The avocado (Persea americana) is a major crop commodity worldwide. Moreover, avocado, a paleopolyploid, is an evolutionary “outpost” among flowering plants, representing a basal lineage (the magnoliid clade) near the origin of the flowering plants themselves. Following centuries of selective breeding, avocado germplasm has been characterized at the level of microsatellite and RFLP markers. Nonetheless, little is known beyond these general diversity estimates, and much work remains to be done to develop avocado as a major subtropical‐zone crop. Among the goals (...) of avocado improvement are to develop varieties with fruit that will “store” better on the tree, show uniform ripening and have better post‐harvest storage. Avocado transcriptome sequencing, genome mapping and partial genomic sequencing will represent a major step toward the goal of sequencing the entire avocado genome, which is expected to aid in improving avocado varieties and production, as well as understanding the evolution of flowers from non‐flowering seed plants (gymnosperms). Additionally, continued evolutionary and other comparative studies of flower and fruit development in different avocado strains can be accomplished at the gene expression level, including in comparison with avocado relatives, and these should provide important insights into the genetic regulation of fruit development in basal angiosperms. BioEssays 30:386–396, 2008. © 2008 Wiley Periodicals, Inc. (shrink)

I claim that one way thought experiments contribute to scientific progress is by increasing scientific understanding. Understanding does not have a currently accepted characterization in the philosophical literature, but I argue that we already have ways to test for it. For instance, current pedagogical practice often requires that students demonstrate being in either or both of the following two states: 1) Having grasped the meaning of some relevant theory, concept, law or model, 2) Being able to apply that theory, concept, (...) law or model fruitfully to new instances. Three thought experiments are presented which have been important historically in helping us pass these tests, and two others that cause us to fail. Then I use this operationalization of understanding to clarify the relationships between scientific thought experiments, the understanding they produce, and the progress they enable. I conclude that while no specific instance of understanding (thus conceived) is necessary for scientific progress, understanding in general is. (shrink)

John D. Norton defends an empiricist epistemology of thought experiments, the central thesis of which is that thought experiments are nothing more than arguments. Philosophers have attempted to provide counterexamples to this claim, but they haven’t convinced Norton. I will point out a more fundamental reason for reformulation that criticizes Norton’s claim that a thought experiment is a good one when its underlying logical form possesses certain desirable properties. I argue that by Norton’s empiricist standards, no thought experiment is ever (...) justified in any deep sense due to the properties of its logical form. Instead, empiricists should consider again the merits of evaluating thought experiments more like laboratory experiments, and less like arguments. (shrink)

Over the last few decades, virtue has become increasingly important in philosophy, psychology, cognitive science, and education. However, as each of these disciplines approaches virtue from a decidedly different perspective, it has proven difficult to come up with an understanding of virtue that satisfies the standards of all four disciplines. In their book, Jennifer Wright, Michael Warren, and Nancy Snow attempt to put forward such an understanding.

While philosophers hold that it is patently absurd to blame robots or hold them morally responsible [1], a series of recent empirical studies suggest that people do ascribe blame to AI systems and robots in certain contexts [2]. This is disconcerting: Blame might be shifted from the owners, users or designers of AI systems to the systems themselves, leading to the diminished accountability of the responsible human agents [3]. In this paper, we explore one of the potential underlying reasons for (...) robot blame, namely the folk's willingness to ascribe inculpating mental states or "mens rea" to robots. In a vignette-based experiment (N=513), we presented participants with a situation in which an agent knowingly runs the risk of bringing about substantial harm. We manipulated agent type (human v. group agent v. AI-driven robot) and outcome (neutral v. bad), and measured both moral judgment (wrongness of the action and blameworthiness of the agent) and mental states attributed to the agent (recklessness and the desire to inflict harm). We found that (i) judgments of wrongness and blame were relatively similar across agent types, possibly because (ii) attributions of mental states were, as suspected, similar across agent types. This raised the question - also explored in the experiment - whether people attribute knowledge and desire to robots in a merely metaphorical way (e.g., the robot "knew" rather than really knew). However, (iii), according to our data people were unwilling to downgrade to mens rea in a merely metaphorical sense when given the chance. Finally, (iv), we report a surprising and novel finding, which we call the inverse outcome effect on robot blame: People were less willing to blame artificial agents for bad outcomes than for neutral outcomes. This suggests that they are implicitly aware of the dangers of overattributing blame to robots when harm comes to pass, such as inappropriately letting the responsible human agent off the moral hook. (shrink)

This is the introduction to the Routledge Companion to Thought Experiments.

Can an ugly experiment be a good experiment? Philosophers have identified many beautiful experiments and explored ways in which their beauty might be connected to their epistemic value. In contrast, the present chapter seeks out (and celebrates) ugly experiments. Among the ugliest are those being designed by AI algorithms. Interestingly, in the contexts where such experiments tend to be deployed, low aesthetic value correlates with high epistemic value. In other words, ugly experiments can be good. Given this, we should conclude (...) that beauty is not generally necessary or sufficient for epistemic value, and increasing beauty will not generally tend to increase epistemic value. (shrink)

Thought experiments are a means of imaginative reasoning that lie at the heart of philosophy, from the pre-Socratics to the modern era, and they also play central roles in a range of fields, from physics to politics. The Routledge Companion to Thought Experiments is an invaluable guide and reference source to this multifaceted subject. Comprising over 30 chapters by a team of international contributors, the Companion covers the following important areas: -/- · the history of thought experiments, from antiquity to (...) the trolley problem and quantum non-locality; -/- · thought experiments in the humanities, arts, and sciences, including ethics, physics, theology, biology, mathematics, economics, and politics; -/- · theories about the nature of thought experiments; -/- · new discussions concerning the impact of experimental philosophy, cross-cultural comparison studies, metaphilosophy, computer simulations, idealization, dialectics, cognitive science, the artistic nature of thought experiments, and metaphysical issues. -/- This broad ranging Companion goes backwards through history and sideways across disciplines. It also engages with philosophical perspectives from empiricism, rationalism, naturalism, skepticism, pluralism, contextualism, and neo-Kantianism to phenomenology. This volume will be valuable for anyone studying the methods of philosophy or any discipline that employs thought experiments, as well as anyone interested in the power and limits of the mind. (shrink)

Sometimes we learn through the use of imagination. The epistemology of imagination asks how this is possible. One barrier to progress on this question has been a lack of agreement on how to characterize imagination; for example, is imagination a mental state, ability, character trait, or cognitive process? This paper argues that we should characterize imagination as a cognitive ability, exercises of which are cognitive processes. Following dual process theories of cognition developed in cognitive science, the set of imaginative processes (...) is then divided into two kinds: one that is unconscious, uncontrolled, and effortless, and another that is conscious, controlled, and effortful. This paper outlines the different epistemological strengths and weaknesses of the two kinds of imaginative process, and argues that a dual process model of imagination helpfully resolves or clarifies issues in the epistemology of imagination and the closely related epistemology of thought experiments. (shrink)

We might think that thought experiments are at their most powerful or most interesting when they produce new knowledge. This would be a mistake; thought experiments that seek understanding are just as powerful and interesting, and perhaps even more so. A growing number of epistemologists are emphasizing the importance of understanding for epistemology, arguing that it should supplant knowledge as the central notion. In this chapter, I bring the literature on understanding in epistemology to bear on explicating the different ways (...) that thought experiments increase three important kinds of understanding: explanatory, objectual and practical. (shrink)

Scientists imagine constantly. They do this when generating research problems, designing experiments, interpreting data, troubleshooting, drafting papers and presentations, and giving feedback. But when and how do scientists learn how to use imagination? Across 6 years of ethnographic research, it has been found that advanced career scientists feel comfortable using and discussing imagination, while graduate and undergraduate students of science often do not. In addition, members of marginalized and vulnerable groups tend to express negative views about the strength of their (...) imaginations and the general usefulness of imagination in science. After introducing these findings and discussing the typical relationship between a scientist and their imagination across a career, we argue that reducing the number or power of active imaginations in science is epistemically counterproductive. We suggest several ways to bring imagination back into science in a more inclusive way, especially through courses on imagination for scientists, good role models, and exemplar-based learning. (shrink)

In this article, we analyse the evidential value of the corpus of experimental philosophy. While experimental philosophers claim that their studies provide insight into philosophical problems, some philosophers and psychologists have expressed concerns that the findings from these studies lack evidential value. Barriers to evidential value include selection bias and p-hacking. To find out whether the significant findings in x-phi papers result from selection bias or p-hacking, we applied a p-curve analysis to a corpus of 365 x-phi chapters and articles. (...) Our results suggest that this corpus has evidential value, although there are hints of p-hacking in a few parts of the x-phi corpus. (shrink)

What role does the imagination play in scientific progress? After examining several studies in cognitive science, I argue that one thing the imagination does is help to increase scientific understanding, which is itself indispensable for scientific progress. Then, I sketch a transcendental justification of the role of imagination in this process.

Neuropsychiatrist Michael T. H. Wong argues that the notions of soul, mind, brain, self and consciousness are no longer adequate on their own to explain humanity. He formulates a “third discourse” that brings philosophy neuroscience theology and psychiatry together as an innovative multilayered narrative for the person in the twenty-first century.

Imagination is extremely important for science, yet very little is known about how scientists actually use it. Are scientists taught to imagine? What do they value imagination for? How do social and disciplinary factors shape it? How is the labor of imagining distributed? These questions should be high priority for anyone who studies or practices science, and this paper argues that the best methods for addressing them are qualitative. I summarize a few preliminary findings derived from recent interview-based and observational (...) qualitative studies that I have performed. These finding include: (i) imagination is only valued for use in addressing maximally specific problems, and only when all else fails; (ii) younger scientists and scientists who are members of underrepresented groups express less positive views about imagination in general, and have less confidence in their own imaginations; (iii) while scientists seem to employ various epistemological frameworks to evaluate imaginings, overall they appear to be epistemic consequentialists about imagination, and this holds also for their evaluations of the tools they use to extend the power of their imaginations. I close by discussing the epistemic and ethical consequences of these findings, and then suggesting a few research avenues that could be explored next as we move forward in the study of scientific imagination. (shrink)

As Nelson Goodman highlighted, there are two main senses of “abstract” that can be found in discussions about abstract art. On the one hand, a representation is abstract if it leaves out certain features of its target. On the other hand, something can be abstract to the extent that it does not represent a concrete subject. The first sense of “abstract” is well-known in philosophy of science. For example, philosophers discuss mathematical models of physical, biological, and economic systems as being (...) abstract in this sense. However, it is the second sense that dominates discussions of abstract art in aesthetics. For example, abstract art was (and is) considered revolutionary precisely for being non-figurative. Through an analysis of artists including Kandinsky, Malevich, and Mondrian, we develop a reading of this second sense, which we call “generative abstraction,” as opposed to “subtractive” abstraction. Generative abstraction is a process in which a new artifact is created which does not represent the initial concrete target system that inspired it (if there was one), where the artifact’s features are explored for their own sake, and where the “language” of the new artifact is in some way more “universal.” Focusing on this sense of abstraction is helpful in revealing the complexity of the process of crafting an abstract artifact, in problematizing the notion that abstraction can always be un-done (or concretized), as well as revealing new ways for abstractions to be epistemically (un)successful. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Hermeneutics, Neuroscience and PsychiatryMichael T. H. Wong, MBBS, MD, MA, MDiv, PhD, FRCPsych, FRANZCP, FHKAM (bio)Hermeneutic practice in mental health has been a theme in Philosophy, Psychiatry, & Psychology (PPP) since its very beginnings. In this essay I argue that hermeneutics, the theory and practice of interpretation, promotes therapeutic interaction between mental health professionals, patients and their family.Why does this patient present in such a way at this particular (...) point in time? The distressing symptoms are there. The changes in behavior are obvious. Impairments of functions are hurting. A mental illness clearly runs in the family. There were early losses of loved ones, physical abuse at home, bullying by peers and self-medication with drugs and alcohol. Three in four adults with a mental illness first experienced that before they turned 24. The brain goes through major reorganization during adolescence and early adulthood. If synaptic pruning went wrong, psychoses emerged. When stresses activated the hypothalamic–pituitary–adrenal axis the elevated cortisol level impacted the size and function of the hippocampus and amygdala in the genetically vulnerable; anxiety, depression, bipolar, and personality disorders developed. The patient needs a voice/language to describe all these experiences and events and the psychiatrist needs a discourse to make sense of them.Eisenberg laments the swings between "brainlessness" and "mindlessness" in psychiatry. Engel argues for a "biopsychosocial" discourse. The major challenge for psychiatry is how to organize clinical information of different nature (categories, dimensions, narratives; i.e., objective vs. subjective, personal vs. interpersonal) into a coherent and comprehensible account for us all. Mental illnesses are not only neuropsychiatric spectrum disorders but also dysfunctions of social relationship and environmental/ecological adaptation. Psychiatry as a clinical neuroscience per se lacks the semantics to address the rich interactions between the physical, psychological, social, cultural, and spiritual in the illness experience of our patients. Explanation in the diagnostic formulation (objective scientific discourse on cause and effect) and understanding in the patient narrative (subjective ordinary everyday discourse on significance and meaning) are irreducible to each other (Wong, 2018). They instead interact with one another to achieve an integrative formulation, not through merging different discourses into a single assertion/monologue but via the dialectic/dialogue of "explaining more in order to understand better," as Ricoeur puts it, and between "the whole and the parts," as Schleiermacher highlights.This "therapeutic hermeneutic circle" of "explanation vs understanding" and "the whole vs the parts" includes symptoms behavior function and life events. It correlates between bio-psychosociocultural-spiritual dimensions/perspectives and does not reduce them to any particular/single [End Page 13] stance. The whole integrates the parts and the parts enrich the whole. It explains but does not explain away. It understands through an articulation of meaning and significance. This discourse is a multilayered (bio-psycho-social-cultural-spiritual) personal narrative that formulates diagnosis and care in a correlative (linking different voices/discourses) and non-reductive (no particular voice/discourse is prejudiced against) manner that is comprehensible to us all (Wong, 2021).PPP will be an excellent forum for discussing clinical hermeneutics in the future. In this digital era of social media and virtual reality, hermeneutics has the never-ending task to tackle the unprecedented challenges to meaning illness and health posed by polarizing discourses.Michael T. H. Wong Michael T.H. Wong, MBBS, MD, MA, MDiv, PhD, FRCPsych, FRANZCP, FHKAM, is Hon Clinical Professor, Department of Psychiatry, School of Clinical Medicine, LKS Faculty of Medicine, The University of Hong Kong, HKSAR, China. Michael is Chair, Section of Philosophy & Humanities in Psychiatry, World Psychiatric Association. He is an Organizational Partner & International Lead with The Collaborating Centre for Values-Based Practice in Health and Social Care, St Catherine's College Oxford. He is Advisor to the Chinese Health Foundation of Australia.ReferencesWong M. T. H. (2018). Ricoeur and the third discourse of the person: From philosophy and neuroscience to psychiatry and theology. London: Lexington Books. Google ScholarWong, M. T. H. (2021). Values, meanings, hermeneutics and mental health. In Stoyanov, D., Fulford, K. M. W. F., Stanghellini, G., Van Staden, W., & Wong, M. TH. (Eds.), International perspectives in values-based mental health practice: Case studies and commentaries (pp. 341–349... (shrink)

Scientists recognize the necessity of imagination for solving tough problems. But how does the cognitive faculty responsible for daydreaming help in solving scientific problems? Philosophers claim that imagination is informative only when it is constrained to be maximally realistic. However, using a case study from space science, we show that scientists use imagination intentionally to break reality-oriented constraints. To do this well, they first target low-confidence constraints, and then higher-confidence constraints, until a plausible solution is found. This paper exemplifies a (...) new approach to epistemology of imagination that focuses on sets of imaginings (rather than individual imaginings), and responsible (rather than reliable) imaginings. (shrink)

Computational systems biologists create and manipulate computational models of biological systems, but they do not always have straightforward epistemic access to the content and behavioural profile of such models because of their length, coding idiosyncrasies, and formal complexity. This creates difficulties both for modellers in their research groups and for their bioscience collaborators who rely on these models. In this paper we introduce a new kind of visualization that was developed to address just this sort of epistemic opacity. The visualization (...) is unusual in that it depicts the dynamics and structure of a computer model instead of that model’s target system, and because it is generated algorithmically. Using considerations from epistemology and aesthetics, we explore how this new kind of visualization increases scientific understanding of the content and function of computer models in systems biology to reduce epistemic opacity. (shrink)

One of the most powerful traditions of the Jewish fascination with language is that of the Name. Indeed, the Jewish mystical tradition would seem a two millennia long meditation on the nature of name in relation to object, and how name mediates between subject and object. Even within the tide of the 20th century's linguistic turn, the aspect most notable in - the almost entirely secular - Jewish philosophers is that of the personal name, here given pivotal importance in the (...) articulation of human relationships and dialogue. The Name of God in Jewish Thought examines the texts of Judaism pertaining to the Name of God, offering a philosophical analysis of these as a means of understanding the metaphysical role of the name generally, in terms of its relationship with identity. The book begins with the formation of rabbinic Judaism in Late Antiquity, travelling through the development of the motif into the Medieval Kabbalah, where the Name reaches its grandest and most systematic statement - and the one which has most helped to form the ideas of Jewish philosophers in the 20th and 21st Century. This investigation will highlight certain metaphysical ideas which have developed within Judaism from the Biblical sources, and which present a direct challenge to the paradigms of western philosophy. Thus a grander subtext is a criticism of the Greek metaphysics of being which the west has inherited, and which Jewish philosophers often subject to challenges of varying subtlety; it is these philosophers who often place a peculiar emphasis on the personal name, and this emphasis depends on the historical influence of the Jewish metaphysical tradition of the Name of God. Providing a comprehensive description of historical aspects of Jewish Name-Theology, this book also offers new ways of thinking about subjectivity and ontology through its original approach to the nature of the name, combining philosophy with text-critical analysis. As such, it is an essential resource for students and scholars of Jewish Studies, Philosophy and Religion. (shrink)

이 연구에서 본인은 construal 이라는 상식적인 심리학적 개념에 대한 철학적 활용에 관하여 예시하고자 한다. Construal 이라는 것은 하나가 다른면에서 경험되어지는 심리적 상태이다. 가장 영향력 있는 철학적 활용으로는 이해관계에 근거한 construal로써 정서에 관한 Robert C. Roberts의 이론이여왔다. 하지만 본인은 이 개념은 아카라시아나 자기통찰 그리고 도교적 사고를 포함하는 몇 가지 다른 영역에서도 활용성을 가지고 있다고 주장하는 바이다. 전반적으로 이 연구가 이처럼 과소평가되는 개념에 대한 철학적 탐색이 더 이루어 질수 있는 자극이 되기를 바란다.

_This sweeping discussion of the philosophy of evolutionary biology is based on the revolutionary idea that species are not kinds of organisms but wholes composed of organisms._.

A coherent treatment of the flow of ideas throughout Darwin's works, this volume presents a unified theoretical system that explains Darwin's investigations, evaluating the literature from a historical, scientific, and philosophical perspective.

Table of Contents: Chapter 1: The Need for Philosophy of Nature Chapter 2: Analogy and the Search for Truth Chapter 3: Doing What Comes Naturally Chapter 4: Dawkins or Aristotle? Chapter 5: The Mystery of Motion Chapter 6: Is Time Real? Chapter 7: Place, Space and Science Fiction Chapter 8: What is a Human Being? Chapter 9: The Powers of the Human Person Chapter 10: Are Humans Really Free? Chapter 11: Human Action Chapter 12: The Place of Law in Human (...) Life Chapter 13: St. Thomas Aquinas and Catholic Social Teaching> Chapter 14: The Just Price Chapter 15: Charging for the Loan of Money Chapter 16: What Happens after Death? Chapter 17: Is That All There Is? Chapter 18: What Can We Say about Fido? Chapter 19: Important Nicknames Chapter 20: Causality and God Chapter 21: The Existence of God (1) Chapter 22: The Existence of God (2) Chapter 23: The unchanging God Chapter 24: "It's God's will!" Chapter 25: Creation. (shrink)

Philosophical conceptual analysis is an experimental method. Focusing on this helps to justify it from the skepticism of experimental philosophers who follow Weinberg, Nichols & Stich. To explore the experimental aspect of philosophical conceptual analysis, I consider a simpler instance of the same activity: everyday linguistic interpretation. I argue that this, too, is experimental in nature. And in both conceptual analysis and linguistic interpretation, the intuitions considered problematic by experimental philosophers are necessary but epistemically irrelevant. They are like variables introduced (...) into mathematical proofs which drop out before the solution. Or better, they are like the hypotheses that drive science, which do not themselves need to be true. In other words, it does not matter whether or not intuitions are accurate as descriptions of the natural kinds that undergird philosophical concepts; the aims of conceptual analysis can still be met. (shrink)

Michael T. Ferejohn presents a new analysis of Aristotle's theory of explanation and scientific knowledge, in the context of its Socratic roots. Ferejohn shows how Aristotle resolves the tension between his commitment to the formal-case model of explanation and his recognition of the role of efficient causes in explaining natural phenomena.

Traditionally, species have been treated as classes. In fact they may be considered individuals. The logical term “individual” has been confused with a biological synonym for “organism.” If species are individuals, then: 1) their names are proper, 2) there cannot be instances of them, 3) they do not have defining properties, 4) their constituent organisms are parts, not members. “ Species " may be defined as the most extensive units in the natural economy such that reproductive competition occurs among their (...) parts. Species are to evolutionary theory as firms are to economic theory: this analogy resolves many issues, such as the problems of “reality” and the ontological status of nomenclatorial types. (shrink)

Imagination is important for many things in science: solving problems, interpreting data, designing studies, etc. Philosophers of imagination typically account for the productive role played by imagination in science by focusing on how imagination is constrained, e.g., by using self-imposed rules to infer logically, or model events accurately. But the constraints offered by these philosophers either constrain too much, or not enough, and they can never account for uses of imagination that are needed to break today’s constraints in order to (...) make progress tomorrow. Thus, epistemology of imagination needs to make room for an element of epistemological anarchy. (shrink)

Classifying is a fundamental operation in the acquisition of knowledge. Taxonomic theory can help students of cognition, evolutionary psychology, ethology, anatomy, and sociobiology to avoid serious mistakes, both practical and theoretical. More positively, it helps in generating hypotheses useful to a wide range of disciplines. Composite wholes, such as species and societies, are “individuals” in the logical sense, and should not be treated as if they were classes. A group of analogous features is a natural kind, but a group of (...) homologous features is not. Imposing hypotheses justified only on the basis of nominalist, realist, phenomenalist, or conceptualist metaphysics upon the neurophysiology of organisms or upon the causes of behavior exemplifies the “psychologist's fallacy” of William James. Levels should be distinguished from their members and from classes of levels, and the ontological status of entities ranked at levels should be made clear. It is important not to confuse such categories as substance and process with one another. Several genetical terms, such as “gene” and chromosome,” are even more equivocal than has been realized. Discussions about units of selection, behavior, and thinking suffer from the ambiguity of a “unit of” an entity. An important source of misunderstanding about natural selection is the habit of treating it as an “agent”: in an important sense, natural selection does not “act” at all. (shrink)

Joshua Greene has argued that the empirical findings of cognitive science have implications for ethics. In particular, he has argued (1) that people’s deontological judgments in response to trolley problems are strongly influenced by at least one morally irrelevant factor, personal force, and are therefore at least somewhat unreliable, and (2) that we ought to trust our consequentialist judgments more than our deontological judgments when making decisions about unfamiliar moral problems. While many cognitive scientists have rejected Greene’s dual-process theory of (...) moral judgment on empirical grounds, philosophers have mostly taken issue with his normative assertions. For the most part, these two discussions have occurred separately. The current analysis aims to remedy this situation by philosophically analyzing the implications of moral dilemma research using the CNI model of moral decision-making – a formalized, mathematical model that decomposes three distinct aspects of moral-dilemma judgments. In particular, we show how research guided by the CNI model reveals significant conceptual, empirical, and theoretical problems with Greene’s dual-process theory, thereby questioning the foundations of his normative conclusions. (shrink)

Scientists imagine for epistemic reasons, and these imaginings can be better or worse. But what does it mean for an imagining to be epistemically better or worse? There are at least three metaepistemological frameworks that present different answers to this question: epistemological consequentialism, deontic epistemology, and virtue epistemology. This paper presents empirical evidence that scientists adopt each of these different epistemic frameworks with respect to imagination, but argues that the way they do this is best explained if scientists are fundamentally (...) epistemic consequentialists about imagination. (shrink)

John D. Norton is responsible for a number of influential views in contemporary philosophy of science. This paper will discuss two of them. The material theory of induction claims that inductive arguments are ultimately justified by their material features, not their formal features. Thus, while a deductive argument can be valid irrespective of the content of the propositions that make up the argument, an inductive argument about, say, apples, will be justified (or not) depending on facts about apples. The argument (...) view of thought experiments claims that thought experiments are arguments, and that they function epistemically however arguments do. These two views have generated a great deal of discussion, although there hasn’t been much written about their combination. I argue that despite some interesting harmonies, there is a serious tension between them. I consider several options for easing this tension, before suggesting a set of changes to the argument view that I take to be consistent with Norton’s fundamental philosophical commitments, and which retain what seems intuitively correct about the argument view. These changes require that we move away from a unitary epistemology of thought experiments and towards a more pluralist position. (shrink)

"Adaptation" has several meanings which have often been confused, including relations, processes, states, and intrinsic properties. It is used in comparative and historical contexts. "Adaptation" and "environment" may designate probabilistic concepts. Recognition of these points refutes arguments for the notions that: 1) all organisms are perfectly adapted; 2) organisms cannot be ill-adapted and survive or well-adapted and die; 3) adaptation is necessarily relative to the environment; 4) change in environment is necessary for evolution; 5) preadaptation implies teleology. Such notions are (...) associated with metaphysical ideas, and may affect the thinking of biologists. (shrink)

One way to interpret the work of Joshua Greene (2001; 2008; 2014) is that the wave of empirical research into moral decision-making is a way for us to become more confident in our ability to gain moral knowledge. We argue that empirical research into moral judgment has shown (both survey-based and brain-based) that the grounds of moral judgment are opaque on several dimensions. We argue that we cannot firmly grasp what the morally relevant/irrelevant features of a decision context are, understand (...) which cognitive system responds to said features, and further know that we are actually basing our judgment upon what we take to be the morally relevant features. That is, we argue that moral judgment is very much like other kinds of judgment: Deeply influenced by facts about the decision-context and the decision-maker. However, if moral judgment is merely the exercise of our general judgment making faculty, we shouldn’t be surprised by this result. We conclude by considering what this means for our practice of making moral judgments. (shrink)

The philosophical literatures on models and thought experiments have been developing exponentially, and independently, for decades. This independence is surprising, given how similar models and thought experiments are. They each have “lives of their own,” they sit between theory and experience, they are important for both pedagogy and cutting-edge science, they galvanize conceptual changes and paradigm shifts, and they involve entertaining imaginary scenarios and working out what happens. Recently, philosophers have begun to highlight these similarities. This entry aims at taking (...) the idea further, by trying to systematically identify places where insights from one literature can be taken up in the other. Along the way, important differences will also be highlighted. (shrink)

The corn wolf : writing apotropaic texts -- Animism and the philosophy of everyday life -- The stories things tell and why they tell them -- Humming -- Excelente zona social -- I'm so angry I made a sign -- Weeks in Palestine : my first visit -- A go slow manifesto -- Iconoclasm dictionary -- The obscene in everyday life -- Syllable and sound -- Don Miguel.

The structure of the brain and the nature of evolution suggest that, despite its uniqueness, language likely depends on brain systems that also subserve other functions. The declarative / procedural model claims that the mental lexicon of memorized word- specific knowledge depends on the largely temporal-lobe substrates of declarative memory, which underlies the storage and use of knowledge of facts and events. The mental grammar, which subserves the rule-governed combination of lexical items into complex representations, depends on a distinct neural (...) system. This system, which is composed of a network of specific frontal, basal - ganglia, parietal and cerebellar structures, underlies procedural memory, which supports the learning and execution of motor and cognitive skills, especially those involving sequences. The functions of the two brain systems, together with their anatomical, physiological and biochemical substrates, lead to specific claims and predictions regarding their roles in language. These predictions are compared with those of other neurocognitive models of language. Empirical evidence is presented from neuroimaging studies of normal language processing, and from developmental and adult- onset disorders. It is argued that this evidence supports the DP model. It is additionally proposed that “ language ” disorders, such as specific language impairment and non-fluent and fluent aphasia, may be profitably viewed as impairments primarily affecting one or the other brain system. Overall, the data suggest a new neurocognitive framework for the study of lexicon and grammar. (shrink)

This is a book review of Karim Bschir and Jamie Shaw (eds.); Interpreting Feyerabend: critical essays. Cambridge: Cambridge University Press, 2021, 290 pp, $99.99 HB.