Hackers How-to

Philosophy

Hacker's how-to ! "Code Crackers Not Crooks, Professor Says." The headline perched atop an Associated Press story, and went on to say: "If a professor could have his way, hackers who crack top-secret computer codes would not be regarded as crooks but as eloquent manipulators of their favorite language. For the record, I was the professor, and the sentiments expressed actually were more or less mine. In view of this history, my reading of this self-described "encyclopedic account of the methods by which security is breached and systems penetrated" might be perceived as biased. Readers, beware. It has not been so long since hackers were celebrated. John Badham's motion picture War Games (1983) opened the gates to many of the now-familiar stereotypes regarding hackers. Youngsters even began aspiring to hacking and phone-phreaking rather than fire-fighting or space exploration. Then followed, unsurprisingly, the demonization of the hacker. Laws were hastily written, and hackers were apprehended and sentenced. Just recently, as I was reading this book unrelated incidents involving students from Brown University and the Massachusetts Institute of Technology MIT) brought hacking back into the news. Hacker activity on the fast-expanding Internet, meanwhile, has provoked calls for tighter rules and control of network users. If the subject matter of the book was not sensational enough already, then recent events have only elevated its profile. Youngsters, take note: computer security is a field of fast market growth and technological innovation. The author declares a hacker to be someone "with an intense love of something, be it computers, writing, nature, or sports. A hacker is a person who, because he or she has this love, also has a deep curiosity about the subject in question.... For a computer hacker that means he respects the ability of computers to put him in contact with a universe of information and other people, and it means he respects those other people and does not intentionally use this knowledge of computers to be mischievous or destructive." This seems so disingenuous that I cringe. It comes from the same person proclaimed on the back cover, in big, bold type, as "every security manager's worst nightmare!" Inside, we read about "brute force attacks," which refer to "hurling passwords at a system until it cracks"; "spoofing," which is "designing dummy screens and delivering fake e-mail"; decryption of password files; and "stair-stepping," which means using a "low-level account to gain ever-higher levels of access." We also read how to sort through trash (after scavenging, "take a shower when you get home," the author advises), and how to examine found disks and screen shots. Snooping and "shoulder surfing," in which "a hacker looms over the shoulder of a legitimate user that [sic!] logs on to a computer system," are also described. In between, the author sketchily outlines elementary notions of access control, communication software, modems and speed bar codes, computer viruses, and so on. The main message, with which the book closes, is: "Don't get caught!" The message is amplified with a list of things to avoid, the "five ways you, the hacker, can get caught hacking: 1. by traces or technical means; 2. by being finked on; 3. by getting many agencies ganged up against you; 4. by making a mistake; or 5. by being [recognized]." If hacking merely expresses love for computers, and if hackers are so respectful, why worry about being caught? This is a book that delivers a mixture of methods and ideas for breaking into other people's systems, and then follows that up with a code of ethics. Though this code emphasizes individual responsibility, some of its elements are controversial. To his (or her) credit, The Knightmare does address some of the big, difficult questions: access to information; the appropriate use of technology to empower people and not restrict their creativity or liberties; individual rights regarding data pertinent to people's lives; and a system of checks and balances in the digital domain, especially in the use of and commerce in databases affecting an individual's right to privacy. "It is pointless," the author writes. "to raise the issue of 'Do you honestly think you can justify snooping with your loopy code of ethics?" A good point, and this brings up the central issue of such a book: Hacking, as the author notes, can be considered an expression of passion. But is it also exempt from moral and social constraints? As Ken Thompson received the Turing award for his co-invention of Unix--the most hacked operating system--he made a point of explaining his attitude toward hackers: "The acts performed by these kids are vandalism at best and probably trespass and theft at worst. It is only the inadequacy of the criminal code that saves the hackers from very serious prosecution." I wish the words were not his. Although Thompson's statement does indeed apply to many hacking cases--including most of the activities described by The Knightmare--he misses the critical point. In fact, Turing himself would have been jailed if the criminalizing of code-breaking had been applied to him. This requires elaboration, because the book I am reviewing misses this same point, too, but from the opposite direction. In Hackers (Anchor Press/Doubleday, 1984), still the best book on the subject, Steven Levy noted that in the early 1960s, "a project undertaken or a product built not solely to fulfill some constructive goal, but with some wild pleasure taken in mere involvement, was called a 'hack'." Levy added that "the artistry with which one hacked was recognized to be considerable." Programming was coming of age, and Peter Samson's code that converted Arabic into Roman numerals was one of the more celebrated hacks. At the annual MIT open house in May 1962, hackers fed into a PDP-1 minicomputer paper tape with 27 pages worth of assembly language code comprising a science fiction game written by students. Thus the interactive game was born--as a hack. "We are prigs. We are intolerable aesthetes," wrote one hacker. The species believed in the art of programming, and their obsession was not with the "salami technique" of stealing money (briefly mentioned in the book) or with piracy. Scientific and technological motivations meshed with social and political values, some childish, others deeply visionary. There is no reason to idealize the romantic age of computation or to trivialize the driving force behind hacking, even if today's scientific and technological motivations are in fact quite different from those of the past. The point is that there is a cognitive and an aesthetic dimension to hacking that separates it from the techniques of phreaking (breaking into the telephone system in order to use it for free) or cracking (hacking without respect for the computers being hacked, according to The Knightmare). Thus the author is right in asserting that hacking is not only a matter of digital technology. But after stating this in the book's opening, he or she abandons any pursuit of broader issues. Sensationalist expositions of methods (some disputable, some ingenious, none new) obscure the more fundamental question of why people hack. The desire to understand is a basic one, and it is the downfaIl of all sorts of barriers to knowledge. Social, cultural, economic, and genetic codes have all been broken, leading me to believe that writing laws that criminalize hacking, without taking into account the specific nature of computer knowledge and access to it, is as ill-advised as writing a book on the so-called "secrets of a super hacker." Societies scared of hackers to the point of criminalizing them lose more than they think they gain by doing so. Gareth Branwyn, who knows quite a bit about the subject, provides good arguments along this line in the book's introduction. The author frequently comments on obsolete statutes regarding computer crime. However, the break-in methods described are similarly anachronistic, carrying over fundamental misconceptions from previous pragmatic frameworks. As science becomes more and more computational, we need to come up with a better understanding of the nature of human activity in the Information Age. The New Frontier Foundation, mentioned in this book, is probably best equipped to help in this respect. Nomadic computation, voice and handwriting recognition, living and working on the information grid, and virtual reality are the new territory of what hacking used to be. Unfortunately, they are not to be found in this book On the contrary, readers might wonder why The Knightmare pays so much attention to MSDOS (Unix is mentioned, too), when so much of today's computation takes place on other platforms. Client-server structures are quite different from old-style, centralized mainframe systems, even for a hacker bent only on "getting in." Surprisingly, the book also repeats some tired stereotypes, identifying hackers by their "thick glasses, modest height [and] fanatic taste for computers, bad movies, and pulp science fiction." It's as bad as the social engineering described by the author in absurd detail. Media coverage of hacking has focused on penetrations of networks carrying sensitive information, intrusions into proprietary files, and piracy. It ignores intriguing or innovative ideas and broader motivations. On a smaller scale, this book does the same thing. The most that happens in this selfdescribed super hacker's account is a penetration of a library system with dial-up access. A computer hacker needs to understand how computers work, to study them, to learn programming. So it struck me as incredible that Secrets of a Super Hacker contained no technical information of which I was not already aware. Instead of holding this against the writer or publisher, I would like to turn it into a final observation. To hack means to be on the frontier, on the border. In computer science and technology. This border is constantly being pushed back, and at a tremendous pace. In truth, a good "how to" book cannot be written on hacking, because with each new hack, a higher level of knowledge is reached that requires newer methods to surpass. To explain hacking, therefore, is to explain it away.


Philosophy

The aim of the paper is to develop general criteria of argumentative validity and adequacy for probabilistic arguments on the basis of the epistemological approach to argumentation. In this approach, as in most other approaches to argumentation, proabilistic arguments have been neglected somewhat. Nonetheless, criteria for several special types of probabilistic arguments have been developed, in particular by Richard Feldman and Christoph Lumer. In the first part (sects. 2-5) the epistemological basis of probabilistic arguments is discussed. With regard to the philosophical interpretation of probabilities a new subjectivist, epistemic interpretation is proposed, which identifies probabilities with tendencies of evidence (sect. 2). After drawing the conclusions of this interpretation with respect to the syntactic features of the probability concept, e.g. one variable referring to the data base (sect. 3), the justification of basic probabilities (priors) by judgements of relative frequency (sect. 4) and the justification of derivative probabilities by means of the probability calculus are explained (sect. 5). The core of the paper is the definition of '(argumentatively) valid derivative probabilistic arguments', which provides exact conditions for epistemically good probabilistic arguments, together with conditions for the adequate use of such arguments for the aim of rationally convincing an addressee (sect. 6). Finally, some measures for improving the applicability of probabilistic reasoning are proposed (sect. 7).

Chapter 104 Probabilistic Arguments in the Epistemological Approach to Argumentation Christoph Lumer University of Siena 1. Introduction: the Epistemological Approach to Argumentation and Probabilistic Arguments In this paper I present a proposal on how to conceptualise and handle probabilistic arguments in an epistemological approach to argumentation. The epistemological approach to argumentation is an approach which aims at rationally convincing addressees or, more precisely, which takes knowledge or justified belief of an addressee to be the standard output of argumentation (Biro 1987, p. 69; Biro & Siegel 1992, pp. 92; 96; Siegel & Biro 1997, pp. 278; 286; Lumer 1990, pp. 43 f.; 1991, p. 100; 2005b, pp. 219-220; Goldman 2003, p. 58).1 Therefore, this approach develops criteria for valid and adequate arguments whose observance leads, or at least is intended to lead, to the production of that output: justified belief. The general way in which this goal is achieved is by guiding the addressee through a process of recognising the truth or acceptability of the argument's thesis. An ordered sequence of judgements, i.e. the reasons, is presented to the addressee whose truths, according to a primary or secondary criterion of truth or acceptability, imply the truth or acceptability of the thesis and which are chosen in such a way that the addressee can immediately check whether they are true or acceptable (Lumer 1990, pp. 44-51; 2005b, pp. 221-224). In an epistemological approach to argumentation, different types of arguments can be distinguished according to the respective epistemological principles on which they are based. There are e.g. deductive arguments based on deductive logic; there are practical arguments based on rational decision theory and its additions like game theory or philosophical theories of practical rationality; there are empirical-theoretic arguments for empirical laws about theoretical entities, which are based on criteria for good empirical theories; there are probabilistic arguments for probability judgements, which are based on probability theory; etc. To be constructively helpful, an epistemological theory of argumentation should not only develop a general definition of 'good argument' but also elaborate precise criteria for such special types of argument. Such criteria have e.g. been proposed within the epistemological approach for deductive arguments (Feldman <1993> 1999, pp. 61-80; 94-100; Lumer 1990, pp. 180-209) or for practical arguments (Feldman 1999, pp. 351-354; 420; Lumer 1990, pp. 319-433). For the realm of probabilistic arguments, criteria for certain subtypes have been developed: criteria for genesis of knowledge arguments (which try to show that the thesis has been correctly verified by someone), which include arguments from testimony and from authority (Feldman 1999, pp. 216-232; 418; Goldman 1999, pp. 103-130; Lumer 1990, pp. 246-260), and for interpretative arguments (which try to establish the causes of known facts and circumstantial evidence through inference to the best explanation based on Bayes's Theorem) (Lumer 1990, pp. 221-246).2 A general theory of probabilistic argumentation which provides exact criteria for the validity and adequacy of these 1142 arguments is so far lacking, however. Such a theory will be proposed in the following, starting from the epistemological approach to argumentation. "Probabilistic argument" here always refers to: an argument with a probability judgement as its thesis. Applying the epistemic approach to such arguments presupposes primary or secondary criteria of the truth or acceptability of probability judgements. Of course, such criteria should be provided by probability theory. But, although there is a rather broad consensus in probability theory about the calculus to be used, there is significant divergence about the interpretation and conceptualisation of probability, which would also lead to different conceptualisations of probabilistic arguments. So we first have to go some way into the philosophical debate on the best concept of probability. 2. Philosophical Concepts of Probability – A Case for Probability as Rational Approximation to Truth Philosophical theories of probability come in two main groups: first, objective or realistic theories, which maintain that probability is an objective, real feature of the world, and, second, subjective, epistemic, or cognitivist theories, which maintain that probability is essentially an epistemic or belief phenomenon, due to our limited knowledge. The two main realistic approaches are, first, relative frequency theories, according to which probabilities are identical to actual relative frequencies (Venn <1866> 2006) or to limiting relative frequencies in a hypothetical infinite row of trials (Reichenbach <1935> 1949; von Mises <1928> 1981), and, second, propensity theories, according to which probabilities are identical to a quantitative disposition in an object or in a type of system to produce a certain result or results with a certain relative frequency (Gillies 2000; Hacking 1965; Mellor 2005; Miller 1994; Popper 1959). Propensity theories have been developed to explain single-event stochastic processes like radioactive decay of single atoms, whereas frequency theories seem to capture particularly well probabilities derived by statistical inferences. At first appearance, only realistic or objective theories seem to be appropriate to provide what an epistemological approach to argumentation needs, namely objective criteria for the truth of probability judgements. This impression, however, is due to an ambiguity of the word "objective". A judgement may be "objective", in a weak sense, of being cognitive, i.e. of being true or of being the result of an interpersonally verifiable process of applying clear criteria. And a judgement may be "objective", in a stronger sense, of being realistic, i.e. of describing a reality that is independent of any subjective attitude. Of course, only realistic theories of probability are objective in the strong sense; however an epistemological approach to probabilistic arguments needs objective criteria for the truth or acceptability of probability judgements only in the weak, cognitivist sense. This weak kind of objectivity can, however, also be provided by some epistemic theories of probability so that the objectivity requirement is no argument in favour of realistic theories of probability. There are many well-known objections against every single realistic theory of probability. (In theories of actual frequencies, e.g. the result of a series of experiments may strongly diverge from the true probability – think of a die rolled only three times in its life and always showing "6" (Hájek <2002> 2009). In theories of limiting relative frequency real infinite series are impossible and soon lead to radical changes of the experimental situation – what a die will look like after having been rolled a billion times? –, whereas hypothetical infinite series have left empiricism behind (ibid.). 1143 Propensity theories share many problems of frequentism; in addition, propensities are causalist and hence asymmetric, whereas probabilities in a certain sense may be "inverted" – Bayes's Theorem e.g. implies such an inversion of conditional probabilities: P(a/b) = (P(b/a)*P(a)) / P(b) –; it may make sense to say that affluent people have a propensity to vote for conservative parties, whereas it makes little sense to say that votes for conservative parties have a propensity to come from affluent people (Humphreys 1985).). I want to stress here, however, only two general objections. The first is ontological. Of course, there are relative frequencies and these provide us with information about probabilities, and there are qualitative structures of a system underlying these relative frequencies. But what are the realistically conceived frequentist or propensity probabilities of a single event? Either the die ends up with "6" on top or it does not; and if it does this was probably determined by laws of nature. We are speaking of probabilities in such cases only because we do not know the result beforehand; we try to approach truth as much as possible before the event by speaking of probabilities. Afterwards our probabilities even change, e.g. to the probability 1 for "6". At least probabilities of single events are epistemic probabilities; and for the objective fact of relative frequencies we have precisely the notion of 'relative frequency', which is different from 'probability'. Probabilities are only an epistemic substitute in case of incomplete knowledge. The other general objection to realist theories of probabilities is particularly relevant to our endeavour to develop an epistemic theory of probabilistic arguments. There are many epistemic uses of probabilities which do not try to capture real tendencies in the world. This holds in particular when we try to find out backward information, like the probable cause of a known fact – e.g. 'the dinosaurs probably (with a probability of 90%) became extinct as a consequence of a giant asteroid hitting the Earth' (cf. Hacking 2001, pp. 128-130) – or the probable meaning of a sentence or the fact indicated by a clue. Such probability statements do not speak of frequencies or propensities in the world but even try to fill our gaps of knowledge backwards. Hence these probabilities are quite obviously epistemic in nature. What, then, about epistemic theories of probability? We have to dismiss rather quickly the traditional Laplacian theory of a priori equiprobability of logical possibilities, which has the immense disadvantage of not incorporating empirical information about relative frequencies,3 and the theory of logical probabilities or inductive logic (Carnap 1950; 1952). Problems of the latter theory, among others, are that its confirmation function is arbitrary or that, contrary to what the theory presupposes, (basic) evidences do not necessarily have the probability of 1. The major remaining approach then is subjectivism or personalism or subjective Bayesianism, which conceives probabilities in a personal or subjective way as rational degrees of belief. Subjectivism conceives degrees of belief in a behaviouristic manner as something revealed by preferences. In the most simple case a subjective probability p of an event e is equated with that value p for which it is true that the subject is indifferent about receiving some amount of money p*m for sure and a lottery by which the subject receives the complete amount m conditional on e. (Ps(e)=p := p*m ≈s <e; m; ¬e; 0>). More complex systems make stronger presuppositions about preferences and measure probabilities as well as utilities (Eells 1982, pp. 9 f.). Behaviouristic conceptions of the degree of belief lead to well-known problems, e.g.: buying and selling prizes usually differ; the utility function of money is not linear, hence the utility of p*m is not identical to p times the utility of m. The general problem behind such difficulties is the 1144 behaviouristic approach, which has to find out too many interdependently acting subjective variables only on the basis of knowledge about the behavioural surface. Let me now add to this a further and less well-known aspect of this problem, which is detrimental to the usual interpretation of subjectivism itself. The standard interpretation of subjectivist probability as degree of belief cannot, though we actually have to, distinguish between, first, a (less than certain) degree of belief or confidence (in a non-technical sense) and, second, a belief with a probabilistic content. That we have to distinguish these two things is obvious in situations where both phenomena are present. Someone has heard from an expert that the probability of some event e is p, or he has inferred this probability from his own frequency counts and hence believes that the probability of e is p. He is not sure about this probability, however, and has only a reduced degree q of belief in it – e.g.because he knows he has a bad memory or cannot recall clearly the value p or because he has some doubts about the expert's reliability. The difference between the two kinds of uncertainty is that the probability believed is part of the belief's content, i.e. the proposition believed in, whereas the degree of belief is outside this propositional content as it is something like the intensity of the propositional attitude. Instead of simply saying 'subject s believes that a' 4 and thus taking 'belief' as a qualitative notion we can take it as a quantitative, functional notion: 's believes that a to the degree q (or with the confidence q)' and we can write this as: Bs,a=q. If the proposition believed in has a probabilistic content, as in the example just given, we can write this as: s believes with the confidence q that the probability of e is p: Bs,(Pe=p)=q. This differentiation, however, constitutes a problem for the usual subjectivist interpretation of probability. The probability now shows up already in the belief's content; what does this (inner) concept of 'probability' then mean? If the probability value and the confidence value differ – as they are supposed to do in most cases – then this probability cannot be the degree of belief. At least it cannot be the degree of belief of that person at that time. The defender of subjective probabilities as degrees of belief may reply to this objection: but it can be the degree of belief of a different person or of the same person at a different time. From the several alternatives – e.g. the subject's earlier belief, the informant's belief or the belief of a rational subject – the latter seems to be the most plausible because this interpretation would be possible in any case and not only in a limited number of cases. However, this proposal faces serious problems too. First, the differentiation in believed probability and degree of belief seems to exist already just from the beginning even for very rational subjects who e.g. have determined some probability on the basis of a frequency count executed a second ago but, because of considering human fallibility, have only a confidence near to one. To what other degree of certainty shall the probability judgment refer to in this case? Second, rational subjects should be exactly the people who base their subjective probabilites on clear epistemic procedures, which are different from simply having a certainty impression (which, perhaps, might be interpreted as the degree of certainty). According to an at least slightly verificationist semantics, some of these procedures would make up the meaning or content of the resulting belief's proposition, so that (1) the probabilistic content would belong to the propositional content and would not make up the external degree of confidence and (2) it would have a meaning other than referring to a degree of belief. All this means we are still lacking an interpretation of 'probability'. What then are probabilities? My proposal for answering this question is: In alethic terms, probabilities are rational approximations to truth under conditions of epistemic limitations. This is supposed to mean that the respective subject does not know whether the real value is 0 or 1, which are the only possible values; but his 1145 knowledge, though not sufficient to establish 0 or 1, indicates a value between these extremes, which may be nearer to 0 (or 1) to a given degree. Given these explanations, an explanation of probabilities in epistemic terms seems to be even more adequate. Therefore, instead of speaking of "approximation to truth" one might also say that probabilities, in justificatory terms, express a certain tendency of evidence for the two possibilities, which we can extract from our limited knowledge. If the probability of an event e is p the tendency of evidence for e is p, with 0≤p≤1, whereas the tendency of evidence for e being false is 1-p.5 In practical terms, finally, probabilities are degrees of rational reliance that the event in question will occur. They are values we ascribe to propositions for decisional purposes and which by maximising expected utility permit us to follow a strategy which, according to the laws of large numbers, in the long run will be the best among the strategies we can follow with our limited knowledge. These three aspects coincide because the epistemic aim is exactly to approach truth as closely as possible with the given information; and using these approximations in one's decisions in a decision-theoretic fashion implies making maximum and specific use of the information at hand. 3. Some Syntactical Features of Probabilities as Tendencies of Evidences According to the explanations just given, probabilities as tendencies of evidences depend on a given corpus of knowledge; i.e. from different corpora of knowledge may result different degrees of probability: after having witnessed the rolling of a die the probability of showing "6" may increase from 1/6 to 1 (or decrease to 0). For nonetheless being able to be objective in the sense of being true, probability judgements have to express this kind of relativity by a respective variable that refers to the particular knowledge on which the probability is based. Given the rationality and cognitivity of the probability striven for, the truth of a probability judgement should not depend on the identity of the believer but on the particular data corpus of which the person disposes. A different person with the same data corpus should, of course, assume the same rational probabilities. This means the knowledge variable of the probability concept should refer to data bases and not to persons (and moments). Of course, this does not exclude that the intended data base is denoted by a definite description that identifies the data with those at hand to a certain person at a certain time: 'Susan's data at that moment'. In ordinary language as well as in theoretic expositions the reference to the data base is rarely expressed explicitly; often it is simply identical to the speaker's data base at that very moment. (The probability relativised in this way, e.g. 'the probability of event e on Susan's data base is q', has to be distinguished from the subjective, or more precisely, from the believed probability, which can be expressed with our probability concept too: 'Susan believes that the probability of the event e (on her present data base) is p.') A further advantage of taking data corpora as the second variable of probabilities is that in this way things like 'scientific' or even 'natural probabilities' can easily be defined. A scientific probability would be one where the data base is the present scientific knowledge. And a natural probability of an event could be one where the data base is a complete (true) description of the world's history before that event plus the (true) natural laws. The other variable – or, in the case of conditional probabilities, the other two variables – of the probability concept refer to the things whose probability is expressed. Sometimes it is assumed that these relata are events, or more generally, states of affairs. This may be true in a realist approach to probability; however, in an epistemic approach 1146 the relata have to be what can be the content of knowlegde, i.e. propositions. To put it another way, the relata of epistemic probabilities have to be more fine-grained than events, namely propositions, because, though 'Peter's murderer has poisoned him' and 'Sara has poisoned Peter' could well denote the same event, the respective data base may not imply that Sara was Peter's murderer so that the probabilities of the two tokens may be different. And this is possible only if, given the identity of the event and of the data base, the tokens are propositions. So, finally, the syntax of basic probability judgements is: 'The probability of the proposition a on the data base d is x' (Pa,d=x or, if one prefers brackets: P(a,d)=x), and of conditional probability judgements it is: 'The probability of a given b on the data base d is x' (P(a/b),d=x or P((a/b),d)=x). (Pa,d does not coincide with P(a/d) because the d in the first instance is supposed to be true but in the second instance it is not. Nor does P(a/b),d coincide with P(a/d) because d does not need necessarily to imply b.) 4. Justifications of Probability Judgements: 1. Basic Probabilities How can probability judgements be recognised in an epistemologically qualified way? In the realm of (more or less) certain knowledge we distinguish between basic or elementary cognition, in particular observation, on the one hand and derivative cognition proceeding by deductive inferences on the other. In the realm of probabilistic knowledge we can distinguish in a similar way between basic cognitions of probabilities via known relative frequencies (these cognitions do not rely on probabilistic premises, hence provide basic probability judgements) and derivative cognitions of probabilities by applications of the probability calculus, which already uses probabilities as inputs. The basic form of probability cognitions of e.g. whether e or ¬e via known relative frequencies, trivially, works as follows. It, first, presupposes that we have no better information about e, e.g. no definite information that e happened. It further presupposes that we know some relative frequencies applying to e, i.e. relative frequencies of the form: 'The relative frequency of Es among Fs is x', where e has the property F and perhaps the property E. Finally, it presupposes that if there are several such relative frequencies we can identify the one which is most specific about e, i.e. entails the most detailed description F of e. In a certain sense this specificity condition is a further special case of the condition that the data base does not contain any further information by means of which we can draw stronger conclusions about e. If all these presuppositions are fulfilled we can infer that the probability of e is x. (We may formalise these conditions as follows: "RF(E/F)=x" shall mean: the relative frequency of Es among Fs is x; "NBI" shall mean: "no better information", i.e. the precedent information is the best in the respective data base about the proposition in question. With these abbreviations the conditions can be formalised as: Foundation Principle: P(e / RF(E/F)=x & f & NBI),d = x), for all E, F, d, e, f and x with P(RF(E/F)=x & f & NBI),d > 0. (This Foundation Principle is a reformulation of Hacking's Principle of Direct Probability (Hacking 1965; 2001, p. 137). Note that this Foundation Principle does not presuppose any probabilistic information as an input of its use: relative frequencies are objective realities, which sometimes can be known with certainty; the same holds for "f", i.e. the fact that the possible event e has 1147 the quality F. Thus the Foundation Principle is really basic in the sense of newly introducing probabilities without already presupposing other probabilities. The use of the Foundation Principle and hence the use of basic probabilities can be justified practically, i.e. as practically rational, on the basis of the laws of large numbers. If we do not dispose of certain information, probabilistic beliefs acquired via the Foundation Principle are the most informative condensation of our information about the event in question. If we use them via expected utility maximisation, of course, this cannot guarantee success in any single case but in the long run will provide better results than the use of any other way of handling uncertain information; as can be shown in comparisons with other decision strategies expected utility maximisation will lead to the highest utility. This justification, however, does not say anything about the success of expected utility maximisation in any single case. So there may be decision situations where the large number presupposition does not hold – e.g. in decisions about life and death, where a fatal result implies simply that there will not be any further risky decision – and where expected utility maximisation may not be the best decision strategy. Hence, the just mentioned practical justification of the Foundation Principle proves the usefulness of employing probabilities calculated by means of this principle in many situations and justifies the use of the utility maximising strategy in many situations but it does not justify always weighting probabilities in decision situations according to the identity function, i.e. the probability x with the weight x. Counting the magnitude of the population and the quantity of the positive cases is the safe way to establishing relative frequencies. This is costly, however, and not always possible. Therefore we need further ways to acquire information about relative frequencies. One less secure way is to try to remember single occurrences of the relative frequency in question and to count them. In addition, fortunately, mother nature has provided us with a not very reliable but at the same time not too bad sense of relative frequencies; on the basis of this we may consider past experiences and estimate in a holistic way their relative frequencies. This sense of relative frequencies can also lead to an uncertain degree of belief in a universal connection of two types of events. Another way to obtain information about relative frequencies, then, is to rate one's degree of certitude about such a connection and to take it as the relative frequency. This strategy may be called "propositionalisation of degrees of certitudes" because the degree of certitude, which is the intensity of the belief and hence not part of its content, is now made available as quantitative information within the beliefs proposition. This makes the quantitative information universally usable. Propositionalisation of certitudes: Ppf(RF(E/F)=y / Bs,(∀x(Fx→Ex))=y & NBI),d=1, for all s, E, F, y, d with P(Bs,(∀x(Fx→Ex))=y & NBI) > 0, where Ppf is a prima facie probability, which may be combined with other prima facie probabilities to obtain the final probability. The final and the weakest way of acquiring information about relative frequencies presupposes that the data base contains absolutely no empirical information about the case in question. In such a situation we may establish relative frequencies in a Laplacian way by counting the logical possibilities. The methods of establishing or estimating relative frequencies described so far scrutinise all the individuals of the population, which is often too expensive or even impossible. The range of these methods can be enormously extended if the scrutinised set can be considered as a (more or less) representative sample of a much bigger population so that the relative frequency established in the sample may be extrapolated 1148 as holding for the whole population. Statistics and considerations about projectability of properties tell us when and with which degree of confidence this can be done. 5. Justifications of Probability Judgements: 2. Derivative Probabilities The other way to cognise probability judgements in an epistemologically qualified way is to calculate probabilities with the help of the probability calculus. Fortunately, this technical part of probability theory is much less controversial; a certain orthodoxy has been achieved. My task here is therefore only to remember some basic principles of this calculus. The basic axioms of the calculus are: Normalcy: For all a and d: 0 ≤ Pa,d ≤ 1. Certainty: Certain propositions have the probability 1. Additivity: If a and b are mutually exclusive then: P(a∨b),d = Pa,d + Pb,d, for all a, b, d. Conditional probabilities: P(a/b),d = (P(a&b),d)/(Pb,d), for all a, b, d with Pb,d>0. From these axioms follow theorems like: Overlap: If a and b are not mutually exclusive then: P(a∨b),d = Pa,d + Pb,d P (a&b),d, for all a, b, d. Complementarity: P(¬a),d = 1-P(a),d, for all a and d. Bayes's Theorem, extended: Let h1 to hn be mutually exclusive and exhaustive hypotheses, and e some relevant evidence, then: P(e/hi),d * P(hi),d P(hi/e),d = ⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯ j=1∑nP(e/hj),d * P(hj),d 6. Rules for Derivative Probabilistic Arguments As described in the introduction, according to the epistemological approach to argumentation, arguments should be able to guide an addressee in a process of recognising the acceptability of the argument's thesis. And they do this by presenting him reasons, i.e. judgements, which according to an epistemological primary or secondary criterion for the acceptability of the thesis imply this acceptability. The addressee may then check the truth of these reasons and of the implication relation and thus convince himself of the thesis's acceptability. So a very simple probabilistic argument may look like this: Thesis q: The probability of rolling a "1" or a "2" in the next cast is 1/3. Indicator of argument: This holds because: Reason r1: The additivity axiom of the probability calculus says that probabilities of mutually exclusive possibilities add up to the probability of the disjunctively combined event. Reason r2: The probability of rolling a "1" (in the next cast) is 1/6. Reason r3: The probability of rolling a "2" (in the next cast) is also 1/6. Reason r4: The possibilities of rolling a "1" and of rolling a "2" are mutually exclusive. 1149 Reason r5: 1/6 + 1/6 = 1/3. Hence the thesis. A formal version of this argument may be clearer: Thesis q: P("1"∨"2"),di=1/3 – with di referring to a particular data base, e.g. Peter's knowledge exactly at 12 noon (five seconds later Peter may already know e.g. that "1" is true, hence: P("1"∨"2"),dj=1). Indicator of argument: Proof: r1: Additivity: If a and b are mutually exclusive then: P(a∨b),d = Pa,d + Pb,d, for all a, b, d. r2: P("1"),di=1/6. r3: P("2"),di=1/6. r4: P("1"&"2"),di=0. r5: 1/6 + 1/6 = 1/3. Q.e.d. In everyday life such explicit and extended arguments are virtually non-existent. But we may find abbreviated versions of them like this: "The probability of rolling a "1" or a "2" in the next cast is 1/3 because the probabilities of both these possibilities individually are 1/6; and because the two possibilities exclude each other their probabilities have to be added, which makes 1/3." So in this abridged version the reference to the data base is missing as well as the quote of the additivity axiom; and the mention of the mutual exclusiveness may be missing as well. Of course, for representing a valid argument the parts omitted in such an abridged argument must hold nonetheless and they must be reconstructable for an addressee. So we have to distinguish ideal, complete probabilistic arguments and non-ideal abridged versions of them whose validity is defined in terms of a corresponding ideal argument. Following these indications, I have tried to provide a reasonably precise definition of 'valid derivative probabilistic argument' in two steps, by first defining what an 'ideal valid derivative probabilistic argument' is and then giving the general definition. x is an ideal (argumentatively) valid derivative probabilistic argument, iff x satisfies the conditions PA0 to PA3. PA0.1: Domain of definition: x is a triple <r°,i,q>, consisting of 1. a set r° of judgements r1, r2, ..., rn, 2. an indicator i of argument, and 3. a judgement q. r1, ..., rn are called the "reasons for q" and q is called "the thesis of x". PA0.2: Structure of the argument: PA0.2.1: Type of thesis: q is of the form: 'The probability of a (given b) on the data base d is p.' (Pa,d=p or P(a/b),d=p). PA0.2.2: Kinds of reasons: 1. At least one of the reasons r1, ..., rn is an axiom or theorem of the probability calculus, hence a general probabilistic judgement. 2. The singular probability judgements among the reasons all refer to the data base d (cf. PA0.2.1) or in part to d and the other part to a predecessor dprior, i.e. d without some evidence e (dprior = d\e). PA1: Indicator of argument: i indicates that x is an argument, that r1, ..., rn are the reasons and that q is the thesis of x. In addition, i can indicate that x is a probabilistic argument. 1150 PA2: Guarantee of truth: PA2.1: True premises: The judgements ri are true. PA2.2: Inferential validity: The axioms and theorems of the probability calculus contained in r° and the other reasons perhaps contained in r° imply mathematically q – i.e. according to deductive and arithmetic rules. PA2.3: Best evidence: d does not contain information that permits stronger conclusions about a (or, respectively, about the conditional probability P(a/b),d). PA3: Adequacy in principle: x fulfils the standard function of arguments; i.e. x can guide a process of recognising the truth of q. PA3.1: The reasons r1 to rn are well-ordered, i.e. as chains of equations and insertions of data in general formulas. PA3.2: Apart from intermediate results, r° does not contain reasons that are superfluous for fulfilling the derivability condition PA2.2. PA3.3: There is a subject s and a time t for which the following holds: PA3.3.1: the subject s at the time t is linguistically competent, open-minded, discriminating and does not know a sufficiently strong justification for the thesis q;6 PA3.3.2: d refers to s' data base at t; and PA3.3.3: if at t x is presented to s and s closely follows this presentation this will make s justifiedly believe that the thesis q is acceptable; this process of cognition will work as follows: s will follow the chains of equations and insertions affirmed in r°, check their truth, thereby coming to a positive result. Explanation regarding PA0.2.1 and PA0.2.2: The thesis of a probabilistic argument in the sense used here is a singular probability judgement, i.e. judgement which attributes a specific probability to a specific proposition. So general probability judgements, i.e. in particular theorems of the probability calculus, are not included for the simple reason that such theorems can be justified in deductive arguments, deriving them deductively from the axioms of the probability calculus – like any mathematical theorem. Such arguments, as opposed to probabilistic arguments, do not depend on the particular data base; their theses are general judgements quantifying over any data base d (cf. the examples given in sect. 5), they are not relative to a particular data base (as di in the example given at the beginning of this section). Only the dependence on a specific data base requires the particular conditions of probabilistic arguments such as the conditions 'best evidence' (PA2.3) or 'data base' (see below, PA5.5). x is a (argumentatively) valid derivative probabilistic argument, iff x satisfies the conditions PA4.1 or PA4.2. PA4.1: Ideal argument: x is an ideal valid derivative probabilistic argument, or PA4.2: Abridged argument: x is not an ideal valid derivative probabilistic argument, but there is such an (ideal valid derivative probabilistic) argument y which to a certain extent is identical with x but for which the following holds: 1. The set of reasons rx° of x is a subset of the set of reasons ry° of y or of abridged versions of these reasons (cf. PA4.2.3). 2. The reasons perhaps missing in rx° are axioms or theorems of the probability calculus or they represent intermediate results; and the chain of equations is not interrupted by these omissions. 3. In the thesis q or in some of the probabilistic reasons of x the reference to the data base d may be omitted. 4. Condition PA3.3 holds analogously also for x. 1151 Valid arguments are instruments for fulfilling a certain function, namely the function to lead to the cognition of the thesis; like all instruments they can fulfil their function only if they are used properly. In particular the valid argument must fit with the addressee's cognitive situation. In the following the adequacy conditions for an epistemically successful use of probabilistic arguments for rationally convincing are sketched. The most particular among these conditions is that the data base referred to in the argument has to be more or less identical to the data base of the addressee (PA5.5). A valid probabilistic argument x is adequate for rationally convincing an addressee h (hearer) at t of the thesis (q) of x and for making him adopt the thesis' probability for himself iff condition PA5 holds: PA5: Situational adequacy: PA5.1: Rationality of the addressee: The addressee h (at t) is linguistically competent, open-minded, discriminating and does not have a sufficiently strong justification for the thesis q. PA5.2: Argumentative knowledge (of the addressee): The addressee h at t knows at least implicitly the idea of the probability calculus and the mathematics used in x. PA5.3: Explicitness: If x is not an ideal argument such that r° does not contain all the reasons of the corresponding ideal argument the addressee h at t is able to add the most important of the missing reasons. PA5.4: Acceptance of the reasons: The addressee h at t has recognised the truth of the reasons ri of x and, in the case of non-ideal arguments, of its corresponding ideal or is able to recognise them immediately. And PA5.5: Data base: The data base dht of h at t is identical to d or so near to d that the resulting probabilities regarding the reasons ri and the thesis q remain unaltered. The just defined probabilistic arguments are not special kinds of deductive arguments or reducible to them. One highlight of the present approach is to make the relativity of probabilistic arguments to specific data bases explicit, by inserting a reference to the data base d, thus resolving the problems of logical non-monotonicity. As a consequence of this explicit relativity to the data base, the arguments can be and have to be (cf. PA2.2, inferential validity) deductively valid; in addition their reasons can be true – even the singular probability judgements among the premises. The problem of probabilistic arguments, i.e. to be only a substitute for stronger arguments in case of insufficient knowledge, which leads to non-monotonicity, however, cannot be eliminated entirely. Here it has been shifted to the pragmatic adequacy conditions, where PA5.5 requires to use an argument with a data base fitting to the addressee. Of course, the addressee may be convinced by an argument that refers to a different data base dj that the probability of an event a on the data base dj is pj; however, if dj is not the addressee's data base at the time being he will not adopt pj as his probability. Deductive arguments do not contain any comparable restriction because they are not relative to the data base; for being rationally convincing the addressee has to be convinced of their premises, yes; but this is not yet a general dependency on the data base. Instead of being logically non-monotonic, probabilistic arguments as they are conceived here are "pragmatically non-monotonic" in the sense of getting pragmatically irrelevant when the data base does no longer fit to the addressee's changed data base. Further irreducible differences with respect to deductive arguments then are that this relativity to the data base also shows up in the adequacy in principle condition (PA3.3.2), that references to a data base are part of the structure of ideal probabilistic arguments (cf. PA0.2.1, PA0.2.2.2) and, finally, the best evidence requirement (PA2.3). 1152 The just provided definitions show that it is possible to develop clear, reasoningguiding and epistemologically justified criteria for probabilistic arguments, which do justice to requirements of objective validity as well to adaptation to the specific epistemic limits of the argument's addressees.7 Notes 1 Proponents of the epistemological approach to argumentation are e.g. Mark Battersby, John Biro, Richard Feldman, Alvin Goldman, Christoph Lumer, Harvey Siegel and Mark Weinstein. An overview of this approach (including bibliography) is provided in: Lumer 2005a. 2 Several other forms of probabilistic arguments and fallacies have been analysed (e.g. Korb 2004; Hahn & Oaksford 2006; 2007), without however providing precise criteria for such arguments. 3 This dismissal as a general theory does not exclude that equiprobability settings play an important role in situations under complete uncertainty about frequentist probabilities. 4 Here and in the following I omit the time variable of 'belief'. 5 The tendency of evidence should be distinguished from the degree or strength of evidence. We may have strong or weak evidence with the same tendency, i.e. for the same probability. We may e.g. have counted 30 black and 60 white balls before putting them into an urn and therefore have strong evidence that the probability of picking a white ball at random is 2/3; and, in a different setting, we may have picked (with replacement) nine balls from the urn, three of them being black and six of them being white, and because of this have the weaker evidence that the probability of picking a white ball at random is again 2/3. 6 That s is "linguistically competent" shall mean that she knows the semantics, syntax and expressions used in the argument; this includes knowledge about the probability concept and the parts of the probability calculus used in the argument. "Openmindedness" refers to the disposition to form one's opinions by rational cognition and not on the basis of prejudices or emotions. A person is "discriminating" if she has the basic faculty of basic cognition and is able to organize respectively complex processes of cognition. (Cf. Lumer 1990, pp. 43 f.) 7 I would like to thank two anonymous referees for their valuable comments. REFERENCES Biro, J.I. (1987). A Sketch of an Epistemic Theory of Fallacies. In F.H. van Eemeren [et al.] (Eds.), Argumentation, Analysis and Practics. Proceedings of the 1986 Amsterdam Conference on Argumentation (pp. 65-73). Dordrecht: Foris. Biro, J.I., & Siegel, H. (1992). Normativity, Argumentation and an Epistemic Theory of Fallacies. In F.H. van Eemeren [et al.] (Eds.), Argumentation Illuminated (pp. 85-103). Amsterdam: SicSat. Carnap, R. (1950). Logical Foundations of Probability. Chicago: University of Chicago Press. 1153 Carnap, R. (1952). The Continuum of Inductive Methods. Chicago: University of Chicago Press. Eells, E. (1982). Rational decision and causality. Cambridge: Cambridge U.P. Feldman, R. (<1993> 1999). Reason and Argument. 2nd Edition. Upper Saddle River, N.J.: Prentice-Hall 1st ed. 1993; 2nd ed. 1999. Gillies, D. (2000). Varieties of Propensity. British Journal for the Philosophy of Science 51, 807-835. Goldman, A.I. (1999). Knowledge in a Social World. Oxford: Clarendon. Goldman, A.I. (2003). An Epistemological Approach to Argumentation. Informal Logic, 23, 51-63. Hacking, I. (1965). The Logic of Statistical Inference. Cambridge: Cambridge U.P. Hacking, I. (2001). An Introduction to Probability and Inductive Logic. Cambridge: Cambridge U.P. Hahn, U., & Oaksford, M. (2006). A Normative Theory of Argument Strength. Informal Logic, 26, 1-24. Hahn, U., & Oaksford, M. (2007). The Rationality of Informal Argumentation: A Bayesian Approach to Reasoning Fallacies. Psychological Review, 114, 704732. Hájek, A. (<2002> 2009). Interpretations of Probability. Stanford Encyclopedia of Philosophy. Web publication: <http://plato.stanford.edu/entries/probabilityinterpret/>, first published 21 October 2002; substantial revisions 31 December 2009. Hansson, S.O. (2004). Philosophical Perspectives on Risk. Techne, 8(1). Humphrey, P. (1985). Why Propensities Cannot Be Probabilities. Philosophical Review, 94, 557-570. Korb, K.B. (2004). Bayesian Informal Logic and Fallacy. Informal Logic, 24, 41-70. Lumer, Ch. (1990). Praktische Argumentationstheorie: Theoretische Grundlagen, praktische Begründung und Regeln wichtiger Argumentationsarten. Braunschweig: Vieweg. Lumer, Ch. (1991). Structure and Function of Argumentations: An Epistemological Approach to Determining Criteria for the Validity and Adequacy of Argumentations. In F.H. van Eemeren [et al.] (Eds.), Proceedings of the Second International Conference on Argumentation (pp. 98-107). Amsterdam: Sicsat. Lumer, Ch. (2005a). The Epistemological Approach to Argumentation: A Map. Informal Logic, 25, 189-212. Lumer, Ch. (2005b). The Epistemological Theory of Argument – How and Why? Informal Logic, 25, 213-243. Mellor, D.H. (2005). Probability: A Philosophical Introduction. London / New York: Routledge. Miller, D.W. (1994). Critical Rationalism: A Restastement and Defence. Chicago: Open Court. Popper, K.R. (1959). The Propensity Interpretation of Probability. British Journal for the Philosophy of Science, 10, 25-42. Ramsey, F.P. (<1926> 1931). Truth and Probability. (1926.) In F.P. Ramsey, The Foundations of Mathematics and Other Logical Essays (pp. 156-198), ed. by R. B. Braithwaite. London: Routledge and Kegan Paul 1931. Reichenbach, H. (<1935> 1949). Wahrscheinlichkeitslehre: Eine Untersuchung über die logischen und mathematischen Grundlagen der Wahrscheinlichkeitsrechnung. (1935.) – Enlarged English translation: The Theory of Probability: An Inquiry into the Logical and Mathematical 1154 Foundations of the Calculus of Probability. Berkeley: University of California Press 1949. Siegel, H., & Biro, J. (1997). Epistemic normativity, argumentation, and fallacies. Argumentation, 11, 277-292. Venn, J. (<1866> 2006). The Logic of Chance. (1st ed. 1866.) Mineola, NY: Dover Publications 5th ed. 2006. von Mises, R. (<1928> 1981). Wahrscheinlichkeit, Statistik und Wahrheit. Wien: J. Springer 1928. – 2nd revised English edition: Probability, Statistics and Truth. New York: Dover 1981.


Philosophy

In this collection of essays, Strawson investigates wide-ranging topics pertaining to the nature of the self: What do we mean by the term âselfâ? In what sense do selves exist? To what extent is continuity over time essential to selfhood? Must one be able to make a story of oneâs life in order to be a coherent self? Must one be self-conscious in order to be conscious at all? and more. The fourteen essays here are not necessarily meant to be read in order. They do not offer a sustained argument, but rather a number of themes
          that appear in different places, like threads in a tapestry.

Philosophy Now – Issue 138 https://philosophynow.org/issues/138/The_Subject_of_Experience_by_Galen_Strawson The Subject of Experience by Galen Strawson Bill Meacham subjects Galen Strawson to his critical experience. The Oracle at Delphi famously advised us to know ourselves. But what is the self which is to be known? This question is at the heart of contemporary British philosopher Galen Strawson's The Subject of Experience. In this collection of essays, Strawson investigates wide-ranging topics pertaining to the nature of the self: What do we mean by the term 'self'? In what sense do selves exist? To what extent is continuity over time essential to selfhood? Must one be able to make a story of one's life in order to be a coherent self? Must one be self-conscious in order to be conscious at all? and more. The fourteen essays here are not necessarily meant to be read in order. They do not offer a sustained argument, but rather a number of themes that appear in different places, like threads in a tapestry. These themes cover so much ground that it would be impossible to do justice to them all in a short review, so I'll just touch on a few salient ones. The first theme is what is meant by the term 'self'. Strawson is a professional analytic philosopher, and one of his strengths is a careful attention to conceptual nuances. Noting that from an early age we realize that our thoughts are private, that is, not observable by others, he asserts that we all have a sense of ourselves as something mental, distinct from our bodies. Whether this sense is accurate is another question; but he says that it has eight components. We ordinarily conceive of or experience our selves in eight ways, listed from the most fundamental to the most broad as follows (p.19). We think of ourself as: 1) A thing or entity; 2) A mental or subjective entity; 3) A single entity when considered at a point in time (synchronically); 4) A single entity when considered over some duration of time (diachronically); 5) Ontically (really or metaphysically) distinct from all other things; 6) A subject of experience – a conscious feeler and thinker; 7) An agent, with choices; and 8) Having a certain character or personality. That's quite a list. The virtue of an analytic approach is that it helps us avoid ambiguity and equivocation. When we make assertions about the self, it helps to know which of these aspects of selfhood we mean. If I tell you that I ate the candy, 'I' refers to me as an agent (#7 in the list): I and not someone else ate the candy. But if I tell you that I didn't really do it, but rather my addiction to sweets overcame me, 'I' here means something else – something 'ontically' or really distinct from my cravings (#5). The Subject of Experience by Galen Strawson | Issue 138 | Philosophy Now https://philosophynow.org/issues/138/The_Subject_of_Experience_by_G... 1 of 5 6/18/2020, 8:57 AM It won't do to ask which of these is the right meaning, as if there could be only one. The analytic approach encourages us to be more precise, and say which sense of 'I' is being used on any given occasion. Consider the question of self as subject of experience (#6). Strawson goes on to list three conceptions of subjecthood (pp.171-172): 1) Human beings along with other animals can be generally said to be subjects of experience. Strawson calls this the 'thick' conception. 2) A subject of experience can be thought of as "some sort of persisting inner locus of consciousness – an inner someone, an inner mental presence". This he calls the 'traditional inner' conception. 3) A subject of experience can be "an inner thing of some sort that exists if and only if experience exists of which it is the subject." This he calls the 'thin' conception. Conceptions 1 and 2 assume that a subject of experience continues to exist even when not having any actual experience, as in dreamless sleep or when heavily sedated. In conceptions 2 and 3, the subject is something different from, or at least distinct from, the whole person taken as body and mind together. Conception 3 reserves the term 'subject' for that which gives unity to an individual moment or episode of experience, and so operates only during that moment or episode of being conscious (this conception of the self was a real difficulty for René Descartes). That there is a unity to episodes of human experience Strawson takes as incontrovertible. In addition to being an analytic philosopher, Strawson is also a phenomenologist, that is, someone who has examined his own experience in some analytical detail. This gives him an edge over those who rely on linguistic or conceptual analysis alone in understanding the self. His description of experience is worth quoting at length: "The total experiential field involves many things – rich interoceptive (somatosensory) and exteroceptive sensation, mood-and-affect-tone, deep conceptual animation, and so on. It has, standardly, a particular focus, and more or less dim peripheral areas, and is, overall, extraordinarily complex in content. But it is for all that a unity... simply in being, indeed, a total experiential field; or equivalently, simply in being the content of the experience of a single subject at that moment. The unity or singleness of the (thin) subject of the total experiential field in the living moment of experience and the unity or singleness of the total experiential field are aspects of the same thing." (p.179) This 'same thing' is an occasion or moment of experience. That each moment of experience is unitive leads Strawson in two directions philosophically. One is toward a conception of personal identity; and the other toward a conception of the ultimate nature of reality. Personal Identity The question of personal identity is central to this book. Strawson reminds us that the ordinary conception of selfhood –the second one above – is of a persisting inner locus of being conscious of one's world (and, I would add, of acting on it too). We think of ourselves as experiencing beings having long-term continuity over time. We wake up in the morning, and without having to think about it, recognize that we are the same person who fell asleep the night before. Strawson thinks that this impression of sameness or continuity is an illusion. What is really real, he says, is conception 3 – a subject of experience that exists only while it experiences. He says this partly on conceptual grounds – how can there be a 'subject of experience' when there is no experience? – and partly on methodological grounds: he thinks that when it comes to metaphysical discussions of selfhood, one has to The Subject of Experience by Galen Strawson | Issue 138 | Philosophy Now https://philosophynow.org/issues/138/The_Subject_of_Experience_by_G... 2 of 5 6/18/2020, 8:57 AM start phenomenologically, by analysing what is actually given in experience (pp.44-45). What is given in experience is episodic moments of experience, not an experience of continuity. As Strawson says, the basic form of our experience is "a gappy series of eruptions of consciousness out of non-consciousness" (p.73). (He adds, "although the gaps are not usually phenomenologically apparent", which seems to call into question his phenomenological premise. This difficulty is resolved by affirming the need to observe more carefully than we usually do what actually goes on in our experience. He recommends the practice of mindfulness meditation to hone such an ability (p.70, p.154 fn. 51).) One might reasonably ask then, where our sense of personal continuity comes from? How do we know we are the same person as we were, not only when we wake up in the morning, but from moment to moment? In response, Strawson agrees with the great American psychologist and philosopher William James (1842-1910), who says that we each consist of a great many short-lived selves. Each momentary self appropriates the experience of its predecessor through the immediately preceding contents of experience forming part of the context in which each new moment of experience arises. This context is both outer and inner; both objective and subjective. Objectively, our present situation usually has an expected continuity with the situation previously experienced. We most often wake up in a familiar place and find it no surprise. Subjectively, we find we have familiar bodily sensations, as well as familiar thoughts, feelings, moods, and so forth. As Strawson says, we have a "constant background awareness of our own mental goings on" (p.47). This familiarity leads us to think of ourselves as the same person we were previously. This sense can change over time, of course. Our sense of self usually changes unnoticeably in small increments from moment to moment, and the difference becomes apparent only when contrasted to some far earlier time. In cases of religious or moral conversion, the change in sense of self may happen rapidly. But even in that case there is a sense of continuity: we know that we are the same person who was thinking differently before. So are we really only a gappy series of momentary subjects of experience; or are we really a continuous being who persists over time? There is no one correct answer to this question. The useful answer depends on the context of inquiry, on what issue we are trying to clarify. For most practical purposes we can confidently affirm that a human being is a persisting psychophysical whole. Certainly, it would be hard to get around in the social world without such a belief. But for questions of fundamental metaphysics, the gappy, momentary nature of serialized selfhood seems quite plausible. And if the Buddhists are to be believed, recognizing this lack of a permanent self is a step toward liberation from suffering. Strawson's contribution is to clarify, sometimes in painstaking detail, just what is involved in such considerations. Image by Paul Gregory The Nature of Reality The idea of the unitive nature of moments of experience leads Strawson to a view of the ultimate nature of reality as well. He is a pluralist, believing that many things exist (using 'thing' in a loose sense). For instance, "there is a plurality of fundamental physical entities (leptons and quarks, say, or 'fields', 'loops', The Subject of Experience by Galen Strawson | Issue 138 | Philosophy Now https://philosophynow.org/issues/138/The_Subject_of_Experience_by_G... 3 of 5 6/18/2020, 8:57 AM 'field quanta'...) or as I will say 'ultimates'."(p.174). But he is also an attributive monist, saying that each of these ultimates is of the same kind; that each is composed of the same kind of stuff (again, using 'stuff' in a loose sense). Strawson's model for the ultimate stuff is a moment of experience consisting of a 'thin' subject (conception #3) and its total experiential field. (His argument for this position can be read in his paper 'Realistic Monism', available on Academia.edu.) Each ultimate, or 'concretely actualized' entity, is, he says, "a concretely existing total experiential field and a concretely existing subject for whom that field is an experiential field" (p.185). This is just what process philosopher Alfred North Whitehead (1861-1947) took to be the nature of what is ultimately real, which he variously called an actual entity, an actual occasion, and an occasion of experience (See Process and Reality, Part 1, Ch. 2, sec. 1, and Adventures of Ideas, p. 221.) So Strawson gives support for Whitehead's process panpsychism, despite his reluctance to put himself in the same category as Whitehead. Consciousness of Consciousness One of Strawson's many other themes is worth a mention. He claims that "All consciousness involves consciousness of that very consciousness" (p.143). Such involvement is 'pre-reflective', 'immanent', and 'non-positional' (p.155). In other words, this is not something you deliberately do. Strawson claims to know the truth of these assertions from his examination of his own experience. I don't find his argument here (such as it is) persuasive at all. In examining my own experience, I find numerous instances of being conscious that involve no trace of being conscious of being conscious – being absorbed in an engaging task, for instance, or in a good book. (I treat this question in detail at bmeacham.com/blog /?p=1660.) Strawson can assert that when I am conscious I am always conscious of being conscious (in addition to whatever I am focusing on), but he can't prove it. And I can't prove that he's wrong, either. The issue is about subjective experience, which is private, not public, and so not objectively either verifiable or falsifiable. The point is that the idea is not amenable to objective verification. The best we can do is to describe our experience in terms that are as unambiguous as possible, so we can at least understand what the other is saying. That itself is a difficult task, and unfortunately, Strawson is here not as careful with his vocabulary as he could be. It's difficult because what we're trying to talk about is not public, which means that the words that one person uses to describe their experience may not mean the same to someone else. The difficulty is compounded in English because we have relevant words that mean roughly the same thing. The words 'conscious' and 'aware', for instance, both translate to a single word in Spanish (consciente) and German (bewusst), so one might think that the two English words are synonyms. And so they are; but not quite. There is still ample room for ambiguity. Strawson says for instance, "By 'awareness' (the mass term) I'll always mean 'conscious awareness'... I'll also use 'consciousness'... for what I mean by 'experience' or 'awareness'." (p.137) In a footnote, he further contrasts this use of 'awareness' to one that means, roughly, knowledge. In this latter sense, one can be said to be aware of a great many things – the current crisis, for instance – even when in deep sleep. By 'conscious awareness', Strawson does not mean awareness in the sense of knowledge. Even so, if 'awareness' means 'conscious awareness', and he uses 'consciousness' to mean 'awareness', then 'conscious awareness' is synonymous with 'conscious consciousness', which is redundant. He also says, "there are contexts in which it makes sense to speak of unconscious awareness" (p.193, fn. 11). What is this unconscious awareness? Substituting putative synonyms, we get 'unconscious consciousness', which is nonsense. Does he mean unconscious knowledge here? If so, he should say so. Strawson may assume that his meaning is sufficiently clear in context. The words 'consciousness', 'awareness', and the like, are familiar ones. But too often readers think they know what a word means just because it is familiar. What they think it means might not be what the author intended. One would hope that a The Subject of Experience by Galen Strawson | Issue 138 | Philosophy Now https://philosophynow.org/issues/138/The_Subject_of_Experience_by_G... 4 of 5 6/18/2020, 8:57 AM philosopher in the analytic tradition would take extra pains to be more careful about this, especially dealing with language so fraught with possibilities for misunderstanding. That being said, this book is worthwhile. I have touched on only a few of its topics; there are a lot more. It's not an easy book. Strawson's work is difficult, but rewarding. If you want a popular, breezy run-through of some ideas on selfhood, then you'd best look elsewhere. But if you enjoy reading a text slowly and carefully, pausing to reflect on, understand, and perhaps argue with the author's assertions, then The Subject of Experience should prove quite gratifying. © Dr Bill Meacham 2020 Bill Meacham received his PhD from the University of Texas at Austin, made his living as a computer programmer, systems analyst and project manager, and is the author of How To Be An Excellent Human and How To Exert Free Will. These and other works can be found at bmeacham.com. • The Subject of Experience by Galen Strawson, Oxford University Press, 2017, $22 pb, 336 pages. ISBN: 978-0198801580 The Subject of Experience by Galen Strawson | Issue 138 | Philosophy Now https://philosophynow.org/issues/138/The_Subject_of_Experience_by_G... 5 of 5 6/18/2020, 8:57 AM


Philosophy

Open Journal of Philosophy, 2016, 6, 412-419 http://www.scirp.org/journal/ojpp ISSN Online: 2163-9442 ISSN Print: 2163-9434 DOI: 10.4236/ojpp.2016.64038 November 2, 2016 Meteorite Impact Origin of Yellowstone Hotspot Hermann G. W. Burchard Department of Mathematics, Oklahoma State University, Stillwater, USA Abstract Origin of the Yellowstone hotspot & Columbia River Basalts has remained uncertain until now. Here, we present evidence of meteorite impact origin. The hotspot is shallow, only 200 km deep, invalidating a theory of mantle plume origin. The hotspot track runs from the Yellowstone National Park in NW Wyoming to the volcanic Modoc Plateau in NE California. We present evidence of apparent remnants of an impact crater existing in the Modoc, a large multi-ring structure at least 160 km diameter. Much of the complex crater has become obliterated by later Cascadia and Sierra orogenies. The crater has a tall 4,100 foot central uplift cone, locally known as Chalk Mountain, consisting of diatomaceous earth, presumably the rebound cone of a meteorite impact. This falsifies a theoretical prohibition of cosmic impact volcanism. Based on recent insights into explosive volcanism a plausible mechanism is proposed for how meteorite impacts can lead to resurgent calderas of the Yellowstone type, & of apparent LIP origin from thin crust ET impacts, invalidating theoretical constructs of mantle plumes. We mention chaotic terrains, including plutons, arising antipodal to impacts. Keywords Yellowstone Hotspot, Meteorite Impact, Mantle Plume, Impact Volcanism, Explosive Volcanism, Mantle Chemistry, Dissolved Volatiles, Diffusive Replenishment, Multi-Ring Impact Structure, Central Uplift, Diatomaceous Earth, Thin-Crust Impact 1. Yellow Stone Thermal Anomaly, Onset 16.6 Ma NE California The Yellowstone thermal anomaly has produced magmatic outflows for about 17 Ma, starting from the Modoc Plateau in NE California. Various theories regarding the origin of the Yellowstone "hotspot" (YS) have been proposed, e.g., the mantle plume theory of Canadian geologist J. Tuzo Wilson (Wilson, 1963) but usually credited to Princeton University geologist W. Jason Morgan (Morgan, 1971), and the competitive How to cite this paper: Burchard, H. G. W. (2016). Meteorite Impact Origin of Yellowstone Hotspot. Open Journal of Philosophy, 6, 412-419. http://dx.doi.org/10.4236/ojpp.2016.64038 Received: October 14, 2016 Accepted: October 30, 2016 Published: November 2, 2016 Copyright © 2016 by author and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY 4.0). http://creativecommons.org/licenses/by/4.0/ Open Access H. G. W. Burchard 413 plate tectonic theory of Donald Anderson (Anderson & Natland, 2005). All of these can now be refuted. We propose to prove conclusively the origin of YS by meteorite (ET) impact on the Modoc plateau at about 16.6 Ma. A plausible mechanism is presented of how an ET impact can produce a hotspot type thermal anomaly. A large igneous province (LIP) normally will be left behind as it did in the case of YS, the widely familiar Columbia River Basalt Province (CRBP), in the US Pacific NW of N California, Oregon and Washington. LIPs are found around the globe, and apparently the origins of many or even most of these are oceanic, although quite a few occur at margins of continents or even are centrally located at least at present. Eruptions continue with the progress of time forming resurgent calderas which may result in a hotspot track. Reproduced below as Figure 1 is an instructive geographical diagram (Foulger, 2006, Figure 2 with permission) of calderas in the NW United States along the track of the YS hotspot from the Modoc to NW Wyoming. The YS thermal anomaly is restricted to the upper mantle, reaching down to a depth of only about 200 km (Christiansen, Foulger, & Evans, 2002). Among several more recent papers coming to the same conclusion, cf. the article by Fouch (Fouch, 2012). Being limited in extent to the upper mantle, there can be no thought of it coming into existence by upwelling from the core-mantle boundary, the so-called D" layer. Figure 1. The Yellowstone resurgent calderas forming the hotspot track from NE California to the National Park in NW Wyoming (courtesy of mantleplumes.org). Also shown are various lithological units of the Columbia River Basalt Province. H. G. W. Burchard 414 Mantle plumes have never been observed by seismic tomography, and would not be likely to be seen even if such existed, because the mantle is essentially transparent to seismic tomography. Not to mention the mathematical difficulties of deconvolution involved, an inherently unstable process, even if all else was favorable. Using continental as well as oceanic empirical data from the Pacific Ocean and the Gulf of Mexico Nash-Perkins discovered that the Yellowstone "hotspot" thermal anomaly (YS) in the mantle produced more than one hundred forty caldera eruptions, resulting in the creation of a hotspot track from NE California to NW Wyoming, caused by volcanic activity with eruptions piercing the crust above (Nash & Perkins, 2002, 2012). As the crustal plate shifts across the anomaly due to plate tectonics this leads to a series of giant volcanic calderas of the resurgent or supervolcano type strung out along a line, called a hotspot track, from NE California through N Nevada and S Idaho to the present location of the National Park in NW Wyoming. The post-impact calderas are age limited by the earliest one among them, High Rock Caldera just East of the Nevada-California state line, which dates to about 16.4 Ma (Nash & Perkins, 2002, 2012). The age of the total magmatic complex including the CRBP extends to 16.6 Ma by dating basaltic & silicic eruptives. For a detailed geological description and analysis see the article by G. R. Foulger on her mantleplumes.org website. 2. YS Meteorite Impact Crater Found Additionally for this case, we are very fortunate in that a large caldera, located in the Modoc plateau and at least 160 km in diameter, a compound crater created by cosmic body impact, has been found and now can be reported here. The crater is at the precise location (the Modoc plateau in NE California) where one would expect the very starting point of the YS hotspot track of Mid-Miocene age, by the Nash-Perkins date of 16.6 Ma (Nash & Perkins, 2002, 2012). There are two parts of the impact structure that have been identified so far, mere remnants of the original impact crater as the entire region has been subject to extensive geological reworking by at least two orogenies, the Cascades and the Sierra, at this western cratonal margin of the North American continent. The greater part still awaits mapping and detailed geological study. Reported here for the first time is our discovery of a part characteristic of many impact craters, the central ring wall structure and central uplift, locally known as "Chalk Mountain", located in Shasta County, Northern California. Here, the underlying sedimentary layers of diatoms have surged into a giant central cone of 4,100 ft eminence above a circular moat inside a 40 km diameter ring wall. The very size of this central rebound cone speaks to the magnitude of the impact. Map coordinates at the summit are 40.994N, 121.809W1. Chalk Mountain rises to an altitude of 5800 ft above sea level at the center of the crater wall. The circular moat forms a canyon in which the Pit River flows winding around 1Best seen on terrain maps. H. G. W. Burchard 415 Chalk Mountain in a wide, almost semicircular bend. The river's turn as it departs from the canyon gives its name to the town of Big Bend, Shasta County (elevation 1,700 ft). A second, non-central, outlier part of the crater had been discovered earlier, as the initial discovery of the the caldera by Tom Bowens in his 1998 MS thesis at CSM (Bowens & Gross, 1998)2. Bowens & Gross indicate that they believe the center of the caldera to be located in Stone Coal Valley, 40 km WSW of the city of Alturas, CA. The map coordinates are 41.364N, 121.019W. However as stated, the actual center of the impact crater is located approximately a further 80 km WSW of Stone Coal Valley, at Chalk Mountain. Tom also has an AGU joint abstract with his advisor that provides additional detail of the caldera (Bowens & Gross, 2001). The delay of three years after graduation from CSM may be the result of later, post-thesis study, as the remarks in the abstract do not appear to be represented fully in the text of the thesis. In their abstract, the authors have described the structure in considerable geological detail, reproduced here next: Regional geologic mapping within the Modoc Plateau has resulted in the discovery of a large volcano-tectonic anomaly some 21-km in diameter approximately 50-km WSW of the city of Alturas in Modoc County, California. Centrally located within this anomaly lies a structural depression some 11-km in diameter which, based on structural, lithologic, and geophysical characteristics, is believed to represent a deeply eroded mid-Miocene caldera. The region extending outward some 5-km from the proposed caldera displays a sharp, localized structural deflection from a NNW to a WNW structural grain. Lying inboard of this deflection, a series of regionally discordant E-W to NE trending, generally down to the north, normal faults were discovered which are believed to represent rim faults to an ancient caldera. Bedding within the hanging wall of these discordant structures displays highly contorted and regionally anomalous dips. By stereographic removal of the regional northeast dip overprinting the area, the anomalous dips were found to display a radial, steeply inward dipping pattern in close proximity to the proposed rim structures while dips located further inboard are generally flatlying . Lithologies within the proposed caldera are regionally anomalous and include abundant tuffaceous and flow dominated breccias, closed basin organic sedimentary facies, and an anomalous concentration of volcanic centers of both mafic and felsic compositions. One of these intrusives was age dated at 12.9 Ma indicating the anomaly formed during mid-Miocene time. The location of the proposed caldera is associated with a 20 mgal gravity high, which stands in contrast to a lesser high of 10 mgal associated with the Medicine Lake Caldera some 50-km to the northwest. Tom Bowens and his advisor appear to have been unaware of Chalk Mountain (Figure 2) as actual center rebound of their caldera. Located in the middle of the volcanic Modoc plateau, Chalk Mountain is an oddity being composed, as the name suggests, of diatomaceous earth which underlies the entire volcanic region in a thickness of up to 100 ft3. 2Tom now is working as an executive for a mining company active in Siberia. 3http://shastacascade.com/accountdetails.php?id=1915 H. G. W. Burchard 416 Figure 2. On the lower left, the inner crater ring, at its center Chalk Mountain, SE from the town of Big Bend. To the ENE, remnants of two outer rings. At a distance of 80 km ENE, Stone Coal Valley is the marked site on the second outer ring, where Tom Bowens found (parts of) a caldera (Google terrain). The geographic region shown measures 150 × 100 km approximately. The combined structure of Stone Coal Valley as described in the Bowens-Gross abstract and of Big Bend-Pit river-Chalk Mountain presumably is the remnant of a much larger multi-ring formation, which in turn suggests a very large impact, that still is partially visible but mostly became obliterated during subsequent Cascadian orogeny (6 Ma) in the West and North and an ongoing Sierra Nevada uplift process since Eocene times in the South. The original caldera would have been at least 160 km in diameter. As described here, the caldera may be identified as of cosmic object impact origin from its characteristic central rebound uplift made of sedimentary non-volcanic material, and therefore of unquestionable ET impact origin. It can now be identified as the YS impact crater, by its geographic location at the head of the YS hotspot track, as seen from the graphic in the mantleplumes.org website shown above. Field research in the Modoc Plateau, additional to the detailed cited results of Tom Bowens, will confirm this our first report of a 160 km Modoc Crater, and establish further criteria through mapping of the exact extent and age of the partially obliterated impact structure in all its details, which will bring out the system of rim faults, remnants of the multi-ring complex impact crater. It would be shown to precede orogenies that have occurred in the region after the mid-Miocene impact event. 3. Explosive Volcanism and ET Origin of Hotspots and LIPs Here we explain a hotspot generation mechanism by cosmic body impact, which indicates how LIPs can be derived from thin crust large impacts-probably comets from H. G. W. Burchard 417 Centaur & Kuiper belts or perhaps Oort cloud-thin crust implies a deep oceanic site, with few exceptions, such as the exceptional YS/CRBP impact considered here, which occurred in shelf sediments at or near the cratonal margin. The YS impact was in fact thin crust, but probably on the outer continental shelf or slope back in the Miocene, and that is why it is chalk, unlike the surrounding igneous rocks. Tom Bowens in an email to me stated that when he did his thesis, he had thought that his Stone Coal Caldera must have to do with Yellowstone. Our present understanding of explosive volcanism, and of the importance of volatiles, largely is due to Steve Sparks, Bristol University (Gilbert & Sparks, 1998). Steve Sparks has won several prestigious awards, including the 2015 Vetlesen prize, LDEO, Columbia Univ, considered the "Nobel prize of the Earth Sciences." Sparks has given the explanation for the lower solidus due to dissolved volatiles (Sparks, 2003): Degassing has profound effects on the phase equilibria of magmas, because rather small amounts of water dissolved in magmas can reduce their liquidus temperature [and hence the solidus] by hundreds of degrees. Conversely, degassing can cause spontaneous crystallization. While these effects have been known about for many decades, it is only relatively recently that their significance for understanding volcanic processes had been widely appreciated. Crystallization due to degassing may prove as important as cooling in igneous petrogenesis. Based on this, we next are able to suggest a plausible mechanism for the generation of hotspots by thin-crust bolide impact typically applicable to oceanic impacts which are responsible for Large Igneous Provinces (LIP). The volcanism is explosive & resurgent because the volatiles come out of solution in the explosion and thereby are depleted locally in the mantle. The cavity almost immediately collapses & refills, so a new cycle starts: The volatiles by diffusion replenish the magmatic melt from surrounding mantle volumes in the vicinity, and this eventually leads to another explosion. The time factor for the diffusive replenishment is important and changes as the hotspot evolves, according to the findings of Nash-Perkins (Nash & Perkins, 2002). In their study of the YS ash layer sequence, marking caldera eruptions, they found initial time intervals of a few ten thousand years, evolving to 600,000 years in the later to recent stage of YS. As time progresses, the hotspot anomaly extends to a greater volume enlarging itself both in depth and width. In the case of the Hawaiian hotspot4, there has been a late evolution to a nearly continuous eruption. 4. Conclusion So here, we have a key example in Yellowstone, the most famous hotspot, & the Columbia River Basalts, perhaps the most famous LIP, at least the first one of which I had ever heard, provably not resulting from a deep mantle plume but from a Miocene impact crater in the Modoc plateau from where the hotspot track goes ENE straight toward NW Wyoming, site of the present-day National Park. 4Here believed to be similarly generated by end-Permian impacts in the West-Siberian Basin & S Kara Sea (unpublished). H. G. W. Burchard 418 Here reported in this essay, we are demonstrating that this LIP, and hence presumably all LIPs, are caused by cosmic object-bolide meteorite-impacts, on the strength of our discovery of parts of a cosmogenic complex impact crater, the Bowens Stone Coal Valley Caldera and 80 km to the WSW the true center Chalk Mountain within a 40 km innermost circular ring wall, at the exact place in NE California, the volcanic Modoc plateau from where the line of YS supervolcano calderas appears to emerge. Also based on prior geological work cited above, we are able to put to rest two classical geological theories that up until now have been accepted widely, the Morgan theory of mantle plumes and the no-impact-volcanism theory of Ivanov-Melosh. This example can serve as a perfect test case because the Yellowstone hotspot cannot have arisen from deep mantle convection as demonstrated in the above cited article by Christiansen et al. (2002). Instead, above we have proved the origin by a large bolide meteorite impact in the volcanic Modoc plateau. The issue of impact volcanism has been a concern for years, geologists being largely gathered behind the Wilson-Morgan idea of mantle plumes rising from the core-mantle boundary, a narrow zone called the D" (Wilson, 1963; Morgan, 1971). These plumes are held responsible for large igneous provinces (LIP). This one example therefore now invalidates a paper by Ivanov and Melosh that is cited widely by geologists, where they claim to prove that impact volcanism cannot occur (Ivanov & Melosh, 2003). Melosh, elected member NAS for his pioneering work on impacts, in his paper with Ivanov (Ivanov & Melosh, 2003) is basing his analysis on incorrect mantle geo-cosmochemistry , ignoring the fact that the mantle has copious volatiles dissolved lowering the melting temperature, the solidus, so that explosive volcanism can occur once a thin crust impact excavates a deep hole, as deep initially as 10-25% of the crater diameter, causing an upper mantle thermal anomaly or hotspot to form. Here is a typical quote citing Ivanov-Melosh which is taken from a paper by several geologists with prominent names including Alvarez and Renne (Richards et al. 2015): Also, a Chicxulub-size impact does not in any case appear capable of generating a large mantle melting event (Ivanov and Melosh, 2003). Yes, ironically LIPs are based on mantle "plumes", but not upwelling ones from deep D" by convection, but exactly opposite growing downward by mantle depletion after an impact cavity opens up the mantle. Also, upon painstaking review of relevant publications, it can be noted that the claim of early Deccan volcanism, pre-K/T extinction event, which is routinely cited in the literature, cannot be verified and should be seen as spurious. Quite possibly confusion with Rajmahal lavas may have led to this mistake initially. Once alerted to this situation, the pervasive effects of ET object impacts are visible everywhere on Earth, from the effects on, and initiation of, plate tectonics, to the realization that craters are a dime a dozen, especially on old surfaces, including ocean bottom, and such antipodal effects as chaotic terrains caused by bolide impacts-in the form of granitic extrusions. A great example is Rio de Janeiro's Sugarloaf Mountain, antipodal of the Ontong Java impact that created the eponymous LIP. H. G. W. Burchard 419 References Anderson, D. L., & Natland, J. H. (2005). A Brief History of the Plume Hypothesis and Its Competitors: Concept and Controversy. In G. R. Foulger, J. H. Natland, D. C. Presnall, & D. L. Anderson, Eds., Plates, Plumes, & Paradigms, GSA Special Paper 388, 119-145. Bowens, T. E., & Gross, L. T. (1998). Geology and Mineral Deposit Reconnaissance in the Stone Coal Valley Region, Modoc County, California. Thesis (M.Sc.), Colorado School of Mines. Bowens, T. E., & Gross, L. T. (2001). Probable Mid-Miocene Caldera in the Modoc Plateau, Northeast California, Details. AGU Fall Meeting. http://abstractsearch.agu.org/meetings/2001/FM/V52A-1047.html Christiansen, R. L., Foulger, G. R., & Evans, J. R. (2002). Upper-Mantle Origin of the Yellowstone Hotspot. Geological Society of America Bulletin, 114, 1245-1256. http://dx.doi.org/10.1130/0016-7606(2002)114<1245:umooty>2.0.co;2 Fouch, M. J. (2012). The Yellowstone Hotspot: Plume or Not? Geology, 40, 479-480. http://dx.doi.org/10.1130/focus052012.1 Foulger, G. R. (2006). Yellowstone. http://www.mantleplumes.org/Yellowstone.html Gilbert, J. S., & Sparks, R. S. J. (Eds.) (1998). The Physics of Explosive Volcanic Eruptions. Geologial Society Special Publication 145, London: The Geologial Society. Ivanov, B. A., & Melosh, H. J. (2003). Impacts Do Not Initiate Volcanic Eruptions: Eruptions Close to the Crater. Geology, 31, 869-872. http://dx.doi.org/10.1130/G19669.1 Morgan, W. J. (1971). Convection Plumes in the Lower Mantle. Nature, 230, 42-43. http://dx.doi.org/10.1038/230042a0 Richards, M. A., Alvarez, W., Self, S., Karlstrom, L., Renne, P. R., Manga, M., Sprain, C. J., Smit, J., Vanderkluysen, L., & Gibson, S. A. (2015). Triggering of the Largest Deccan Eruptions by the Chicxulub Impact. Geological Society of America Bulletin, 127, 1507-1520. http://dx.doi.org/10.1130/B31167.1 Sparks, R. S. J. (2003). Dynamics of Magma Degassing. In C. Oppenheimer, D. M. Pyle, & J. Barclay, Eds., Volcanic Degassing, London: The Geological Society. http://dx.doi.org/10.1144/gsl.sp.2003.213.01.02 Wilson, J. T. (1963). A Possible Origin of the Hawaiian Islands. 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