A hitherto neglected form of explanation is explored, especially its role in population genetics. “Statistically abstractive explanation” (SA explanation) mandates the suppression of factors probabilistically relevant to an explanandum when these factors are extraneous to the theoretical project being pursued. When these factors are suppressed, the explanandum is rendered uncertain. But this uncertainty traces to the theoretically constrained character of SA explanation, not to any real indeterminacy. Random genetic drift is an artifact of such uncertainty, and it is (...) therefore wrong to reify it as a cause of evolution or as a process in its own right. *Received July 2009. †To contact the author, please write to: Department of Philosophy, University of Toronto, 170 St. George St., Toronto, ON M5R 2M8, Canada; e‐mail: [email protected]. (shrink)

Matthen (Philos Sci 76(4):464–487, 2009) argues that explanations of evolutionary change that appeal to natural selection are statistically abstractive explanations, explanations that ignore some possible explanatory partitions that in fact impact the outcome. This recognition highlights a difficulty with making selective analyses fully rigorous. Natural selection is not about the details of what happens to any particular organism, nor, by extension, to the details of what happens in any particular population. Since selective accounts focus on (...) tendencies, those factors that impact the actual outcomes but do not impact the tendencies must be excluded. So, in order to properly exclude the factors irrelevant to selection, the relevant factors must be identified, and physical processes, environments, and populations individuated on the basis of being relevantly similar for the purposes of selective accounts. Natural selection, on this view, becomes in part a measure of the robustness of particular kinds of outcomes given variations over some kinds of inputs. (shrink)

Several modern accounts of explanation acknowledge the importance of abstraction and idealization for our explanatory practice. However, once we allow a role for abstraction, questions remain. I ask whether the relation between explanations at different theoretical levels should be thought of wholly in terms of abstraction, and argue that changes of the quantities in terms of which we describe a system can lead to novel explanations that are not merely abstractions of some more detailed picture. I use the (...) example of phase transitions as described by statistical mechanics and thermodynamics to illustrate this, and to demonstrate some details of the relationship between abstraction, idealization, and novel explanation. (shrink)

We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealised explanation game in which players collaborate to find the best explanation for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to explore overlapping causal (...) patterns of variable granularity and scope. We characterise the conditions under which such a game is almost surely guaranteed to converge on a optimal explanation surface in polynomial time, and highlight obstacles that will tend to prevent the players from advancing beyond certain explanatory thresholds. The game serves a descriptive and a normative function, establishing a conceptual space in which to analyse and compare existing proposals, as well as design new and improved solutions. (shrink)

Scientific explanation is an important goal of scientific practise. Philosophers have proposed a striking diversity of seemingly incompatible accounts of explanation, from deductive-nomological to statistical relevance, unification, pragmatic, causal-mechanical, mechanistic, causal intervention, asymptotic, and model-based accounts. In this dissertation I apply two novel methods to reexamine our evidence about scientific explanation in practise and thereby address the fragmentation of philosophical accounts. I start by collecting a data set of 781 articles from one year of the journal Science. Using automated text (...) mining techniques I measure the frequency and distribution of several groups of philosophically interesting words, such as "explain", "cause", "evidence", "theory", "law", "mechanism", and "model". I show that "explain" words are much more common in scientific writing than in other genres, occurring in roughly half of all articles, and that their use is very often qualified or negated. These results about the use of words complement traditional conceptual analysis. Next I use random samples from the data set to develop a large number of small case studies across a wide range of scientific disciplines. I use a sample of "explain" sentences to develop and defend a new general philosophical account of scientific explanation, and then test my account against a larger set of randomly sampled sentences and abstracts. Five coarse categories can classify the explanans and explananda of my cases: data, entities, kinds, models, and theories. The pair of the categories of the explanans and explanandum indicates the "form" of an explanation. The explain-relation supports counterfactual reasoning about the dependence of qualities of the explanandum on qualities of the explanans. But for each form there is a different "core relation" between explanans and explanandum that supports the explain-relation. Causation, modelling, and argument are the core relations for different forms of scientific explanation between different categories of explanans and explananda. This flexibility allows me to resolve some of the fragmentation in the philosophical literature. I provide empirical evidence to show that my general philosophical account successfully describes a wide range of scientific practise across a large number of scientific disciplines. (shrink)

We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealisedexplanation gamein which players collaborate to find the best explanation(s) for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to explore overlapping causal patterns of (...) variable granularity and scope. We characterise the conditions under which such a game is almost surely guaranteed to converge on a (conditionally) optimal explanation surface in polynomial time, and highlight obstacles that will tend to prevent the players from advancing beyond certain explanatory thresholds. The game serves a descriptive and a normative function, establishing a conceptual space in which to analyse and compare existing proposals, as well as design new and improved solutions. (shrink)

We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealised explanation game in which players collaborate to find the best explanation for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to explore overlapping causal (...) patterns of variable granularity and scope. We characterise the conditions under which such a game is almost surely guaranteed to converge on a optimal explanation surface in polynomial time, and highlight obstacles that will tend to prevent the players from advancing beyond certain explanatory thresholds. The game serves a descriptive and a normative function, establishing a conceptual space in which to analyse and compare existing proposals, as well as design new and improved solutions. (shrink)

ABSTRACT. Probability and statistics play an important role in contemporary -philosophy of causality. They are viewed as glasses through which we can see or detect causal relations. However, they may sometimes act as blinding glasses, as I will argue in this paper. In the 19th century, Francis Galton tried to statistically analyze hereditary phenomena. Although he was a far better statistician than Gregor Mendel, his biological theory turned out to be less fruitful. This was no sheer accident. His knowledge (...) of statistics generated two explananda (unknown to Mendel) which in turn generated constraints for any theory of heredity. These constraints misguided Galtons search for the causal mechanism of inheritance. This is not just. an interesting case for philosophers and historians of ·science. Notwithstanding the progress made by statitics, Galtons problem is still relevant today. In the final section, I briefly explore the implications for statistical techniques such as structural equation modelling. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:NARRATIVE AND EXPLANATION: EXPLAINING ANNA KARENINA IN THE LIGHT OF ITS EPIGRAPH Marina Ludwigs University ofCalifornia, Irvine In this paper, I will be examining the relation of explanation to narrative, looking briefly at the theoretical side ofthe problematic and in more detail at specific explanatory issues that arise in Tolstoy's novel Anna Karenina. Although the use itselfofthe term "explanation" is not as visible in the humanities as it is (...) in the sciences, the explanatory enterprise by other names is just as prominent. For indeed, an animating impetus behind textual interpretation is an explanation ofhowatextcan be brought into a correspondence with another text, while contemporary critical-theoretical activities of demystifying aesthetic and cultural assumptions, contextualizing historical knowledge, or laying bare ideological presuppositions are, in one way or another, engagements in the explanation ofthe workings of language. I approach humanistic explanation via a brief detour of scientific explanation, which constitutes an already established discourse with a set of defined issues and standard arguments, limiting myself to touching upon issues relevant to the narrativization of explanation. In scientific debates, explanation is defined as an answer to the question of "why?," in contradistinction to the question of "what?," which prompts a description of a phenomenon in question. Descriptive and explanatory conceptual frameworks, however, are interdependent. A physical description involves an "in-depth" understanding of underlying regularities. An explanatory answer to a question is, in its turn, an argument that logically deduces the explanandum (the description ofa phenomenon to be explained) from the explanans (well-understood regularities). This Marina Ludwigs125 formal definition of an explanation necessitates a symmetry between explanation and prediction, because the reconstructed logical sequence can also be read in the other direction, demonstrating the inevitability of what has occurred. Thus the sight of shattered glass and a baseball lying about allows me to explain the accident by invoking the law ofthe conservation ofmomentum and the low shock-resistance ofglass. But the knowledge of these regularities would have also allowed me to predict the same outcome had I seen the baseball flying in its direction ofthe window. The ontological status of "regularities" has elicited a lively debate in the scientific community pertaining to the problem ofthe "real." The standard view of regularities defines them as general laws (the kind we learn about in physics classes) that could be deductive or inductive, deterministic or statistical. A general law may be subsumed under another, even more general law, thus forming a unifying hierarchy of laws. A rival conception appeals to causal mechanisms and defines regularities as established chains oftemporal succession. Both models, the covering-law and the causal one, have been criticized: the former—for its failure to distinguish a law from an accidental generalization; the latter—for its resurrection ofthe metaphysical notion ofcausal influence and its inability to deal with probabilistic events. One of the later contenders is Nancy Cartwright's model, that proposes to conceive of regularities as so-called "nomological machines"—"fixed (enough) arrangements] ofcomponents, or factors, with stable (enough) capacities that in the right sort of stable (enough) environment will, with repeated operation, give rise to the kind of regular behavior that we represent in our scientific laws" (Cartwright 50). Cartwright claims that scientific models work on the ceteris paribus (everything else being equal) basis. That is to say they "hold only in circumscribed conditions or so long as no factors relevant to the effect besides those specified occur" (Cartwright 28), such as inside a battery, refrigerator, or a rocket—insofar as special shielding conditions are in effect (as a counterexample, imagine usingNewton's laws ofmechanics for describing the motion of a dropped crumpled dollar). Cartwright's explanatory framework is thus pragmatic and local, avoiding the twin pitfalls of the metaphysical assumptions underlying the two older models—the totalizing and unifying idea of a covering law, on the one hand, and the influence of causal "force," on the other. What is instead emphasized by her is a procedural aspect of scientific knowledge that has been historically prevalent and reflects the practical exigencies of human existence—the experience of dangers and natural obstacles to human 126Explaining 'Anna Karenina ' desires. When ill-defined impediments are analyzed and reduced to concrete difficulties, specific... (shrink)

The goal of this dissertation is to show that cognitive science, while dealing with the special subject of the mind, can nonetheless fit into the same general model that Bas van Fraassen provides for the natural sciences. The dissertation focuses specifically on the nature of explanation in the cognitive sciences. ;Chapter One makes clear what I take cognitive science to be in the work. The two central cases here are Noam Chomsky's theory of generative syntax, and David Marr's computational theory (...) of vision. The bulk of this chapter is devoted to setting out the structure of the two theories, in order to provide concrete case studies in the sorts of explanations they give. ;Chapter Two sets out the model of explanation employed by considering the relative virtues of several recent approaches--Hempel's classic D-N model, Salmon's statistical relevance model, and Stalnaker and Lewis' counterfactual approach--and concluding with van Fraassen's pragmatics-oriented model. Like many accounts, van Fraassen's takes explanations to be answers to "Why?" questions, and emphasizes the pragmatic machinery at work in question-asking. ;Chapter Three considers two influential views of explanation in cognitive science. Such explanations are often said to be functional or dispositional. I look at proposals of each sort and argue that none of the explanatory strategies singled out can count as the central one in cognitive scientific explanation, because cognitive science has no central explanatory strategy. ;In Chapter Four I hold instead that cognitive science uses all the relevance relations found in natural science. The odd features of cognitive scientific explanation turn instead around the sorts of objects and processes that get posited in its theories--abstract, multiply-instantiable objects that can act as representations, and abstract processes of transformation on these objects. I do not, then, deny that we get new sorts of explanation in cognitive science--only that the source of this novelty has been properly located. (shrink)

In this paper, a criticism of the traditional theories of approximation and idealization is given as a summary of previous works. After identifying the real purpose and measure of idealization in the practice of science, it is argued that the best way to characterize idealization is not to formulate a logical model – something analogous to Hempel's D-N model for explanation – but to study its different guises in the praxis of science. A case study of it is then made (...) in thermostatistical physics. After a brief sketch of the theories for phase transitions and critical phenomena, I examine the various idealizations that go into the making of models at three difference levels. The intended result is to induce a deeper appreciation of the complexity and fruitfulness of idealization in the praxis of model-building, not to give an abstract theory of it. (shrink)

This article focuses on a case that expert practitioners count as an explanation: a mathematical account of Plateau’s laws for soap films. I argue that this example falls into a class of explanations that I call abstract explanations.explanations involve an appeal to a more abstract entity than the state of affairs being explained. I show that the abstract entity need not be causally relevant to the explanandum for its features to be explanatorily relevant. However, it remains unclear (...) how to unify abstract and causal explanations as instances of a single sort of thing. I conclude by examining the implications of the claim that explanations require objective dependence relations. If this claim is accepted, then there are several kinds of objective dependence relations. 1 Introduction2 A Case3 Abstract and Causal Explanations4 Recent Work on Mathematical Explanation5 Explanation and Dependence6 Conclusion. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:ChatGPT:a psychomachiaChristopher Norris (bio)The human mind is not, like ChatGPT and its ilk, a lumbering statistical engine for pattern matching, gorging on hundreds of terabytes of data and extrapolating the most likely conversational response or most probable answer to a scientific question. On the contrary, the human mind is a surprisingly efficient and even elegant system that operates with small amounts of information; it seeks not to infer brute (...) correlations among data points but to create explanations.—Satya P. MohantyIt remains to be seen whether AI poems will eventually go beyond intended or unintended parody and trigger emotional responses in human readers that run deeper than wry amusement.... Current AI poets are in essence mining the metaphors that humans have already formed and planted in texts–in the view of Robert Frost, 'The richest accumulation of the ages is the noble metaphors we have rolled up." Could AI create genuinely novel metaphors, rather than only variations of those we humans have come up with already?—Keith HolyoakeNoteThis poem started out as a debate in clearly-marked dialogue form (alternating roman and italic print) between an advocate of ChatGPT who thinks that 'strong' AI is, or will soon be, capable of writing 'authentic' poetry, and a poet who resists that claim on various grounds, personal and philosophical. The opening, strict-form sonnet proposes that the issue be tested by running it (the poem itself) past the software and seeing what results as the sonnet-sequence unfolds from that speculative source-point. As it goes along, the sonnet-forms multiply, the contending viewpoints seem to merge or even change sides, the roman-italic alternation breaks down, and the project (theirs or mine?) loses its intended clarity of theme and treatment. I include the poem here as a kind of performative commentary on the way that thematic concerns or intentions may get lost once the AI software really starts doing its wondrous, intriguing, or humanly ominous thing.One way to test this thing, ChatGPT:Let's run a really strict-form poem on it,Like a Petrarchan or Shakespearean sonnet,Then input 'do thou likewise,' just to seeWhat comes out. Does the poem rhyme and scan [End Page 77] Correctly yet, as claimed, hit off the styleConvincingly, and thereby close the fileOn what's unique about the species 'man'?If so, you'll find it difficult to tellWhat's what with this example of the kind,Along with other cases you may findWorth putting to the online test as well.And don't get spooked if, like myself, you're proneTo think you're someone (something?) else's clone.You crease me up, you poets, with your fearsThat some new bit of software (albeit oneOf quite superior powers) might have outdoneYou in those self-apportioned special spheresOf excellence where you and some few peers,Each special, each unique, affect to shunAll thought that your fine poems may just runOn lines devised by AI gadgeteers.A nice idea, last refuge of the weakIn mind but good in heart, the valiant fewTo whose deluded faith it falls to holdOut still for what you fantasists may seekYet scarcely hope to find: new ways to doThe genius thing, transmute base stuff to gold!Read slowly, sensitively; don't permitYourself, dear reader, nobbled as no doubtYou've been by those who have the techno-clout,To take that stuff on board and let a bitOf pseudo-Keats, spoof Yeats, identikit'Stuffed-owl'-grade Wordsworth, or what else they toutAs the real deal demand you read withoutDiscerning what no moving finger's writ.Just hearken, let your quickened sense respondTo all that yet eludes the furthest reachOf AI artefacts. They had you connedAt first, though soon you missed the living speechUn-missed by those who cannot hear beyondWhat any tin-eared programmer could teach.Let's bring the reader in on this, I say.We've need of them, we disputants with much [End Page 78] At stake in different ways, they there to payOur... (shrink)

Abstract:The haptic sense is an essential component of aesthetic evaluation that is often overlooked in today’s mobile internet age. Unlike hearing and vision, the sense of touch is less widely transmitted. Unfortunately, most aesthetic theories and explanations have focused solely on the visual and auditory senses, with minimal attention given to tactile evaluation. To address this gap in knowledge, we have collected studies on tactile aesthetics within the framework of experimental aesthetics from 2000 to 2022. After statistical generalization, our (...) findings suggest the following: The criteria for evaluating tactile aesthetics were mostly dichotomous, that is, positive (like/appreciation/pleasure) and negative (dislike/disgust/unpleasant). Tactile aesthetics predominantly involved the toucher dimension (synesthesia/need for touch/touch pattern) and the touch sample dimension (shape/type/texture), with the commonly overlooked factors of “need for touch” and “touch pattern.” Some studies did not restrict the shape and material of the touch samples. Based on our findings, we have systematically summarized and concluded what tactile factors influence aesthetic evaluation and have analyzed future research trends. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Spiritually Bilingual:Buddhist Christians and the Process of Dual Religious BelongingJonathan HomrighausenSociologists studying convert Buddhism in America have found that a surprisingly large number of Buddhists also identify as Christian.1 However, little empirical literature examines these Buddhist-Christian “dual religious belongers.”2 This study aims to fill that gap. Based on extensive interviews with eight self-identified “Buddhist Christians” of varying levels of doctrinal and experiential understanding, this study examines the conversion process (...) of these dual belongers and how they combine these religious traditions. Building on Michael von Brück’s contention that one’s first religion is like a mother tongue, I compare taking on a second religious tradition to learning a second language.3 As practitioners become more “fluent” in the second religion, they differentiate the two religions more clearly while combining them more seamlessly in their daily lives.methodologyThis study employs grounded theory and a qualitative, inductive methodology. Grounded theory is designed to elucidate the dynamic changes involved in a social process, with rich descriptions of categories and explanations for variations between different people’s experiences.4 While the use of qualitative methods with a small sample size means that my results have little statistical significance, such methods have been used in recent research on conversion and dual belonging and yield deep theoretical insight.5Eight participants for this study were solicited via word of mouth, personal acquaintance, and posting in a Buddhist-Christian Yahoo Group. In particular, I focused on Buddhist-Catholic practitioners to limit my sample group. Interviews were conducted and recorded in person or on the phone over a three-month period in fall, 2011. Interviews were open-ended, each lasting from sixty to ninety minutes. Several participants later received a draft of the paper to ensure they felt adequately represented; five participants responded. Names of participants have been changed for [End Page 57] confidentiality. To complement these interviews, I also incorporate written accounts of Buddhist-Christian conversion from both Catholic and Protestant authors.6participants’ backgroundsIt can be difficult to define Buddhist identity in the West, as many people who regularly practice meditation in a sangha do not self-identify as Buddhist.7 This study focuses on those who both practice Buddhist and Christian spirituality and belong to religious groups of both traditions. The eight participants have a range of religious expertise and commitment to both traditions. In terms of Catholic identity, six are laypeople (one in a secular religious order), one a priest, and one a nun. Three participants are theology professors. Seven have been Catholics from birth. One spent a decade living in a Buddhist monastery, two of them are roshis, and five give Buddhist teaching or meditation instruction formally. Seven of them practice various forms of Ch’an or Zen, while one practices Tibetan Buddhism.Cathy went not from Catholicism to Buddhism, but from Buddhism to Catholicism. A former Mormon and Unitarian, she began learning meditation at a Ch’an temple. This Ch’an temple normally only reached out to the Chinese community, but there was a Taiwanese nun there who wanted to reach out to non-Chinese community members. After practicing there for a few years, Cathy moved to another location, where she could not find any sangha that fit her needs. After attending Mass with a friend, she decided to become Catholic because she needed a community. It was not a hard transition for Cathy, who described feeling in meditation “some kind of entity, whether you call it God or Creator or atomic process.” She was confirmed as a Catholic in 2011.Rachel has been a nun for fifty years and a practicing Zen Buddhist for thirty, ten of those years living and working in a Zen monastery in the mountains of California. She described feeling an emptiness in her faith, a lack of practical knowledge of how to attain the spiritual goals that her Catholic tradition had for her. After hearing Zen teacher Cheri Huber speak at a conference, she took Huber on as her teacher. She has facilitated meditation workshops for many years. Though meditation instruction is not her full-time ministry, “meditation is my life … so in a sense... (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Journal of the History of Ideas 61.4 (2000) 539-560 [Access article in PDF] Plenitude, Possibility, and the Limits of Reason: A Medieval Arabic Debate on the Metaphysics of Nature Taneli Kukkonen In a recent article Simo Knuuttila has examined the argumentative patterns of modern cosmology, especially the search in fundamental physics for an "ultimate explanation," a unified "Theory of Everything" that would subsume all more local theories under its (...) aegis. Knuuttila goes on to compare contemporary modes of explanation with previous ways of conceiving of the metaphysics of understanding. As it turns out, on the cosmological borderline where physics shades into metaphysics desires similar at heart have fueled the efforts of thinkers throughout the history of western thought. When what is at stake is the final intelligibility of the world, shared ideals of necessity, transparency, and simplicity come to the fore. More often than not, theological concerns and preconceptions accompany these notions. 1One can react to this finding in one of two ways, either by retorting that the moderns have not gotten very far or by pointing out that earlier discussions on the topic were often quite philosophically sophisticated. In this article I propose to investigate how some of the issues raised by Knuuttila figure in a specific historical context. This is the debate on the pre-eternity of the world initiated by the celebrated Muslim theologian Abû Hâmid al-Ghazâlî (1058-1111) in his polemic arguing for The Incoherence of the Philosophers (Tahâfut al-falâsifa, 1095) and later picked up by the Andalusian philosopher Averroës (1126-98) in [End Page 539] his reply, The Incoherence of the Incoherence (Tahâfut al-tahâfut, 1180). 2 The exceptionally rich cosmological materials could be taken in any number of directions, but I will focus on three main issues: the discussants' construction of the domain of possibilities (i.e. the relation of the possible to the actual), their understanding of the reasonability of creation, and the question of its finitude and infinity. The study is undertaken partly to illustrate the sophistication with which the topics were handled in medieval Islamic philosophy, but in each case I will also draw parallels with certain modern conceptions, and I submit that in each case al-Ghazâlî's and Averroës's debate throws light on the contemporary discussion. In the final section I will develop this contention further by pointing to a connection between finitude and possibilities which I believe has both heuristic and existential value. Plenitude and Possibility Among historians of philosophy it is now acknowledged that in late medieval discussions certain modal theoretical innovations were instrumental in bringing about profound change in the western worldview. A conceptual shift occurred where, roughly speaking, a single intelligible universe was exchanged for several possible worlds. In Knuuttila's estimation this change in worldviews was in some ways more fundamental than anything modern science has produced since. 3 This claim deserves consideration but I would like first to outline what the change was about, for in al-Ghazâlî's and Averroës's debate this shift in modal paradigms is clearly discernible.Representative of the philosophers' point of view, Averroës holds onto the received Arabic Aristotelian interpretation of setting possibilities in a statistical temporal-frequency framework. According to this account, what is truly possible must at some time be realized--this is a technical interpretation of what has after Lovejoy commonly become known as the principle of plenitude. 4 As a [End Page 540] corollary, what always is is necessarily. The cosmological consequences of these assumptions can be outlined as follows. First, lest God's creative possibilities be limited, it must be admitted that the world could have been created however long ago in the past. By extension God must have been able to create the world an infinite time ago. But if it is a genuine possibility that the world is eternally old, then according to the principle of plenitude, this possibility is an actual fact. Once it is... (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Cause, Fault, NormJohn Z. Sadler (bio)Keywordscriminality, mental disorder, responsibilityThanks to the commentators for their fine work. In my brief comments I cannot address all that is raised, but can touch upon everyone’s discussion briefly.In her commentary, Gwen Adshead reflects on her experience as a forensic psychiatrist and therapist for violent offenders. Although Adshead discusses a number of important points, I found her insight into why some vices find their (...) way into psychiatric classification particularly compelling and thought provoking. I will here interpret these in my own terms. Dr. Adshead implies that a (perhaps) assumed folk psychology underlies our motivation to classify (as disorder) some, but not all vices. The contribution of this folk psychology does not depend on particular details, but rather, the folk psychology concerns the degree to which the vice–actor’s actions are amenable to explanation, or are transparently understandable or interpretable. We (think we) understand why prostitutes sell themselves and why tax evaders cheat; their folk psychologies are variously constituted by moralistic constructs like desperation, oppression, licentiousness, greed, opportunism, and indignation. In contrast, some offenses step outside our empathic realm: the pedophile, or the serial killer, or even the persistently acting-out child provoke onlookers to wonder, “There has to be something wrong with a person who does that!” “Loud” symptoms in themselves do not qualify; seemingly incomprehensible loud symptoms fit better into the “sick” category. Indeed, in a recent translation of Foucault’s lectures at the College de France, Foucault describes the “monster” as combining “the impossible and the forbidden.” (Foucault 1999, 56) When confronted with the impossible and forbidden, the lust for classification is irresistible.Adshead’s wonderment about the use of “really” to question the explanation of wrongful conduct (what’s “really” going on) leads naturally to Michael First’s discussion. The Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV really tries to make a firm distinction between vice and mental disorder, and First describes the DSM approach.Drawing on his experience as the DSM-IV Text Editor, Dr. First provides a particularly lucid presentation of the distinction between what I call “vice” and mental disorder. He supplies vivid examples to illustrate his points. The DSM key for distinguishing disorder from vice is whether “the deviance or conflict is a symptom of a dysfunction in the individual.” As other commentators point out later, First notes that the “vice action” (a term coined by Morse in his own commentary following) may disguise a number of possible explanations: the car thief may simply be seeking thrills and profit, or may be motivated by a delusion—leading to alternative explanations for the behavior. Sometimes the explanation for vice actions are transparent—as in the red Mustang example, but other times they are not so clear. The DSM approach requires the clinician to [End Page 51] make an explanatory claim in order to distinguish the appearance of vice versus the appearance of disorder. I think everyone would agree that an explanation of the phenomenon is required in distinguishing vice from disorder, so that much can be accepted.In my view, the problems with the DSM account are three: (1) The requirement for an internal psychological dysfunction is an easy claim to make for virtually any vice condition. The prostitute’s vice may be attributable to childhood trauma, deviant social learning, pathological desire to sexually control others, and so on. The tax evader may in turn have a pathological resentment of authority combined with a desperate financial situation and a pathological denial and avoidance of paying taxes. Every misbehavior has its psychology, and if we proclaim this psychology is abnormal or deviant, then we have an “internal dysfunction.” Indeed, it is easy to proclaim a psychology as abnormal if it is less than an ideal response to circumstances, or even an adequate response to circumstances; after all, not everyone who is exposed to sexual trauma becomes a prostitute nor does every financially desperate individual cheat on taxes. The DSM’s overinclusiveness on this account defaults to an arbitrariness about what counts as a legitimate (or not) internal dysfunction. Here there will be great argument.(2) First (and later, Wells) admits there... (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Reviewed by:Logics of Failed Revolt: French Theory After May ‘68Ronald ShustermanLogics of Failed Revolt: French Theory After May ‘68, by Peter Starr; xi & 232 pp. Stanford: Stanford University Press, 1995, $45.00 cloth, $14.95 paper.Failed revolt? For many people, current French theory is more a revolt of failed logic. Anyone yearning for a definitive refutation of these threatening foreign trends will get no satisfaction from Peter Starr’s volume. His (...) concept of the “logics of failed revolts” involves the obsession of revolutionaries with what they see as the inevitable return of the past. Starr proposes to examine the explanations given for the failure of revolutionary action “in representative texts by Jacques Lacan, Roland Barthes, Julia Kristeva, Hélène Cixous, Jacques Derrida, and others” (p. 2). The “revolution” in question is the May 1968 uprising.George Orwell, as a defender of proper usage and an explorer of politics and the English language, always insisted that the title of his Nineteen Eighty-Four be written out in full; the informality of the abbreviation “May ‘68” is emblematic of the spirit of the events of that year: May ‘68 was supposed to be a liberation from useless tradition and constraint. That the movement was seen as a failure is the first premise of Starr’s argument; what he proposes to analyze is the theorization of the failure. Starr sees three “scenarios”: “the logic of specular doubling” is where “revolutionary action is doomed to repetition because revolutionaries inevitably construct themselves as mirror images of their rivals” (p. 2). There is also a “logic of structural repetition” and a “logic of recuperation” in which revolutionary actions actually reinforce established structures of power (pp. 2–3). Starr goes on to argue that “these logics served as argumentative pretexts, allowing Barthes, Kristeva, Cixous, and others to construct the existing political field as an impasse in order to justify significant displacements of political energies (including a politicization of the literary text)” (p. 7). This seems like a fancy way of saying that these thinkers used theory to find a decent way out of direct political commitment. Indeed, once one has understood and granted the point, there really is not much else in Starr’s book but fancy ways of repeating it.Starr tries to delineate a specific “theoretical moment” (p. 4) beginning in 1965 and ending in 1977, but it is difficult to be so definitive about the limits of a period when one is writing only twenty years later. This lack of temporal distance leads to certain debatable assertions. For example, Starr claims that tier-mondisme—France’s obsession with models taken from the Third World—“never recovered” from certain fatal “blows” (p. 4). Yet there is no actual evidence given for this claim. The problem with this kind of history is that it either makes concrete statements which are easy to contest, or it ends up vacuous: Starr sees in his period “a play of continuity and discontinuity” (p. 7). Who could deny such an assertion? All periods involve both continuity and discontinuity (except perhaps the period of the sinking of Atlantis...). Starr [End Page 191] mentions works on specific French thinkers by other theorists (such as Culler) and points out that his “aim has been to bridge the gap between such studies on the one hand and the work of historians and sociologists on the other” (pp. 10–11). The question is whether such an interdisciplinary project is feasible or even desirable. The theorists do not really care about the genealogy of the theory; the historians do not need to know if the theory is right. To take one example, Starr gives us statistics of the evolution of university enrollment in France (p. 113) a few pages after discussing Lacan’s “phallic comedy” (p. 104). How many readers are going to be equipped for, or interested in, a study which combines sociological statistics, political theory, general history, psychoanalytic principles, and feminist criticism?I was convinced by Starr’s basic argument that French thinkers were obsessed by this vision of the inevitable failure of revolt. Nevertheless, the point is both belabored and often tenuous. There are times when Starr’s... (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Anthropological Perspectives in Psychiatric NosologyJuan J. López-Ibor Jr. (bio) and María-Inés López-Ibor (bio)KeywordsDSM, etiology, Aristotelian causes, social dramasPsychiatry and clinical psychology, as we learn in this paper, are disciplines in need of an ontological perspective. Very few branches of contemporary learning share this characteristic. Probably only theoretical physic and theology—as the rest have long ago given up trying to define and understand the essence of their object, for example, (...) life in the case of biology or mind in psychology. Consequently, the paper by Pérez-Álvarez, Sass and García-Montes, “The Ontology of Mental Disorders in Constructivist Perspective,” (2008) should be welcomed and indeed included in the reading lists for trainees in psychiatry and clinical psychology.The authors propose an approach to the understanding of mental disorders that is extremely attractive and well articulated, and which also has practical implications for clinicians. It is not just another “philosophical divertimento” devoid of scientific and practical importance. Let us analyze the article in an orderly way.Less DsmThe authors of the target paper disapprove of the Diagnostic and Statistical Manual of Mental Disorders (DSM)-III/IV approach to defining illnesses by starting from the symptoms that are present—on the grounds that this may lead clinicians to assume that their sole role is to identify, fight, and suppress the symptoms by whichever procedure. They propose an alternative that is dear to myself because it follows the path of the so-called “anthropological” psychiatry of Binswanger, von Gebsattel, Erwin Strauss, Zutt, López-Ibor, Sr., and others. In essence, this is a phenomenological approach to the meaning of mental diseases, one that emphasizes how the illness is revealed to the patient him- or herself.The target article’s criticism of DSM should be considered in the context of the abuses committed on its behalf. The DSM is not a textbook of psychiatric disorders, nor does it contain a definition of the diseases. The DSM does not tell what a disease is (Klerman et al. 1984)—something that is impossible with a classification system based on the manifestations of the diseases, the signs and symptoms. The DSM, as its title states, is just a diagnostic and statistical manual, which does not contain anything about the origin of [End Page 259] any disease nor an explanation of why it exists or what it means. The DSM is, in fact, just a tool to determine whether a disease is present, and therefore to facilitate communication between professionals and with other individuals, without saying anything about the disease’s aitia—a key term (associated with notions of essence as well as cause) to be discussed below. In theory, most clinicians should understand these limitations; it may be, however, that this is not really the case for many who read or use the DSM. In the world there are around 200,000 psychiatrists; since 1980 the number of DSM copies sold is in the order of several hundred thousand.The misuse of a classification system is even more noticeable in the International Classification of Diseases (ICD)-10 Research Version. The instructions for the use of this version recommend that the first step is to make an inventory of all the symptoms present, and then to construct a diagnosis based on them. This how all computer-assisted systems work. This procedure can, however, only be valid if the clinician has already reached a diagnostic conclusion by other means—a diagnosis then to be confirmed for research purposes. It may be that this is one of the reasons why the ICD-10 Research Version has almost never actually been used for research.Furthermore, the concept of symptoms in psychiatry applies only to organic mental disorders (Schneider 1959), conditions in which the patient’s attitude and way of experiencing the symptoms do not play the kind of role that they play in schizophrenia and other mental disorders. The quotation from the important paper by Sass and Parnas in this context is most appropriate. It is indeed that case that “subjective experience can play an important causal role in the progressive experiential transformations of a developing schizophrenic illness... (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Ontological and Other AssumptionsLloyd A. Wells (bio) and Sandra J. Rackley (bio)Fahrenberg and Cheetham have conducted an immensely thought-provoking study of the assumptions about human nature made by 800 students and pose a question about the future impact of these assumptions on individuals’ practice in professions including medicine and psychotherapy.This work represents a branch of “philosophical anthropology,” which considers assumptions people make about human nature. The authors used a (...) questionnaire, much of which was newly designed, to assess the assumptions made by university students studying psychology, philosophy, sciences, and other disciplines. Most of the respondents were studying at Freiburg, but some were sampled at several other universities in both the former East and West Germanies. Questions involved consciousness and the brain, evolution, free will, belief in God, the meaning of life, and theodicy.Given the importance of these beliefs and assumptions in so many peoples’ lives, it is quite surprising that there are so few modern data available, and this study ventures an important first step in assessing these assumptions. However, there are many problems inherent in this study (and any like it).The first, for us, is the validity of the questionnaire itself, an issue that was not specifically addressed in the paper. Face validity is a problem even in the few questions quoted directly in the paper. For example, some statements contain two clauses, and one could well agree with one without agreeing with another: “I do not know whether a God exists and I do not believe it is possible to know.” This is the most relevant answer for a true agnostic, but the assumption that “I do not know whether a God exists” does not necessarily link at all with “I do not believe it is possible to know.” Similarly, a theist might have trouble with the two clauses, “I know God really exists” and “I do not doubt this.” (Technically, knowledge does imply a lack of doubt, but belief certainly does not.) Particularly in the trilemmas, where various patterns of response were analyzed, these multiple-clause statements may have led students to respond in a manner inconsistent with their true beliefs and assumptions. Furthermore, many of the questions contain terms that may have been unfamiliar to first-year university students. The authors explain their rationale in not defining terms, but the lack of clarity about definitions may have led some of the students to not fully understand the questions asked and to perhaps influence the answers they chose.Misunderstanding of the questions may account for some of the disparities reported in the results. Other apparent inconsistencies, however, do not seem to be a result of unclear questions. For example, sixty percent of the students agreed with the statement that “I believe in … existence after death,” whereas forty-seven percent agreed with the statement that “when my brain is dead my consciousness and my person cease to be.” These [End Page 203] findings do not add up, and this study has several similar sets of data. People contradict themselves in long and complex questionnaires, and this may be a simple explanation for these findings, but is this the only explanation? How seriously did the students take the questionnaire, often given as part of their class? How honest were their responses?How generalizable are the findings of this study? It is very difficult even to speculate about this. The statistics are incomprehensible in light of the data given, and one must essentially take them on faith, wherever one falls on the God/theodicy questions. The design has many flaws, but we do learn how a subsample of German university students rate important factors about the meaning of life. Statements are made in the paper that the students’ results correlate with similar results for the general population, but this assertion seems to be based on a very few questions. One would like much more delineation of this apparent correlation, because we wonder about the juxtaposition of developmental factors with the answers the students gave to this questionnaire. First-year university students are at a critical developmental point, and it would be fascinating to follow this large cohort of students over time to see whether... (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Vice and ViciousnessGwen Adshead (bio)Keywordspsychiatric diagnosis, antisocial behaviorI am Grateful to Professor Sadler for such a clear and helpful account of how human misconduct (or vice) has been confounded diagnostically with human disease (as defined by the Diagnostic and Statistical Manual of Mental Disorders [DSM] classificatory system); and even more grateful for the chance to offer comment. Professor Sadler’s paper raises questions about the DSM enterprise as a whole; (...) and this is a field in which I have no particular experience to offer for additional discussion. But his other main point is that psychiatrists are constantly invited to distinguish between vice and disease, and he gives three examples, one of which is a clinical case from my own research. I entirely agree with him that this is a good example, and in this commentary, I will explain why.The argument is about how to distinguish between human behaviors that reflect chosen deviance from prosocial norms and behaviors that reflect a diseased state of mind. Arguments are both legal and political: Aristotle, in the Nichomachean Ethics sets out conditions in which a man should not be blamed for his behaviors, and to some extent these conditions still hold good in the criminal court; ignorance of the meaning of one’s actions, or being forced to act under duress, are good legal defenses. Politically, as Professor Sadler makes clear, the arguments were set out first by Foucault and then Szasz; it is possible for the state to use medical discourse to turn what might be a legitimate social grievance into individual pathology—the ultimate ad hominem argument.These arguments have not gone away, despite the best efforts of a materialist wing of neuropsychiatry, aided and abetted by pharmaceutical companies, who have a great interest in reductionist arguments in the biosciences. This is particularly so in relation to antisocial behaviors, especially crime. I want to focus on one particular type of antisocial behaviors, namely, the wish to hurt another person. I focus on this because it is my clinical bread and butter: My work as a forensic psychiatrist and psychotherapist requires me to try and understand how and why people want to hurt others. But I think it also makes sense to focus on this because it is the most problematic wish socially and demands understanding. All three of Professor Sadler’s examples involve hurt and harm to others, and it is noteworthy that neuroreductionist or medicalized explanations are rarely sought for theft or tax evasion. This must be in part because socially we think it is normal to try and profit yourself, even illegally, if you can get away with it. (I actually think that such behavior is not all that normal, but that is an argument for another day).Let us take the clinical example from my own work, cited by Professor Sadler. It is an example of what is called in the DSM “Factitious Disorder by Proxy” (FDP), although it also has an unhelpful eponym of “Munchausen’s Syndrome by Proxy.” As a practicing forensic psychiatrist, it is one of the best examples I know of what has been crudely dichotomized as a “mad or bad?” debate. A [End Page 23] mother quite deliberately makes her child ill, and then presents the child to medical services as in need of hospital treatment. In the case I described with Dr. Bluglass, the mother smothered her baby girl and then presented her as having “breathing difficulties” (which was, of course, quite true in one sense). There are two examples of vice here: deliberately hurting your child and lying to others about it; the lies also have the indirect result of potentially causing more harm to the baby. Harming your child, and then lying about it, in a not-for-profit way, are criteria for FDP.Quite how these actions ever made it into the DSM is puzzling, when they are quite straightforwardly antisocial. If a man in the street were to smother another man to the point of asphyxia, and then lie about it, we might well ask many questions about why he had done it, but we would not say that no offence had occurred. We... (shrink)

In lieu of an abstract, here is a brief excerpt of the content:A Third Way: Social Disability and Person-Centered AssessmentChristopher Heginbotham (bio)Keywordsimpaired functioning, psychopathic, personality disorder, neurological damage, psychotherapyJohn Sadler’s Fascinating Paper identifies a significant problem with existing diagnostic classifications. But in doing so he raises further unresolved philosophical, nosological, and practical problems. Although he is undoubtedly right in showing that the Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV (and International Classification of Diseases [ICD]-10) do not provide an adequate (...) categorization, he is I believe wrong to use the term “vice” to describe the cluster of wrongful acts.“Vice” conjures up images of Miami, drugbusting police, prostitution, and other activities that are characterized by one thing—by and large, these are actions undertaken knowingly, usually for financial gain. These are not the actions of people with impaired mental functioning as a result of mental disorder or neurological damage. It is of course true that human trafficking and enforced prostitution may mean women forced into prostitution against their will, but rarely are these women considered mentally disordered solely as a result of their prostitution. Yet it is capacitated, premeditated wrongdoing that is normally considered to be “vice.”By contrast, all the cases cited in the paper describe conditions that are almost certainly the result of some form of impaired functioning, either owing to early childhood experiences (Case A), familial culture and conditioning (Case B), or neurological damage (Case C). The common thread in these cases is impaired capacity—in Case A this could be described as due to psychopathic or personality disorder (I distinguish the two separately rather than describe the phenomenon as “psychopathic personality disorder”) as a result of multiple childhood traumas. Their presentation is not unexpected given the person’s history and, although the condition may have become refractory, it might be amenable to treatment with psychoanalytically oriented psychotherapy, given sufficient time and a nurturing environment (Bateman and Fonagy 2006, 2008; Cordess and Cox 1996; Levy 2008).The description of Case B leaves a lot of room for doubt and uncertainties. Did Ms A really try to smother her child? She confessed to one occasion, but was this under duress? Did she feel that if she agreed she would be treated more leniently? And if she was guilty, does it suggest “vice,” a premeditated act, or is there another explanation—attention [End Page 31] seeking because of low self-esteem or a personality disorder as a result of some abuse that had not been identified? Almost certainly from the description given this would not count, for me at any rate, as vice. Her actions may be odd, bizarre, or dangerous, but did they demonstrate a mens rea? Was Ms A making adequate evaluative judgments of her situation and that of her child? We know from clinical work with very damaged women in forensic mental health services that early physical, emotional, or sexual abuse leads in turn to women harming both themselves and their children (Bland et al. 1999; Cordess and Cox 1996; see also for example, Jeffcote and Watson 2004). Or perhaps, speculatively, her condition was Munchausen’s by proxy?Case C is horrendous but does not lend itself readily to the forms of psychiatric classification available. Indeed there is no easy way to describe such actions other than those of someone who is either incapable of understanding the nature and consequence of the actions that he has undertaken, or is simply “mad” in a folk sense. Prima facie this seems to be the result of permanent and little understood neurological damage. However, this case comes closest to the evil that is implied in the term “vice”; and might be diagnosed similarly to a celebrated English murderer, that of Peter Sutcliffe, the so-called Yorkshire Ripper. Sutcliffe was diagnosed as suffering from paranoid schizophrenia, although the jury at his trial found that he was fit to plead, and he was initially sent to prison, where he deteriorated. He is now, and has for some time, been in Broadmoor high secure hospital.The result of these comments is that I agree fully with John Sadler’s conclusions, but for rather different reasons. DSM-IV categories try and fail to offer a symptomatology for... (shrink)

The phenomenon of regression toward the mean is notoriously liable to be overlooked or misunderstood; regression fallacies are easy to commit. But even when regression phenomena are duly recognized, it remains perplexing how they can feature in explanations. This article develops a philosophical account of regression explanations as “statistically autonomous” explanations that cannot be deepened by adducing details about causal histories, even if the explananda as such are embedded in the causal structure of the world. That (...) regression explanations have statistical autonomy was first suggested by Ian Hacking and has recently been defended and elaborated by André Ariew, Yasha Rohwer, and Collin Rice. However, I will argue that these analyses fail to capture what regression’s statistical autonomy consists in and how it sets regression explanations apart from other kinds of explanation. The alternative account I develop also shows what is amiss with a recent denial of regression’s statistical autonomy. Marc Lange has argued that facts that can be explained as regression phenomena can in principle also be explained by citing a conjunction of causal histories. The account of regression explanation developed here shows that his argument is based on a misunderstanding of the nature of statistical autonomy. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Clinicians’ “Folk” Taxonomies and the DSM: Pick Your PoisonG. Scott Waterman (bio)Keywordsnosology, classification, diagnosis, psychopathologyWith attention turning to the process of formulating the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-V; e.g., Kendler et al. 2008), the study by Flanagan and Blashfield (2007) of the similarities and differences between clinicians’ “folk” taxonomies and psychiatry’s official one is timely, and its lessons are in need of (...) analysis. In this commentary I first address questions raised by the existence of multiple de facto taxonomies, and by the characteristics of those taxonomies themselves, before focusing attention on the DSM diagnostic system and its attributes that make acceptance by its constituencies far less than complete. Although the aim of Flanagan’s and Blashfield’s study is explicitly descriptive rather than normative, it provides an important opportunity to examine the extent to which our taxonomies serve the purposes for which they were constructed—whether by experts or by clinicians.There are certainly reasons to expect significant deviations between clinicians’ everyday taxonomies and the official one. Perhaps the most glaring reason is the fact that—even if it were desirable—no one can be familiar with the enormous number of categories codified by the DSM. On the other hand, the remarkable hegemony of the DSM—in the education and training of physicians and clinical psychologists, in clinical communication, and in the ubiquitous administrative functions of billing and coding—makes such deviations at least somewhat surprising and in need of scrutiny and explanation. The first question, however, is whether one should be concerned by the existence (surprising or otherwise) of multiple taxonomies. Flanagan and Blashfield make the compelling case that, given the high rate at which Americans seek clinical attention for psychiatric problems, the stakes are commensurately high for our efforts at categorizing those problems in valid and useful ways. And the extent to which a gulf exists between the way psychiatry and clinical psychology are written about and taught on the one hand, and conceptualized and practiced by clinicians on the other, invites a multitude of problems—among which cynicism about our disciplines may be one of the most pernicious.At least as important as their finding of only moderate correlations between clinicians’ taxonomies [End Page 271] and that of the DSM are the characteristics of clinicians’ diagnostic systems themselves. One potentially major artifact of their methodology, however, must be borne in mind: the instruction to the clinicians in their study to “[p]ut together the diagnoses that have similar treatments…” (emphasis mine). Although they cite previous work (Flanagan and Blashfield 2006) in defense of the proposition that such instruction did not unduly influence their findings, it was certainly an avoidable potential problem, which itself likely reflects the history of our clinical disciplines in which the treatment cart frequently pulled the diagnosis horse. It is, therefore, not unlikely that clinicians’ taxonomies might emphasize treatment considerations even if they had not been directed to do so. The fallacious reasoning behind such intuitively appealing practice, however, must be exposed. The implicit assumption that treatment response is a proxy for other important characteristics of illnesses is predicated on the false proposition that our treatments exert their effects via similar mechanisms across the various indications for their uses, thus allowing us to infer from such responses that what was awry in the first place among the conditions for which a given treatment is effective must be closely related. Categorizing mania and trigeminal neuralgia together by virtue of their shared responses to anticonvulsant therapy, or considering autoimmune platelet deficiencies to be closely related to abdominal trauma due to the fact that each sometimes requires splenectomy, are examples of the potential results of acting on that false premise.Another parameter on which the clinicians in the current study based their nosologies—most explicitly by the “dimensional experts”—is the “environmental” versus “biological” one. Given that a coherent dichotomy would either distinguish environmental from genetic etiological factors, or would contrast psychological (i.e., subjective or first-person) from biological (i.e., objective or third-person) manifestations of illness, a taxonomy one of whose axes purports to represent an environmental/biological continuum cannot... (shrink)

Through his S–R model of statistical relevance, Wesley Salmon offers a solution to the scientific explanation of objectively improbable events.

Really statistical explanation is a hitherto neglected form of noncausal scientific explanation. Explanations in population biology that appeal to drift are RS explanations. An RS explanation supplies a kind of understanding that a causal explanation of the same result cannot supply. Roughly speaking, an RS explanation shows the result to be mere statistical fallout.

While the fundamental laws of physics are time-reversal invariant, most macroscopic processes are irreversible. Given that the fundamental laws are taken to underpin all other processes, how can the fundamental time-symmetry be reconciled with the asymmetry manifest elsewhere? In statistical mechanics, progress can be made with this question. What I dub the ‘Zwanzig–Zeh–Wallace framework’ can be used to construct the irreversible equations of SM from the underlying microdynamics. Yet this framework uses coarse-graining, a procedure that has faced much criticism. I (...) focus on two objections in the literature: claims that coarse-graining makes time-asymmetry ‘illusory’ and ‘anthropocentric’. I argue that these objections arise from an unsatisfactory justification of coarse-graining prevalent in the literature, rather than from coarse-graining itself. This justification relies on the idea of measurement imprecision. By considering the role that abstraction and autonomy play, I provide an alternative justification and offer replies to the illusory and anthropocentric objections. Finally, I consider the broader consequences of this alternative justification: the connection to debates about inter-theoretic reduction and the implication that the time-asymmetry in SM is weakly emergent. 1Introduction 1.1Prospectus2The Zwanzig–Zeh–Wallace Framework3Why Does This Method Work? 3.1The special conditions account3.2When is a density forwards-compatible?4Anthropocentrism and Illusion: Two Objections 4.1The two objections in more detail4.2Against the justification by measurement imprecision5An Alternative Justification 5.1Abstraction and autonomy5.2An illustration: the Game of Life6Reply to Illusory7Reply to Anthropocentric8The Wider Landscape: Concluding Remarks 8.1Inter-theoretic relations8.2The nature of irreversibility. (shrink)

Probabilistic phenomena are often perceived as being problematic targets for contrastive explanation. It is usually thought that the possibility of contrastive explanation hinges on whether or not the probabilistic behaviour is irreducibly indeterministic, and that the possible remaining contrastive explananda are token event probabilities or complete probability distributions over such token outcomes. This paper uses the invariance-under-interventions account of contrastive explanation to argue against both ideas. First, the problem of contrastive explanation also arises in cases in which the probabilistic behaviour (...) of the explanandum is due to unobserved causal heterogeneity. Second, it turns out that, in contrast to the case of pure indeterminism, the plausible contrastive explananda under causal heterogeneity are not token event probabilities, but population-level statistical facts. (shrink)

The book explores several open questions in the philosophy of statistical mechanics. Each chapter is written by a leading expert in the field. Here is a list of some questions that are addressed in the book: 1) Boltzmann showed how the phenomenological gas laws of thermodynamics can be derived from statistical mechanics. Since classical mechanics is a deterministic theory there are no probabilities in it. Since statistical mechanics is based on classical mechanics, all the probabilities statistical mechanics talks about cannot (...) be fundamental. However, if probabilities are epistemic, how can they play a role, as they seem to do, in laws, explanation, and prediction? 2) Many physicists use the notion of typicality instead of the one of probability when discussing statistical mechanics. What is the connection between the two notions? 3) How can one extend Boltzmann’s analysis to the quantum domain, where some theories are indeterministic? 4) Boltzmann’s explanation fundamentally involves cosmology: for the explanation to go through the Big Bang needs to have had extremely low entropy. Does the fact that the Big Bang was a low entropy state imply that it was, in some sense, “highly improbable” and requires an explanation? 5) What exactly is the connection between statistical and classical mechanics? Is the one of theory reduction or there is no such thing? 6) Statistical mechanics has two main formulation: one due to Botzmann and the other due to Gibbs. What is the connection between the two formulations . (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Reviewed by:Logics of Failed Revolt: French Theory After May ‘68Ronald ShustermanLogics of Failed Revolt: French Theory After May ‘68, by Peter Starr; xi & 232 pp. Stanford: Stanford University Press, 1995, $45.00 cloth, $14.95 paper.Failed revolt? For many people, current French theory is more a revolt of failed logic. Anyone yearning for a definitive refutation of these threatening foreign trends will get no satisfaction from Peter Starr’s volume. His (...) concept of the “logics of failed revolts” involves the obsession of revolutionaries with what they see as the inevitable return of the past. Starr proposes to examine the explanations given for the failure of revolutionary action “in representative texts by Jacques Lacan, Roland Barthes, Julia Kristeva, Hélène Cixous, Jacques Derrida, and others” (p. 2). The “revolution” in question is the May 1968 uprising.George Orwell, as a defender of proper usage and an explorer of politics and the English language, always insisted that the title of his Nineteen Eighty-Four be written out in full; the informality of the abbreviation “May ‘68” is emblematic of the spirit of the events of that year: May ‘68 was supposed to be a liberation from useless tradition and constraint. That the movement was seen as a failure is the first premise of Starr’s argument; what he proposes to analyze is the theorization of the failure. Starr sees three “scenarios”: “the logic of specular doubling” is where “revolutionary action is doomed to repetition because revolutionaries inevitably construct themselves as mirror images of their rivals” (p. 2). There is also a “logic of structural repetition” and a “logic of recuperation” in which revolutionary actions actually reinforce established structures of power (pp. 2–3). Starr goes on to argue that “these logics served as argumentative pretexts, allowing Barthes, Kristeva, Cixous, and others to construct the existing political field as an impasse in order to justify significant displacements of political energies (including a politicization of the literary text)” (p. 7). This seems like a fancy way of saying that these thinkers used theory to find a decent way out of direct political commitment. Indeed, once one has understood and granted the point, there really is not much else in Starr’s book but fancy ways of repeating it.Starr tries to delineate a specific “theoretical moment” (p. 4) beginning in 1965 and ending in 1977, but it is difficult to be so definitive about the limits of a period when one is writing only twenty years later. This lack of temporal distance leads to certain debatable assertions. For example, Starr claims that tier-mondisme—France’s obsession with models taken from the Third World—“never recovered” from certain fatal “blows” (p. 4). Yet there is no actual evidence given for this claim. The problem with this kind of history is that it either makes concrete statements which are easy to contest, or it ends up vacuous: Starr sees in his period “a play of continuity and discontinuity” (p. 7). Who could deny such an assertion? All periods involve both continuity and discontinuity (except perhaps the period of the sinking of Atlantis...). Starr [End Page 191] mentions works on specific French thinkers by other theorists (such as Culler) and points out that his “aim has been to bridge the gap between such studies on the one hand and the work of historians and sociologists on the other” (pp. 10–11). The question is whether such an interdisciplinary project is feasible or even desirable. The theorists do not really care about the genealogy of the theory; the historians do not need to know if the theory is right. To take one example, Starr gives us statistics of the evolution of university enrollment in France (p. 113) a few pages after discussing Lacan’s “phallic comedy” (p. 104). How many readers are going to be equipped for, or interested in, a study which combines sociological statistics, political theory, general history, psychoanalytic principles, and feminist criticism?I was convinced by Starr’s basic argument that French thinkers were obsessed by this vision of the inevitable failure of revolt. Nevertheless, the point is both belabored and often tenuous. There are times when Starr’s... (shrink)

Complexity theory attempts to explain, at the most general possible level, the interesting behaviors of complex systems. Two such behaviors are the emergence of simple or stable high-level behavior from relatively complex low-level behavior, and the emergence of sophisticated high-level behavior from relatively simple low-level behavior; they are often found nested in the same system. Concerning the emergence of simplicity, this essay examines Herbert Simon's explanation from near-decomposability and a stochastic explanation that generalizes the approach of statistical physics. A more (...) general notion of an abstract difference-making structure is introduced with examples, and a discussion of evolvability follows. Concerning the emergence of sophistication, this essay focuses on, first, the energetics approach associated with dissipative structures and the fourth law of thermodynamics, and second, the notion of a complex adaptive system. (shrink)

In the recent literature on causal and non-causal scientific explanations, there is an intuitive assumption according to which an explanation is non-causal by virtue of being abstract. In this context, to be ‘abstract’ means that the explanans in question leaves out many or almost all causal microphysical details of the target system. After motivating this assumption, we argue that the abstractness assumption, in placing the abstract and the causal character of an explanation in tension, is misguided in ways that (...) are independent of which view of causation or causal explanation one takes to be most accurate. On major accounts of causation, as well as on major accounts of causal explanation, the abstractness of an explanation is not sufficient for it being non-causal. That is, explanations are not non-causal by dint of being abstract. (shrink)

Shapiro and Sober claim that Walsh, Ariew, Lewens, and Matthen give a mistaken, a priori defense of natural selection and drift as epiphenomenal. Contrary to Shapiro and Sober’s claims, we first argue that WALM’s explanatory doctrine does not require a defense of epiphenomenalism. We then defend WALM’s explanatory doctrine by arguing that the explanations provided by the modern genetical theory of natural selection are ‘autonomous-statistical explanations’ analogous to Galton’s explanation of reversion to mediocrity and an explanation of the (...) diffusion ofgases. We then argue that whereas Sober’s theory of forces is an adequate description of Darwin’s theory, WALM’s explanatory doctrine is required to understand how themodern genetical theory of natural selection explains large-scale statistical regularities. 1 Introduction2 Shapiro and Sober’s ‘Epiphenomenalism Do’s and Don’ts’3 WALM’s Explanatory Doctrine4 Galton’s Autonomous-Statistical Explanation5 A Second Example: The Statistical Explanation of the Diffusion of Gases6 Distinguishing Two Theories of Evolution by Natural Selection7 A Possible Objection: Are Statistical Laws Sufficient for Explanation?8 Conclusion. (shrink)

The statistical aspects of quantum explanation are intrinsic to quantum physics; individual quantum events are created in the interactions associated with observation and are not describable by predictive theory. The superposition principle shows the essential difference between quantum and non-quantum physics, and the principle is exemplified in the classic single-photon two-slit interference experiment. Recently Mandel and Pfleegor have done an experiment somewhat similar to the optical single-photon experiment but with two independently operated lasers; interference is obtained even with beam intensity (...) so small that only one photon is in the apparatus at a time. The result can be understood in terms of the superposition of states; or, in terms of the Uncertainty Principle, which is found to forbid the determination of which of the two lasers is the source of a given photon (if conditions for interference are to obtain). The Mandel-Pfleegor experiment gives a physical argument against the continuous localization of a photon that is assumed in the hidden variable theories and therefore gives further support for the generally accepted view that an observed entity (observed state) is created in the observation event. This aspect of quantum physics implies a subjectivism on the level of individual quantum-level occurrences, since there is in quantum theory no basis for asserting the existence of the event independently of observation of it. Extension of this subjectivism to large scale, non-quantum phenomena falls within the principles of quantum theory; counter considerations that argue against such an extension are noted. (shrink)

THE ART OF CAUSAL CONJECTURE Glenn Shafer Table of Contents Chapter 1. Introduction........................................................................................ ...........1 1.1. Probability Trees..........................................................................................3 1.2. Many Observers, Many Stances, Many Natures..........................................8 1.3. Causal Relations as Relations in Nature’s Tree...........................................9 1.4. Evidence............................................................................................ ...........13 1.5. Measuring the Average Effect of a Cause....................................................17 1.6. Causal Diagrams..........................................................................................20 1.7. Humean Events............................................................................................23 1.8. Three Levels of Causal Language................................................................27 1.9. An Outline of the Book................................................................................27 Chapter 2. Event Trees............................................................................................... .....31 2.1. Situations and Events...................................................................................32 2.2. The Ordering of Situations and Moivrean Events.......................................35 2.3. Cuts................................................................................................ ..............39 2.4. Humean Events............................................................................................43 2.5. (...) Moivrean Variables......................................................................................49 2.6. Humean Variables........................................................................................53 2.7. Event Trees for Stochastic Processes...........................................................54 2.8. Timing in Event Trees.................................................................................56 2.9. Intersecting Event Trees...............................................................................60 2.10. Notes on the Literature...............................................................................61 Chapter 3. Probability Trees...........................................................................................63 3.1. Some Types of Probability Trees.................................................................64 ii 3.2. Axioms for the Probabilities of Moivrean Events.......................................68 3.3. Zero Probabilities....................................................................................... ..70 3.4. A Sample-Space Analysis of the Event-Tree Axioms.................................72 3.5. Probabilities and Expected Values for Variables.........................................74 3.6. Martingales......................................................................................... .........79 3.7. The Expectation of a Variable in a Cut........................................................83 3.8. Conditional Expected Value and Conditional Expectation.........................87 Chapter 4. The Meaning of Probability...........................................................................91 4.1. The Interpretation of Expected Value..........................................................92 4.2. The Interpretation of Expectation................................................................95 4.3. The Long Run..............................................................................................98 4.4. Changes in Belief.........................................................................................101 4.5. The Empirical Validation of Probability......................................................106 4.6. The Diversity of Uses of Probability...........................................................108 4.7. Notes on the Literature.................................................................................110 Chapter 5. Independent Events.......................................................................................113 5.1. Independence........................................................................................ .......114 5.2. Weak Independence.....................................................................................118 5.3. The Principle of the Common Cause...........................................................121 5.4. Conditional Independence............................................................................128 5.5. Notes on the Literature.................................................................................133 Chapter 6. Events Tracking Events.................................................................................135 6.1. Tracking............................................................................................ ...........137 6.2. Tracking and Conditional Independence.....................................................142 6.3. Stochastic Subsequence...............................................................................143 6.4. Singular Diagrams for Stochastic Subsequence...........................................147 6.5. Conjunctive and Interactive Forks...............................................................149 Chapter 7. Events as Signs of Events..............................................................................153 iii 7.1. Sign................................................................................................ ..............154 7.2. Weak Sign................................................................................................ ....159 7.3. The Ethics of Causal Talk............................................................................160 7.4. Screening Off...............................................................................................16 2 Chapter 8. Independent Variables...................................................................................167 8.1. Unconditional Independence........................................................................170 8.2. Conditional Independence............................................................................175 8.3. Independence for Partitions.........................................................................177 8.4. Independence for Families of Variables......................................................182 8.5. Individual Properties of the Independence Relations...................................186 Chapter 9. Variables Tracking Variables........................................................................189 9.1. Tracking and Conditional Independence: A Summary...............................190 9.2. Strong Tracking............................................................................................ 192 9.3. Strong Tracking and Conditional Independence..........................................198 9.4. Stochastic Subsequence...............................................................................201 9.5. Functional Dependence................................................................................203 9.6. Tracking in Mean.........................................................................................204 9.7. Linear Tracking............................................................................................ 207 9.8. Tracking by Partitions..................................................................................210 9.9. Tracking by Families of Variables...............................................................212 Chapter 10. Variables as Signs of Variables...................................................................215 10.1. Sign................................................................................................ ............219 10.2. Linear Sign................................................................................................ .222 10.3. Scored Sign................................................................................................ 225 10.4. Families of Variables.................................................................................227 Chapter 11. AnTheory of Event Trees.............................................................229 11.1. Event Trees as Sets of Sets........................................................................230 11.2. Event Trees as Partially Ordered Sets........................................................232 iv 11.3. Regular Event Trees...................................................................................240 11.4. The Resolution of Moivrean Variables......................................................244 11.5. Humean Events and Variables...................................................................246 Chapter 12. Martingale Trees..........................................................................................247 12.1. Examples of Decision Trees......................................................................249 12.2. The Meaning of Probability in a Decision Tree.........................................253 12.3. Martingales......................................................................................... .......257 12.4. The Structure of Martingale Trees.............................................................261 12.5. Probability and Causality...........................................................................265 12.6. Lower and Upper Probability.....................................................................269 12.7. The Law of Large Numbers.......................................................................272 12.8. Notes on the Literature...............................................................................274 Chapter 13. Refining............................................................................................ ...........275 13.1. Examples of Refinement............................................................................277 13.2. A Constructive Definition of Finite Refinement.......................................281 13.3. Axioms for Refinement..............................................................................282 13.4. Lifting Moivrean Events and Variables.....................................................288 13.5. Refining Martingale Trees.........................................................................288 13.6. Grounding........................................................................................... .......294 Chapter 14. Principles of Causal Conjecture..................................................................299 14.1. The Diversity of Causal Explanation.........................................................302 14.2. The Mean Effect of the Happening of a Moivrean Event..........................305 14.3. The Effect of a Humean Variable..............................................................311 14.4. Attribution and Generality.........................................................................316 14.5. The Statistical Measurement of the Effect of a Cause...............................319 14.6. Measurement by Experiment.....................................................................320 14.7. Using Our Knowledge of How Things Work............................................322 v 14.8. Sampling Error...........................................................................................329 14.9. The Sampling Frame..................................................................................329 14.10. Notes on the Literature.............................................................................330 Chapter 15. Causal Models.............................................................................................3 31 15.1. The Causal Interpretation of Statistical Prediction....................................333 15.2. Generalizing to a Family of Exogenous Variables....................................337 15.3 Some Joint Causal Diagrams......................................................................339 15.4. Causal Path Diagrams................................................................................342 15.5. Causal Relevance Diagrams.......................................................................346 15.6. The Meaning of Latent Variables..............................................................352 15.7. Notes on the Literature...............................................................................357 Chapter 16. Representing Probability Trees...................................................................359 16.1. Three Graphical Representations...............................................................361 16.2. Skeletal Simplifications.............................................................................368 16.3. Martingale Trees in Type Theory...............................................................371 Appendix A. Huygens’s Probability Trees.....................................................................379 Huygens’s Manuscript in Translation..................................................................380 Appendix B. Some Elements of Graph Theory..............................................................385 B1. Undirected Graphs........................................................................................385 B2. Directed Graphs............................................................................................38 6 Appendix C. Some Elements of Order Theory...............................................................393 C1. Partial and Quasi Orderings.........................................................................393 C2. Singular and Joint Diagrams for Binary Relations.......................................394 C3. Lattices............................................................................................ .............395 C4. The Lattice of Partitions of a Set..................................................................396 Appendix D. The Sample-Space Framework for Probability.........................................399 D1. Probability Measures....................................................................................399 D2. Variables........................................................................................... ...........400 vi D3. Families of Variables...................................................................................401 D4. Expected Value............................................................................................402 D5. The Law of Large Numbers.........................................................................405 D6. Conditional Probability................................................................................406 D7. Conditional Expected Value........................................................................407 Appendix E. Prediction in Probability Spaces................................................................409 E1. Conditional Distribution...............................................................................411 E2. Regression on a Single Variable...................................................................412 E3. Regression on a Partition or a Family of Variables......................................415 E4. Linear Regression on a Single Variable.......................................................418 E5. Linear Regression on a Family of Variables................................................422 Appendix F. Sample-Space Concepts of Independence.................................................425 F1. Overview............................................................................................ ...........426 F2. Independence Proper.....................................................................................432 F3. Unpredictability in Mean..............................................................................434 F4. Simple Uncorrelatedness..............................................................................437 F5. Mixed Uncorrelatedness...............................................................................438 F6. Partial Uncorrelatedness...............................................................................440 F7. Independence for Partitions..........................................................................442 F8. Independence for Families of Variables.......................................................445 F9. The Basic Role of Uncorrelatedness.............................................................448 F10. Dawid’s Axioms.........................................................................................449 Appendix G. Prediction Diagrams..................................................................................453 G1. Path Diagrams............................................................................................ ..454 G2. Generalized Path Diagrams..........................................................................462 G3. Relevance Diagrams.....................................................................................466 G4. Bubbled Relevance Diagrams......................................................................475 Appendix H. Abstract Stochastic Processes...................................................................479 vii H1. Probability Conditionals and Probability Distributions...............................477 H2. Abstract Stochastic Processes......................................................................479 H3. Embedding Variables and Processes in a Sample Space.............................480 References.......................................................................................... ..............................491. (shrink)

argumentation has been shown to be a powerful tool within many fields such as artificial intelligence, logic and legal reasoning. In this paper we enhance Dung’s well-known abstract argumentation framework with explanatory capabilities. We show that an explanatory argumentation framework (EAF) obtained in this way is a useful tool for the modeling of scientific debates. On the one hand, EAFs allow for the representation of explanatory and justificatory arguments constituting rivaling scientific views. On the other hand, different procedures for selecting (...) arguments, corresponding to different methodological and epistemic requirements of theory evaluation, can be formulated in view of our framework. (shrink)

We argue that two powerful error-theoretic concepts provide a general framework that satisfactorily accounts for key aspects of the explanation of physical patterns. This method gives an objective criterion to determine which mathematical models in a class of neighboring models are just as good as the exact one. The method also emphasizes that abstraction is essential for explanation and provides a precise conceptual framework that determines whether a given abstraction is explanatorily relevant and justified. Hence, it increases our epistemological understanding (...) of how one should go about reconstructing scientific practices by making clear that, at a fundamental level, a key aspect of mathematical modeling consists in exactly solving nearby problems. (shrink)

(1988). Explanation, subjunctives and statistical theories. International Studies in the Philosophy of Science: Vol. 3, No. 1, pp. 80-96. doi: 10.1080/02698598808573326.

Abstraction and idealization are the two notions that are most often discussed in the context of assumptions employed in the process of model building. These notions are also routinely used in philosophical debates such as that on the mechanistic account of explanation. Indeed, an objection to the mechanistic account has recently been formulated precisely on these grounds: mechanists cannot account for the common practice of idealizing difference-making factors in models in molecular biology. In this paper I revisit the debate and (...) I argue that the objection does not stand up to scrutiny. This is because it is riddled with a number of conceptual inconsistencies. By attempting to resolve the tensions, I also draw several general lessons regarding the difficulties of applying abstraction and idealization in scientific practice. Finally, I argue that more care is needed only when speaking of abstraction and idealization in a context in which these concepts play an important role in an argument, such as that on mechanistic explanation. (shrink)

What role does language play in our thoughts? A longstanding proposal that has gained traction among supporters of embodied or grounded cognition suggests that it serves as a cognitive scaffold. This idea turns on the fact that language—with its ability to capture statistical regularities, leverage culturally acquired information, and engage grounded metaphors—is an effective and readily available support for our thinking. In this essay, I argue that language should be viewed as more than this; it should be viewed as a (...) neuroenhancement. The neurologically realized language system is an important subcomponent of a flexible, multimodal, and multilevel conceptual system. It is not merely a source for information about the world but also a computational add-on that extends our conceptual reach. This approach provides a compelling explanation of the course of development, our facility with abstract concepts, and even the scope of language-specific influences on cognition. (shrink)

Some philosphers of science of an empiricist and pragmatist bent have proposed models of statistical explanation, but have then become sceptical of the adequacy of these models. It is argued that general considerations concerning the purpose of function of explanation in science which are usually appealed to by such philosophers show that their scepticism is not well taken; for such considerations provide much the same rationale for the search for statistical explanations, as these philosophers have characterized them, as they (...) do for lawlike explanations. But, it is further argued, a significant piece of what is frequently offered as an explanation of well known phenomena in statistical mechanics, fails to meet this general "pragmatic rationale" for statistical, or indeed any kind of, explanation. The question then arises whether the physicists have misconstrued the value of this piece of physical theorizing, ergodic theory, taking it to be explanatory when it is actually not; or whether, instead, the philosopher's account of just what is genuinely explanatory is too narrow. (shrink)

A subarea of the debate over the nature of evolutionary theory addresses what the nature of the explanations yielded by evolutionary theory are. The statisticalist line is that the general principles of evolutionary theory are not only amenable to a mathematical interpretation but that they need not invoke causes to furnish explanations. Causalists object that construction of these general principles involves crucial causal assumptions. A recent view claims that some biological explanations are statistically autonomous explanations (...) (SAEs) whereby phenomena are accounted for statistically and which prescind from micro-causal details. I raise three major problems for this account and then advance a view which unifies SAEs as mathematical explanations: the MSAE view. The MSAE view not only resolves the issues bedeviling the original SAE account but serves to importantly broaden the class of non-causal explanations in population biology. (shrink)

For the case of statistical theories, the criteria of explanation, prediction, and testability can all be viewed as particular instances of a more general evaluation scheme. Using the ideas of a gain matrix and expected gain from statistical decision theory, these three criteria can be compared in terms of the elements in their associated gain matrices. This analysis leads to (1) further understanding of the interrelationship between the current criteria, (2) the proposal of an ordering for the criteria, and (3) (...) the suggestion of a new criterion. (shrink)

This paper explores the scientific viability of the concept of causality—by questioning a central element of the distinction between “fundamental” and non-fundamental physics. It will be argued that the prevalent emphasis on fundamental physics involves formalistic and idealized partial models of physical regularities abstracting from and idealizing the causal evolution of physical systems. The accepted roles of partial models and of the special sciences in the growth of knowledge help demonstrate proper limitations of the concept of fundamental physics. We expect (...) that a cause precedes its effect. But in some tension with this point, fundamental physical law is often held to be symmetrical and all-encompassing. Physical time, however, has not only measurable extension, as with spatial dimensions, it also has a direction—from the past through the present into the future. This preferred direction is time’s arrow. In spite of this standard contrast of time with space, if all the fundamental laws of physics are symmetrical, they are indifferent to time’s arrow. In consequence, excessive emphasis on the ideal of symmetrical, fundamental laws of physics generates skepticism regarding the common-sense and scientific uses of the concept of causality. The expectation has been that all physical phenomena are capable of explanation and prediction by reference to fundamental physicals laws—so that the laws and phenomena of statistical thermodynam- ics —and of the special sciences—must be derivative and/or secondary. The most important and oft repeated explanation of time’s arrow, however, is provided by the second law of thermodynamics. This paper explores the prospects for time’s arrow based on the second law. The concept of causality employed here is empirically based, though acknowledging practical scientific interests, and is linked to time’s arrow and to the thesis that there can be no causal change, in any domain of inquiry, without physical interaction. (shrink)

Starting from simple topological arguments due to Dirac on the classical rotational properties of extended rigid bodies, we abstract the concept of a finite-size spinor (FSS). The FSS is a concept distinct from both point spinors (e.g., electrons) and composite spinors (e.g., nuclei), and suggests a new model for baryons. The FSS offers a natural explanation of “threeness” for the quarks, excludes the existence of free quarks, denies the operational definition of quark spin statistics, and, moreover, leads to the dual (...) model of hadronic interactions. (shrink)

Phylogenies are increasingly being used to investigate human history, diversification and cultural evolution. While using phylogenies in this way is not new, new modes of analysis are being applied to inferring history, reconstructing past states, and examining processes of change. Phylogenies have the advantage of providing a way of creating a continuous history of all current populations, and they make a large number of analyses and hypothesis tests possible even when other forms of historical information are patchy or nonexistent. In (...) common with approaches taken in other historical sciences, phylogenetics is a way of reconstructing past and processes using the traces left in the present day. Trees, based on DNA, language, cultural traits, or other evidence, are now sprouting all over the academic landscape. The increasing use of phylogenetic analysis to understand human cultural evolution has been embraced by some, and scorned by others. The purpose of this article is not to review methods and applications of phylogenetic analyses, nor to consider the growing field of cultural phylogenetics, but, more broadly, to explore how we interpret phylogenies as narratives about human diversification. The first half of the article deals with meaning: phylogenies are often interpreted as histories, but a bifurcating tree is at best an abstract representation of history, and its connections to past events and processes is dependent on the data used, the assumptions made in the analysis, and the degree to which nodes in the tree (where one lineage splits into two) can be connected to change and movement in real populations. The second half of the article explores the purpose of phylogenies: a tree does not have to be a literal history of human lineages in order to be useful for investigating processes of human diversification. Phylogenies should not be read as accurate records of history, but as a way of exploring plausible explanations for current patterns of diversity. Phylogenies provide important information that can be used to test ideas about human diversity, and can help to guard against errors of inference arising from statistical artifacts. (shrink)

This paper explores the scientific viability of the concept of causality—by questioning a central element of the distinction between “fundamental” and non-fundamental physics. It will be argued that the prevalent emphasis on fundamental physics involves formalistic and idealized partial models of physical regularities abstracting from and idealizing the causal evolution of physical systems. The accepted roles of partial models and of the special sciences in the growth of knowledge help demonstrate proper limitations of the concept of fundamental physics. We expect (...) that a cause precedes its effect. But in some tension with this point, fundamental physical law is often held to be symmetrical and all-encompassing. Physical time, however, has not only measurable extension, as with spatial dimensions, it also has a direction—from the past through the present into the future. This preferred direction is time’s arrow. In spite of this standard contrast of time with space, if all the fundamental laws of physics are symmetrical, they are indifferent to time’s arrow. In consequence, excessive emphasis on the ideal of symmetrical, fundamental laws of physics generates skepticism regarding the common-sense and scientific uses of the concept of causality. The expectation has been that all physical phenomena are capable of explanation and prediction by reference to fundamental physicals laws—so that the laws and phenomena of statistical thermodynamics—and of the special sciences—must be derivative and/or secondary. The most important and oft repeated explanation of time’s arrow, however, is provided by the second law of thermodynamics. This paper explores the prospects for time’s arrow based on the second law. The concept of causality employed here is empirically based, though acknowledging practical scientific interests, and is linked to time’s arrow and to the thesis that there can be no causal change, in any domain of inquiry, without physical interaction. (shrink)