Berichte zur Wissenschaftsgeschichte, Volume 45, Issue 3, Page 344-354, September 2022.

Having offered the “argument from bad lot”, Bas van Fraassen has raised an important criticism on the Inference to the Best Explanation (IBE) and challenged scientific realism. Regardless of scientific realism, and given the reliance of today's scientific methods on IBE, this criticism poses a deeper threat to the validity of scientific enquiry. In this article, we will try to provide a way to deal with this threat, according to the structure of the scientific community. Some structural features of the (...) contemporary scientific community have caused the scientific enquiry to be limited to the science derived from the Western tradition and deprived it of the theoretical opportunities of various traditions. The main claim of this article is that paying attention to different traditions together to produce science is a good way to expand scientific enquiry and deal with the mentioned threat. In the first section, we will depict how the argument from bad lot threatens the validity of scientific enquiry. In the second section, we discuss the close relationship between science and tradition, and then examine the status of this relationship in the contemporary scientific society. The final section is devoted to proposing the idea of pluralism regarding the use of the theoretical opportunities of different traditions in scientific enquiry, as a proposed solution to counter this threat. (shrink)

To arrive at their final evaluation of a manuscript or grant proposal, reviewers must convert a submission’s strengths and weaknesses for heterogeneous peer review criteria into a single metric of quality or merit. I identify this process of commensuration as the locus for a new kind of peer review bias. Commensuration bias illuminates how the systematic prioritization of some peer review criteria over others permits and facilitates problematic patterns of publication and funding in science. Commensuration bias also foregrounds a range (...) of structural strategies for realigning peer review practices and institutions with the aims of science. (shrink)

“Ancient DNA Research” is the practice of extracting, sequencing, and analyzing degraded DNA from dead organisms that are hundreds to thousands of years old. Today, many researchers are interested in adapting state-of-the-art molecular biological techniques and high-throughput sequencing technologies to optimize the recovery of DNA from fossils, then use it for studying evolutionary history. However, the recovery of DNA from fossils has also fueled the idea of resurrecting extinct species, especially as its emergence corresponded with the book and movie Jurassic (...) Park in the 1990s. In this paper, I use historical material, interviews with scientists, and philosophical literature to argue that the search for DNA from fossils can be characterized as a data-driven and celebrity-driven practice. Philosophers have recently argued the need to seriously consider the role of data-driven inquiry in the sciences, and likewise, this history highlights the need to seriously consider the role of celebrity in shaping the kind of research that gets pursued, funded, and ultimately completed. On this point, this history highlights that the traditional philosophical and scientific distinctions between data-driven and hypothesis-driven research are not always useful for understanding the process and practice of science. Consequently, I argue that the celebrity status of a particular research practice can be considered as a “serious epistemic strategy” that researchers, as well as editors and funders, employ when making choices about their research and publication processes. This interplay between celebrity and methodology matters for the epistemology of science. (shrink)

Philosophers of science diverge on the question what drives the growth of scientific knowledge. Most of the twentieth century was dominated by the notion that theories propel that growth whereas experiments play secondary roles of operating within the theoretical framework or testing theoretical predictions. New experimentalism, a school of thought pioneered by Ian Hacking in the early 1980s, challenged this view by arguing that theory-free exploratory experimentation may in many cases effectively probe nature and potentially spawn higher evidence-based theories. Because (...) theories are often powerless to envisage workings of complex biological systems, theory-independent experimentation is common in the life sciences. Some such experiments are triggered by compelling observation, others are prompted by innovative techniques or instruments, whereas different investigations query big data to identify regularities and underlying organizing principles. A distinct fourth type of experiments is motivated by a major question. Here I describe two question-guided experimental discoveries in biochemistry: the cyclic adenosine monophosphate mediator of hormone action and the ubiquitin-mediated system of protein degradation. Lacking underlying theories, antecedent data bases, or new techniques, the sole guides of the two discoveries were respective substantial questions. Both research projects were similarly instigated by theory-free exploratory experimentation and continued in alternating phases of results-based interim working hypotheses, their examination by experiment, provisional hypotheses again, and so on. These two cases designate theory-free, question-guided, stepwise biochemical investigations as a distinct subtype of the new experimentalism mode of scientific enquiry. (shrink)

To identify and conceptualize research problems in science, philosophers and often scientists rely on classical accounts of problems that focus on intellectual problems defined in relation to theories. Recently, philosophers have begun to study the structures and functions of research problems not defined in relation to theories. Furthermore, scientists have long pursued research problems often labeled as practical or applied. As yet, no account of problems specifies the description of both so-called intellectual problems and so-called applied problems. This article proposes (...) a new conceptual framework of problems that accounts both for intellectual aspects of problems and for their practical or applied aspects. I illustrate the account with an example of a recent research project from evolutionary biology, and I indicate further routes by that to develop the account, especially in connection to empirical studies of science. (shrink)

Researchers often pursue proof of concept research, but criteria for evaluating such research remain poorly specified. This article proposes a general framework for proof of concept research that k...

Leading animal models are powerful tools for translational research, but they also present obstacles. Poorly conducted preclinical research in animals is a common cause of translational failure, but even when such research is well-designed and carefully executed, challenges remain. In particular, dominant models may bias research directions, elide essential aspects of human disease, omit important context, or subtly shift research targets. Recognizing these stumbling blocks can help us find ways to avoid them: employing a wider range of models, incorporating more (...) realistic environmental conditions, better aligning studies between animals and patients, and focusing on human biology and therapeutic goals. Such changes are costly; but insisting it would be impractical or unrealistic to change strategies offers no way out of the current impasse. Rather, we must acknowledge the obstacles as well as the advantages presented by core models, and direct some of our investments in translational research toward getting around them. The dominance of biomedical research by a handful of animal models introduces subtle but significant obstacles to translation. Recognizing these obstacles is a critical first step toward finding ways around them; this paper describes how dominant models can create roadblocks, and suggests strategies to improve the efficiency of translation from animal models to humans. (shrink)

The issue of the conservatism of scientific research questions the nature and the role of the internal and external forces controlling the emergence of new research questions or problems, the exploration of risky directions of research, or the use of risky research methods. This issue has recently gained a new framing in connection with the growing importance of the peer-review process and of the social and economic pressures weighing on the funding of scientific research. Current literature then interrogates the external (...) and internal features that promote what are described as conservative tendencies in scientific research. In this paper, I propose to contribute to this debate by clarifying what might be internal sources of conservatism in science; that is, that are inherent to the research process itself. I distinguish two possible understandings of the sources and manifestations of this internal conservatism. I first present a representational description of the nature and origin of conservatism in science, which brings to the fore the difficulties researchers find in setting aside their conceptual framework. I then offer for consideration a larger perspective on conservatism by arguing for the existence of a practical conservatism generated by all the dimensions of scientific activities. In this framework, conservatism in science can be explained by the tendency of all practices to close in on their own local objectives. I illustrate this view by reference to an historical episode: the discovery of the chemical nature of genes by Avery. (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)

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)

Computer simulation of an epistemic landscape model, modified to include explicit representation of a centralized funding body, show the method of funding allocation has significant effects on communal trade-off between exploration and exploitation, with consequences for the community’s ability to generate significant truths. The results show this effect is contextual, and depends on the size of the landscape being explored, with funding that includes explicit random allocation performing significantly better than peer-review on large landscapes. The paper proposes a way of (...) incorporating external institutional factors in formal social epistemology, and offers a way of bringing such investigations to bear on current research policy questions. (shrink)

Computer simulation of an epistemic landscape model, modified to include explicit representation of a centralized funding body, show the method of funding allocation has significant effects on communal trade-off between exploration and exploitation, with consequences for the community’s ability to generate significant truths. The results show this effect is contextual, and depends on the size of the landscape being explored, with funding that includes explicit random allocation performing significantly better than peer review on large landscapes. The article proposes a way (...) of incorporating external institutional factors in formal social epistemology, and offers a way of bringing such investigations to bear on current research policy questions. 1Introduction2Theoretical Background3Model Description4Simulation Details 4.1Simulating the epistemic landscape4.2Simulating agents4.3Simulating communal knowledge4.4Simulating funding strategies4.5Simulating merit dynamics5Results and Discussion 5.1Experiment 1: The winner-takes-it-all mechanism only5.2Experiment 2: All dynamic mechanisms5.3Experiment 3: Adding a new funding mechanism 5.4Experiment 4: Varying the degree of myopia5.5Experiment 5: Variability of individual epistemic gain5.6Experiment 6: Likelihood of renewal6Discussion7Conclusion. (shrink)

This paper presents current work in philosophy of science in practice that focusses on practices that are detrimental to the production of scientific knowledge. The paper argues that philosophy of scientific malpractice both provides an epistemological complement to research ethics in understanding scientific misconduct and questionable research practices, and provides a new approach to how training in responsible conduct of research can be implemented.

At the interface of developmental biology and evolutionary biology, the very criteria of scientific knowledge are up for grabs. A central issue is the status of evolutionary genetics models, which some argue cannot coherently be used with complex gene regulatory network (GRN) models to explain the same evolutionary phenomena. Despite those claims, many researchers use evolutionary genetics models jointly with GRN models to study evolutionary phenomena. This dissertation compares two recent research projects in which researchers jointly use the two kinds (...) of models. I use methods from the empirical social sciences, such as digital corpus analysis, content analysis, and structured case analysis. I infer three primary conclusions about projects of the kind studied. First, they employ an implicit concept of gene that enables the joint use of both kinds of models. Second, they pursue more epistemic aims besides mechanistic explanation of phenomena. Third, they don’t work to create and export broad synthesized theories. Rather, they focus on phenomena too complex to be understood by a common general theory, they distinguish parts of the phenomena, and they apply models from different theories to the different parts. For such projects, seemingly incompatible models are synthesized largely through mediated representations of complex phenomena. (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)

Project selection by funding bodies directly influences the division of cognitive labour in scientific communities. I present a novel adaptation of an existing agent-based model of scientific research, in which a central funding body selects from proposed projects located on an epistemic landscape. I simulate four different selection strategies: selection based on a god's-eye perspective of project significance, selection based on past success, selection based on past funding, and random selection. Results show the size of the landscape matters: on small (...) landscapes historical information leads to slightly better results than random selection, but on large landscapes random selection greatly outperforms historically-informed selection. (shrink)

There is an increasing push by journals to ensure that data and products related to published papers are shared as part of a cultural move to promote transparency, reproducibility, and trust in the scientific literature. Yet few journals commit to evaluating their effectiveness in implementing reporting standards aimed at meeting those goals (1, 2). Similarly, though the vast majority of journals endorse peer review as an approach to ensure trust in the literature, few make their peer review data available to (...) evaluate effectiveness toward achieving concrete measures of quality, including consistency and completeness in meeting reporting standards. Remedying these apparent disconnects is critical for closing the gap between guidance recommendations and actual reporting behavior. We see this as a collective action problem requiring leadership and investment by publishers, who can be incentivized through mechanisms that allow them to manage reputational risk and through continued innovation in journal assessment. (shrink)