According to David Chalmers, the hard problem of consciousness consists of explaining how and why qualitative experience arises from physical states. Moreover, Chalmers argues that materialist and reductive explanations of mentality are incapable of addressing the hard problem. In this chapter, I suggest that Chalmers’ hard problem can be usefully distinguished into a ‘how question’ and ‘why question,’ and I argue that evolutionary biology has the resources to address the question of why qualitative experience arises from brain states. From this (...) perspective, I discuss the different kinds of evolutionary explanations (e.g., adaptationist, exaptationist, spandrel) that can explain the origins of the qualitative aspects of various conscious states. This argument is intended to clarify which parts of Chalmers’ hard problem are amenable to scientific analysis. (shrink)

Through discussing scientific whaling, the paper brings the necessity of retrieving natural philosophy. The paper’s arguments favor an expanded vision of human encounter with nature, through the lens of natural philosophy, with a priority focus of expanding our imaginations to embrace the vast natural world. -/- There is no doubt that both the philosophy and science, two of the three significant areas of cultural and intellectual engagement (the other one is religion), have gone through changes over time. It is also (...) conspicuous that the modern natural science marginalized and suppressed specific concerns which were previously an indefeasible part of natural philosophy. -/- Bringing both historical and critical discussion of natural philosophy, the paper explores prospective retrieval of natural philosophy in contemporary modern science. Emphasizing the significance of natural philosophy’s imperatives both in the intellectual and field application of modern science, the paper reiterates commentary of Nicholas Maxwell, who advocates to correct three loopholes (Maxwell 2017): change the nature of social inquiry; opt aim-oriented rationality methods; and generalize the progress achieving methods of science. (shrink)

In this paper, we provide a macro level analysis of the visibility of philosophy of science in the sciences over the last four decades. Our quantitative analysis of publications and citations of philosophy of science papers, published in 17 main journals representing the discipline, contributes to the longstanding debate on the influence of philosophy of science on the sciences. It reveals the global structure of relationships that philosophy of science maintains with science, technology, engineering and mathematics and social sciences and (...) humanities fields. Explored at the level of disciplines, journals and authors, this analysis of the relations between philosophy of science and a large and diversified array of disciplines allows us to answer several questions: what is the degree of openness of various disciplines to the specialized knowledge produced in philosophy of science? Which STEM and SSH fields and journals have privileged ties with philosophy of science? What are the characteristics, in terms of citation and publication patterns, of authors who get their philosophy of science papers cited outside their field? Complementing existing qualitative inquiries on the influence of specific authors, concepts or topics of philosophy of science, the bibliometric approach proposed in this paper offers a comprehensive portrait of the multiple relationships that links philosophy of science to the sciences. (shrink)

Science and scientific knowledge have been questioned in many ways for a long period of time. Especially, after the scientific revolution of 16th- and 17th-century Europe, science and its knowledge have been mainly accepted one of the most valuable and trustable information. However, in 20th century, autonomy of scientific knowledge and its dominant position over other kinds of knowledge have been mainly criticised. Social and other factors that were tried to be excluded before have been incorporated into the work by (...) the influence of the Strong Programme. In this article, it will be argued that while people are presenting scientific knowledge, their interests, beliefs and the communities they are involved in are also shown to be effective in producing this information. Thus, the desired result is that it is not reasonable to talk about the absolute autonomy of scientific knowledge. (shrink)

The term “scientism” is used in a variety of ways with both negative and positive connotations. I suggest that some of these uses are inappropriate, as they aim simply at dismissing without argument an approach that a particular author does not like. However, there are legitimate negative uses of the term, which I explore by way of an analogy with the term “pseudoscience.” I discuss these issues by way of a recent specific example provided by a controversy in the field (...) of bioethics concerning the value, or lack thereof, of homeopathy. I then frame the debate about scientism within the broader context of C.P. Snow’s famous essay on the “two cultures.”. (shrink)

For a long time, philosophers of science have expressed little interest in the so-called demarcation project that occupied the pioneers of their field, and most now concur that terms like “pseudoscience” cannot be defined in any meaningful way. However, recent years have witnessed a revival of philosophical interest in demarcation. In this paper, I argue that, though the demarcation problem of old leads to a dead-end, the concept of pseudoscience is not going away anytime soon, and deserves a fresh look. (...) My approach proposes to naturalize and down-size the concept, anchoring it in real-life doctrines and fields of inquiry. First, I argue against the definite article “the” in “the demarcation problem”, distinguishing between territorial and normative demarcation, and between different failures and shortcomings in science apart from pseudoscience. Next, I argue that pseudosciences can be fruitfully regarded as simulacra of science, doctrines that are not epistemically warranted but whose proponents try to create the impression that they are. In this element of imitation or mimicry, I argue, lies the clue to their common identity. Despite the huge variety of doctrines and beliefs gathered under the rubric of “pseudoscience”, and the wide range of defects from which they suffer, pseudosciences all engage in similar strategies to create an impression of epistemic warrant. The indirect, symptomatic approach defended here leads to a general characterization of pseudosciences in all domains of inquiry, and to a useful diagnostic tool. (shrink)

This article on the epistemology of computational models stems from an analysis of the Gaia hypothesis (GH). It begins with James Kirchner’s criticisms of the central computational model of GH: Daisyworld. Among other things, the model has been criticized for being too abstract, describing fictional entities (fictive daisies on an imaginary planet) and trying to answer counterfactual (what-if) questions (how would a planet look like if life had no influence on it?). For these reasons the model has been considered not (...) testable and therefore not legitimate in science, and in any case not very interesting since it explores non actual issues. This criticism implicitly assumes that science should only be involved in the making of models that are ‘‘actual’’ (by opposition to what-if) and ‘‘specific’’ (by opposition to abstract). I challenge both of these criticisms in this article. First by showing that although the testability—understood as the comparison of model output with empirical data—is an important procedure for explanatory models, there are plenty of models that are not testable. The fact that these are not testable (in this restricted sense) has nothing to do with their being ‘‘abstract’’ or ‘‘what-if’’ but with their being predictive models. Secondly, I argue that ‘‘abstract’’ and ‘‘what-if’’ models aim at (respectable) epistemic purposes distinct from those pursued by ‘‘actual and specific models’’. Abstract models are used to propose how-possibly explanation or to pursue theorizing. What-if models are used to attribute causal or explanatory power to a variable of interest. The fact that they aim at different epistemic goals entails that it may not be accurate to consider the choice between different kinds of model as a ‘‘strategy‘‘. (shrink)

This article on the epistemology of computational models stems from an analysis of the Gaïa hypothesis. It begins with James Kirchner’s criticisms of the central computational model of GH: Daisyworld. Among other things, the model has been criticized for being too abstract, describing fictional entities and trying to answer counterfactual questions. For these reasons the model has been considered not testable and therefore not legitimate in science, and in any case not very interesting since it explores non actual issues. This (...) criticism implicitly assumes that science should only be involved in the making of models that are “actual” and “specific”. I challenge both of these criticisms in this article. First by showing that although the testability—understood as the comparison of model output with empirical data—is an important procedure for explanatory models, there are plenty of models that are not testable. The fact that these are not testable has nothing to do with their being “abstract” or “what-if” but with their being predictive models. Secondly, I argue that “abstract” and “what-if” models aim at epistemic purposes distinct from those pursued by “actual and specific models”. Abstract models are used to propose how-possibly explanation or to pursue theorizing. What-if models are used to attribute causal or explanatory power to a variable of interest. The fact that they aim at different epistemic goals entails that it may not be accurate to consider the choice between different kinds of model as a “strategy“. (shrink)

In the present study we analyze if the risk concept of the hegemonic epidemiologychanges its nature in purportedly alternative currents as ecoepidemiology and socialepidemiology focused in multilevel analysis.We analyze the way this concept is distinguishedin every current and its relationship with other epidemiologic key notions as cause. We findthat the risk concept and the notion of cause remain relatively unchanged among the differentcurrents even when there is some theoretical discussion about the complexity of multilevelsystems and other explanations for the events. (...) Finally we discuss some consequences aboutthe appropriation of the risk concept in multiple interventions in the health field. We indicatethat the fragmented nature of the risk concept is problematic because it can make thesocial aspects of the disease considered only in a functional perspective. Alternatively to thatwe develop the vulnerability concept as a knowledge framed in a hermeneutical perspective.The vulnerability concept acts as a mediator knowledge between epidemiology and theinterventions in the health field. In the same way we point out some concerns from the anthropologicalfield about the simplification of social senses and omission of meanings aboutthe health of the communities. (shrink)