Volume 9, Number 3March 2015

thereasoner.orgISSN 1757-0522

Contents

Editorial 18

Features 19

News 22

What’s Hot in . . . 24

Events 25

Courses and Programmes 26

Jobs and Studentships 27

Editorial

It is a great pleasure to return as guest editor of The Reasoner,especially as this time I had the opportunity to interview threetowering figures in contemporary philosophy of biology, basedin three different continents, about the characteristics of thisfield and the ways in which it contributes to general philoso-phy: Professor James Griesemer from University of CaliforniaDavis; Professor Rachel Ankeny from the University of Ade-laide; and my colleague Professor John Dupre from the Uni-versity of Exeter. I hope you enjoy their discussion as muchas I did, and that you take this as an invitation to reflect onthe relation between the philosophy of the special sciences andphilosophy at large, as well as on the role that philosophers ofscience can play in developing understandings of the world atlarge. I view this as an extremely important conversation, astoo often it is assumed that the only relevance of the philos-ophy of special sciences is to the development of the specificfields that it analyses (and even this may be questioned, espe-cially in cases where philosophical and scientific work are com-

pletely disconnected). On the contrary, I think that serious at-tempts to ground philosophical insight on the historical and sci-entific study of specific research areas should be seen as crucialcontributions to general epis-temology. As demonstratedcountless times in the historyof philosophy, abstract dis-cussions of modes of knowl-edge can benefit enormouslyfrom critical reflection onhow knowledge is actuallydeveloped and used—suchas that emerging from thestudy of specific reasoningprocesses, and their rela-tion to ever-shifting prac-tical constraints, opportuni-ties, and social and materialinfrastructures. An excel-lent exemplification of thisapproach is the work of Werner Callebaut, Scientific Direc-tor of the Konrad Lorenz Institute for Evolution and CognitionResearch and Professor in philosophy of science at the Uni-versity of Hasselt (1995–2009) and Vienna (2009–2014), whodied unexpectedly in November last year. I want to take thisoccasion to honour and highlight his contributions, which werebuilt on insights from general philosophy (particularly, over thelast few years, Kantian scholarship), philosophy of science (es-pecially debates on theory change and perspectivism), historyand philosophy of biology, and several scientific fields (includ-ing developmental and evolutionary biology, cognitive scienceand economics). This unique capacity to bridge disciplinaryboundaries led Werner to important contributions to centralphilosophical debates such as the role of naturalism, models,perspectives and representations in the development of knowl-edge. This outlook on the role of the philosophy of science ischampioned by many scholars within the philosophy of biol-

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ogy, as well as by societies like the International Society forthe History, Philosophy and Social Studies of Science and theSociety for the Philosophy of Science in Practice, but is toooften dismissed as irrelevant within general epistemology. Ofcourse, efforts towards improved communication should comefrom both sides, and I should note that few philosophers ofbiology (including myself) pay attention to contemporary de-velopments in epistemology and logic. This is partly a mat-ter of cognitive constraints, as it is of course very difficult tokeep abreast of a large variety of scholarly discussions, es-pecially when trying to follow scientific debates at the sametime—Werner was quite unique in that respect. The Reasoneris ideally positioned to provide a conduit for dialogue and con-frontation across philosophical sub-fields, and I hope contribu-tors will continue to take advantage of this venue in this way.

Sabina LeonelliUniversity of Exeter

Features

Interview with Rachel Ankeny, John Dupre andJames Griesemer on the philosophy of biologySabina Leonelli: How would you characterise the philosophyof biology, with respect to other branches of philosophy?

John Dupre: Philosophy of biology reflects on the meth-ods, assumptions and findings of the life sciences. Inrecent decades it has tended to focus overwhelmingly onevolutionary theory, but more recently it has expanded itsscope to include a much wider range of work in biology.Philosophy of biology isgenerally assumed to be asubfield of philosophy of sci-ence which, in turn, providesan essential perspective onepistemology and meta-physics. For naturalists, whobelieve that science is ourbest way of knowing aboutthe world, understandinghow science works is es-sential to epistemology, andunderstanding the contentof what science tells usabout the world is central tometaphysics. The latter claims have, however, led to someoften heated debates with metaphysicians and epistemologistswho do not share the naturalistic viewpoint. The recent growthof philosophy of biology, as also of philosophy of physics andof other particular sciences, reflects in part increasing doubtsabout the existence of any universal or general truths aboutscience and, concomitantly, doubts about the value of so-calledgeneral philosophy of science.

Rachel Ankeny: I generally view philosophy of biology asa subfield within philosophy of science, which in turn is afield that primarily has explored epistemology but also issuesrelating to metaphysics and ethics. Philosophy of biologyarguably has begun to reorient the traditional epistemologicalassumptions which underlay general philosophy of science

due in part to its tendency to focus on the physical sciences.Given that the biological and biomedical sciences exploreliving, evolving, and contextualized entities, the types ofphilosophical issues that arise within it are considerably differ-ent than those envisaged in most general philosophy of science.

James R. Griesemer: Philosophy of biology is a “philosophyof X,” like other specialty “branches” of philosophy such asphilosophy of art, phi-losophy of religion, orphilosophy of physics. Assuch, some of its problemscome from the specialsubject matter it studiesrather than out of “general”philosphical questions thatseem to transcend particu-lar subject matter such as“what is knowledge?”, “why is there something rather thannothing?”, “what is a/the good life?”. Philosophers of biologyseek answers to questions about how best to understandconcepts, methods, practices, and theories in the life sciences,e.g., whether fitness is a causal concept, how general isDarwin’s theory of evolution by natural selection, or whatis/can be a gene. They also seek to understand substantialchanges of method and practice, such as the turn toward“model organisms” and experimentation in the late 19th and20th centuries, or how genetics became (or was supersededby) genomics, or the impact of digital computers and theInternet on theories (stochastic theories, agent-based models)and practices (simulation, sophisticated statistical methods,big data) in the life sciences since the 1960’s. Increasingly,philosophers of biology are interested in the entanglement ofbiologists’ pursuit of knowledge about the living world withsocial, economic, and political practices and processes, suchas the increasing engagement of ecologists with the role ofhumans in ecosystems. In my view, people come to philosophyof biology as a research subject either, like myself, frombiological backgrounds seeking answers to broad questionsof concept, method, practice, and theory about biology, orfrom philosophical backgrounds seeking answers to generalphilosophical questions for which the special subject matter ofbiology poses special problems to epistemology, metaphysics,or ethics or holds special promise of expansion of or challengeto general philosophical views, e.g., on concepts of simplicity,similarity, causation, or the moral worth of non-human animals.

SL: How do you think this field contributes to a philosophicalunderstanding of scientific reasoning?

JD: If philosophy of biology didn’t contribute to our under-standing of scientific reasoning, this would be a damningindictment of the field: this is one of its central aims. Themore difficult question is whether it contributes to the under-standing of scientific reasoning generally, or rather just to theunderstanding of reasoning in biology, or in particular areas ofbiology. A moderate answer is that it does both to some degree.Concepts such as explanation, causation, induction, scientificmodel or law, etc., have relevance across the sciences, andprovide legitimate space for a general philosophy of science.But what can be said about them in general is too abstract tohave much immediate relevance to particular sciences, and

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their role in reasoning in, for example, biology to specificsub-fields of biology. Philosophical insight into these generalconcepts is a necessary input into the analysis of reasoning inspecific areas of science, but more detailed contextualisationwith respect to methods, practice and theory in particularscientific fields, as for example is studied in philosophy ofbiology, is essential for understanding of scientific reasoning.

RA: I believe that understanding reasoning in the biolog-ical and bio-medical sciences is an essential part of com-ing to a more well-rounded understanding of scientific rea-soning in general. To base our vision of science on anyone particular field within it undoubtedly would render ourviews of scientific reasoning (and scientific practice whichI believe is a critical context for the development of anyaccount of scientific rea-soning) far too narrow andconstrained. The philoso-phy of biology has madeimportant contributions tokey debates about scientificreasoning with regard toexperimentation, laws, andmodels, just to name a fewtopics. Often the contribu-tions that have been madeare critically grounded inthe complex and messydetails that make biologyitself so interesting, andhence many of the mostprovocative and productiveaccounts of biology draw onhistorical, sociological and other disciplinary methodologiesas the basis for their explorations of scientific reasoning.These rich approaches have assisted us to develop a muchdeeper understanding of scientific practice and reasoning moregenerally.

JRG: Since the positivism(s) of the 19th century, biology hasbeen thought of as a science in the middle of a hierarchyof sciences: not fundamental like physics, nor so special,messy, and fraught as the social sciences as to risk at timesthe epithet “pseudo-science”. This hierarchical view, dividingsciences into fundamental and special, poses problems fora general theory of scientific reasoning, since what seemsto work in physics (highly mathematized, general theoriesof astonishing accuracy, depth, and explanatory power butonly for the very simplest of phenomena) appears not towork well for the “special” sciences, which may seek orsettle for statistical, un-law-like regularities, explanations andpredictions of limited and contingent scope in exchange forsome power of control over phenomena in a limited contextof great practical interest or outright eschew universal lawsin favor of local mechanisms and small subsets of knowncausal factors as most salient to reasoning. Model-based viewsof science and scientific reasoning are far more popular inphilosophy of biology than in so-called “general philosophyof science” because the diversity of reasoning practices inthe sciences is widely recognized by those who do not seekexplanatory reduction of all science to physics by derivinglaws of the special sciences from laws of physics. In taking

biology as subject rather than a positivistic view of physicsfor understanding scientific reasoning, we have learned thatthere is no single best all-purpose theoretical model, so thatpractical, pragmatic, and ethical concerns can find their wayinto biological reasoning in ways that suggest a deep under-standing of scientific reasoning will also be messy. A tidy viewof scientific reasoning is bound to be a false or misleading view.

SL: In your work, are you interested in contributing to discus-sions in general philosophy, and if so, how?

JD: Very much so. To begin with, and referring back to mylast comments, the philosophical understanding of concepts ingeneral philosophy of science, such as causation or explana-tion, evolves in two-way interaction with studies in particularsciences. The test of their validity is to a considerable degreetheir usefulness in application to particular sciences. Second,as a naturalist, I believe that the philosophy of science ingeneral, and of biology in particular, has a central contributionto make to epistemology and metaphysics. It seems bizarre tosuppose that an understanding of how we come to know theworld and what we know about it could be pursued in isolationfrom philosophical examination of our greatest successes incoming to know about the world. Third, and of greatest interestin my own work, concepts central to many areas of philosophyare open to major illumination from biology. One very obviousexample is the nature of the human, and the concept of humannature. Human nature, of course, is a concept that has figuredin areas ranging from ethics and political philosophy to thephilosophy of mind and philosophical psychology; but it isalso a concept that has derived great illumination from the phi-losophy of biology. As one related example, an important trendin recent work on personal identity is so-called animalism, theview that the persistence of a human is just the persistence ofan animal. Unfortunately this proposal is generally pursued asif our understanding of what an animal is had reached its cul-mination with Aristotle. This philosophical movement badlyneeds to be connected with the active and exciting discussionsin contemporary philosophy of biology about the nature of anorganism. Another issue that has concerned my own work forseveral decades has been the nature of classification and ofnatural kinds. This has been a major topic in metaphysics formillennia, and underwent a particular surge of interest in the1970’s with the work of Putnam and Kripke. Many examplesemployed in this work were drawn from biology, but often witha very naive understanding of the real problems in biologicalclassification. The nature of biological classification, on theother hand, has been a major topic of work in the philosophyof biology for many years, and more sophisticated appreciationof the character of biological kinds has gradually had a majorimpact on general philosophical understanding of classificationand of the kinds, natural or otherwise, that classification aimsto distinguish.

RA: My research on model organisms is a good example: manydiscussions about ‘models’ in general philosophy of sciencehave been rather impoverished or at least not well-groundedin the actual practices of scientists who use such models.Together with you [Sabina Leonelli] among others, I havesought to contribute to more general discussions of the rolesand validity of models, using detailed case studies focusedon a particular set of practices within contemporary biology.

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My work in the philosophy of the biological and biomedicalsciences also has explored the role of cases in these fields, atheme that makes contributions to developing an understandingof the units of investigation used in fields well beyond thelife sciences, and to exploration of the epistemological basesfor the use of such units of investigation in a range of typesof practices. Finally, recent work on norms associated withopen science and data sharing has much broader implicationsfor those interested in excavating values associated with thegeneration and sharing of knowledge within academia andbeyond.

JRG: It is undoubtedly the hope of every scholar to have animpact beyond one’s own special subject. Although I am nodifferent in this regard, I view my subject as “biology studies”rather than philosophy of biology per se. I engage historical,sociological, and cultural methods, findings, and colleagues aswell as philosophical ones. I seek answers to questions that arehistorical or sociological and not only philosophical, e.g., in mywork on the Museum of Vertebrate Zoology at Berkeley, whichis as much interested in the social organization of work as it isin the role of researchers in the museum in originating the newdiscipline of “evo-devo”. With age and experience working ina philosophy department (since I have no academic degrees inphilosophy), I have come to better appreciate some of the goalsand some of the methods of “general philosophy” and to seehow views in epistemology, metaphysics, and ethics bear onmy work and how my work might bear on these “core” topics inphilosophy. My epistemological views regarding empirical bi-ology, from studies of genetic, embryological and evolutionaryconcepts of germ and soma, genotype and phenotype, gene andcharacter, are converging on an externalist “tracking” accountlike those of Nozick or Roush. My metaphysical views on bi-ological individuality and reproduction processes are converg-ing on a “process ontology,” although I am reluctant to call itWhiteheadian, or to align with either perdurantism or enduran-tism in analytic metaphysics. Perhaps my view will amountto nothing more than Russell’s quip that event is to process aspoint is to line and that’s all there is to be said on the matter.I think a more exciting prospect for an impact of my work ongeneral philosophy is an approach to linking epistemic, onto-logical, and ethical dimensions of reasoning in an account I amdeveloping of scientific reasoning practices in biology. Even ifthe model is flawed, it might provide a useful general heuristicfor exploring the entanglement of ethical concerns in what areusually taken to be “purely” epistemic or ontological questions.

Three logicians walk into a bar—a modest pro-posal for teaching epistemic logicWhen teaching epistemic logic to undergraduates, instructorsmight try this story that has floated around the internet for awhile:

Three logicians walk into a bar. Bartender ask: ‘Y’allall want a beer?’ Says the first: ‘Hmm..., don’t know.’The second: ‘Me neither!’ Goes the third: ‘So yes!Three pints, please’.

Readily found funny, and thus a genuine joke, or not, theseare the learning outcomes: (i) achieve a correct translation ofthe speakers’ commitments into a formal language with epis-temic operators; (ii) evaluate the reasoning underlying the third

logician’s inferential behaviour with respect to validity, and(iii) explain why (only) someone with a formal backgroundmight find the story amusing. Based on (i-iii), ask students(iv) to construct an analogous story—perhaps a better one!

In class tell this storytwice and present it on ascreen or hand-out whilegiving students five minutesto “explain what’s going onhere, please!” Have studentsform groups of three—quickly—discuss for fiveminutes, change partners, and repeat for another three minutes.Then ask for explanation-proposals; collect key-words on theblackboard, continuing until “all” is said. Now invoke thedetails (below), making clear that students should uncoverevery assumption needed to explain the story.

The following assists in creating less usual class-time. Dothis well and your students might even find it is fun to self-develop along these lines, where ‘Ln’ abbreviates ‘logician n’,‘KLn’ stands for ‘Ln knows that’, ‘Ln: φ’ denotes ‘Ln commitsto φ’, and ‘p’ stands for ‘All (logicians) want a beer’. Othersymbols take their “classical” meaning.

(1) Bartender: p?

(2) L1: KL1 (p ∨ ¬p) [i.e., “I, L1, do not know whetherp or not p.”]

(3) L2: K L2 (p∨ ¬p) [i.e., “I, L2, do not know whetherp or not p.”]

(4) L3:p

L3’s reasoning is: “if L1 did not want a beer, then L1 wouldhave replied ‘¬p’; but since L1 didn’t state ‘¬p’, infer that L1

wants a beer. Similarly for L2. Finally, speaking from L3’sperspective, since I want a beer, it follows that all of us wanta beer. Hence: state ‘p’.” (One may decompose ‘p’ in orderto formalize L’’s reasoning as: ‘∀x [logician (x) → want (x,beer)]’, where x ranges over the domain of those having enteredthe bar.)

Easy enough! You could stop here; chances are many of yourstudents won’t get further on their own. But the best is yet tocome! Having pointed the story’s “logical side,” move towardsa broadly language-philosophical analysis to uncover implicitassumptions. (Extra points to whoever readily points out suchassumptions!) To elicit answers use the Socratic Method, ask-ing relevant questions. We now provide short versions of whatbetter answers amount to.

First, under normal assumptions on human memory, onemust assume that the logicians had not previously exchangedtestimonies on their drink-preferences, particularly that none ofthem has stated that she visits the bar in order to have a beer (asopposed to milk, tea, or a change of location). Yes, that’s odd;one regularly shares drink-preferences explicitly before a groupsets out. In fact, ‘shall we go for a beer?’ is the unmarked formin informal contexts. Stay cool as this objection arises; you canblame the oddity on our characters being logicians. Call thisthe ‘No Previous Testimony-Condition (for normal memory)’.

Second, L3 must assume that the others answered the bar-tender’s question truthfully, and that each can introspectively

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access their personal drink-preferences. Hence, one must as-sume that they stated ‘¬KLn(p ∨ ¬p)’ for reasons other than alack of introspective access. After all, if either L1 or L2 doesnot want a beer, or if at least one lacks access to their pref-erences, then L3’s assertion in line (4) is incorrect, hence herreasoning would be invalid. Call this the ‘Truthfulness or Non-(Self-)Deception Condition (under introspective access)’.

Third: the three logicians must coordinate on the same mean-ing of ‘all’ in line (1). While semantic coordination remainsconcealed when formalizing the bartender’s question as ‘p?’,the need to coordinate nonetheless becomes clear by distin-guishing a collective from a distributive reading of ‘all’. Take‘the logicians carried all the burden of the department’s restruc-turing’, for instance. On the collective reading they jointly car-ried this burden; the distributive reading sees each do this onher own. (Exchange ‘burden’ for ‘piano’ if you like.) Obvi-ously, truth-conditions for both readings differ; the last sen-tence is true only if each logician carries the burden individ-ually, the former is true only if they carry the burden together.Similarly the bartender’s question may query whether the threelogicians wish to share one and the same beer—few thingsare inconceivable with logicians—or whether each wants theirown. So they have to coordinate on the distributive reading;otherwise L3’s reasoning is invalid (better: L3’s answer wouldbe incorrect if at least one of them had a collective reading inmind). Call this the ‘Meaning Coordination-Condition’.

Finally, at least one further meaning-coordination conditionis needed, a trickier one: Witness a bartender asking “y’all wantbeer?” and you witness that ‘I don’t know’ normally reveals ig-norance of the utterer’s personal preferences but normally doesnot reveal ignorance of others’ preferences. Hence, ‘I don’tknow’ normally fails to mean ‘I don’t know whether everyonewants a beer’; rather, it means ‘I don’t know yet what I want todrink.’ Call this the ‘Conventional Meaning-Condition’.

In private communication,a colleague of ours—alogician—argued that thefirst condition is dispens-able given the other three,i.e., Truthfulness, MeaningCoordination, and Con-ventional Meaning, jointlysuffice for L3’s reasoningto be valid; if so, the No-Previous Testimony condition is superfluous. But we takeNo-Previous Testimony to ensure that logicians #1 and #2 areunable to truthfully state p; so, in our view, this conditionremains needed. Incidentally, this very disagreement mayinitiate a discussion among students on what ‘necessary’ and‘dispensable’ mean here (hint: necessary for the joke to workvs necessary for L3’s inference to be valid).

One story then, four conditions, one instructor, and your stu-dents. Where is the joke? Well, why not discuss also this ques-tion, and openly too! If there is a joke, we think, it resides withour logicians interpreting the bartender’s question differentlyin this context than is done conventionally. Again, blame it onthem being logicians.

“Very well,” you say, “but is that story funny?”—or so youwill ask and be asked. Well, yes and no! Irrespective, your stu-dents better understand all assumptions underlying the relevant

reasoning.

Jeroen SmidLund University

Frank ZenkerLund University

News

Inductive logic and confirmation in science II, 24–25 OctoberThe second Inductive Logic and Confirmation in Science Con-ference was held at the University of Utah this past October24th and 25th. The conference was hosted by professors JonahSchupbach and Jacob Stegenga. The conference focused on theuse and role of inductive logic and confirmation in science andthe philosophy of science. One question that was discussed waswhether science has the ability to fix its mistakes. Two of thepapers presented worries regarding science’s ability to do this.Felipe Romero argued that science is self-correcting only if anumber of conditions are meet. However, the social structurethat science is embedded in often does not allow these condi-tions to be met.

Matt Haber discussed what he calls positively misleading er-rors, which occur when, as we collect more data, we nonethe-less converge on a mistaken hypothesis. Understanding posi-tively misleading errors, Haber urged, will give us a better un-derstanding of how we extract information from large data sets.

Another theme from the conference was the logic and jus-tification of how we update our beliefs and evaluate theories.Justin Dallman argued that we should disregard evidence forwell corroborated beliefs in favor of evidence for beliefs aboutwhich we have little information. Doing so, Dallman argued,will result in more accurate beliefs.

Elliot Sober, the first keynote speaker, dealt with theorychoice in evolutionary biology. He examined a number of epis-temic issues concerning how similarities provide evidence forcommon ancestry, for example, under what conditions will thefact that two species have a common trait be evidence that theyshare a common ancestor and which types of similarities pro-vide strong evidence for common ancestry. Sober showed howdifferent uses of the likelihood principle can illuminate theseissues.

An important issue discussed here was the role that prag-matic considerations play in justifying our theory choice.Aaron Kenna argued that induction is justified on pragmaticgrounds—induction dominates other predictive models in thesense that it retains any potential virtues of any non-inductivemodel while possibly having virtues these other models lack.

Jonathan Livengood argued that our selection criteria formodels are infected with pragmatic considerations. Livengoodshowed that four selection criteria—mathematical tractability,loss minimization, statistical efficiency, and robustness—areinfected with pragmatic considerations, like suffering a loss oftime or money.

Several papers examined and clarified the logical conceptsthat are at play in confirmation and induction. Sean Walsh ex-amined the probabilistic liar, a statement that says of itself thatit is unlikely. Walsh examined the nature and problems with thekinds of self-reference that are involved in the probabilistic liarand different solutions to it.

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Marta Sznajder examined the geometrical representations ofconceptual frameworks in Carnap’s ‘A Basic System of Induc-tive Logic.’ She discussed how these geometrical representa-tions can depict the relationships between concepts. She alsodiscussed two rules that link confirmation to features of thesegeometrical representations.

Paul Weirich examined arguments to the conclusion thatagents’ degrees of belief must conform to the probability ax-ioms. He evaluated attempts to ground probabilism in compar-ative norms of belief. Weirich concluded that satisfying thesecomparative norms is necessary but not sufficient for conform-ing to the probability axioms. Therefore, comparative normsdo not supply a foundational argument for probabilism.

The last set of themes discussed at the conference were In-ference to the Best Explanation (IBE), Bayesianism, and theprinciple of total evidence. Tania Lombrozo, another keynotespeaker, examined how the beauty of theories affects their ex-planatory power. Lombrozo looked at whether explanation im-proves or impedes learning when the theory is beautiful or ugly.The results of Lombrozo’s empirical tests showed that, whenthe theory was beautiful, explanation improved learning. How-ever, when the theory was not beautiful, explanation hurt learn-ing.

Leah Henderson, the third keynote speaker, discussed thecompatibility between Bayesianism and IBE. She argued thatthe compatibility of Bayesianism and IBE emerges from theBayesian proceeding in the manner that they normally would.This occurs because a Bayesian will assign higher probabilitiesto better explanations. In this way, emergent compatibilism canexplain why we prefer better explanations.

Greg Gandenberger argued that Bayesian arguments that sci-entists should not use frequentism because it violates the likeli-hood principle are too quick. He said that these arguments fail,but suggested an alternative way in which we can still see fre-quentist violations of the likelihood principle as a weaknesses.

Greg Wheeler looked at certain violations of the Bayesianprinciple of total evidence where using less evidence actuallyresults in objectively better outcomes. Wheeler resolved a puz-zle responsible for this “less is more effect” and showed howthis effects is related to coherentism.

Bengt Autzen clarified and defended the principle of totalevidence. Autzen said that we should conceive of the princi-ple of total of evidence as being an intra-theoretic constraint,not inter-theoretic, and, once we do, we see that a number ofchallenges posed for the principle no longer work.

The second conference on Inductive Logic and Confirmationin Science highlighted the diversity of the ongoing research inthe area. The conference included both philosophers and sci-entists, established figures and those earlier in their career. Thepapers discussed historical topics as well as contemporary con-cerns, theoretical matters as well as applied issues. In additionto being enlightening, it was an enjoyable two days in the SaltLake Valley.

Anthony P. SmithUniversity of Utah

Epistemic and practical normativity: explana-tory connections, 16 JanuaryThe workshop was held at the University of Southamp-ton as part of their ‘Normativity: Epistemic and

Practical’ AHRC-funded project. It considered howepistemic and practical normativity are connected toeach other with regards to how we explain them.

Asbjørn Steglich-Petersonpresented first (‘EpistemicNormativity: Absolutist orInstrumental?’), with a re-sponse by Ema Sullivan-Bissett. Steglich-Petersonargued for consequentialismabout epistemic normativity.While the view’s opponentssee epistemic normativity asdivorced from practical andmoral normativity, Steglich-Peterson observed that sep-arating normativity like thiswould make epistemic as-sessments of beliefs insignificant in light of other evaluations.Consequentialism, he thinks, can avoid this. Assessments ofa belief concerning its truth are indeed distinct from those us-ing other measures, but do not in themselves stipulate whethera subject ought to have the belief. Practical and moral con-siderations determine if she should seek the truth in any givensituation.

Conversely, in the last talk (‘Why and How To Be An Epis-temic Nonconsequentialist’), Kurt Sylvan argued for noncon-sequentialism about epistemic norms. Victor Verdejo gave aresponse. Sylvan proposed that consequentialism cannot ac-count for the fact that rationality is an epistemic norm, sincefollowing the dictates of rationality does not always lead oneto achieve the suggested epistemic goals of truth and knowl-edge. Further, the view faces the additional criticism that con-sequentialism about epistemic value is, for Sylvan, subject tothe Swamping Problem. Non-consequentialism, however, canaccount for epistemic normativity. Those not following the re-quirements of rationality are subject to blame for ignoring theobjectively-construed norm of respect, in this case, for truth.

The second presentation (‘Reasoning with Reasons’), wasgiven by Daniel Star with a response by Daniel Fogal. Stardisagreed with the views of Setiya and Way, who think thata reason (epistemic or practical) is best understood as being apremise in good reasoning. This, Star argued, is only to de-scribe the role reasons play and leaves unspecified what re-alises that role, which he suggested is evidence that one oughtto do something or believe that something is the case. Further,he argued that we should not think of reasons as being sim-ply premises in good reasoning that are appropriate to act onbecause frequently a reason for acting is outweighed by otherreasons, and so is inappropriate to act on.

The third talk was by Ulrike Heuer (‘Two Kinds of wrongReasons’), with a response by Chris Howard. It addressed thedebate concerning how to characterise right and wrong kindsof reasons. Heuer argued that fitting attitude accounts try toexplain this contrast but alternative suggestions, which takewrong kinds of reasons to be those that do not rationalise theattitude and are not adhered to directly, are concerned with adifferent, unobvious, distinction. Further, she argued, the con-trast drawn by such alternative proposals do not hold acrossattitude types. We cannot, then, explain the reasons for everysort of attitude with a single theory.

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The next workshop in the series will run this spring.

Sophie KeelingUniversity of Southampton

Scientific discovery in the social sciences, 30–31JanuaryThe conference was the final event for the Economic and So-cial Research Council funded project Automatic Generation ofScientific Theories and supported by the Centre for the Philos-ophy of Natural and Social Science at the London School ofEconomics. The project created a methodology for automati-cally developing theories in psychology using techniques basedon genetic programming. A system for representing psycholog-ical data, a class of process based models, and algorithms forevolving models was produced along with a theory languagefor implementing cognitive models in a symbolic process basedparadigm.

Conference keynote speakers, presenters and participantscame from a wide range of countries including Canada, Greece,Spain, Poland and the United States, and disciplines as variedas computer science, economics, particle physics, philosophyand sociology. For reasons of space not all the talks are men-tioned here but abstracts and slides can be found here.

The workshop began with the first keynote by Margaret Bo-den (cognitive science, University of Sussex) who consideredthe feasibility of computers conducting social research. Shediscussed the difficulty of appropriately interpreting some kindsof data, such as tweets, and how this might relate to issuesabout the analysis of big data. Next was a talk on computa-tional scientific discovery from Piotr Giza (philosophy, MariaCurie-Skłodowska University) examining the insight which au-tomated discovery systems could offer into questions about thenature of induction. Fernand Gobet (psychology, Universityof Liverpool and London School of Economics) presented anoverview of the results achieved by the Automatic Genera-tion of Scientific Theories project to date and offered sugges-tions about problems and prospects for the future. The sec-ond keynote was a joint presentation by Maria Dimarogkona(philosophy, National Technical University of Athens) and Pet-ros Stefaneas (mathematics, National Technical University ofAthens) about the roles of syntactic and semantic considera-tions in the formalisation of social science theories. It cov-ered the importance of categorical abstraction of the conceptsof satisfaction, sentence, signature and model for characteris-ing and integrating the diverse logics used in scientific theoryformalisation. The first day ended with a presentation by Abi-gail Klassen (philosophy, University of York) on the extent oflegitimate reduction within social science theories.

The second day opened with the third keynote by Kevin Dun-bar (psychology, University of Maryland College Park) whodiscussed whether the advent of big data meant the end of tra-ditional hypothetico-deductive methodology in science. Usingdata collected from laboratory scientists it was argued that bigdata will bring about significant changes in scientific methodol-ogy but there is still a role for hypotheses. The conference con-cluded with some reflections from Amos Witztum (economics,London School of Economics) and Peter Abell (managementscience, London School of Economics) on the extent to whicheconomics could legitimately be thought to engage in scientificdiscovery, and the types of Bayesian causal mechanisms which

could underpin this.The conference was organised by Mark Addis, Fernand Go-

bet, Peter Lane and Peter Sozou.

Mark AddisBirmingham City University

Calls for PapersThe Realist Turn: special issue of Methode - Analytic Perspec-tives, deadline 15 March.Causation and Mental Causation: special issue of Hu-mana.Mente, deadline 15 March.Inductive StatisticalMethods: special issue of Entropy, dead-line 31 May.Logic Theorems: special issue of Logica Universalis, deadline31 July.

What’s Hot in . . .

Uncertain ReasoningThe question of telling certainty from very high prob-ability is conceptually intriguing, technically de-manding and philosophically slippery. The develop-ment of the theory of probability from Bernoulli toBorel is dotted with more or less successful attemptsat providing a theoretical ar-gument in support of the fol-lowing otherwise very intu-itive consideration. Takinginto account arbitrarily smallorders of probability can atbest lead to inaction, and of-ten leads to full-fledged neu-rosis. As an illustration,consider that A. Gelman, N.Silver, and A. Edlin (2012:What Is the Probability YourVote Will Make a Differ-ence? Economic Inquiry, 50(2), 321-326) calculate that theprobability of casting a decisive vote in the US presidentialelections is (on average) in the region of 1 in 60 million. Nowcompare this with the odds of 1:112 which are being reportedby the US National Security Council of dying in a motor ve-hicle crash. Though the latter are computed with respect to anindividual’s lifetime, one may understandably pause and thinkwhether driving to cast one’s vote is really worthwhile. Luckilyfor our democratic societies common sense often prevails anddismisses the above calculations (or attempts at them) as plainneurotic.

Be this as it may, we still would like to have a good the-ory of the extremely unlikely—or if one plans to make moneyin financial markets, of the morally certain. Formalising thisdifficult concept is one of the key ideas underpinning the game-theoretic, as opposed to measure-theoretic, foundation of prob-ability put forward over the past couple of decades by GlennShaver and Vladimir Vovk. The idea, in a nutshell (see What’sHot in Uncertain Reasoning on the September 2012 issue ofThe Reasoner for more background) is to set up a game be-tween Skeptic and Reality which provides an interpretation of

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an almost sure event as one allowing Skeptic to become in-finitely rich without facing the risk of going broke if the eventfails to happen (this is the analogue of a probability 1 eventin measure-theoretic probability). This setting provides the in-terpretation of a winning strategy for Skeptic. An interestingquestion that followed the initial developments reported in G.Shafer, and V. Vovk (2001: Probability and Finance: It’s Onlya Game! John Wiley and Sons) concerns the conditions underwhich Reality has a(n intuitively meaningful) winning strategy.This has been the topic of recent work which takes an inter-esting twist in K. Miyabe and A Takemura (2015: Derandom-ization in game-theoretic probability. Stochastic Processes andTheir Applications, 125, 39-59.) The paper, as it can be ex-pected, is quite technical—it involves, among others, diagonal-isation methods in complexity theory—so I will refrain fromsumming it up. I’d just like to point out why the question is con-ceptually intriguing besides being technically quite involved.In this game-theoretic set up Reality can be seen as generatingrandom variables against which Skeptic is challenged to playtheir best strategy. Hence a ‘strategy for Reality’ effectivelymeans de-randomising Reality’s behaviour as a consequenceof their (rational) choice. Hence the conceptual quandary andthe mathematical challenge to disentangle it.

Hykel HosniMarie Curie Fellow,

CPNSS, London School of Economics

Evidence-Based MedicineAlzheimer’s disease is a neurodegenerative disorder associatedwith the aggregation of proteins in the brain, where this ag-gregation ultimately damages brain function. Last month, thenewspapers paid a good deal of attention to a laboratory ‘break-through’ in Alzheimer’s research. They were talking about thisarticle.

The Guardian reported that the authors of the articlehad found that a human molecule Brichos ‘put the brakeson a runaway process in the brain that leads to the mostcommon form of dementia . . . by slowing the accumula-tion of sticky clumps of protein in the brain’. In fact,the authors investigated in vitro a mechanism in livingmouse brain tissue. But granting that a correspondingmechanism exists in the human brain, can we concludethat the molecule does in-deed slow the relevant pro-tein aggregation?

Commenting on the ar-ticle, NHS choices pointsout that ‘[a]lthough Brichosstopped damage occurring ina specific amyloid-related bi-ological pathway, some ofthe damage associated withAlzheimer’s disease couldoccur via other routes’. Thatis, the relevant mechanismlinking the molecule Bri-chos and protein aggregationmay well exist in the humanbrain, but the molecule maynot slow the protein aggre-gation since there may exist

further unknown mechanisms in humans that counteract theoriginal mechanism involving the molecule and the aggrega-tion. This is the so-called problem of masking. Some havesuggested that one way to overcome the problem of masking isto gather some evidence of correlation, i.e., evidence that themolecule does in fact make the appropriate difference to pro-tein aggregation in humans. For more on the interplay betweenevidence of mechanisms and evidence of correlation, readersmight want to check out this paper by Phyllis Illari.

Over at the EBM+ blog, Jon Williamson has written aboutEvidence integration in systems medicine. There is also someinformation on a Doctoral training initiative at the Universityof Kent, to work on Evidence and its quality.

MichaelWildePhilosophy, Kent

Events

March

AHR: Workshop on Behavior Coordination Between Animals,Humans, and Robots, Portland, Oregon, 2 March.BICoB: 7th International Conference on Bioinformatics andComputational Biology, Honolulu, Hawaii, 9–11 March.WiS: What is Science?, Barnes, London, 12 March.FON: Edinburgh Foundations of Normativity Workshop, Uni-versity of Edinburgh, 13–14 March.PHA: Workshop on Powers and Human Agency, Durham Uni-versity, 16–18 March.LI: Logic and Inference, Institute of Philosophy, London, 19–20 March.TRiP: Pictures and Proofs, Columbia, South Carolina, 19–21March.SPR: Scientific Progress and Realism, University of Leeds, 24March.KRR: Knowledge Representation and Reasoning, StanfordUniversity, 23–25 March.BMHEE: Bayesian Models for Health Economics Evaluation,Royal Statistical Society, London, 27 March.SCS: SMART Cognitive Science: The Amsterdam Conference,Amsterdam, 25–28 March.PI: Workshop on Philosophy of Information, University Col-lege London, 30–31 March.

April

L & R: Congress on Logic and Religion, Brazil, 1–5 April.CI: Causal Inference Meeting, University of Bristol, 15–17April.TPLP: Truth, Pluralism & Logical Pluralism, University ofConnecticut, 17–19 April.PROGIC: The 7th Workshop on Combining Probability andLogic, University of Kent, 22–24 April.PL: Conference in philosophy and Logic, University of Bel-grade, 24–26 April.

May

EoM: Epistemology of Metaphysics Workshop, University ofHelsinki, 8 May.

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DT: Decision Theory Workshop, University of Cambridge, 13–19 May.SLACRR: St. Louis Annual Conference on Reasons and Ra-tionality, Moonrise Hotel / Washington University in St. Louis,MO, 17–19 May.TIoP: The Idea of Pragmatism, University of Sheffield, 18–19May.TAMC: Theory and Applications of Models of Computation,School of Computing, National University of Singapore, 18–20 May.MR: Metacognition and Reasoning, Dubrovnik, Croatia.21–23MayTruth and Grounds: Mount Truth, Ascona, Switzerland, 24–29 May.CD: Compromise and Disagreement, University ofCopenhagen.27–29 MayTOFB: The Odds for Bayesianism, University of Vienna, 28-30May.

Courses and Programmes

CoursesCombining Probability and Logic: University of Kent, 20–21April.EPICENTER: Spring Course in Epistemic Game Theory,Maastricht University, 8–19 June.EPICENTER: Mini-course on Games with Unawareness,Maastricht University, 22–23 June.

ProgrammesAPhil: MA/PhD in Analytic Philosophy, University ofBarcelona.Master Programme: MA in Pure and Applied Logic, Univer-sity of Barcelona.Doctoral Programme in Philosophy: Language, Mind andPractice, Department of Philosophy, University of Zurich,Switzerland.HPSM: MA in the History and Philosophy of Science andMedicine, Durham University.Master Programme: in Statistics, University College Dublin.LoPhiSC: Master in Logic, Philosophy of Science & Epis-temology, Pantheon-Sorbonne University (Paris 1) and Paris-Sorbonne University (Paris 4).Master Programme: in Artificial Intelligence, Radboud Uni-versity Nijmegen, the Netherlands.Master Programme: Philosophy and Economics, Institute ofPhilosophy, University of Bayreuth.

MA in Cognitive Science: School of Politics, InternationalStudies and Philosophy, Queen’s University Belfast.MA in Logic and the Philosophy ofMathematics: Departmentof Philosophy, University of Bristol.MA Programmes: in Philosophy of Science, University ofLeeds.MA in Logic and Philosophy of Science: Faculty of Philosophy,Philosophy of Science and Study of Religion, LMU Munich.MA in Logic and Theory of Science: Department of Logic ofthe Eotvos Lorand University, Budapest, Hungary.MA in Metaphysics, Language, and Mind: Department of Phi-losophy, University of Liverpool.MA inMind, Brain and Learning: Westminster Institute of Ed-ucation, Oxford Brookes University.MA in Philosophy: by research, Tilburg University.MA in Philosophy, Science and Society: TiLPS, Tilburg Uni-versity.MA in Philosophy of Biological and Cognitive Sciences: De-partment of Philosophy, University of Bristol.MA in Rhetoric: School of Journalism, Media and Communi-cation, University of Central Lancashire.MA programmes: in Philosophy of Language and Linguistics,and Philosophy of Mind and Psychology, University of Birm-ingham.MRes in Methods and Practices of Philosophical Research:Northern Institute of Philosophy, University of Aberdeen.MSc in Applied Statistics: Department of Economics, Mathe-matics and Statistics, Birkbeck, University of London.MSc in Applied Statistics and Datamining: School of Mathe-matics and Statistics, University of St Andrews.MSc in Artificial Intelligence: Faculty of Engineering, Uni-versity of Leeds.

MA in Reasoning

A programme at the University of Kent, Canterbury, UK. Gainthe philosophical background required for a PhD in this area.

Optional modules available from Psychology, Computing,Statistics, Social Policy, Law, Biosciences and History.

MSc in Cognitive& Decision Sciences: Psychology, UniversityCollege London.MSc in Cognitive Systems: Language, Learning, and Reason-ing, University of Potsdam.MSc in Cognitive Science: University of Osnabruck, Germany.MSc in Cognitive Psychology/Neuropsychology: School ofPsychology, University of Kent.MSc in Logic: Institute for Logic, Language and Computation,University of Amsterdam.MSc in Mind, Language & Embodied Cognition: School ofPhilosophy, Psychology and Language Sciences, University ofEdinburgh.

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MSc in Philosophy of Science, Technology and Society: Uni-versity of Twente, The Netherlands.MRes in Cognitive Science and Humanities: Language, Com-munication and Organization: Institute for Logic, Cognition,Language, and Information, University of the Basque Country(Donostia San Sebastian).OpenMind: International School of Advanced Studies in Cog-nitive Sciences, University of Bucharest.

Jobs and Studentships

JobsPost doc: in the Emergence of Relativism, University of Vi-enna, deadline 1 March.Lecturer: in Modern Philosophy, University of Cambridge,deadline 6 March.Senior post doc: in Machine Learning, University of Cam-bridge, deadline 6 March.Lecturer: in Statistics, University of Glasgow, deadline 13March.Professorship: in Meta-Ethics, Kings College London, dead-line 15 March.Research Associate: in Philosophy of Science, University ofKent, deadline 15 March.Professorship: in The History of Philosophy, University ofHamburg, deadline 19 March.Junior Professorship: in Theoretical Philosophy, University ofHamburg, deadline 19 March.Postdoctoral Fellow: in Perceptual Epistemology, Universityof Toronto Mississauga, deadline 23 March.Tenure track: in Philosophy of Economics/Social Science,Frankfurt School of Finance & Management, deadline 31March.Assistant Professorship: in Analytic Philosophy, University ofSaskatchewan, deadline 31 March.Assistant Professorship: in Social and Political Philosophy/

Value Theory, University of Saskatchewan, deadline 31 March.Associate Professorship: in Philosophy/Logic, Los Rios Com-munity College, deadline 6 April.

StudentshipsPhD position: in causal inference, University of Amsterdam,deadline 1 March.PhD position: in Cognitive Science, Lund University, deadline2 March.PhD position: in Practical Philosophy, University of Gothen-burg, deadline 3 March.PhD positions: in Evidence and its quality, University of Kent,deadline 6 March.3 PhD positions: in Causation, Complexity and Evidence inHealth Sciences, Norwegian University of Life Sciences, dead-line 10 March.PhD Fellowship: in Philosophy of Mind/Philosophy of Psy-chology/Epistemology, University of Oslo, deadline 15 March.PhD position: in Collective Reasoning, University of Luxem-bourg, deadline 31 March.PhD position: in applied philosophy, University of Aberdeen,deadline 31 March.Dissertation Prize: in Logic, Language, and Information,deadline 27 April.

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