The question of when to stop an unsuccessful experiment can be difficult to answer from an individual perspective. To help to guide these decisions, we turn to the social epistemology of science and investigate knowledge inquisition within a group. We focused on the expensive and lengthy experiments in high energy physics, which were suitable for citation-based analysis because of the relatively quick and reliable consensus about the importance of results in the field. In particular, we tested whether the time spent (...) on a scientific project correlates with the project output. Our results are based on data from the high energy physics laboratory Fermilab. They point out that there is an epistemic saturation point in experimenting, after which the likelihood of obtaining major results drops. With time the number of less significant publications does increase, but highly cited ones do not get published. Since many projects continue to run after the epistemic saturation point, it becomes clearer that decisions made about continuing them are not always rational. (shrink)

Scientific reasoning represents complex argumentation patterns that eventually lead to scientific discoveries. Social epistemology of science provides a perspective on the scientific community as a whole and on its collective knowledge acquisition. Different techniques have been employed with the goal of maximization of scientific knowledge on the group level. These techniques include formal models and computer simulations of scientific reasoning and interaction. Still, these models have tested mainly abstract hypothetical scenarios. The present thesis instead presents (...) data-driven approaches in social epistemology of science. A data-driven approach requires data collection and curation for its further usage, which can include creating empirically calibrated models and simulations of scientific inquiry, performing statistical analyses, or employing data- mining techniques and other procedures. -/- We present and analyze in detail three co-authored research projects on which the thesis’ author was engaged during her PhD. The first project sought to identify optimal team composition in high energy physics laboratories using data-mining techniques. The results of this project are published in (Perović et al. 2016), and indicate that projects with smaller numbers of teams and team members outperform bigger ones. In the second project, we attempted to determine whether there is an epistemic saturation point in experimentation in high energy physics. The initial results from this project are published in (Sikimić et al. 2018). In the thesis, we expand on this topic by using computer simulations to test for biases that could induce scientists to invest in projects beyond their epistemic saturation point. Finally, in previous examples of data-driven analyses, citations are used as a measure of epistemic efficiency of projects in high energy physics. In order to additionally justify and analyze the usage of this parameter in their data-driven research, in the third project Perović & Sikimić (2019) analyzed and compared inductive patterns in experimental physics and biology with the reliability of citation records in these fields. They conclude that while citations are a relatively reliable measure of efficiency in high energy physics research, the same does not hold for the majority of research in experimental biology. -/- Additionally, contributions of the author that are for the first time published in this theses are: (a) an empirically calibrated model of scientific interaction of research groups in biology, (b) a case study of irregular argumentation patterns in some pathogen discoveries, and (c) an introductory discussion of the benefits and limitations of data- driven approaches to the social epistemology of science. Using computer simulations of an empirically calibrated model, we demonstrate that having several levels of hierarchy and division into smaller research sub-teams is epistemically beneficial for researchers in experimental biology. We also show that argumentation analysis in biology represents a good starting point for further data-driven analyses in the field. Finally, we conclude that a data-driven approach is informative and useful for science policy, but requires careful considerations about data collection, curation, and interpretation. (shrink)

We used agent-based modelling to highlight the advantages and disadvantages of several management styles in biology, ranging from centralized to egalitarian ones. In egalitarian groups, all team members are connected with each other, while in centralized ones, they are only connected with the principal investigator. Our model incorporated time constraints, which negatively influenced weakly connected groups such as centralized ones. Moreover, our results show that egalitarian groups outperform others if the questions addressed are relatively simple or when the communication among (...) agents is limited. Complex epistemic spaces are explored best by centralized groups. They outperform other team structures because the individual members can develop their own ideas with less interference of the opinions of others. The optimal ratio between time spent on experimentation and dissemination varies between different organizational structures. Furthermore, if the evidence is shared only after a relevant degree of certainty is reached, all investigated groups epistemically profit. We discovered that the introduction of seminars to the model changes the epistemic performance in favour of weakly connected teams. Finally, the abilities of the principal investigator do not seem to outperform cognitive diversity, as group performances were not strongly influenced by the increase of her abilities. (shrink)

Recently, philosophers and social scientists have turned their attention to the epistemological shifts provoked in established sciences by their incorporation of big data techniques. There has been less focus on the forms of epistemology proper to the investigation of algorithms themselves, understood as scientific objects in their own right. This article, based upon 12 months of ethnographic fieldwork with Russian data scientists, addresses this lack through an investigation of the specific forms of epistemic attention paid to algorithms by (...) data scientists. On the one hand, algorithms are unlike other mathematical objects in that they are not subject to disputation through deductive proof. On the other hand, unlike concrete things in the world such as particles or organisms, algorithms cannot be installed as the objects of experimental systems directly. They can only be evaluated in their functioning as components of extended computational assemblages; on their own, they are inert. As a consequence, the epistemological coding proper to this evaluation does not turn on truth and falsehood but rather on the efficiency of a given algorithmic assemblage. This article suggests that understanding the forms of algorithmic rationality employed in such inquiry is crucial for charting the place of data science within the contemporary academy and knowledge economy more generally. (shrink)

Our ability for scientific reasoning is a byproduct of cognitive faculties that evolved in response to problems related to survival and reproduction. Does this observation increase the epistemic standing of science, or should we treat scientific knowledge with suspicion? The conclusions one draws from applying evolutionary theory to scientific beliefs depend to an important extent on the validity of evolutionary arguments (EAs) or evolutionary debunking arguments (EDAs). In this paper we show through an analytical model that (...) cultural transmission of scientific knowledge can lead toward representations that are more truth-approximating or more efficient at solving science-related problems under a broad range of circumstances, even under conditions where human cognitive faculties would be further off the mark than they actually are. (shrink)

Our ability for scientific reasoning is a byproduct of cognitive faculties that evolved in response to problems related to survival and reproduction. Does this observation increase the epistemic standing of science, or should we treat scientific knowledge with suspicion? The conclusions one draws from applying evolutionary theory to scientific beliefs depend to an important extent on the validity of evolutionary arguments (EAs) or evolutionary debunking arguments (EDAs). In this paper we show through an analytical model that (...) cultural transmission of scientific knowledge can lead toward representations that are more truth-approximating or more efficient at solving science-related problems under a broad range of circumstances, even under conditions where human cognitive faculties would be further off the mark than they actually are. (shrink)

A naturalistic impulse has taken speculative analytic metaphysics in its critical sights. Importantly, the claim that it is desirable or requisite to give metaphysics scientific moorings rests on underlying epistemological assumptions or principles. If the naturalistic impulse toward metaphysics is to be well-founded and its prescriptions to have normative force, those assumptions or principles should be spelled out and justified. In short, advocates of naturalized or scientific metaphysics require epistemic infrastructure. This paper begins to supply it. The (...) author first sketches her conception of suitably naturalized or scientific metaphysics. She then lays out a number of candidate epistemic principles centring around the notion of theoretical constraint. The author offers several arguments for the principles, based on statistical likeliness, agreement, falsity avoidance, and methodological efficiency and inefficiency. Finally, she shows how scientific metaphysics satisfies the epistemic principles and is therefore preferable to its traditional rivals. (shrink)

Experimental research is commonly held up as the paradigm of "good" science. Although experiment plays many roles in science, its classical role is testing hypotheses in controlled laboratory settings. Historical science is sometimes held to be inferior on the grounds that its hypothesis cannot be tested by controlled laboratory experiments. Using contemporary examples from diverse scientific disciplines, this paper explores differences in practice between historical and experimental research vis-à-vis the testing of hypotheses. It rejects the claim that historical research (...) is epistemically inferior. For as I argue, scientists engage in two very different patterns of evidential reasoning and, although there is overlap, one pattern predominates in historical research and the other pattern predominates in classical experimental research. I show that these different patterns of reasoning are grounded in an objective and remarkably pervasive time asymmetry of nature. (shrink)

Berichte zur Wissenschaftsgeschichte, Volume 45, Issue 3, Page 301-305, September 2022.

Berichte zur Wissenschaftsgeschichte, Volume 45, Issue 3, Page 301-305, September 2022.

Dating back to the early modern theories of Burke and Kant, philosophical accounts have made cognitive failure central to the experience of the sublime. This essay argues for a re-conception of the sublime in terms of the notion of epistemic expansion. Doing so not only provides a plausible account of traditional examples of the sublime, but also provides us with language that can capture an important but neglected aesthetic dimension of experimental science: the expansion of human perception. Recognizing this (...) dimension, it is argued, also enriches our understanding of the ways in which experimental science can facilitate broader public engagement with science. (shrink)

As more objections have been raised against grant peer-review for being costly and time-consuming, the legitimate question arises whether machine learning algorithms could help assess the epistemic efficiency of the proposed projects. As a case study, we investigated whether project efficiency in high energy physics can be algorithmically predicted based on the data from the proposal. To analyze the potential of algorithmic prediction in HEP, we conducted a study on data about the structure and outcomes of HEP experiments with (...) the goal of predicting their efficiency. In the first step, we assessed the project efficiency using Data Envelopment Analysis of 67 experiments conducted in the HEP laboratory Fermilab. In the second step, we employed predictive algorithms to detect which team structures maximize the epistemic performance of an expert group. For this purpose, we used the efficiency scores obtained by DEA and applied predictive algorithms – lasso and ridge linear regression, neural network, and gradient boosted trees – on them. The results of the predictive analyses show moderately high accuracy, indicating that they can be beneficial as one of the steps in grant review. Still, their applicability in practice should be approached with caution. Some of the limitations of the algorithmic approach are the unreliability of citation patterns, unobservable variables that influence scientific success, and the potential predictability of the model. (shrink)

Empirical multiple determination (multiple determination, for short) is the epistemic strategy of establishing the same result by means of multiple and independent procedures. It is an important epistemic strategy praised by both philosophers of science and practicing scientists. Commentators from different contexts have referred to multiple determination as one of the main strategies that researchers use to establish the reliability of their results. Multiple determination has been used to address a variety of problems that arise because of the (...) fallibility of experimental procedures. It is generally believed that being able to establish the same result (or provide evidence for a hypothesis of interest) by means of different and independent procedures is somewhat ‘‘better’’ than doing the same by a single procedure. Despite the heavy appeal to the multiple determination strategy, however, not much philosophical analysis has been provided regarding the grounds on which its epistemic desirability and virtues rest. Not much has been said regarding the structure and rationale underlying arguments which rely on multiple determination, and there is no general agreement regarding the epistemological import of these arguments. In my dissertation, I address these issues. More specifically, my dissertation: a. Provides a conceptual clarification of the epistemic strategy of multiple determination by making evident its differences, in both structure and epistemic import, from other notions and epistemic strategies from which it is often not distinguished in the literature such as robustness, consilience of inductions, variety of evidence, etc. b. Traces the historical and philosophical roots of multiple determination in the 19th century philosophical discussions and scientific developments. Especially, it makes the claim that the emergence of empirical multiple determination as a distinctive epistemic strategy emerged as a response to the scientific and philosophical difficulties facing the atomic and molecular hypotheses of matter and, more generally, the study of unobservable entities, in the end of the 19th century. c. Provides a general conceptual framework for understanding the structure and epistemic import of arguments that rely on the application of the multiple determination strategy in actual scientific research. d. The distinctive feature of my dissertation is that it examines its subject matter from a temporal perspective, by paying close attention to the historical emergence and development of the multiple determination strategy. As such, it also considers the implications of the debates regarding the structure and epistemic import of multiple determination for the relationship between history of science and philosophy of science. (shrink)

The aim of this paper is to investigate the consequences of the bibliometrics-based evaluation system of scientific production on the contents and methods of sciences. The research has been conducted by means of in-depth interviews to a multi-disciplinary panel of Italian researchers. We discuss the implications of bibliometrics-based evaluation on the choice of the research topic, on the experimental practices, on the dissemination habits. We observe that the validation of the bibliometrics-based evaluation practices relies on the acceptance and diffusion (...) within the scientific community, and that these practices are self-sustained through their wide application. We discuss possible evolving scenarios, also considering the recent development of digital archives. (shrink)

This article explores local variations in scientific practice through the lens of scientists’ international mobility. Its aim is twofold: to explore how the notion of epistemic living spaces may be mobilised as a tool for systematically exploring differences in scientific practice across locations, and to contribute to literature on scientific mobility. Using material from an interview study with scientists with experience of international mobility, and epistemic living spaces as an analytical frame, the paper describes a (...) set of aspects of life in science that interviewees described as being different in different places. These axes of variation were: embodied routines of research; resource levels and salaries; daily or longer-term rhythms of scientific life ; ‘efficiency’ and how work time is used; degree of hierarchy; the nature of social interactions between colleagues; the purposes of research; the social and interpersonal organisation of knowledge production; and the scale or ambition of research. In presenting an exploratory overview of these variations, the article points the way for future comparative investigation of epistemic cultures through studies of international mobility. (shrink)

Epistemic accounts of scientific collaboration usually assume that, one way or another, two heads really are more than twice better than one. We show that this hypothesis is unduly strong. We present a deliberately crude model with unfavorable hypotheses. We show that, even then, when the priority rule is applied, large differences in successfulness can emerge from small differences in efficiency, with sometimes increasing marginal returns. We emphasize that success is sensitive to the structure of competing communities. Our (...) results suggest that purely epistemic explanations of the efficiency of collaborations are less plausible but have much more powerful socioepistemic versions. (shrink)

In this paper I examine the feminist claim that non-epistemic values ought to play a role in scientific inquiry. I examine four holist arguments that non-epistemic values ought to play a role not only in the external aspects of scientific inquiry such as problem selection and the ethics of experimentation but also in its internal aspects, those that have to do with epistemic justification. In supporting their conclusion, I argue that they establish that the (...) traditional external/internal distinction has served as a marker for more fundamental distinctions between non-epistemic and epistemic values and between the means by which each are pursued. However, I also contend that these arguments do nothing to deny these distinctions between epistemic and non-epistemic values. Maintaining these distinctions, I argue for an epistemic holism suggesting ways in which both substantive claims about non-epistemic values and reliable processes/methods for the legitimization of non-epistemic values may also be truth-conducive, thereby serving the epistemic ends of scientific inquiry. (shrink)

“Proof of concept” is a phrase frequently used in descriptions of research sought in program announcements, in experimental studies, and in the marketing of new technologies. It is often coupled with either a short definition or none at all, its meaning assumed to be fully understood. This is problematic. As a phrase with potential implications for research and technology, its assumed meaning requires some analysis to avoid it becoming a descriptive category that refers to all things scientifically exciting. I provide (...) a short analysis of proof of concept research and offer an example of it within synthetic biology. I suggest that not only are there activities that circumscribe new epistemological categories but there are also associated normative ethical categories or principles linked to the research. I examine these and provide an outline for an alternative ethical account to describe these activities that I refer to as “extended agency ethics”. This view is used to explain how the type of research described as proof of concept also provides an attendant proof of principle that is the result of decision-making that extends across practitioners, their tools, techniques, and the problem solving activities of other research groups. (shrink)

Technoscientific research, a kind of scientific research conducted within the decontextualized approach (DA), uses advanced technology to produce instruments, experimental objects, and new objects and structures, that enable us to gain knowledge of states of affairs of novel domains, especially knowledge about new possibilities of what we can do and make, with the horizons of practical, industrial, medical or military innovation, and economic growth and competition, never far removed from view. The legitimacy of technoscientific innovations can be appraised only (...) in the course of considering fully what sorts of objects technoscientific objects are: objects that embody scientific knowledge confirmed within DA; physical/chemical/biological objects, realizations of possibilities discovered in research conducted within DA, brought to realization by means of technical/experimental/instrumental interventions; and components of social/ecological systems, objects that embody the values of technological progress and (most of them) values of capital and the market. What technoscientific objects are - their powers, tendencies, sources of their being, effects on human beings and social/economic systems, how they differ from non technoscientific objects - cannot be grasped from technoscientific inquiry alone; scientific inquiry that is not reducible to that conducted within DA is also needed. The knowledge that underlies and explains the efficacy of technoscientific objects is never sufficient to grasp what sorts of object they are and could become. Science cannot be reduced to technoscience. (shrink)

Scientific research is constrained by limited resources, so it is imperative that it be conducted efficiently. This paper introduces the notion of epistemic expression, a kind of representation that expedites the solution of research problems. Epistemic expressions are representations that (i) contain information in a way that enables more reliable information to place the most stringent constraints on possible solutions and (ii) make new information readily extractible by biasing the search through that space. I illustrate these conditions (...) using historical and contemporary examples of biomolecular structure determination. Then, I argue that the notion of epistemic expression parts ways with pragmatic accounts of scientific representation and an understanding of models as artifacts, neither of which require models to accurately represent. Explicating epistemic expression thus fills a gap in our understanding of scientific practice, extending Morrison and Morgan's (1999) conception of models as investigative instruments. (shrink)

Experimental modeling in biology involves the use of living organisms (not necessarily so-called "model organisms") in order to model or simulate biological processes. I argue here that experimental modeling is a bona fide form of scientific modeling that plays an epistemic role that is distinct from that of ordinary biological experiments. What distinguishes them from ordinary experiments is that they use what I call "in vivo representations" where one kind of causal process is used to stand in for (...) a physically different kind of process. I discuss the advantages of this approach in the context of evolutionary biology. (shrink)

This paper revisits the debate between Harry Collins and Allan Franklin, concerning the experimenters’ regress. Focusing my attention on a case study from recent psychology (regarding experimental evidence for the existence of a Mozart Effect), I argue that Franklin is right to highlight the role of epistemological strategies in scientific practice, but that his account does not sufficiently appreciate Collins’s point about the importance of tacit knowledge in experimental practice. In turn, Collins rightly highlights the epistemic uncertainty (and (...) skepticism) surrounding much experimental research. However, I will argue that his analysis of tacit knowledge fails to elucidate the reasons why scientists often are (and should be) skeptical of other researchers’ experimental results. I will present an analysis of tacit knowledge in experimental research that not only answers to this desideratum, but also shows how such skepticism can in fact be a vital enabling factor for the dynamic processes of experimental knowledge generation. (shrink)

Data production in experimental sciences depends on localised experimental systems, but the epistemic properties of data transcend the contingencies of the processes that produce them. Philosophers often believe that experimental systems instantiate but do not produce the epistemic properties of data. In this paper, we argue that experimental systems' local functioning entails intrinsic capacities to produce the epistemic properties of data. We develop this idea by applying Derrida's model of arche-writing to study a case of theory-oriented experimental (...) practice. Derrida's model relativises or dissolves the conceptual distinction between the moment of data production and a subsequent moment of data dissemination. It thus has consequences for understanding both data production (despite being intrinsically local, data production a priori generates transferrable and modellable information) and data dissemination (when modelling information, researchers needs to refer this information to the context of its production). We study a case of data production in a non-exploratory experimental system designed to test a pre-existing hypothesis in visual neuroscience. A case of theory-oriented experimental practice should allow us to identify the autonomous functioning of experimental systems in data production more clearly, insofar as it allows us to study the limits of pre-existing theory in the activities of these systems. We suggest that pre-existing concepts, hypotheses and theories condition the relevance but not the production of experimental data. (shrink)

Several philosophical issues in connection with computer simulations rely on the assumption that results of simulations are trustworthy. Examples of these include the debate on the experimental role of computer simulations :483–496, 2009; Morrison in Philos Stud 143:33–57, 2009), the nature of computer data Computer simulations and the changing face of scientific experimentation, Cambridge Scholars Publishing, Barcelona, 2013; Humphreys, in: Durán, Arnold Computer simulations and the changing face of scientific experimentation, Cambridge Scholars Publishing, Barcelona, 2013), and (...) the explanatory power of computer simulations :277–292, 2008; Durán in Int Stud Philos Sci 31:27–45, 2017). The aim of this article is to show that these authors are right in assuming that results of computer simulations are to be trusted when computer simulations are reliable processes. After a short reconstruction of the problem of epistemic opacity, the article elaborates extensively on computational reliabilism, a specified form of process reliabilism with computer simulations located at the center. The article ends with a discussion of four sources for computational reliabilism, namely, verification and validation, robustness analysis for computer simulations, a history of successful implementations, and the role of expert knowledge in simulations. (shrink)

Experimental philosophy of science gathers empirical data on how key scientific concepts are understood by particular scientific communities. In this paper we briefly describe two recent studies in experimental philosophy of biology, one investigating the concept of the gene, the other the concept of innateness. The use of experimental methods reveals facts about these concepts that would not be accessible using the traditional method of intuitions about possible cases. It also contributes to the study of conceptual change in (...) science, which we understand as the result of a form of conceptual ecology, in which concepts become adapted to specific epistemic niches. (shrink)

This article outlines a philosophy of science in practice that focuses on the engineering sciences. A methodological issue is that these practices seem to be divided by two different styles of scientific reasoning, namely, causal-mechanistic and mathematical reasoning. These styles are philosophically characterized by what Kuhn called ?disciplinary matrices?. Due to distinct metaphysical background pictures and/or distinct ideas of what counts as intelligible, they entail distinct ideas of the character of phenomena and what counts as a scientific explanation. (...) It is argued that the two styles cannot be reduced to each other. At the same time, although they are incompatible, they must not be regarded as competing. Instead, they produce different kinds of epistemic results, which serve different kinds of epistemic functions. Moreover, some scientific breakthroughs essentially result from relating them. This view of complementary styles of scientific reasoning is supported by pluralism about metaphysical background pictures. (shrink)

Philosophy of Experimental Biology explores some central philosophical issues concerning scientific research in experimental biology, including genetics, biochemistry, molecular biology, developmental biology, neurobiology, and microbiology. It seeks to make sense of the explanatory strategies, concepts, ways of reasoning, approaches to discovery and problem solving, tools, models and experimental systems deployed by scientific life science researchers and also integrates developments in historical scholarship, in particular the New Experimentalism. It concludes that historical explanations of scientific change that are based (...) on local laboratory practice need to be supplemented with an account of the epistemic norms and standards that are operative in science. This book should be of interest to philosophers and historians of science as well as to scientists. (shrink)

The central role of such epistemic concepts as theory, explanation, model, or mechanism is rarely questioned in philosophy of science. Yet, what is their actual use in the practice of science? In this philosophy of science project, we deploy text-mining methods to investigate the usage of 61 epistemic notions in a corpus of full-text articles from the biological and biomedical sciences (N=73,771). The influence of disciplinary context is also examined by splitting the corpus into sub-disciplinary clusters. The results (...) reveal the intricate semantic networks that these concepts actually form in the scientific discourse, not always following our intuitions, at least in some parts of science. The research is published in: Malaterre, Christophe & Martin Léonard. 2023. "Epistemic markers in the scientific discourse", Philosophy of Science. (shrink)

Scientific realism does not view theoretical terms as mere instruments of experimental predictions; it grants referential status to natural kind terms with 'epistemic access' and view scientific theories and terms as corresponding to physical phenomena and entities which exist independently of observation, and as thereby being the source of objective -approximate and not absolute- knowledge of the physical realm. As a result, scientific realism is accused of ontologising the unobservables. Against this charge, scientific realism posits (...) the idea of the dialectical relation between theoretical terms referring to the unobservables and scientific methods. The second argument made by realism is the ‘no miracle’ thesis. These arguments stand challenged by the Copenhagen interpretation of quantum mechanics. The aim of the paper is to examine the relevance of the two arguments of scientific realism in countering the idea that the existence of quantum states in the microphysical world renders realism obsolete. (shrink)

One of the more visible recent developments in philosophical methodology is the experimental philosophy movement. On its surface, the experimentalist challenge looks like a dramatic threat to the apriority of philosophy; ‘experimentalist’ is nearly antonymic with ‘aprioristic’. This appearance, I suggest, is misleading; the experimentalist critique is entirely unrelated to questions about the apriority of philosophical investigation. There are many reasons to resist the skeptical conclusions of negative experimental philosophers; but even if they are granted—even if the experimentalists are right (...) to claim that we must do much more careful laboratory work in order legitimately to be confident in our philosophical judgments— the apriority of philosophy is unimpugned. The kinds of scientific investigation that experimental philosophers argue to be necessary involve merely enabling sensory experiences. Although they are not enabling in the sense of permitting concept acquisition, they are enabling in another epistemically significant way that is also consistent with the apriority of philosophy. (shrink)

Some experimental results in science are productively surprising or beautiful. Such results are disruptive in their epistemic nature: by violating epistemic expectations they mark the phenomenon at hand as worthy of further investigation. Could it be that there are emotions beyond these two which are also useful for the epistemic evaluation of scientific experiments? Here, I conduct a structured sociological survey to explore affective experiences in scientific experimental research. I identify that learning the results of (...) an experiment is the high emotional point in the experimenting process. Thus, experimental results can be challenging, beautiful, or boring, and they can worry, amuse, make one sad, and so on. They can also drive meta-cognitive evaluations as well as motivate specific research-related actions. From this, I advance two claims: that emotions beyond surprise and disruptive beauty are epistemically useful in empirical research, and that emotions help to overcome specific challenges of reasoning about new experimental results. (shrink)

In general, epistemic emotions can be characterized as emotions that concern the subject's own states and mental processes and are associated with cognition and knowledge acquisition. They are the result of a cognitive inconsistency that may appear as a consequence of unexpected information that contradicts previous knowledge. They have a significant impact on the exploration and generation of knowledge about oneself and the world, as well as on conceptual changes and cognitive efficiency. There is no interspecies comparative perspective in (...) experimental studies on epistemic emotions. At first glance, this situation is not controversial, because the category of epistemic emotions has been defined in such a way that it seems to belong only to people. Inconsistencies arise when comparative research in the field of cognitive ethology, primatology or comparative psychology is analyzed. Researchers point to a number of behaviors of nonhuman animals that prove that they have a wide range of emotions - including those that stand out in the catalog of epistemic emotions, i.e. surprise, curiosity or uncertainty. The presented article is an attempt to answer the questions posed in the title and an introduction to research on an adequate model of epistemic emotions, taking into account the results of research in the above-mentioned areas. (shrink)

I examine how particular social arrangements and incentive structures encourage the honest reporting of experimental results and minimize fraudulent scientific work. In particular I investigate how epistemic communities can achieve this goal by promoting members to police the community. Using some basic tools from game theory, I explore a simple model in which scientists both conduct research and have the option of investigating the findings of their peers. I find that this system of peer policing can in many (...) cases ensure high levels of honesty. (shrink)

Klaming and Vedder (2010) have argued that enhancement technologies that improve the epistemic efficiency of the legal system (“epistemic enhancements”) would benefit the common good. But there are two flaws to Klaming and Vedder’s argument. First, they rely on an under-theorised and under-specified conception of the common good. When theory and specification are supplied, their CGJ for enhancing eyewitness memory and recall becomes significantly less persuasive. And second, although aware of such problems, they fail to give due weight (...) and consideration to the tensions between the individual and common good. Taking these criticisms onboard, this article proposes an alternative, and stronger, CGJ for epistemic enhancements. The argument has two prongs. Drawing from the literature on social epistemology and democratic legitimacy, it is first argued that there are strong grounds for thinking that epistemic enhancements are a desirable way to improve the democratic legitimacy of the legal system. This gives prima facie but not decisive weight to the CGJ. It is then argued that due to the ongoing desire to improve the way in which scientific evidence is managed by the legal system, epistemic enhancement is not merely desirable but perhaps morally necessary. Although this may seem to sustain tensions between individual and common interests, I argue that in reality it reveals a deep constitutive harmony between the individual good and the common good, one that is both significant in its own right and one that should be exploited by proponents of enhancement. (shrink)

This paper addresses three aspects of Bio Art: iconography, artificial life, and wetware. The development of models for innovation require hybrid practices which generate knowledge through epistemic experimental practices. The intersection of art and the biological sciences contain both scientific data as well as the visualization of its cultural imagination. In the Bio Art Lab at the School of Visual Arts, artists use the tools of science to make art.

A collective understanding that traces a debate between ‘what is science?’ and ‘what is a science about?’ has an extraction to the notion of scientific knowledge. The debate undertakes the pursuit of science that hardly extravagance the dogma of pseudo-science. Scientific conjectures invoke science as an intellectual activity poured by experiences and repetition of the objects that look independent of any idealist views (believes in the consensus of mind-dependence reality). The realistic machinery employs in an empiricist exposition of (...) the objective phenomenon by synchronizing the general method to make observational predictions that cover all the phenomena of the particular entity without any exception. The formation of science encloses several epistemological purviews and a succession of conjectures cum refutation that a newer theorem could reinstate. My attempt is to advocate a holistic plea of scientific conjectures that outruns the restricted regulation of experience or testable hypothesis to render the validity of a chain of logical reasoning (deductive or inductive) of basic scientific statements. The milieu of scientific intensification integrates speculation that loads efficiency towards a new experimental dimension where the reality is not itself objective or observers relative; in fact the observed phenomenon divulges in the constructive progression of preferred methods of falsifiability and uncertainty. (shrink)

This article explores the aesthetic dimensions of scientific experimentation, addressing specifically how aesthetic features enter the construction, evaluation and reception of an experiment. I highlight the relationship between experiments and artistic acts in the early years of the Royal Society where experiments do not serve only epistemic aims but also aim to generate feelings of awe and pleasure. I turn to analysing which aspects of experiments are appreciated aesthetically, identifying several contenders, from the ability of an experiment (...) to uncover nature’s beauty, to encapsulating original designs and human creativity. Following this analysis, I focus on the notion of beauty: what makes an experiment beautiful? Several common qualities are explored, from the simplicity and economy of the experiment, to the significance of the experimental results. (shrink)

A collective understanding that traces a debate between 'what is science?’ and ‘what is a science about?’ has an extraction to the notion of scientific knowledge. The debate undertakes the pursuit of science that hardly extravagance the dogma of pseudo-science. Scientific conjectures invoke science as an intellectual activity poured by experiences and repetition of the objects that look independent of any idealist views (believes in the consensus of mind-dependence reality). The realistic machinery employs in an empiricist exposition of (...) the objective phenomenon by synchronizing the general method to make observational predictions that cover all the phenomena of the particular entity without any exception. The formation of science encloses several epistemological purviews and a succession of conjectures cum refutation that a newer theorem could reinstate. My attempt is to advocate a holistic plea of scientific conjectures that outruns the restricted regulation of experience or testable hypothesis to render the validity of a chain of logical reasoning (deductive or inductive) of basic scientific statements. The milieu of scientific intensification integrates speculation that loads efficiency towards a new experimental dimension where the reality is not itself objective or observers relative; in fact the observed phenomenon divulges in the constructive progression of preferred methods of falsifiability and uncertainty. (shrink)

This release includes the code and supplementary information mentioned in: Malaterre, Christophe & Martin Léonard. 2023. "Charting the Territories of Epistemic Concepts in the Practice of Science: A Text-Mining Approach", British Journal for the Philosophy of Science.

Forensic science error rates are needlessly high. Applying the perspective of veritistic social epistemology to forensic science could produce new institutional designs that would lower forensic error rates. We make such an application through experiments in the laboratory with human subjects. Redundancy is the key to error prevention, discovery, and elimination. In the “monopoly epistemics” characterizing forensics today, one privileged actor is asked to identify the truth. In “democratic epistemics,” several independent parties are asked. In an experiment contrasting them, democratic (...) epistemics reduced the rate at which biased observers obscured the truth by two-thirds. These results highlight, first, the potential of “epistemic systems design,” which employs the techniques of economic systems design to address issues of veracity rather than efficiency, and second, the value of “experimental epistemology,” which employs experimental techniques in the study of science. (shrink)

In recent months months the hashtag #overlyhonestmethods has steadily been gaining popularity. Posts under this hashtag—presumably by scientists—detail aspects of daily scientific research that differ considerably from the idealized interpretation of scientific experimentation as standardized, objective and reproducible. Over and above its entertainment value, the popularity of this hashtag raises two important points for those who study both science and scientists. Firstly, the posts highlight that the generation of data through experimentation is often far less standardized (...) than is commonly assumed. Secondly, the popularity of the hashtag together with its relatively blasé reception by the scientific community reveal that the actions reported in the tweets are far from shocking and indeed may be considered just “part of scientific research”. Such observations give considerable pause for thought, and suggest that current conceptions of data might be limited by failing to recognize this “inherent variability” within the actions of generation—and thus within data themselves. Is it possible, we must ask, that epistemic virtues such as standardization, consistency, reportability and reproducibility need to be reevaluated? Such considerations are, of course, of particular importance to data sharing discussions and the Open Data movement. This paper suggests that the notion of a “moral professionalism” for data generation and sharing needs to be considered in more detail if the inherent variability of data are to be addressed in any meaningful manner. (shrink)

The purpose of this paper is to show how the degree of experimental validity of scientific procedures is crucially involved in determining two typical pragmatic modes in science, namely, the preservation of useful procedures and the disposal of useless ideas. The term 'pragmatic' will here be used following Schurz's characterisation of being internally pragmatic, as referring to that which proves useful for scientific or epistemic goals. The first part of the paper consists in a characterisation of the (...) notion of experimental validity. The second part is focused on several historical examples illustrating how the above pragmatic modes relate to the question of experimental validity. The Michelson-Morley experiment is presented as a case of a highly valid and useful experiment preserved through the development of different theories (like, on the one hand, the ether theory, upheld by Fitzgerald and Lorentz, and, on the other hand, Einstein's special theory of relativity). The concept of caloric will be discussed as an example of an idea that was discarded once it became useless, after heat was understood as a form of energy within the new frame provided by the kinetic theory of heat towards the middle of the 19th century. (shrink)

In this paper I examine the epistemic function of agent-based models of scientific inquiry, proposed in the recent philosophical literature. In view of Boero and Squazzoni’s classification of ABMs into case-based models, typifications and theoretical abstractions, I argue that proposed ABMs of scientific inquiry largely belong to the last category. While this means that their function is primarily exploratory, I suggest that they are epistemically valuable not only as a temporary stage in the development of ABMs of (...) science, but by providing insights into theoretical aspects of scientific rationality. I illustrate my point with two examples of highly idealized ABMs of science, which perform two exploratory functions: Zollman’s ABM which provides a proof-of-possibility in the realm of theoretical discussions on scientific rationality, and an argumentation-based ABM, which provides insights into potential mechanisms underlying the efficiency of scientific inquiry. (shrink)

As in other sciences, an economic experiment is an artificial situation created by a researcher for the purpose of answering one or more scientific questions. Experiments of various types are used in economics to understand the causes of poverty and how it might be alleviated. The methods can identify causal relationships between variables and thereby isolate factors that can lead to poverty as well as to document the behavioral consequences of poverty. Experiments can also be used to provide test (...) beds for proposed policies to alleviate poverty. This essay describes a variety of ways in which experiments have been employed to understand and combat poverty. A line of laboratory experiments that considers which economic institutions are conducive to economic growth is discussed in detail. The results show that decentralized markets are conducive to allowing an economy to operate as efficiently as it can. However, in an economy with a theoretical “poverty trap,” the market works more efficiently if accompanied by a democratic voting process and freedom of communication. (shrink)

According to a widely held view, scientific modelling consists in entertaining a set of model descriptions that specify a model. Rather than studying the phenomenon of interest directly, scientists investigate the phenomenon indirectly via a model in the hope of learning about some of the phenomenon’s features. I call this view the description-driven modelling (DDM) account. I argue that although an accurate description of much of scientific research, the DDM account is found wanting as regards the mechanistic modelling (...) found in many branches of biology. By analysing research practices in cancer immunology concerning the development of mechanistic models of the process of cancer metastasis, this paper presents and argues for a complementary account of scientific modelling, herein called the experimentation-driven modelling (EDM) account. In EDM, scientists investigate a set of experimental systems and then integrate the results obtained from experiments into a mechanistic model. While EDM shares some key features with DDM, the two are epistemically very different approaches to research. (shrink)

For two centuries, collaborative research has become increasingly widespread. Various explanations of this trend have been proposed. Here, we offer a novel functional explanation of it. It differs from ac- counts like that of Wray by the precise socio-epistemic mech- anism that grounds the beneficialness of collaboration. Boyer-Kassem and Imbert show how minor differences in the step-efficiency of collaborative groups can make them much more successful in particular configurations. We investigate this model further, derive robust social patterns concerning the (...) general successfulness of collaborative groups, and argue that these patterns can be used to defend a general functional account. (shrink)

The unexpected and premature passing away of Professor Ebrahim H. "Abe" Mamdani on January, 22, 2010, was a big shock to the scientific community, to all his friends and colleagues around the world, and to his close relatives. Professor Mamdani was a remarkable figure in the academic world, as he contributed to so many areas of science and technology. Of great relevance are his latest thoughts and ideas on the study of language and its handling by computers. The fuzzy (...) logic community is particularly indebted to Abe Mamdani (1941-2010) who, in 1975, in his famous paper An Experiment in Linguistic Synthesis with a Fuzzy Logic Controller, jointly written with his student Sedrak Assilian, introduced the novel idea of fuzzy control. This was an elegant engineering approach to the modeling and control of complex processes for which mathematical models were unknown or too difficult to build, yet they could effectively and efficiently be controlled by human operators. This ground-breaking idea has found innumerable applications and can be considered as one of the main factors for the proliferation and adoption of fuzzy logic technology. Professor Mamdani's own life and vital experience are illustrative of his “never surrendering” attitude while facing adversaries, which is normal for a person proposing any novel solution, and represent a great example for everybody. His subtle sense of humor, his joy for life, and his will to critically help people, especially young people, were characteristics deeply appreciated by all the people who enjoyed and benefited from his friendship and advice. This book constitutes a posthumous homage to Abe Mamdani. It is a collection of original papers related in some way to his works, ideas and vision, and especially written by researchers directly acquainted with him or with his work. The underlying goal of this book will be fulfilled if, in the very spirit of Mamdani's legacy, the papers will trigger a scientific or philosophical debate on the issues covered, or contribute to a cross-fertilization of ideas in the various fields. (shrink)

The scientist's decision of accepting a given proposition is assumed to be dependent on two factors: the scientist's 'private' information about the value of that statement and the proportion of colleagues who also accept it. This interdependence is modelled in an economic fashion, and it is shown that it may lead to multiple equilibria. The main conclusions are that the evolution of scientific knowledge can be path, dependent, that scientific revolutions can be due to very small changes in (...) the empirical evidence, and that not all possible equilibria are necessarily efficient, neither in the economic nor in the epistemic sense. These inefficiencies, however, can be eliminated if scientists can form coalitions. (shrink)