources with the aim of developing scientific tools and ideas. In this paper, we offer an account of scientific pursuitworthiness which takes criticizability as its starting point. We call this (...) the apokritic model of pursuit. Its core ideas are that pursuits are practices governed by norms for asking and answering questions, and that criticism arises from the breach of these norms. We illustrate and advertise our approach using examples from institutional grant review, neuroscience, and sociology. We show that the apokritic model can unify several indices of criticizability, that it can account for the importance of criticizing pursuits in scientific practice, and that it can offer ameliorative advice to erstwhile pursuers. (shrink)

This paper advocates for making epistemic interests a central object of philosophical analysis in epistemology and philosophy of science. It is argued that the importance of epistemic interests derives from their fundamental importance for the notion of objectivity. Epistemic interests are defined as individuated by a set of objectives, each of which represents a dimension of the search for truth. Among these dimensions, specificity, sensitivity, and productivity are discussed in detail. It is argued that the relevance of productivity is often (...) overlooked in debates about the ends and means of science. A definition of the objectivity of inquiry is proposed that takes the notion of epistemic interest as its starting point. (shrink)

Recent years have seen a notable increase in the production of scientific expertise by large multidisciplinary groups. The issue we address is how reports may be written by such groups in spite of their size and of formidable obstacles: complexity of subject matter, uncertainty, and scientific disagreement. Our focus is on the International Panel on Climate Change, unquestionably the best-known case of such collective scientific expertise. What we show is that the organization of work within the IPCC aims to make (...) it possible to produce documents that are indeed expert reports. To do so, we first put forward the epistemic norms that apply to expert reports in general, that is, the properties that reports should have in order to be useful and to help decision-making. Section 2 claims that these properties are: intelligibility, relevance and accuracy. Based on this analysis, section 3 points to the difficulties of having IPCC reports indeed satisfying these norms. We then show how the organization of work within the IPCC aims at and to a large extent secures intelligibility, relevance and accuracy, with the result that IPCC reports can be relied on for decision-making. Section 4 focuses on the fundamentals of IPCC’s work organization--that is, division of labour within the IPCC--while section 5 investigates three frameworks that were introduced over the course of the functioning of the IPCC: the reviewing procedure of IPCC reports, the language that IPCC authors use to express uncertainty and the Coupled Model Intercomparison Project. Concluding remarks are offered in section 6. (shrink)

This historiographical study aims at introducing the category of “situated mathematics” to the case of Ancient Egypt. However, unlike Situated Learning Theory, which is based on ethnographic relativity, in this paper, the goal is to analyze a mathematical craft knowledge based on concrete particulars and case studies, which is ubiquitous in all human activity, and which even covers, as a specific case, the Hellenistic style, where theoretical constructs do not stand apart from practice, but instead remain grounded in it.The historiographic (...) interpretation that we will give of situated mathematics is inscribed in a characterization of mathematical styles that focuses on the role of mathematical practice. This categorization describes three types of mathematization, where, on the one hand, type I represents the classical and dominant Hellenocentric approach, which seeks to generate a body of principles that could then be applied in other fields. On the other hand, types II and III represent two kinds of situated mathematics, a parametrized and a concrete one. Type II proceeds in the opposite direction from Type I describing an application of a previously obtained theory. That is, given a practice in any domain, it seeks to build a mathematical systematization a posteriori to explain said practice. Finally, type III starts from a concrete practice and develops another similar practice that explains analogically the relationship.Based on the typology adopted, we seek to describe a case study within ancient Egyptian mathematics, which reveals how it is possible to subsume it in the two types of situated mathematization II and III. The foregoing will allow to bridge the gap between theory and practice. (shrink)

Naturalism is often defined by reference to what it is not. The non-naturalisms to which naturalism is contrasted are a heterogeneous bunch. And what it is important not to be is a function of the particular concerns of a philosophical culture at a particular time. Most recently naturalism was taken to be science-based analysis. A survey of the sciences relevant to epistemology supports the pessimistic conclusion that none of them is ready to replace or even play a major role in (...) informing philosophical epistemology. The lecture proposes that naturalism in epistemology takes empirical subjects as model cognitive agents, and that epistemic norms are best thought of as sedimented conventions rather than as transcendent rules. (shrink)

Formal and social epistemologists have devoted significant attention to the question of how to aggregate the credences of a group of agents who disagree about the probabilities of events. Moss and Pettigrew argue that group credences can be a linear mean of the credences of each individual in the group. By contrast, I argue that if the epistemic value of a credence function is determined solely by its accuracy, then we should, where possible, aggregate the underlying statistical models that individuals (...) use to generate their credence functions, using “stacking” techniques from statistics and machine learning first developed by Wolpert. (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)

Much work performed under the banner of social epistemology still centers the problems of the individual cognitive agent. AU distinguishes multiple senses of "social," some of which are more social than others, and argues that different senses are at work in various contributions to social epistemology. Drawing on work in history and philosophy of science and addressing the literature on testimony and disagreement in particular, this paper argues for a more thoroughgoing approach in social epistemology.

Conventional accounts of epistemic opacity, particularly those that stem from the definitive work of Paul Humphreys, typically point to limitations on the part of epistemic agents to account for the distinct ways in which systems, such as computational methods and devices, are opaque. They point, for example, to the lack of technical skill on the part of an agent, the failure to meet standards of best practice, or even the nature of an agent as reasons why epistemically relevant elements of (...) a process may be inaccessible. In this paper I argue that there are certain instances of epistemic opacity— particularly in computational methods such a computer simulations and machine learning processes—that do not arise from, are not responsive to, and are therefore not explained by the epistemic limitations of an agent. I call these instances agent-neutral and agent-independent instances of epistemic opacity respectively. As a result, I also argue that conventional accounts of epistemic opacity offer a limited understanding of the full spectrum of kinds and sources of epistemic opacity, particularly of the kind found in computational methods. In particular, as I will show below, the limitations of these accounts are reflected in the way they fail to provide satisfactory explanations when faced with certain instances of opacity. (shrink)

The thesis of this paper is that, if it is construed individualistically, epistemic justification does not capture the conditions that philosophers of science would impose on justified belief in a scientific hypothesis. The difficulty arises from beliefs acquired through testimony. From this I derive a lesson that epistemologists generally, and epistemologists of testimony in particular, should learn from philosophers of science: we ought to repudiate epistemic individualism and move towards a more fully social epistemology.

It is often claimed that only experiments can support strong causal inferences and therefore they should be privileged in the behavioral sciences. We disagree. Overvaluing experiments results in their overuse both by researchers and decision-makers, and in an underappreciation of their shortcomings. Neglecting other methods often follows. Experiments can suggest whether X causes Y in a specific experimental setting; however, they often fail to elucidate either the mechanisms responsible for an effect, or the strength of an effect in everyday natural (...) settings. In this paper, we consider two overarching issues. First, experiments have important limitations. We highlight problems with: external, construct, statistical conclusion, and internal validity; replicability; and with conceptual issues associated with simple X-causes-Y thinking. Second, quasi-experimental and non-experimental methods are absolutely essential. As well as themselves estimating causal effects, these other methods can provide information and understanding that goes beyond that provided by experiments. A research program progresses best when experiments are not treated as privileged but instead are combined with these other methods. (shrink)

Large research collaborations constitute an increasingly prevalent form of social organization of research activity in many scientific fields. In the last decades, the concept of distributed cognition has provided a suitable basis for thinking about collective knowledge in the philosophy of science. Karin Knorr-Cetina’s and Ronald Giere’s analyses of high energy physics experiments are the most prominent examples. Although they both conceive the processes of knowledge production in these experiments in terms of distributed cognition, their accounts regarding the epistemic subject (...) of knowledge thus produced are quite different. While Knorr-Cetina argues for an irreducibly collective subject, Giere argues for eliminating the epistemic subject and opting for using the passive voice in describing collectively produced knowledge. Neither of these views are easy to assimilate within an epistemological account, since epistemology traditionally operates within an individualist framework. They both entail that we should deny knowledge to individuals when the processes of knowledge production are distributed. I will argue that epistemology should be extended in a way that can accommodate collectively produced knowledge, but that we would have a serious problem if we deny scientific knowledge to individuals. If the members of a large collaboration cannot be said to know, we have to accept the absurd conclusion that either no one or only a supra-individual entity learns from the most successful research collaborations we have. I will argue instead for conceiving research collaborations in terms of a cognitive system that produces knowledge, which can eventually be possessed by constituent individuals when certain conditions are met. Firstly, the distributed research process should be reliable in producing scientific evidence and secondly, there should be a reliable distributed process of criticism for scrutinizing the reliability of the scientific evidence that is collectively produced. I will analyze both conditions in terms of distributed first-order and second-order justification, where I put forward a reliabilist account of justification that is compatible with epistemic dependence. I will conclude that the notion of justified epistemic dependence enables us to attribute knowledge to individuals when knowledge production is irreducibly social. (shrink)

The social identity of a researcher can affect their position in a community, as well as the uptake of their ideas. In many fields, members of underrepresented or minority groups are less likely to be cited, leading to citation gaps. Though this empirical phenomenon has been well-studied, empirical work generally does not provide insight into the causes of citation gaps. I will argue, using mathematical models, that citation gaps are likely due in part to the structure of academic communities. The (...) existence of these ‘structural causes’ has implications for attempts to lessen citation gaps, and for proposals to make academic communities more efficient. These proposals have the potential to create feedback loops, amplifying current structural inequities. (shrink)

MOND, MOdified Newtonian Dynamics, attempts to explain deviations between, on the one hand, observations, and, on the other hand, expectations based on the gravitational forces due to baryonic matter — via a change in the law of gravitation rather than via dark matter. Despite its ad-hoc nature, MOND is still interesting because the observations on which it is based are undisputed and it is at least unclear whether the corresponding phenomena arise naturally in the context of mainstream astrophysics. However, the (...) debate is often not healthy, which impedes progress. As someone with a stake neither in MOND nor in conventional astrophysical explanations of the corresponding phenomena, I suggest some ways to improve the debate on what is certainly an important topic. (shrink)

In the past few years, social epistemologists have developed several formal models of the social organisation of science. While their robustness and representational adequacy has been analysed at length, the function of these models has begun to be discussed in more general terms only recently. In this article, I will interpret many of the current formal models of the scientific community as representing the latest development of what I will call the ‘Kuhnian project’. These models share with Kuhn a number (...) of questions about the relation between individuals and communities. At the same time, they also inherit some of Kuhn’s problematic characterisations of the scientific community. In particular, current models of the social organisation of science represent the scientific community as essentially value-free. This may put into question both their representational adequacy and their normative ambitions. In the end, it will be shown that the discussion on the formal models of the scientific community may contribute in fruitful ways to the ongoing debates on value judgements in science. (shrink)

According to the Variety of Evidence Thesis items of evidence from independent lines of investigation are more confirmatory, ceteris paribus, than e.g. replications of analogous studies. This thesis is known to fail Bovens and Hartmann, Claveau. How- ever, the results obtained by the former only concern instruments whose evidence is either fully random or perfectly reliable; instead in Claveau, unreliability is modelled as deterministic bias. In both cases, the unreliable instrument delivers totally irrelevant information. We present a model which formalises (...) both reliability, and unreliability, differently. Our instruments are either reliable, but affected by random error, or they are biased but not deterministically so. Bovens and Hartmann’s results are counter-intuitive in that in their model a long series of consistent reports from the same instrument does not raise suspicion of “too-good-to- be-true” evidence. This happens precisely because they neither contemplate the role of systematic bias, nor unavoidable random error of reliable instruments. In our model the Variety of Evidence Thesis fails as well, but the area of failure is considerably smaller than for Bovens and Hartmann, Claveau and holds for realistic cases. The essential mechanism which triggers VET failure is the rate of false to true positives for the two kinds of instruments. Our emphasis is on modelling beliefs about sources of knowledge and their role in hypothesis confirmation in interaction with dimensions of evidence, such as variety and consistency. (shrink)

According to the diversity-beats-ability theorem, groups of diverse problem solvers can outperform groups of high-ability problem solvers. We argue that the model introduced by Lu Hong and Scott Page is inadequate for exploring the trade-off between diversity and ability. This is because the model employs an impoverished implementation of the problem-solving task. We present a new version of the model which captures the role of ‘ability’ in a meaningful way, and use it to explore the trade-offs between diversity and ability (...) in scientific problem solving. (shrink)

If one had to identify the biggest change within the philosophical tradition in the twenty-first century, it would certainly be the rapid rise of experimental philosophy to address differences in intuitions about concepts. It is, therefore, surprising that the philosophy of medicine has so far not drawn on the tools of experimental philosophy in the context of a particular conceptual debate that has overshadowed all others in the field: the long-standing dispute between so-called naturalists and normativists about the concepts of (...) health and disease. In this paper, I defend and advocate the use of empirical methods to inform and advance this and other debates within the philosophy of medicine. (shrink)

This paper investigates how the credit incentive to engage in questionable research practices interacts with cumulative advantage, the process whereby high-status academics more easily increase their status than low-status academics. I use a mathematical model to highlight two dynamics that have not yet received much attention. First, due to cumulative advantage, questionable research practices may pay off over the course of an academic career even if they do not appear attractive at the level of individual publications. Second, because of the (...) role of bottleneck moments in academic careers, questionable research practices may be selected for even if they do not provide a benefit in expectation. I also observe that, within the model, the most successful academics are the most likely to have benefited from fraud. -/- This paper has been published under a different title. See PhilPapers record HEECAA or DOI 10.1086/716235. (shrink)

What justifies the use of Bayesian statistics in science? The traditional answer is that Bayesian statistics is simply an instance of orthodox expected utility theory. Thus, Bayesian statistical methods, like principles of utility theory, are justified by norms of individual rationality. In particular, most Bayesians argue that a scientist's credences must satisfy the probability axioms if she adheres to norms of practical and epistemic rationality. We argue that, to justify Bayesian statistics as a tool for science, it is necessary that (...) a scientist's public credences obey the probability axioms. We claim that norms of collective science help justify this restricted view, termed public probabilism. (shrink)

Currie (2019) has introduced a novel account of creativity within the social epistemology of science. The account is intended to capture how conservatism can be detrimental to the health of inquiry within certain scientific communities, given the aims of research there. I argue that recent remarks by Rovelli (2018) put pressure on the applicability of the account. Altogether, it seems we do not yet well understand the relationship between creativity, conservatism, and the health of inquiry in science.

The practice of HARKing---hypothesizing after results are known---is commonly maligned as undermining the reliability of scientific findings. There are several accounts in the literature as to why HARKing undermines the reliability of findings. We argue that none of these is right and that the correct account is a Bayesian one. HARKing can indeed decrease the reliability of scientific findings, but it can also increase it; which effect HARKing produces depends on the difference of the prior odds of hypotheses characteristically selected (...) ex ante and ex post to observing data. Further, we show how misdiagnosis of HARKing can lead to misprescription in the context of the replication crisis. (shrink)

Philosophers of science and metascientists alike typically model scientists’ behavior as driven by credit maximization. In this article I argue that this modeling assumption cannot account for how scientists have a default level of trust in each other’s assertions. The normative implication of this is that science policy should not focus solely on incentive reform.

There is an ongoing and robust tradition of science and technology studies scholars conducting ethnographic laboratory studies. These laboratory studies—like all ethnographies—are each conducted at a particular time, are situated in a particular place, and are about a particular culture. Presumably, this contextual specificity means that such ethnographies have limited applicability beyond the narrow slice of time, place, and culture that they each subject to examination. But we do not always or even often treat them that way. It is beyond (...) common for us to speak about what one or another laboratory study reveals about the laboratory, or “science” much more broadly. Given the contextual specificity of our ethnographic laboratory studies, what justifies this presumed generalizability? Initially, this manuscript surveys typical responses to this question, but then it pursues an unusual one: the potential replicability of ethnographic results. This potential is hereby explored, via an ethnographic replication attempt—one designed and conducted in order to test the generalizability of a particular laboratory study, that of Latour and Woolgar’s classic Laboratory Life. The results of the ethnographic replication attempt are reported, and a remarkable degree of replicability is established. (shrink)

This paper seeks to examine the roles and identities of engineers constituting one of the fundamental, but a completely indescribable community in modern big science with particle accelerators. Large communities of accelerator and detector specialists, which replaced experimenters and instrumentalists of the middle of the last century, themselves exhibit a complex structure and are divided. However, this division is in turn grounded on the division of those whose activities focus on the phenomena of nature considered independent of human beings and (...) those who design processes and phenomena of an artificial, technical nature. Nevertheless, in terms of their modus operandi and identity, the kinship between engineers and experimental scientists is considerable. I argue that such exclusion of the engineering community from epistemic practices can serve as an example of participatory injustice. As one of the ways to transcend participatory injustice, I suggest that the communities should be encouraged to work together in epistemically tantamount roles while structural hindrances to the mobility between communities need to be alleviated. (shrink)

Empirical philosophers of science aim to base their philosophical theories on observations of scientific practice. But since there is far too much science to observe it all, how can we form and test hypotheses about science that are sufficiently rigorous and broad in scope, while avoiding the pitfalls of bias and subjectivity in our methods? Part of the answer, we claim, lies in the computational tools of the digital humanities, which allow us to analyze large volumes of scientific literature. Here (...) we advocate for the use of these methods by addressing a number of large-scale, justificatory concerns—specifically, about the epistemic value of journal articles as evidence for what happens elsewhere in science, and about the ability of DH tools to extract this evidence. Far from ignoring the gap between scientific literature and the rest of scientific practice, effective use of DH tools requires critical reflection about these relationships. (shrink)

Review of Nicola Möβner’s 'Visual Representations in Science. Concept and Epistemology'. Forthcoming in Grazer Philosophische Studien.

The history of the research on peptic ulcer disease is characterized by a premature abandonment of the bacterial hypothesis, which subsequently had its comeback, leading to the discovery of Helicobacter pylori – the major cause of the disease. In this paper we examine the received view on this case, according to which the primary reason for the abandonment of the bacterial hypothesis in the mid-twentieth century was a large-scale study by a prominent gastroenterologist Palmer, which suggested no bacteria could be (...) found in the human stomach. To this end, we employ the methodof digital textual analysis and study the literature on the etiology of PUD published in the decade prior to Palmer’s article. Our findings suggest that the bacterial hypothesis had already been abandoned before the publication of Palmer’s paper, which challenges the widely held view that his study played a crucial role in the development of this episode. In view of this result, we argue that the PUD case does not illustrate harmful effects of a high degree of information flow, as it has frequently been claimed in the literature on network epistemology. Moreover, we argue that alternative examples of harmful effects of a high degree of information flow may be hard to find in the history of science. (shrink)

Often machine learning programs inherit social patterns reflected in their training data without any directed effort by programmers to include such biases. Computer scientists call this algorithmic bias. This paper explores the relationship between machine bias and human cognitive bias. In it, I argue similarities between algorithmic and cognitive biases indicate a disconcerting sense in which sources of bias emerge out of seemingly innocuous patterns of information processing. The emergent nature of this bias obscures the existence of the bias itself, (...) making it difficult to identify, mitigate, or evaluate using standard resources in epistemology and ethics. I demonstrate these points in the case of mitigation techniques by presenting what I call ‘the Proxy Problem’. One reason biases resist revision is that they rely on proxy attributes, seemingly innocuous attributes that correlate with socially-sensitive attributes, serving as proxies for the socially-sensitive attributes themselves. I argue that in both human and algorithmic domains, this problem presents a common dilemma for mitigation: attempts to discourage reliance on proxy attributes risk a tradeoff with judgement accuracy. This problem, I contend, admits of no purely algorithmic solution. (shrink)

Beginning at the end of the nineteenth century, systematic scientific abstracting played a crucial role in reconfiguring the sciences on an international scale. For mathematicians, the 1931 launch of the Zentralblatt für Mathematik and 1940 launch of Mathematical Reviews marked and intensified a fundamental transformation, not just to the geographic scale of professional mathematics but to the very nature of mathematicians’ research and theories. It was not an accident that mathematical abstracting in this period coincided with an embrace across mathematical (...) research fields of a distinctive form of symbolic and conceptual abstraction. This essay examines the historical, institutional, embodied, and conceptual bases of mathematical abstracting and abstraction in the mid-twentieth century, placing them in historical context within the first half of the twentieth century and then examining their consequences and legacies for the second half of the twentieth century and beyond. Focused on scale, media, and the relationship between mathematical knowledge and its forms of articulation, my analysis connects the changing social structure of modern mathematical research communities to their changing domains of investigation and resources for representation and collective understanding. (shrink)

Sometimes retracted or refuted scientific information is used and propagated long after it is understood to be misleading. Likewise, retracted news items may spread and persist, despite being publi...

We argue that the appraisal of models in social epistemology requires conceiving of them as argumentative devices, taking into account the argumentative context and adopting a family-of-models perspective. We draw up such an account and show how it makes it easier to see the value and limits of the use of models in social epistemology. To illustrate our points, we document and explicate the argumentative role of epistemic landscape models in social epistemology and highlight their limitations. We also claim that (...) our account could be fruitfully used in appraising other models in philosophy and science. (shrink)

The priority rule in science has been interpreted as a behavior regulator for the scientific community, which benefits society by adequately structuring the distribution of intellectual labor across pre-existing research programs. Further, it has been lauded as part of society's "grand reward scheme" because it fairly rewards people for the benefits they produce. But considerations about how news of scientific developments spreads throughout a scientific community at large suggest that the priority rule is something else entirely, which can disadvantage historically (...) underrepresented or otherwise marginalized social groups. (shrink)

The way research is, and should be, funded by the public sphere is the subject of renewed interest for sociology, economics, management sciences, and more recently, for the philosophy of science. In this contribution, I propose a qualitative, epistemological criticism of the funding by lottery model, which is advocated by a growing number of scholars as an alternative to peer-review. This lottery scheme draws on the lack of efficiency and of robustness of the peer-review based evaluation to argue that the (...) majority of public resources for basic science should be allocated randomly. I first differentiate between two distinct arguments used to defend this alternative funding scheme based on considerations about the logic of scientific research. To assess their epistemological limits, I then present and develop a conceptual frame, grounded on the notion of “system of practice”, which can be used to understand what precisely it means, for a research project, to be interesting or significant. I use this epistemological analysis to show that the lottery model is not theoretically optimal, since it underestimates the integration of all scientific projects in densely interconnected systems of conceptual, experimental, or technical practices which confer their proper interest to them. I also apply these arguments in order to criticize the classical peer-review process. I finally suggest, as a discussion, that some recently proposed models that bring to the fore a principle of decentralization of the evaluation and selection process may constitute a better alternative, if the practical conditions of their implementation are adequately settled. (shrink)

Scientists are becoming increasingly aware of a “replicability crisis” in the behavioral, social, and biomedical sciences. Researchers have made progress identifying statistical and methodological...

Typically, public discussions of questions of social import exhibit two important properties: they are influenced by conformity bias, and the influence of conformity is expressed via social networks. We examine how social learning on networks proceeds under the influence of conformity bias. In our model, heterogeneous agents express public opinions where those expressions are driven by the competing priorities of accuracy and of conformity to one’s peers. Agents learn, by Bayesian conditionalization, from private evidence from nature, and from the public (...) declarations of other agents. Our key findings are that networks that produce configurations of social relationships that sustain a diversity of opinions empower honest communication and reliable acquisition of true beliefs, and that the networks that do this best turn out to be those which are both less centralized and less connected. (shrink)

Replicability is widely taken to ground the epistemic authority of science. However, in recent years, important published findings in the social, behavioral, and biomedical sciences have failed to replicate, suggesting that these fields are facing a “replicability crisis.” For philosophers, the crisis should not be taken as bad news but as an opportunity to do work on several fronts, including conceptual analysis, history and philosophy of science, research ethics, and social epistemology. This article introduces philosophers to these discussions. First, I (...) discuss precedents and evidence for the crisis. Second, I discuss methodological, statistical, and social-structural factors that have contributed to the crisis. Third, I focus on the philosophical issues raised by the crisis. Finally, I discuss proposed solutions and highlight the gaps that philosophers could focus on. (shrink)

This paper offers a new angle on the common idea that the process of science does not support epistemic diversity. Under minimal assumptions on the nature of journal editing, we prove that editorial procedures, even when impartial in themselves, disadvantage less prominent research programs. This purely statistical bias in article selection further skews existing differences in the success rate and hence attractiveness of research programs, and exacerbates the reputation difference between the programs. After a discussion of the modeling assumptions, the (...) paper ends with a number of recommendations that may help promote scientific diversity through editorial decision making. (shrink)

Reflective equilibrium between physics and philosophy, and between GR and particle physics, is fruitful and rational. I consider the virtues of simplicity, conservatism, and conceptual coherence, along with perturbative expansions. There are too many theories to consider. Simplicity supplies initial guidance, after which evidence increasingly dominates. One should start with scalar gravity; evidence required spin 2. Good beliefs are scarce, so don't change without reason. But does conservatism prevent conceptual innovation? No: considering all serious possibilities could lead to Einstein's equations. (...) GR is surprisingly intelligible. Energy localization makes sense if one believes Noether mathematics: an infinity of symmetries shouldn't produce just one energy. Hamiltonian change results from Lagrangian-equivalence. Causality poses conceptual questions. For GR, what are canonical 'equal-time' commutators? For massive spin 2, background causality exists but is violated. Both might be cured by engineering a background null cone respected by a gauge groupoid. Perturbative expansions can enlighten. They diagnose Einstein's 1917 'mass'-Lambda analogy. Ogievetsky-Polubarinov invented an infinity of massive spin 2 gravities---including ghost-free de Rham-Gabadadze-Tolley theories!---perturbatively, and achieved the impossible : spinors in coordinates. (shrink)

Fraud and misleading research represent serious impediments to scientific progress. We must uncover the causes of fraud in order to understand how science functions and in order to develop strategies for combating epistemically detrimental behavior. This paper investigates how the incentive to commit fraud is enhanced by the structure of the scientific reward system. Science is an "accumulation process:" success begets resources which begets more success. Through a simplified mathematical model, I argue that this cyclic relationship enhances the appeal of (...) fraud and makes combating it extremely difficult. (shrink)

Big data is opening new angles on old questions about scientific progress. Is scientific knowledge cumulative? If yes, how does it make progress? In the life sciences, what we call the Consensus Principle has dominated the design of data discovery and integration tools: the design of a formal classificatory system for expressing a body of data should be grounded in consensus. Based on current approaches in biomedicine and systematic biology, we formulate and compare three types of the Consensus Principle: realist, (...) contextual-best, and coordinative. Contrasted with the realist program of the Open Biomedical Ontologies Foundry, we argue that historical practices in systematic biology provide an important and overlooked alternative based on coordinative consensus. Systematists have developed a robust system for referring to taxonomic entities that can deliver high quality data discovery and integration without invoking consensus about reality or “settled” science. (shrink)

Traditionally, epistemologists have distinguished between epistemic and pragmatic goals. In so doing, they presume that much of game theory is irrelevant to epistemic enterprises. I will show that this is a mistake. Even if we restrict attention to purely epistemic motivations, members of epistemic groups will face a multitude of strategic choices. I illustrate several contexts where individuals who are concerned solely with the discovery of truth will nonetheless face difficult game theoretic problems. Examples of purely epistemic coordination problems and (...) social dilemmas will be presented. These show that there is a far deeper connection between economics and epistemology than previous appreciated. (shrink)

We offer a new account of the role of values in theory choice that captures a temporal dimension to the values themselves. We argue that non-epistemic values sometimes serve as “inquiry tickets,” justifying scientists’ pursuit of certain questions in the short run, while the answers to those questions mitigate transient underdetermination in the long run. Our account of inquiry tickets shows that the role of non-epistemic values need not be restricted to belief or acceptance in order to be relevant to (...) hypothesis choice: the relevance of non-epistemic values to a particular cognitive attitude with respect to h vary over time. (shrink)

Peer review is often taken to be the main form of quality control on academic research. Usually journals carry this out. However, parts of maths and physics appear to have a parallel, crowd-sourced model of peer review, where papers are posted on the arXiv to be publicly discussed. In this paper we argue that crowd-sourced peer review is likely to do better than journal-solicited peer review at sorting papers by quality. Our argument rests on two key claims. First, crowd-sourced peer (...) review will lead on average to more reviewers per paper than journal-solicited peer review. Second, due to the wisdom of the crowds, more reviewers will tend to make better judgments than fewer. We make the second claim precise by looking at the Condorcet Jury Theorem as well as two related jury theorems developed specifically to apply to peer review. (shrink)

Scientific research is based on the division of cognitive labour: every scientist has to trust that other colleagues have checked whether the items that are taken as knowledge, and she cannot check by herself, are reliable enough. I apply ideas from the field known as ‘information economics’ to analyse the scientists’ incentives to produce items of knowledge of an ‘adequate’ quality, under the assumption that a big part of what one observes in her empirical research is not available for the (...) readers of the paper. I also discuss some criticisms to this ‘marketization’ of science studies. (shrink)