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7 of 9 people found the following review helpful
5.0 out of 5 stars Historians should be Bayesians
Bayesian reasoning is widely used in a range of scientific disciplines. According to the GP Margaret McCartney, for example, Bayesian reasoning is "a good description of how medicine is practised" (The Patient Paradox: Why Sexed Up Medicine is Bad for Your Health). Historians, however, have yet to discover the delights of Bayes's Theorem, and Richard Carrier wants that to...
Published 21 months ago by Sphex

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4 of 5 people found the following review helpful
3.0 out of 5 stars If you already know Bayes' Theorem wait for volume 2
As a mathematician, and atheist, with an interest in religious belief and the development of religious thought I was instantly attracted by the title of this book. First of all if, like me, you understand Bayes' Theorem, you will probably find reading this book very frustrating. Carrier is targetting a non-mathematical audience and so, often, takes several pages of...
Published 12 months ago by Euclidean Norm


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4 of 5 people found the following review helpful
3.0 out of 5 stars If you already know Bayes' Theorem wait for volume 2, 14 Dec 2013
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As a mathematician, and atheist, with an interest in religious belief and the development of religious thought I was instantly attracted by the title of this book. First of all if, like me, you understand Bayes' Theorem, you will probably find reading this book very frustrating. Carrier is targetting a non-mathematical audience and so, often, takes several pages of natural language to describe things that can be expressed in a few lines of equations. On several occasions I found myself having to look back over previous pages to remind myself of the hypothesis or evidence Carrier was discussing - doubly frustrating when reading the Kindle version. Carrier also has a tendency to re-emphasise points several times (sometimes to the extent it verges on a rant) - again if you got the point first time its frustrating. In fact, I found myself speed-reading several pages at a time on several occasions. For me, the book could have been a third the length and not lost anything.

I do have to say that I contacted the author because I thought I'd spotted an error in one of his equations. Within 10 minutes of sending the email, I realised it wasn't an error. But the author emailed me back with a gracious reply, so kudos to him for that.

So if I=Book is interesting and M=mathematically trained, then I would set P(I|M)=0.3. I did find some of the historical discussion (e.g. Matthew's tomb description being inspired by Daniel) interesting. But I was also disappointed that the application of BT to the historicity of Jesus is in a second volume - not an obvious assumption given the title of the book. Unfortunately, I cannot be 'not myself' therefore I cannot provide a value for P(I|~M) no matter how hard I try with Bayes' Theorem (BT). This is the problem that Carrier has. He is trying to argue that BT provides the framework for a Historical Method as a analogue to the Scientific Method. But BT is neither axiomatic nor complete - it is a simple derivation from the law of conditional probability. So Carrier's Historical Method should really be (a) hypothesize; and, (b) evaluate the probability that the hypothesis is true. (b) replaces 'do an experiment' in the Scientific Method. This requires a complete probabilistic framework
rather than just BT.

Carrier spends much of the first chapter explaining why we should only trust professional historians and then only some of them some of the time. A brave gambit given that he is about to step into the fields of mathematical logic and statistics - themselves professional endeavours. I'm sure he's had his fill of mathematicians and statisticians pointing that out to him. I don't actually mind, many breakthroughs do come at the boundaries between disciplines and if it means that historians and editorial boards of historical journals and conferences need to make themselves more numerate then that's a good thing. To all you historians out there, no-one says "I can't do history" so don't come with the "I can't do maths".

Back to the book. It is essentially Bayes Theorem for the innumerate. Unfortunately, you won't get a sense of the importance of Bayes' Theorem in assessing witness testimony or drug trials or any of the other areas where it has made great strides. You also won't get a sense of it being applied to the quest for the historical Jesus - that's volume 2. Something that's not made clear in the Amazon summary. Overall, I applaud the author's advocacy of Bayes' Theorem. But if you have never heard of it before, this is not the book to convince you. By keeping the mathematical content to a bare minimum some of the examples and arguments become rather long and convoluted, so P(I|~M) is unlikely to be 1.
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7 of 9 people found the following review helpful
5.0 out of 5 stars Historians should be Bayesians, 4 April 2013
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Bayesian reasoning is widely used in a range of scientific disciplines. According to the GP Margaret McCartney, for example, Bayesian reasoning is "a good description of how medicine is practised" (The Patient Paradox: Why Sexed Up Medicine is Bad for Your Health). Historians, however, have yet to discover the delights of Bayes's Theorem, and Richard Carrier wants that to change. In this important book Carrier pursues two related objectives: "first, to demonstrate when and why existing methods of historical reasoning are valid; and second, to provide a model of reasoning that can be directly employed in historical analysis and argument. The latter is methodological, the former is epistemological."

For those historians who baulk at what appears to be a purely scientific methodology, and one that involves a daunting-looking equation, Carrier points out that many sciences such as geology and cosmology are in fact historical, in the sense that they "explore not merely scientific generalizations but historical particulars, such as when the Big Bang occurred". Indeed, much of science involves field observations and doesn't rely on experiments. "History is thus continuous with science. The difference between them is only quantitative: history must work with much less data, of much less reliability."

Every time we say that some event is "implausible" or "unlikely" we are "covertly making a mathematical statement of probability" - whether or not that is what we think we are doing. (In Believing in Magic: Psychology of Superstition, the psychologist Stuart Vyse makes a similar point: "Much of our day-to-day thinking is quantitative, whether we are aware of it or not.") Carrier tabulates a canon of probabilities, with five percentages on either side of "even odds" that range from "virtually impossible" to "virtually certain" (both one in a million) and include "very improbable" and "very probable" (both one in twenty). Thus he links familiar verbal descriptions with their underlying numbers, emphasizing the probabilistic nature of historical knowledge.

Judgements about degrees of belief reflect the uncontroversial fact that ignorance and uncertainty are hallmarks of good scholarship in any discipline. In history, as in science, very little is known for sure, and confidence must often be measured in relative degrees of certainty. Historians learn to avoid black-and-white terms like "true" and "false" and to be comfortable with ambiguity, uncertainty and ignorance (just like scientists, according to Firestein in Ignorance: How It Drives Science). This state of affairs is tailor-made for Bayes's Theorem, which can be formulated as a theory of warrant rather than of truth: it tells us what we are warranted in believing, not what is true in any absolute sense.

One sign of poor scholarship - and a common failure of critical thinking - is eagerness to adopt a particular explanation just because it "fits the evidence". Many explanations will fit (in fact, an infinite number are logically possible), but not all are equally believable. Working out the probability that our hypothesis is true (in the language of Bayes) entails not only examining "the specific evidence that requires explanation" (which our hypothesis purports to explain), but also taking into account any relevant background knowledge ("everything all historians know or should be able to know") and all the significant alternative hypotheses. Bayes's Theorem shows that the probability that our hypothesis is true follows necessarily from four other probabilities (technically, the prior and consequent probabilities).

One huge advantage of Bayes over the historicity criteria that have "so dismally failed" is that the theorem has been proved and is therefore logically valid. The maths represents a logic that "models the structure of all sound historical reasoning". (Logic matters, since invalid arguments can never reliably produce true conclusions; see, for example, Rulebook for Arguments. Logic is also no respecter of departmental boundaries, even if some corners of the academy are less respectful of logic than they should be.)

In a short first chapter Carrier outlines the central problem that bedevils attempts to get to the "real" historical Jesus (the method of criteria), the consequences of the failure of this methodology (a more confused picture of Jesus), and the solution (Bayes's Theorem). A second chapter covers the basics, the set of methodological assumptions to which all historians should subscribe, and a third introduces Bayes's Theorem. The core of the book comprises two chapters on the Bayesian analysis of historical methods and criteria, in which Carrier aims to show both the limitations of some aspects of the existing methodology and the power of the Bayesian approach. For example, the criterion of coherence ("the most insidious of them all") "assumes that anything that coheres with what has been established with other criteria is also historical." The problem here is that good fiction is often just as "coherent" as historical fact. Indeed, it can be even more so, for coherence is easy to create by design, and "is just as common and expected on hypotheses of fabrication."

The most egregious example of historians using the same method on the same facts to get a whole range of different results is in Jesus studies. For Carrier, this shows that the method of criteria "is invalid and should be abandoned" and he insists that "agreement on the fundamentals of method is the first essential requirement for any community of experts to deem itself an objective profession." To this end he proposes that professional historical inquiry should be based on a set of core epistemological assumptions: the twelve axioms of historical method that "represent the epistemological foundation of rational-empirical history." For good measure, there are also twelve rules all historians should follow. Again, axioms and rules may seem alien in a subject like history, but many of these will already be familiar to historians, and to anyone with a grounding in critical thinking (for example, the eleventh axiom invalidates cherry-picking and special pleading and other abuses of logic and evidence).

In Did Jesus Exist?: The Historical Argument for Jesus of Nazareth, Bart Ehrman relies heavily on the method of criteria (for example, "the criterion of dissimilarity") to establish his conclusion that the historicist position is right and the mythicist position wrong. While Carrier does not fully address the historicity of Jesus here (he will do that in a forthcoming volume), he does undermine the consensus position: "the many contradictory versions of Jesus now confidently touted by different Jesus scholars" cannot all can be true, but they can all be false. And if they are all false, does that mean there never was a historical Jesus?

Carrier offers three basic rules to laypeople who ask him what history to trust: "(1) don't believe everything you read; (2) always ask for the primary sources of a claim you find incredible; and (3) beware of scholars who make amazing claims about history but who are not experts in the period". As a layreader, I confess that I found the book tough going in places (nearly a third is taken up with the final chapter, ominously called "The Hard Stuff"). For the professional historian, however, "it's too hard" is not an excuse we should ever hear, "because mastering difficult methods is what separates professionals from amateurs." In one important respect, however, Bayes's Theorem should make the historian's life easier, since it brings into the open unstated assumptions and so facilitates the resolution of disagreements.

Only cranks and crackpots challenge the ability of science to understand the world around us. So why is history, which is the study of the world no longer around us, so firmly rooted in the humanities? Few historians will dispute Carrier's claim that they "need solid and reliable methods" and that their arguments must be logically valid and factually sound. (Those that do dispute this claim ought to pack up and become historical novelists instead.) Although Carrier makes a good case for Bayes's Theorem to be taken seriously by historians, it remains to be seen whether they will embrace Bayes with any enthusiasm. What does seem certain is that Bayesian reasoning will help us to see more clearly into our past, and that this book will help historians see more clearly the value of Bayes's Theorem.
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1 of 2 people found the following review helpful
5.0 out of 5 stars Short review on the go - BRILLIANT!, 6 July 2013
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This review is from: Proving History: Bayes's Theorem and the Quest for the Historical Jesus (Kindle Edition)
This book is amazing in delivering scientific method of testing hypothesis, namely by introduction of Bayes Theorem to historians, and then using it to test any supernatural and natural claim we may encounter, not only regarding the existence of mythological creatures like Jesus. Bayes Theorem is an useful tool to test probabilities of any hypothesis and should be learned by everyone working with scientific method. Read that book not only if you're interested in proving or disproving Jesus but mainly to learn about usefulness of Bayes Theorem in science and testing hypothesis even if your only estimated possibilities are vague descriptions, not hard numbers. Highly recommended!
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