In this introduction to the Topical Collection on Social and Cognitive Diversity in Science, we map the questions that have guided social epistemological approaches to diversity in science. Both social and cognitive diversity of different types is claimed to be epistemically beneficial. The challenge is to understand how an increase in a group’s diversity can bring about epistemic benefits and whether there are limits beyond which diversity can no longer improve a group’s epistemic performance. The contributions to the Topical Collection (...) discuss various proposals to maintain an appropriate amount of cognitive diversity in science, for instance, by recruiting and retaining practitioners from underrepresented social groups, providing incentives for explorative and risky research, encouraging interdisciplinary collaborations and stakeholder participation in research, requiring industry scientists to share their evidence, and developing strategies to encounter politically motivated attempts to manufacture doubt. To be successful, efforts to promote diversity in science should anticipate risks related to institutional interventions, navigate trade-offs between different types of epistemically good outcomes, and identify hidden costs that such policies may cause for various actors. Such efforts need to be assessed not only from an epistemic perspective but also from the point of view of fairness and the political legitimacy of scientific institutions. (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)

To believe that every single scientist ought to be individually engaged in ethical thinking in order for science to be responsible at a collective level may be too demanding, if not plainly unrealistic. In fact, ethical labor is typically distributed across different kinds of scientists within the scientific community. Based on the empirical data collected within the Horizon 2020 ‘RRI-Practice’ project, we propose a classification of the members of the scientific community depending on their engagement in this collective activity. Our (...) classification offers, on the one hand, a model of how the ethical aspects of science are taken into consideration by scientists and, on the other, some indications on how to institutionalize ethics in science. (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)

The question of the division of cognitive labor has given rise to various models characterizing the way scientists should distribute their efforts. These models often consider the scientific community as a self-governed sphere constituted by rational agents making choices on the basis of fixed rules. Such models have recently been criticized for not taking into account the real mechanisms of science funding. Hence, the question of the utility of the DCL models in guiding science policy remains an open one. In (...) this paper, we show that two unconsidered dimensions would have to be taken into account. First, DCL studies miss the existence of distinct levels of epistemic objectives organizing the research process. Indeed, the scientific field is structured as a system of hierarchical, interconnected practices which are defined both by their inherent purposes and by various superposed external functions. Second, I criticize the absence of ontological considerations, since the epistemological significance of pluralism is highly dependent on the nature of the object under study. Because of these missing dimensions, current DCL models might have a limited usefulness to identify good practices of research governance. (shrink)

There is a commonly made distinction between two types of scientists: risk-taking, trailblazing mavericks and detail-oriented followers. A number of recent papers have discussed the question what a desirable mixture of mavericks and followers looks like. Answering this question is most useful if a scientific community can be steered toward such a desirable mixture. One attractive route is through credit incentives: manipulating rewards so that reward-seeking scientists are likely to form the desired mixture of their own accord. Here I argue (...) that this idea is less straightforward than it may seem. Interpreting mavericks as scientists who prioritize rewards over speed and risk, I show in a deliberatively simple model that there is a fixed mixture which is not particularly likely to be desirable and which credit incentives cannot alter. I consider a way around this result, but this has some major drawbacks. I conclude that credit incentives are not as promising a way to create a desirable mixture of mavericks and followers as one might have thought. (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)

There has been much discussion of the moral, legal and prudential implications of geoengineering, and of governance structures for both the research and deployment of such technologies. However, insufficient attention has been paid to how such measures might affect geoengineering in terms of the incentive structures which underwrite scientific progress. There is a tension between the features that make science productive, and the need to govern geoengineering research, which has thus far gone underappreciated. I emphasize how geoengineering research requires governance (...) which reaches beyond science’s traditional boundaries, and moreover requires knowledge which itself reaches beyond what we traditionally expect scientists to know about. How we govern emerging technologies should be sensitive to the incentive structures which drive science. (shrink)

This essay argues that scientific systems have two main functions typical to self-organising adaptive and complex systems: Exploration for and exploitation of information. The self-organising nature, or spontaneous order, of scientific systems was prominently conceived by polymath Michael Polanyi. Revisiting Polanyi’s philosophy of science reveals why scientific freedom is still today as important a value as ever, even though the notion of “freedom” itself must be revised. Namely, freedom of inquiry should serve to maintain a diverse and adaptive balance between (...) exploration and exploitation. This essay argues that current trends within science policy and scientific communities, from impact assessments to targeted research funding, are often inherently biased towards advancing exploitative functions over explorative activities. Concerns are raised over whether these exploitative biases suppress the explorative nature of scientific inquiry, and thus disturb the self-organisation of scientific systems by favouring hasty and sometimes negligent exploitation. Further concerns are raised as to whether these impaired adaptive capacities of scientific systems lead to reduced resilience of broader society. Finally, Polanyi’s vision of a Society of Explorers, where free exploration is vindicated and safeguarded, is revived in a 21st century context. (shrink)

IntroductionAllocation of research funds relies on peer review to support funding decisions, and these processes can be susceptible to biases and inefficiencies. The aim of this work was to determine which past interventions to peer review and decision-making have worked to improve research funding practices, how they worked, and for whom.MethodsRealist synthesis of peer-review publications and grey literature reporting interventions in peer review for research funding.ResultsWe analysed 96 publications and 36 website sources. Sixty publications enabled us to extract stakeholder-specific context-mechanism-outcomes (...) configurations for 50 interventions, which formed the basis of our synthesis. Shorter applications, reviewer and applicant training, virtual funding panels, enhanced decision models, institutional submission quotas, applicant training in peer review and grant-writing reduced interrater variability, increased relevance of funded research, reduced time taken to write and review applications, promoted increased investment into innovation, and lowered cost of panels.ConclusionsReports of 50 interventions in different areas of peer review provide useful guidance on ways of solving common issues with the peer review process. Evidence of the broader impact of these interventions on the research ecosystem is still needed, and future research should aim to identify processes that consistently work to improve peer review across funders and research contexts. (shrink)

There are now several proposals for introducing random elements into the process of funding allocation for research, and some initial implementation of this policy by funding bodies. The proposals have been supported on efficiency grounds, with models, including social epistemology models, showing random allocation could increase the generation of significant truths in a community of scientists when compared to funding by peer review. The models in the literature are, however, fairly abstract. This paper introduces some of the considerations that are (...) required to build on the modelling work towards a fully-fledged policy proposal, including issues of cost and fairness. (shrink)

In 2013 the Health Research Council of New Zealand began a stream of funding titled 'Explorer Grants', and in 2017 changes were introduced to the funding mechanisms of the Volkswagen Foundation 'Experiment!' and the New Zealand Science for Technological Innovation challenge 'Seed Projects'. All three funding streams aim at encouraging novel scientific ideas, and all now employ random selection by lottery as part of the grant selection process. The idea of funding science by lottery has emerged independently in several corners (...) of academia, including in philosophy of science. This paper reviews the conceptual and institutional landscape in which this policy proposal emerged, how different academic fields presented and supported arguments for the proposal, and how these have been reflected in actual policy. The paper presents an analytical synthesis of the arguments presented to date, notes how they support each other and shape policy recommendations in various ways, and where competing arguments highlight need for further analysis or more data. In addition, it provides lessons for how philosophers of science can engage in shaping science policy, and in particular highlights the importance of mixing complementary expertise: it takes a village to raise policy. (shrink)

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)