Molecular biologists exploit information conveyed by mechanistic models for experimental purposes. In this article, I make sense of this aspect of biological practice by developing Keller’s idea of the distinction between ‘models of’ and ‘models for’. ‘Models of (phenomena)’ should be understood as models representing phenomena and are valuable if they explain phenomena. ‘Models for (manipulating phenomena)’ are new types of material manipulations and are important not because of their explanatory force, but because of the interventionist strategies they afford. This (...) is a distinction between aspects of the same model. In molecular biology, models may be treated either as ‘models of’ or as ‘models for’. By analysing the discovery and characterization of restriction–modification systems and their exploitation for DNA cloning and mapping, I identify the differences between treating a model as a ‘model of’ or as a ‘model for’. These lie in the cognitive disposition of the modeller towards the model: a modeller will look at a model as a ‘model of’ if interested in its explanatory force, or as a ‘model for’ if interested in the material manipulations it can possibly afford. (shrink)

In the past few years, the ethical ramifications of AI technologies have been at the center of intense debates. Considerable attention has been devoted to understanding how a morally responsible practice of data science can be promoted and which values have to shape it. In this context, ethics and moral responsibility have been mainly conceptualized as compliance to widely shared principles. However, several scholars have highlighted the limitations of such a principled approach. Drawing from microethics and the virtue theory tradition, (...) in this paper, we formulate a different approach to ethics in data science which is based on a different conception of “being ethical” and, ultimately, of what it means to promote a morally responsible data science. First, we develop the idea that, rather than only compliance, ethical decision-making consists in using certain moral abilities, which are cultivated by practicing and exercising them in the data science process. An aspect of virtue development that we discuss here is moral attention, which is the ability of data scientists to identify the ethical relevance of their own technical decisions in data science activities. Next, by elaborating on the capability approach, we define a technical act as ethically relevant when it impacts one or more of the basic human capabilities of data subjects. Therefore, rather than “applying ethics”, data scientists should cultivate ethics as a form of reflection on how technical choices and ethical impacts shape one another. Finally, we show how this microethical framework concretely works, by dissecting the ethical dimension of the technical procedures involved in data understanding and preparation of electronic health records. (shrink)

Recently, biologists have argued that data - driven biology fosters a new scientific methodology; namely, one that is irreducible to traditional methodologies of molecular biology defined as the discovery strategies elucidated by mechanistic philosophy. Here I show how data - driven studies can be included into the traditional mechanistic approach in two respects. On the one hand, some studies provide eliminative inferential procedures to prioritize and develop mechanistic hypotheses. On the other, different studies play an exploratory role in providing useful (...) generalizations to complement the procedure of prioritization. Overall this paper aims to shed light on the structure of contemporary research in molecular biology. (shrink)

A recent article by Herzog provides a much-needed integration of ethical and epistemological arguments in favor of explicable AI in medicine. In this short piece, I suggest a way in which its epistemological intuition of XAI as “explanatory interface” can be further developed to delineate the relation between AI tools and scientific research.

In the past few years, machine learning (ML) tools have been implemented with success in the medical context. However, several practitioners have raised concerns about the lack of transparency—at the algorithmic level—of many of these tools; and solutions from the field of explainable AI (XAI) have been seen as a way to open the ‘black box’ and make the tools more trustworthy. Recently, Alex London has argued that in the medical context we do not need machine learning tools to be (...) interpretable at the algorithmic level to make them trustworthy, as long as they meet some strict empirical desiderata. In this paper, we analyse and develop London’s position. In particular, we make two claims. First, we claim that London’s solution to the problem of trust can potentially address another problem, which is how to evaluate the reliability of ML tools in medicine for regulatory purposes. Second, we claim that to deal with this problem, we need to develop London’s views by shifting the focus from the opacity of algorithmic details to the opacity of the way in which ML tools are trained and built. We claim that to regulate AI tools and evaluate their reliability, agencies need an explanation of how ML tools have been built, which requires documenting and justifying the technical choices that practitioners have made in designing such tools. This is because different algorithmic designs may lead to different outcomes, and to the realization of different purposes. However, given that technical choices underlying algorithmic design are shaped by value-laden considerations, opening the black box of the design process means also making transparent and motivating (technical and ethical) values and preferences behind such choices. Using tools from philosophy of technology and philosophy of science, we elaborate a framework showing how an explanation of the training processes of ML tools in medicine should look like. (shrink)

We claim that in contemporary studies in molecular biology and biomedicine, the nature of ‘manipulation’ and ‘intervention’ has changed. Traditionally, molecular biology and molecular studies in medicine are considered experimental sciences, whereas experiments take the form of material manipulation and intervention. On the contrary “big science” projects in biology focus on the practice of data mining of biological databases. We argue that the practice of data mining is a form of intervention although it does not require material manipulation. We also (...) suggest that material manipulation, although still present in in the practice of data mining, fulfill a different epistemic role. (shrink)

We argue that mechanistic models elaborated by machine learning cannot be explanatory by discussing the relation between mechanistic models, explanation and the notion of intelligibility of models. We show that the ability of biologists to understand the model that they work with severely constrains their capacity of turning the model into an explanatory model. The more a mechanistic model is complex, the less explanatory it will be. Since machine learning increases its performances when more components are added, then it generates (...) models which are not intelligible, and hence not explanatory. (shrink)

In the science and values literature, scholars have shown how science is influenced and shaped by values, often in opposition to the ‘value free’ ideal of science. In this paper, we aim to contribute to the science and values literature by showing that the relation between science and values flows not only from values into scientific practice, but also from (allegedly neutral) science to values themselves. The extant literature in the ‘science and values’ field focuses by and large on reconstructing, (...) post hoc, how values have influenced science; our reconstruction of the case studies, instead, aims to show that scientific concepts and methods _too, because of specific identifiable characteristics,_ can promote some values rather than (or at the expense of) others. We explain this bidirectional relation in analogy to debates on the normativity of technical artifacts and on feminist approaches in science, and we illustrate our claims with cases from the health sciences and machine learning. While our arguments in this paper also draw on post hoc reconstructions, we intend to show where, in the science in the making, we should engage not only with the question whether a practice is value-laden, but also how specific conceptual and methodological choices can influence values down the road. All in all, these considerations expand the ways in which philosophers can contribute to more value-aware scientific practices. (shrink)

The notion of biological function is fraught with difficulties—intrinsically and irremediably so, we argue. The physiological practice of functional ascription originates from a time when organisms were thought to be designed and remained largely unchanged since. In a secularized worldview, this creates a paradox which accounts of functions as selected effect attempt to resolve. This attempt, we argue, misses its target in physiology and it brings problems of its own. Instead, we propose that a better solution to the conundrum of (...) biological functions is to abandon the notion altogether, a prospect not only less daunting than it appears, but arguably the natural continuation of the naturalisation of biology. (shrink)

In biology—as in other scientific fields—there is a lively opposition between big and small science projects. In this commentary, I try to contextualize this opposition in the field of biomedicine, and I argue that, at least in this context, big science projects should come first.

Machine learning (ML) has been praised as a tool that can advance science and knowledge in radical ways. However, it is not clear exactly how radical are the novelties that ML generates. In this article, I argue that this question can only be answered contextually, because outputs generated by ML have to be evaluated on the basis of the theory of the science to which ML is applied. In particular, I analyze the problem of novelty of ML outputs in the (...) context of molecular biology. In order to do this, I first clarify the nature of the models generated by ML. Next, I distinguish three ways in which a model can be novel (from the weakest to the strongest). Third, I dissect the way ML algorithms work and generate models in molecular biology and genomics. On these bases, I argue that ML is either a tool to identify instances of knowledge already present and codified, or to generate models that are novel in a weak sense. The notable contribution of ML to scientific discovery in the context of biology is that it can aid humans in overcoming potential bias by exploring more systematically the space of possible hypotheses implied by a theory. (shrink)

In the last few years, biologists and computer scientists have claimed that the introduction of data science techniques in molecular biology has changed the characteristics and the aims of typical outputs (i.e. models) of such a discipline. In this paper we will critically examine this claim. First, we identify the received view on models and their aims in molecular biology. Models in molecular biology are mechanistic and explanatory. Next, we identify the scope and aims of data science (machine learning in (...) particular). These lie mainly in the creation of predictive models which performances increase as data set increases. Next, we will identify a tradeoff between predictive and explanatory performances by comparing the features of mechanistic and predictive models. Finally, we show how this a priori analysis of machine learning and mechanistic research applies to actual biological practice. This will be done by analyzing the publications of a consortium—The Cancer Genome Atlas—which stands at the forefront in integrating data science and molecular biology. The result will be that biologists have to deal with the tradeoff between explaining and predicting that we have identified, and hence the explanatory force of the ‘new’ biology is substantially diminished if compared to the ‘old’ biology. However, this aspect also emphasizes the existence of other research goals which make predictive force independent from explanation. (shrink)

I diagnose the current debate between epistemological and ontological emergentism as a Kantian antinomy, which has reasonable but irreconcilable thesis and antithesis. Kantian antinomies have recently returned to contemporary philosophy in part through the work of Luciano Floridi, and the method of levels of abstraction. I use a thought experiment concerning a computer simulation to show how to resolve the epistemological/ontological antinomy about emergence. I also use emergentism and simulations in artificial life to illuminate both levels of abstraction and theoretical (...) challenge for building intelligent agents. (shrink)

In the past few years, scholars have been questioning whether the current approach in data ethics based on the higher level case studies and general principles is effective. In particular, some have been complaining that such an approach to ethics is difficult to be applied and to be taught in the context of data science. In response to these concerns, there have been discussions about how ethics should be “embedded” in the practice of data science, in the sense of showing (...) how ethical issues emerge in small technical choices made by data scientists in their day-to-day activities, and how such an approach can be used to teach data ethics. However, a precise description of how such proposals have to be theoretically conceived and could be operationalized has been lacking. In this article, we propose a full-fledged characterization of ‘embedding’ ethics, and how this can be applied especially to the problem of teaching data science ethics. Using the emerging model of ‘microethics’, we propose a way of teaching daily responsibility in digital activities that is connected to the higher level ethical challenges discussed in digital/data ethics. We ground this microethical approach into a virtue theory framework, by stressing that the goal of a microethics is to foster the cultivation of moral virtues. After delineating this approach of embedding ethics in theoretical detail, this article discusses a concrete example of how such a ‘micro-virtue ethics’ approach could be practically taught to data science students. (shrink)

In the last few years, biologists and computer scientists have claimed that the introduction of data science techniques in molecular biology has changed the characteristics and the aims of typical outputs (i.e. models) of such a discipline. In this paper we will critically examine this claim. First, we identify the received view on models and their aims in molecular biology. Models in molecular biology are mechanistic and explanatory. Next, we identify the scope and aims of data science (machine learning in (...) particular). These lie mainly in the creation of predictive models which performances increase as data set increases. Next, we will identify a tradeoff between predictive and explanatory performances by comparing the features of mechanistic and predictive models. Finally, we show how this a priori analysis of machine learning and mechanistic research applies to actual biological practice. This will be done by analyzing the publications of a consortium—The Cancer Genome Atlas—which stands at the forefront in integrating data science and molecular biology. The result will be that biologists have to deal with the tradeoff between explaining and predicting that we have identified, and hence the explanatory force of the ‘new’ biology is substantially diminished if compared to the ‘old’ biology. However, this aspect also emphasizes the existence of other research goals which make predictive force independent from explanation. (shrink)

In its last round of publications in September 2012, the Encyclopedia Of DNA Elements (ENCODE) assigned a biochemical function to most of the human genome, which was taken up by the media as meaning the end of ‘Junk DNA’. This provoked a heated reaction from evolutionary biologists, who among other things claimed that ENCODE adopted a wrong and much too inclusive notion of function, making its dismissal of junk DNA merely rhetorical. We argue that this criticism rests on misunderstandings concerning (...) the nature of the ENCODE project, the relevant notion of function and the claim that most of our genome is junk. We argue that evolutionary accounts of function presuppose functions as ‘causal roles’, and that selection is but a useful proxy for relevant functions, which might well be unsuitable to biomedical research. Taking a closer look at the discovery process in which ENCODE participates, we argue that ENCODE’s strategy of biochemical signatures successfully identified activities of DNA elements with an eye towards causal roles of interest to biomedical research. We argue that ENCODE’s controversial claim of functionality should be interpreted as saying that 80 % of the genome is engaging in relevant biochemical activities and is very likely to have a causal role in phenomena deemed relevant to biomedical research. Finally, we discuss ambiguities in the meaning of junk DNA and in one of the main arguments raised for its prevalence, and we evaluate the impact of ENCODE’s results on the claim that most of our genome is junk. (shrink)

The applications of machine learning and deep learning to the natural sciences has fostered the idea that the automated nature of algorithmic analysis will gradually dispense human beings from scientific work. In this paper, I will show that this view is problematic, at least when ML is applied to biology. In particular, I will claim that ML is not independent of human beings and cannot form the basis of automated science. Computer scientists conceive their work as being a case of (...) Aristotle’s poiesis perfected by techne, which can be reduced to a number of straightforward rules and technical knowledge. I will show a number of concrete cases where at each level of computational analysis, more is required to ML than just poiesis and techne, and that the work of ML practitioners in biology needs also the cultivation of something analogous to phronesis, which cannot be automated. But even if we knew how to frame phronesis into rules, still this virtue is deeply entrenched in our biological constitution, which computers lack. Whether computers can fully perform scientific practice independently of humans is an ill-posed question. (shrink)

In the last decade, Systems Biology has emerged as a conceptual and explanatory alternative to reductionist-based approaches in molecular biology. However, the foundations of this new discipline need to be fleshed out more carefully. In this paper, we claim that a relational ontology is a necessary tool to ground both the conceptual and explanatory aspects of Systems Biology. A relational ontology holds that relations are prior—both conceptually and explanatory—to entities, and that in the biological realm entities are defined primarily by (...) the context they are embedded within—and hence by the web of relations they are part of. (shrink)

In this chapter, we propose a non-traditional RCR training in data science that is grounded in a virtue theory framework. First, we delineate the approach in more theoretical detail by discussing how the goal of RCR training is to foster the cultivation of certain moral abilities. We specify the nature of these ‘abilities’: while the ideal is the cultivation of virtues, the limited space allowed by RCR modules can only facilitate the cultivation of superficial abilities or proto-virtues, which help students (...) to familiarize themselves with moral and political issues in the data science environment. Third, we operationalize our approach by stressing that (proto-)virtue acquisition (like skill acquisition) occurs through the technical and social tasks of daily data science activities, where these repetitive tasks provide the opportunities to develop (proto-)virtue capacity and to support the development of ethically robust data systems. Finally, we discuss a concrete example of implementing this approach. In particular, we describe how this method is applied to teach data ethics to students participating in the CODATA-RDA Data Science Summer Schools. (shrink)

It has been argued that ethical frameworks for data science often fail to foster ethical behavior, and they can be difficult to implement due to their vague and ambiguous nature. In order to overcome these limitations of current ethical frameworks, we propose to integrate the analysis of the connections between technical choices and sociocultural factors into the data science process, and show how these connections have consequences for what data subjects can do, accomplish, and be. Using healthcare as an example, (...) attention to sociocultural conversion factors relevant to health can help in navigating technical choices that require broader considerations of the sociotechnical system, such as metric tradeoffs in model validation, resulting in better ethical and technical choices. This approach promotes awareness of the ethical dimension of technical choices by data scientists and others, and that can foster the cultivation of 'ethical skills' as integral to data science. (shrink)

Making public policy choices based on available scientific evidence is an ideal condition for any policy making. However, the mechanisms governing these scenarios are complex, non-linear, and, alongside the medical-health and epidemiological issues, involve socio-economic, political, communicative, informational, ethical and epistemological aspects. In this article we analyze the role of scientific evidence when implementing political decisions that strictly depend on it, as in the case of the COVID-19 pandemic. In carrying out this analysis, we will focus above all on the (...) Italian case. This, on the one hand, precisely because Italy led the way regarding the containment policies of the pandemic. Secondly, the government's action was immediately criticized in various respects. Some were calling into question not only the cumbersome political mechanisms, but also suggesting a scarce ability to take scientific evidence into account. On other fronts, there are those who have criticized Italy for its blind and uncritical faith in science and for the paternalism of its decisions. This debate therefore offers the possibility of dealing with some aspects concerning scientific results and their implementation at the political level from the point of view of a political philosophy of science, roughly in the spirit suggested by John Dupré. (shrink)

In the past few years, calls for integrating ethics modules in engineering curricula have multiplied. Despite this positive trend, a number of issues with these ‘embedded’ programs remains. First, learning goals are underspecified. A second limitation is the conflation of different dimensions under the same banner, in particular confusion between ethics curricula geared towards addressing the ethics of individual conduct and curricula geared towards addressing ethics at the societal level. In this article, we propose a tripartite framework to overcome these (...) difficulties. Our framework analytically decomposes an ethics module into three dimensions. First, there is the ethical dimension, which pertains to the learning goals. Second, there is the moral dimension, which addresses the moral relevance of engineers’ conduct. Finally, there is the political dimension, which scales up issues of moral relevance at the civic level. All in all, our framework has two advantages. First, it provides analytic clarity, i.e. it enables course instructors to locate ethical dilemmas in either the moral or political realm and to make use of the tools and resources from moral and/or political philosophy. Second, it depicts a comprehensive ethical training, which enables students to both reason about moral issues in the abstract, and to socially contextualize potential solutions. (shrink)

In the last decade, robustness has been extensively mentioned and discussed in biology as well as in the philosophy of the life sciences. Nevertheless, from both fields, someone has affirmed that this debate has resulted in more semantic confusion than in semantic clearness. Starting from this claim, we wish to offer a sort of prima facie map of the different usages of the term. In this manner we would intend to predispose a sort of “semantic platform” which could be exploited (...) by those who wish to discuss or simply use it. We do this by starting from a core distinction between the robustness of representations, which is a philosophy of science issue, and the representations of robustness, which instead pertains to science. We illustrate our proposal with examples from biology, physics and mathematics. (shrink)

NCG 4.0 is the latest update of the Network of Cancer Genes, a web-based repository of systems-level properties of cancer genes. In its current version, the database collects information on 537 known (i.e. experimentally supported) and 1463 candidate (i.e. inferred using statistical methods) cancer genes. Candidate cancer genes derive from the manual revision of 67 original publications describing the mutational screening of 3460 human exomes and genomes in 23 different cancer types. For all 2000 cancer genes, duplicability, evolutionary origin, expression, (...) functional annotation, interaction network with other human proteins and with microRNAs are reported. In addition to providing a substantial update of cancer-related information, NCG 4.0 also introduces two new features. The first is the annotation of possible false-positive cancer drivers, defined as candidate cancer genes inferred from large-scale screenings whose association with cancer is likely to be spurious. The second is the description of the systems-level properties of 64 human microRNAs that are causally involved in cancer progression (oncomiRs). Owing to the manual revision of all information, NCG 4.0 constitutes a complete and reliable resource on human coding and non-coding genes whose deregulation drives cancer onset and/or progression. NCG 4.0 can also be downloaded as a free application for Android smart phones. (shrink)

Epigenetic research has brought several important technological achievements, including identifying epigenetic clocks and signatures, and developing epigenetic editing. The potential military applications of such technologies we discuss are stratifying soldiers’ health, exposure to trauma using epigenetic testing, information about biological clocks, confirming child soldiers’ minor status using epigenetic clocks, and inducing epigenetic modifications in soldiers. These uses could become a reality. This article presents a comprehensive literature review, and analysis by interdisciplinary experts of the scientific, legal, ethical, and societal issues (...) surrounding epigenetics and the military. Notwithstanding the potential benefit from these applications, our findings indicate that the current lack of scientific validation for epigenetic technologies suggests a careful scientific review and the establishment of a robust governance framework before consideration for use in the military. In this article, we highlight general concerns about the application of epigenetic technologies in the military context, especially discrimination and data privacy issues if soldiers are used as research subjects. We also highlight the potential of epigenetic clocks to support child soldiers’ rights and ethical questions about using epigenetic engineering for soldiers’ enhancement and conclude with considerations for an ethical framework for epigenetic applications in the military, defense, and security contexts. (shrink)

This volume reviews examples and notions of robustness at several levels of biological organization. It tackles many philosophical and conceptual issues and casts an outlook on the future challenges of robustness studies in the context of a practice-oriented philosophy of science. The focus of discussion is on concrete case studies. These highlight the necessity of a level-dependent description of robust biological behaviors.Experts from the neurosciences, biochemistry, ecology, biology, and the history and the philosophy of life sciences provide a multiplex perspective (...) on the topic. Contributions span from protein folding, to cell-level robustness, to organismal and developmental robustness, to sensorimotor systems, up to the robustness of ecological systems.Several chapters detail neurobiological case-studies. The brain, the poster child of plasticity in biology, offers multiple examples of robustness. Neurobiology explores the importance of temporal organization and multiscalarity in making this robustness-with-plasticity possible. The discussion also includes structures well beyond the brain, such as muscles and the complex feedback loops involved in the peculiar robustness of music perception. Overall, the volume grounds general reflections upon concrete case studies, opening to all the life sciences but also to non-biological and bio-inspired fields such as post-modern engineering. It will appeal to researchers, students, as well as non-expert readers. (shrink)

This research note is the eighth instalment in our series of preliminary findings on the census and study of the reception of De iure belli ac pacis. The note presents a bibliographical description of Laurentius’ 1647 re-issue of the 1631 edition by Blaeu, considers Laurentius’ motivation and methods of production, lists and maps the currently known twenty-three surviving copies, and briefly describes two notable exemplars.

This article aims to analyze how the so-called ‘pedagogy of work’ attempts to answer the challenges of unemployment and job insecurity characterizing the labor market in contemporary society. The authors reflect on the concepts of nihilist pedagogies and the ‘end of work’ by distinguishing two approaches: an active and a passive nihilist pedagogy. The passive approach, based on resignation, is opposed to an active attitude in which labor pedagogy offers tools to address current challenges. The authors support the idea that (...) pedagogy as a human-improving science cannot adopt the position of passive nihilism in interpreting work in contemporary society. To better understand the dynamics related to job insecurity and corrective solutions by pedagogy, the authors analyzed the thoughts of three contemporary philosophers: Zygmunt Bauman, Jeremy Rifkin, and Dominique Méda. These authors redefined the concept of work in connection with the transformations because of globalization, the advent of new communication technologies, and digital work. These changes have redefined not only the concept of work but also the models of work pedagogy in the Western world: capitalism and Marxism. Considering the current challenges, the pedagogy of work needs to be rethought, starting from the problem of employability and focusing on the new occupations in demand in the Internet age. By integrating ideas on interpreting work from the theories of Bauman, Rifkin, and Méda, it is possible to propose a pedagogy of work in the age of change and to outline possible values of education inspired by it. (shrink)

This article argues that Robert Alexy's influential theory of balancing is affected by a contradiction that makes it unfeasible as an instrument by which to explain some aspects of law and legal reasoning it aims to clarify. In particular, I will show that one of the premises of Alexy's theory of balancing is incompatible with its conclusion. Alexy's theory is based upon a sharp distinction between rules and principles. However, as my analysis will demonstrate, its conclusion implies that it is (...) impossible to distinguish between rules and principles. This is because the so‐called weight formula and the law of colliding principles (i.e., the two main notions used by Alexy to explain balancing) cancel out any difference between these two types of norms. (shrink)

The dual career allows elite athletes to attain their maximum competitive and academic performance, but the COVID-19 pandemic hindered their development and changed their perception of the importance given to the sporting and educational environment. For this reason, the aim of the present study was to determine the differences in the motivations and perceived barriers, the importance given to academic qualifications, and the perception of the dual career from a multifactorial perspective, of elite athletes according to sex, type of sport (...) practiced, job performance, time of sports career, type of athlete, and type of scholarship received. A total of 100 student-athletes participated in the research study by completing the “Perceptions of dual career student-athletes” questionnaire. The results showed that athletes from individual modalities and those who did not receive any scholarships described more barriers. In addition, women studied more because they enjoyed it ; athletes from individual modalities studied to work later ; athletes who do not work perceived a greater influence between study and sports performance ; at the beginning and at the best stage of their sports career, a greater influence of academics on performance was perceived ; and athletes who considered themselves professionals, and athletes who did not receive any scholarships, reported that the conciliation between sports and academic life was difficult. The results obtained point to the importance of dual career scholarships for student-athletes, as well as the need for the programs implemented for these athletes to consider sex, sport modality or type of scholarship granted. (shrink)

What, if any, are the limits of the Husserlian concept of Gegebenheit? Is there a limit beyond which nothing can be seen by the phenomenologist? In asking these questions, we allude to a distinction typical of Kantian criticism: “Grenze” or “Schranke”, limit or boundary? These same questions are reformulated in a famous review of Ideen I by Paul Natorp, a Marburg neo-Kantian who directly attacks the unlimited scope Husserl gives to the phenomenological principle of intuition. From a phenomenological point of (...) view, however, the Achilles’ heel of the critical method lies in the impossibility of accessing by intuition, beyond phenomena, the thing-in-itself. A major consequence is that the phenomenological dissolution of the “Grenze” prescribes a limitless opening to the horizon of phenomena. But if we can speak of a limitless openness, it is because in a certain way everything gives itself to be seen. What kind of vision is this? And what kind of Gegebenheit is at work here? The Husserlian answer lies in the recovery of a concept, the “idea in the Kantian sense”, without its counterpart, the “limit”, whereas for Kant as well as for Natorp it is precisely the concept of “limit” that characterizes the gnoseological status of the “idea”. (shrink)

This note studies the 1650 edition of Hugo Grotius’s De iure belli ac pacis. Using online and card catalogues, we have located eighty-nine copies, thirty-seven of which we examined in person, with an additional six fully digitised copies online. We hope that this research note on the preliminary results will generate greater interest in this unduly neglected edition. The note shows how, despite the connection established in the history of seventeenth-century politics that emphasized the ties between Grotius and the Peace (...) of Westphalia, the reception of Grotius’s 1650 edition bore no relation to the debates at Osnabrück and Münster. However, this is an influential edition, cherished by collectors and authors. According to our findings, it would be reproduced in a number of later reprints. (shrink)

Book reviewed in this article: Principles of Biomedical Ethics. By Tom L. Beauchamp and James F. Childress.

This research note offers a contextual overview of the printing history of Johann Blaeu’s 1646 octavo edition of Hugo Grotius’s De iure belli ac pacis (ibp). The note examines the printing process of the last edition that was prepared while Grotius was still alive, though it was published after his death. The note also sheds light on the theological dimension of some readers’ annotations, and concludes by discussing the impact this edition had on the modern versions of the text.

To understand the endogenous components of the event-related brain potential (ERP), we must use data about the components' antecedent conditions to form hypotheses about the information-processing function of the underlying brain activity. These hypotheses, in turn, generate testable predictions about the consequences of the component. We review the application of this approach to the analysis of the P300 component. The amplitude of the P300 is controlled multiplicatively by the subjective probability and the task relevance of the eliciting events, whereas its (...) latency depends on the duration of stimulus evaluation. These and other factors suggest that the P300 is a manifestation of activity occurring whenever one's model of the environment must be revised. Tests of three predictions based on this “context updating” model are reviewed. Verleger's critique is based on a misconstrual of the model as well as a partial and misleading reading of the relevant literature. (shrink)

In arguing against a supposed ambiguity, philosophers often rely on the zeugma test. In an application of the zeugma test, a supposedly ambiguous expression is placed in a sentence in which several of its supposed meanings are forced together. If the resulting sentence sounds zeugmatic, that is taken as evidence for ambiguity; if it does not sound zeugmatic, that is taken as evidence against ambiguity. The aim of this article is to show that arguments based on the second direction of (...) the test are misguided: ambiguous expressions, and in particular philosophically contested ones, do not reliably lead to zeugmaticity, so an absence of zeugmaticity provides no meaningful evidence for an absence of ambiguity. (shrink)