Here I want to briefly try to explain what I believe is the fundamental difference between a “known event” in history and a “probable” event. (This is, of course, a continuation of the ideas I presented in my four-part series on what I attempted to argue was Richard Carrier’s misapplication to Bayesian probability to “all historical claims”.)
Carrier does not believe that all our knowledge is a question of degree of probability.
All claims have a nonzero epistemic probability of being true, no matter how absurd they may be (unless they’re logically impossible or unintelligible), because we can always be wrong about anything. And that entails there is always a nonzero probability that we are wrong, no matter how small that probability is. And therefore there is always a converse of that probability, which is the probability that we are right (or would be right) to believe that claim. This holds even for many claims that are supposedly certain, such as the conclusions of logical or mathematical proofs. For there is always a nonzero probability that there is an error in that proof that we missed. Even if a thousand experts check the proof, there is still a nonzero probability that they all missed the same error. The probability of this is vanishingly small, but still never zero. Likewise, there is always a nonzero probability that we ourselves are mistaken about what those thousand experts concluded. And so on. The only exception would be immediate experiences that at their most basic level are undeniable (e.g., that you see words in front of you at this very moment, or that “Caesar was immortal and Brutus killed him” is logically impossible). But no substantial claim about history can ever be that basic. History is in the past and thus never in our immediate experience. And knowing what logically could or couldn’t have happened is not even close to knowing what did. Therefore, all empirical claims about history, no matter how certain, have a nonzero probability of being false, and no matter how absurd, have a nonzero probability of being true. Therefore, because we only have finite knowledge and are not infallible, apart from obviously undeniable things, some probability always remains that we are mistaken or misinformed or misled. (Proving History, 24f)
When I first read those words soon after Proving History was published I went along with them, believing them to be at least theoretically true. In theory, yes, we can always be wrong about anything, so yes, even the most secure knowledge must have a non-zero chance of being wrong even if that chance is infinitesimally small. But is that really true in practice, or in the practical world of experience?
Yes, history is “in the past” but does it follow, as Carrier reasons above, that every single claim about the past has a “nonzero probability of being false”? In theory I might surmise that to be so. I might surmise that I don’t even exist and everything I am experiencing is someone else’s dream. But in reality, in the real world where I have to live, I don’t really believe that.
Look at the exception that I have highlighted in the quotation. What the example points to is empirical experience, the experience of our senses. We can call this empirical knowledge. We do not think that there is a nonzero possibility that we are wrong, that there is some chance that we are not really experiencing these words right now. Some things we do know with absolute certainty.
We not only know what we can empirically experience but we can also communicate our empirical knowledge to one another. Further, we can establish ways of assuring others that the knowledge we transmit is reliable. When I read inscribed words on monuments testifying to a tragic event that happened before my time, I know that event happened. There are a host of empirical markers that assure me of the authenticity of the event being recorded in the inscription: the public space the monument occupies, the official emblems and standardised quality of the monument, the names and dates I can verify in other public records, and so forth. There is no doubt and no room for doubt — not even an “infinitesimally small” doubt — that the event memorialised actually happened. I have used the example of the Japanese bombing of Pearl Harbor as an example of such an empirically grounded historical event for which there is no room at all to doubt that it happened.
It does not follow that because something is not part of our immediate experience, that it happened in the past, that there is necessarily some room for doubt about its past reality. Is there room for any doubt about the reality of the atomic bombing of Hiroshima and Nagasaki? Or of the events known as the Holocaust? Or of the displacement of indigenous peoples by white settlers in certain countries throughout the nineteenth century? We have records that we can test for authenticity and that confirm these events of the past. There is no room for any doubts at all. They are all empirically established facts of the past. We can prove they all happened without any shadow of doubt.
The further back we go, generally speaking, the fewer remains we have of past events and the less we know. But what we do know is based on the same kinds of verifiable empirical evidence. (I am speaking generally. Sometimes hoaxers, for example, planted forgeries with the intent to deceive. But those sorts of examples only highlight the need for care we take as a rule to authenticate our sources.)
Humans have the ability to communicate information along with ways of assuring others of its authenticity. Being human, we know how easy it is to be deceived and for others to practise deception. Hence we build safeguards and apply empirical methods to establish authenticity and assurance.
When historians research the events of the past, as a rule they are researching events that have been empirically determined to have happened. They are seeking to understand those events. Different historians will have different views about those events but the events themselves will be empirically determined to have happened. (Yes, there are some grey areas where doubts are raised but I am speaking generally, for the most part.)
Where the Historical Problem Enters
If after I have empirically established the reality of the event of Japan’s attack on Pearl Harbor, I still have a giant gap in my knowledge. What is missing is not complete assurance that it happened — I have full assurance that it happened — but I do not know the reality of what it was like. I do not know all the details and I can only guess or imagine what the participants experienced. The event is gone. It no longer exists. It has to be reconstructed. That’s where my imagination enters, informed as best it can be by surviving records of the event. No reconstruction can ever recreate the event exactly as it happened. Every reconstruction must inevitably be partial and from a particular perspective.
That is the problem of historical knowledge per se. In the history wars in Australia, for example, different parties want to reconstruct past events relating to the Aboriginals differently. Some want to see the killings as the work of a few “bad apples” and far from systematic. Others believe it is necessary to introduce other sources that point to racist attitudes that enabled the killings. Some debate the relevance and interpretations of those new sources. And so forth. That is where the historical debates tend to happen. There is no question that certain events did actually take place. Arguments will often centre over the physical extent of those events, the motivations or awareness of those involved, etc.
Some can view the British and Roman empires of blessings to humanity. Some will view them as horrific blights on history. Others will have various shades in between. But that there were such empires in history cannot be doubted any more than you can doubt that you are reading these words right now. The empirical evidence for them leaves no room for doubt.
Empirically established knowledge is not the same as Bayesian probabilistic knowledge.
A few readers have indicated to me that my recent series of posts on the problematic use of Bayes Theorem for assessing “historical claims” have failed to make their intended point.
Hopefully here I can succinctly explain why Bayes cannot help us decide whether Christianity began with a historical Jesus.
Reason #1: If our question is simply, Did Jesus Exist? then it is meaningless. What is of interest is the question of how Christianity originated. What might Jesus have done that gave birth to the Christian religion? What did others do during the time of Jesus or after him that shaped or established Christianity? Those are the meaningful questions. Simply saying Jesus did or did not exist is somewhat pointless — unless, perhaps, one wants a negative answer in order to irritate believers.
Reason #2: If by using Bayes one concludes that Jesus “probably did not exist” then again, we have to ask, So what? If it appears unlikely that he existed then after weighing up the probabilities on the basis of the various strands of data, that tells the historian nothing useful at all. Simply saying that Jesus fits the pattern of mythical persons, if that’s where Bayesian inference leads, does not answer the question of whether he existed or not. Simply saying that there is, say, an 80% chance he did not exist still leaves open the possibility that he did exist. So what has been achieved? Nothing useful for the historian at all. Likewise, calculating that there is an 80% chance that he did exist would still leave open the possibility that he did not. The historian is no better off with either result.
I suspect King Philip II of Spain saw the odds of his Spanish Armada crushing the English fleet as overwhelmingly high. The odds against an event happening are irrelevant are irrelevant if they happen. And many times the unexpected and “out of the blue” does happen in history. That they may have been judged to have been unlikely at the time makes no difference to the fact that they happened and are part of the historical record.
Most historical events are “unlikely” or unforeseen until after they happen. After they happen commentators and the rest of us can see how “inevitable” they were. We can always predict what will happen after it happens. Carrier’s mythicist hypothesis can predict the type of evidence the historian will find after the hypothesis was originally formulated on the basis of that evidence. One might look at any number of events in the past and ask, What was the likelihood of X happening? The chances that I will be struck by lightning are very slim indeed. But if I were to be struck by lightning this weekend — stormy weather appears to be approaching — the odds against it happening will mean absolutely nothing against the fact (fingers crossed it won’t be a fact) that it “happened”! Odds against something happening are meaningless when investigating “what did happen”.
We don’t need Bayesian calculations to decide whether there was a Roman empire, or whether its emperors were worshiped as deities, or whether the Roman power destroyed the Jewish temple in 70 CE. The kind of evidence we have for the “raw facts” of the past, including who lived and who did what, are grounded in the same kinds of judgments we make in testing the authenticity of modern claims, whether they be events reported in the news or checking the reliability of advertised claims about a product that interests us. Some of us are less careful with respect to such matters than is healthy and easily believe false claims, present and past. When a historian is interested in whether “new facts” can be dug up to throw new light on a question, it is to the archives, to official records, to diaries and letters and reports of various kinds that they turn. These are tested for authenticity and reliability. If there is doubt about any detail it is more likely to find its way into publication by way of a footnote — with its questionable status clearly noted.
The only justifiable approach to reconstructing Christian origins is to build on the sources we have and on what we know about them — not on what we surmise about them. That approach will not allow us to join in the games of imagining what Jesus and his followers may have done. (We have stories of Jesus and we cannot assume — without justification that would pass the test in any other field of sound empirical inquiry — that they must be based on true events.) We will not have the wealth of details we would like if we avoid make-believe games. But the professional will not apologize for tailoring the question and scope of inquiry to accord with the extent and nature of the source material.
Sure, there is room for Bayesian probability when it comes to drawing certain kinds of inferences from archaeological data or for comparing the likelihood of competing hypotheses, but claiming that so-and-so did or did not exist is by itself a rather meaningless exercise for the reason I stated above.
(See also the section of my earlier post pointing out that not even postmodernist historians work with “what probably happened“.)
To address one specific point I referred to in my recent series: It may well be that one can find in literature more mythical persons who fit a Rank-Raglan hero type, but that is irrelevant to the fact that some historical persons did resurface in later literature wearing Rank-Raglan features (born of a virgin, died on a hill, etc). But even Raglan himself understood that the historicity of a figure was unrelated to the fact that fanciful tales were later told about him or her. If Jesus scores more highly than other historical figures on the R-R scale, so be it: such a “fact” would have no bearing whatever on whether or not he might have been historical. Ask Raglan himself.
Next, he devised a thought experiment, a 1700s version of a computer simulation. Stripping the problem to its basics, Bayes imagined a square table so level that a ball thrown on it would have the same chance of landing on one spot as on any other. Subsequent generations would call his construction a billiard table, but as a Dissenting minister Bayes would have disapproved of such games, and his experiment did not involve balls bouncing off table edges or colliding with one another. As he envisioned it, a ball rolled randomly on the table could stop with equal probability anywhere.
We can imagine him sitting with his back to the table so he cannot see anything on it. On a piece of paper he draws a square to represent the surface of the table. He begins by having an associate toss an imaginary cue ball onto the pretend tabletop. Because his back is turned, Bayes does not know where the cue ball has landed.
Next, we picture him asking his colleague to throw a second ball onto the table and report whether it landed to the right or left of the cue ball. If to the left, Bayes realizes that the cue ball is more likely to sit toward the right side of the table. Again Bayes’ friend throws the ball and reports only whether it lands to the right or left of the cue ball. If to the right, Bayes realizes that the cue can’t be on the far right-hand edge of the table.
He asks his colleague to make throw after throw after throw; gamblers and mathematicians already knew that the more times they tossed a coin, the more trustworthy their conclusions would be. What Bayes discovered is that, as more and more balls were thrown, each new piece of information made his imaginary cue ball wobble back and forth within a more limited area.
As an extreme case, if all the subsequent tosses fell to the right of the first ball, Bayes would have to conclude that it probably sat on the far left-hand margin of his table. By contrast, if all the tosses landed to the left of the first ball, it probably sat on the far right. Eventually, given enough tosses of the ball, Bayes could narrow the range of places where the cue ball was apt to be.
Bayes’ genius was to take the idea of narrowing down the range of positions for the cue ball and—based on this meager information—infer that it had landed somewhere between two bounds. This approach could not produce a right answer. Bayes could never know precisely where the cue ball landed, but he could tell with increasing confidence that it was most probably within a particular range. Bayes’ simple, limited system thus moved from observations about the world back to their probable origin or cause. Using his knowledge of the present (the left and right positions of the tossed balls), Bayes had figured out how to say something about the past (the position of the first ball). He could even judge how confident he could be about his conclusion. (p. 7)
In the late 1990s Earl Doherty revitalized public interest in the question of whether Jesus had been a historical figure with the Jesus Puzzle website (a new version is now available here) and book, The Jesus Puzzle (link is to a publicly available version — though Doherty subsequently published a much more detailed volume a few years later). In the wake of that controversy Richard Carrier undertook to examine the arguments for and against the existence of Jesus with the authority of a doctorate in ancient history behind him. To this end, Carrier initially published two works, the first, Proving History, laying the groundwork of the method he would be using to address the question of Jesus’ historicity, and then On the Historicity of Jesus, the volume in which he applied his Bayesian probability* approach to the question. In that second volume Carrier concluded that the odds against Jesus having existed were significantly higher than the opposing view.
Carrier regularly argued that the evidence to be found in the New Testament was predicted or could well have been predicted by the hypothesis that Jesus did not exist. As noted in my previous post, the term he used most often was “expected”, but he made clear in Proving History by “expectation” in this context he meant “predicted”.
Prediction or Circularity?
It would have been more accurate to have simply said that the evidence cited is consistent with the view that Jesus did not exist. The hypothesis did not “predict” any evidence. Indeed, one might even say that the hypothesis was drawn from the sources in the first place, so it is circular logic to then say that the hypothesis predicted the evidence that gave rise to that hypothesis.
Carrier’s stated aim is to form a
hypotheses that make[s] … substantial predictions. This will give us in each case a minimal theory, one that does not entail any ambitious or questionable claims . . . a theory substantial enough to test. (On the Historicity [henceforth = OHJ], 30 – bolding is my own in all quotations)
I argue, rather, that all Carrier has been able to accomplish is to show that a hypothesis is consistent with the data that it was created to explain. Historical research, as I have been attempting to show in the previous posts, cannot “predict” in the ways Carrier asserts.
Carrier begins with a “minimal Jesus myth theory”:
. . . the basic thesis of every competent mythicist, then and now, has always been that Jesus was originally a god, just like any other god (properly speaking, a demigod in pagan terms; an archangel in Jewish terms; in either sense, a deity), who was later historicized, just as countless other gods were, and that the Gospel of Mark (or Mark’s source) originated the Christian myth familiar to us by building up an edifying and symbolically meaningful tale for Jesus, drawing on passages from the Old Testament and popular literature, coupled with elements of revelation and pious inspiration. The manner in which Osiris came to be historicized, moving from being just a cosmic god to being given a whole narrative biography set in Egypt during a specific historical period, complete with collections of wisdom sayings he supposedly uttered, is still an apt model, if not by any means an exact one. Which is to say, it establishes a proof of concept. It is in essence what all mythicists are saying happened to Jesus.
Distilling all of this down to its most basic principles we get the following set of propositions:
1. At the origin of Christianity, Jesus Christ was thought to be a celestial deity much like any other.
2. Like many other celestial deities, this Jesus ‘communicated’ with his subjects only through dreams, visions and other forms of divine inspiration (such as prophecy, past and present).
3. Like some other celestial deities, this Jesus was originally believed to have endured an ordeal of incarnation, death, burial and resurrection in a supernatural realm.
4. As for many other celestial deities, an allegorical story of this same Jesus was then composed and told within the sacred community, which placed him on earth, in history, as a divine man, with an earthly family, companions, and enemies, complete with deeds and sayings, and an earthly depiction of his ordeals.
5. Subsequent communities of worshipers believed (or at least taught) that this invented sacred story was real (and either not allegorical or only ‘additionally’ allegorical).
That all five propositions are true shall be my minimal Jesus myth theory. (OHJ 52f)
By explaining that his “minimal myth theory” consists of the core of what Jesus myth exponents themselves have claimed, Carrier in fact is conceding that his “minimal” points are based on the information available in the sources that he will proceed to say he will “expect” to find, or to “predict” will be in the sources. (Earl Doherty, in particular, was Carrier’s source for the interpretation that Jesus was originally understood to be a deity in heaven rather than a man on earth.)
Now those mythicists such as Earl Doherty arrived at their concept of a mythical Jesus in large measure as a result of analysing and drawing conclusions directly from the New Testament itself as well as from extra-biblical sources. So when Carrier declares that the evidence in the New Testament is what his “minimal Jesus myth theory” “expected” or “predicted”, he is in effect reasoning in a circle. The mythicist view of Doherty (and of many other earlier mythicists) was based on his reading of the New Testament. So the passages in the New Testament can hardly have been what would be “expected” according to mythicism; rather, they were the beginning of the “theory”, not its expected conclusion.
The approach as Carrier sets it out sounds scientific enough ….
We have to ask of each piece of evidence:
1. How likely is it that we would have this evidence if our hypothesis is true? (Is this evidence expected? How expected?)
2. How likely is it that the evidence would look like it does if our hypothesis is true? (Instead of looking differently; having a different content, for example.)
3. Conversely, how likely is it that we would have this evidence if the other hypothesis is true? (Again, is this evidence expected? How expected?)
4. And how likely is it that the evidence would look like it does if that other hypothesis is true? (Instead of looking differently; having a different content, for example.)
And when asking these questions, the ‘evidence’ includes not just what we have, but also what we don’t have. Does the evidence—what we have and what we don’t, what it says and what it doesn’t—make more sense on one hypothesis than the other? How much more? That’s the question. (OHJ, 278)
But the problem is that all of those questions were raised and fully addressed by Earl Doherty and others when they formulated their view that, on the basis of their answers to those questions, Jesus was a mythical creation and not a historical figure. So to turn around and begin with the conclusions of mythicists to say that the evidence we find in the New Testament is exactly what we would expect according to mythicism, is to simply work backwards from what the mythicists have done in the first place.
In other words, there is no prediction of what one might find in the evidence. There is no “expectation” that we might find such and such sort of idea. Rather, the sources themselves have long raised the kinds of questions that have led to the mythicist theory in the first place.
Example 1: Clement’s Letter
Look at the example of Carrier’s reference to the letter of 1 Clement:
The fact that this lengthy document fully agrees with the expectations of minimal mythicism, but looks very strange on any version of historicity, makes this evidence for the former against the latter. . . . [O]n minimal mythicism this is exactly the kind of letter we would expect to be written in the first century entails that its consequent probability on mythicism is 100% (or near enough). (OHJ, 314f – italics in the original in all quotations)
But Doherty’s mythicist view was shaped by such evidence. So the characteristics of Clement’s letter are what lay behind the mythicist view, so it is erroneous to say that the letter is what we would expect if mythicism were true. Doherty, for example, notes
Clement must be unfamiliar with Jesus’ thoughts in the same vein, as presented in Matthew’s Sermon on the Mount and Luke’s Sermon on the Plain. Clement also shows himself to be unfamiliar with the Gospel teachings of Jesus on many other topics discussed in his letter.
When Clement comes to describe Jesus’ suffering (ch.16) we must assume that he has no Gospel account to paraphrase or quote from memory, for he simply reproduces Isaiah 53. His knowledge of Jesus’ passion comes from scripture. Clement’s ignorance on other Gospel elements has been noted at earlier points in this book. . . .
Since Clement knows so little of oral traditions about Jesus . . . .
We have seen in the Pauline letters that the heavenly Christ was regarded as giving instructions to prophets through revelation. Clement shares in the outlook that sees Christ’s voice as residing in scripture. . . .
In Clement’s world, these things have come to be associated with revelations from the spiritual Christ. . . (Jesus Puzzle, 261f)
The oddities in the letter of Clement have piqued the curiosity of those who have seen in them support for the mythicist view of Jesus. The mythicist view of Jesus does not “predict” that such a letter would exist. It is the other way around.
Example 2: Extra-Biblical Sources
Notice another instance of this circularity.
When it came to the pervasive silence in other external documents (Christian and non-Christian), and the lack of many otherwise expected documents, I assigned no effect either way (although sterner skeptics might think that far too generous to minimal historicity). . . .
The probabilities here estimated assume that nothing about the extrabiblical evidence is unexpected on minimal mythicism. So the consequent probability of all this extrabiblical evidence on … (minimal mythicism) can be treated as 100% across the board . . . . Either way, as a whole, the extrabiblical evidence argues against a historical Jesus. It’s simply hard to explain all its oddities on minimal historicity, but not hard at all on minimal mythicism. (OHJ, 356, 358)
On the contrary, it is the extra-biblical sources that have been in part responsible for generating doubts about the historicity of Jesus ever since at least the early nineteenth century. If the extra-biblical evidence were different then the question of Jesus’ historicity is unlikely to have arisen in the first place.
I have no quibble with Carrier’s last two sentences in the above quotation if they are taken alone, without the context of “expectation/prediction”. What they are really confirming is that the available evidence is consistent with the mythicist view, not that it is predicted by mythicism.
Example 3: Expected Fiction?
In discussing one particular miraculous event in the life of Jesus Carrier concludes:
As history, all this entails an improbable plethora of coincidences; but as historical fiction, it’s exactly what we’d expect. (OHJ, 487)
In this case what is said to be “expected” is nothing more than a definition of the nature of fiction. The unbelievable coincidences define the story as fiction. They are not the expected observation of something already known to be fiction. They are the fiction.
Example 4: Paul’s Letters
The foundation of all Jesus myth views from Arthur Drews and Paul-Louis Couchoud to George Albert Wells and Earl Doherty has been the epistles of Paul. The questions raised by what Paul does not say and the ways he speaks in what he has to say have raised perennial questions among theologians so there is no surprise to find many passages becoming bedrock among mythicist arguments. So to say that those passages in Paul are what might be predicted by mythicism is getting everything back to front. Those passages are largely the foundation of the mythicist views, the port from which mythicism sailed, not the new continent of evidence it discovered or “expected”.
Again Carrier phrases the problem in terms of “prediction” of what one will find in the sources:
So even if, for example, a passage is 90% expected on history (and thus very probable in that case), if that same passage is 100% expected on myth, then that evidence argues for myth . . . .This is often hard for historians to grasp, because they typically have not studied logic and don’t usually know the logical basis for any of their modes of reasoning . . . .
I have to conclude the evidence of the Epistles, on all we presently know, is simply improbable on h (minimal historicity), but almost exactly what we expect on -h (minimal mythicism). . . .
Paul claimed these things came to him by revelation, another thing we expect on mythicism. . . .
On the [mythicism] theory, this is pretty much exactly what we’d expect Paul to write. . . .
This passage in Romans is therefore improbable on minimal historicity, but exactly what we could expect on minimal mythicism. . . .
Whereas this is all 100% expected on minimal mythicism.
The evidence of the Epistles is exactly 100% expected on minimal mythicism. . . In fact, these are pretty much exactly the kind of letters we should expect to now have from Paul (and the other authors as well) if minimal mythicism is true. (OHJ, 513, 528, 536, 566, 573, 574, 595)
Predicting or Matching the Evidence?
So Carrier is able to conclude,
All the evidence is effectively 100%, what we could expect if Jesus didn’t exist and minimal mythicism, as defined [above], is true. (OHJ, 597)
On the contrary, I suggest that many readers have noticed that the sources contain difficulties if we assume Jesus to have lived in the real world outside the gospels. It is from those “difficulties” that are apparently inconsistent with a historical figure that the Jesus myth view has arisen. By proposing to “test” the mythicist view by setting up “expectations” of what we will find in the sources really comes down to merely confirming the problematic passages in the sources that gave rise to the myth view in the first place.
What Carrier is doing, I suggest, is simply describing the sources that have given rise to doubts about the existence of Jesus. There is no prediction involved at all. He is describing the state of the evidence and showing how it is consistent with his “minimal Jesus myth theory”, something all other Jesus myth scholars before him have done — only without the veneer of scientific assurance.
Historians as a rule cannot predict what will be found in the available sources that might test their hypotheses. They usually do no more than point to what they believe to be consistent with their hypotheses.
The Rank-Raglan Hero Class and Prediction Therefrom
In the opening post of this series I addressed Carrier’s use of the Rank-Raglan “hero class” as a conceptual framework for certain types of persons in ancient myths and legends. There I noted that it is misleading to apply a percentage probability figure to Jesus (or anyone) being a member of that class because the total number of persons sharing the features of that class are well below 100. This is more than a pedantic point. The numbers of characters are not only limited, but they belong to distinctively unique cultural settings. This is the nature of all historical events. No two events are ever alike and no events are ever repeated except in the most general sense. Yes, there have been wars forever, but no two wars are ever alike. Each has had its own causes that are unrepeatable.
Here are the twenty-one names studied by Raglan as sharing a features (born from a virgin, nothing of his childhood is known, etc) from a second list of random length (Raglan said he could have added many more common features — see the earlier post):
Oedipus
Theseus
Romulus
Heracles
Perseus
Jason
Bellerophon
Pelops
Asclepios
Dionysos
Apollo
Zeus
Joseph
Moses
Elijah
Watu Gunung
Nyikang
Sigurd or Siegfried
Llew Llawgyffes
Arthur
Robin Hood
We know that historical persons have been associated with mythical stories overlapping with the lives of those in the above list: Sargon, Cyrus, Alexander the Great, even Plato was said to have been born from a virgin mother, fathered by the god Apollo. But those mythical or “hero class” features of Cyrus and Alexander are quite distinct from the actual historical person; that fantastical myths have been told about real people makes no difference to the reality of those historical persons. As Raglan himself declared:
If, however, we take any really historical person, and make a clear distinction between what history tells us of him and what tradition tells us, we shall find that tradition, far from being supplementary to history, is totally unconnected with it, and that the hero of history and the hero of tradition are really two quite different persons, though they may bear the same name. (The Hero, 165)
If historical persons are known to have accrued mythical features of the Rank-Raglan type, then it does not follow that any person about whom such tales are told is likely to have not existed in reality. Simply counting up so many features (e.g. born of a virgin, attempt on his life as a child, etc) and saying “real myths” had more of those features than historical persons does not make any difference. Adding up more “hero class” labels to apply to any one person would be nothing more than evidence of more highly creative composers. Moreover, such fanciful tales appear to be born from the minds of the literate at a specific time and are not haphazard accretions of illiterate storytelling:
If biblical scholars took note of Raglan’s point here about such myths being literary and not popular in origin they would need to take a second hard look at their attempts to find the historical Jesus through oral traditions and memory theory, since oral traditions and memory theory are built on the assumption that the tales were of popular origin.
It should . . . be noted that this association of myths with historical characters is literary and not popular. There is no evidence that illiterates ever attach myths to real persons. The mythical stories told of English kings and queens—Alfred and the cakes, Richard I and Blondel, Queen Eleanor and Fair Rosamund, Queen Margaret and the robber, and so on—seem to have been deliberately composed; a well-known character and an old story were considered more interesting when combined. . . .
“From the researchers of J. Bedier upon the epic personages of William of Orange, Girard de Rousillon, Ogier the Dane, Raoul de Cambrai, Roland, and many other worthies, it emerges that they do not correspond in any way with what historical documents teach us of their alleged real prototypes.” (The Hero, 172, 174 — the latter citing A. van Gennep)
The conclusion we must draw is that the miraculous tales told about Jesus are at most evidence of the creative imaginations of literate classes. Whether a Jesus existed historically behind these tales is still quite possible and the mythical tales about him make no difference to that possibility. Tales are indeed told of historical persons that “do not correspond in any way” with the true historical figure. The only aspect in common seems to have been their name. If Jesus has more and more amazing tales told about him than others it follows that literate story tellers were more abundant or creative than for other figures. Such tales tell us nothing about the likelihood of his historicity.
I conclude that it is erroneous to use the Rank-Raglan hero class to indicate a prior probability of whether Jesus existed or not. Every situation in history is different. If the Greeks had many heroes of a certain type, and if the tales told about Jesus shared many tropes of those Greek heroes, it might mean nothing more than that very fanciful tales were told about Jesus that caused the “real Jesus” to be lost behind the world of myth. Many theologians would agree. In other words, the historian cannot make predictions based on probabilities to determine how likely any historical event or person might have been. Historical events and persons are contingent. They are all distinctive and unrepeatable. They either happen or exist or they do not. Or the researcher simply does not know if they did or not. Probability does not enter the discussion.
The Evidence: Expected or Known in Advance?
What Carrier calls “expected evidence” is, rather, a description of what has been with us (and Jesus myth researchers) from the beginning. The state of evidence gave rise to certain questions that led to suspicions that Jesus was not a historical figure. So returning to that evidence and saying that the myth notion “predicted” the state of that evidence is a misplaced project.
Try to imagine, if you can, that you have never heard of Christianity. Try to imagine what a new ancient religion would look like if it combined features of Greco-Roman mystery cults and some form of Judaism. If you had never heard of Christianity would you really imagine a religion that turned out to be very much like Christianity? I doubt it. You might postulate a series of angelic beings or just one of them, or a translated Enoch, in the distant mythical past turned into saviour deities in some fashion. You would surely see little reason to introduce a human deity in recent times. Yet Carrier concludes his major study on the historicity of Jesus with the conviction that his hypothesis predicted (or “could have predicted”) the beginnings of Christianity:
So we should actually have expected Jewish culture to find a way to integrate the same idea; after all, every other national culture was doing so. And this is where we have to look at the possibilities in light of what we now know. Had I been born in the year 1 and was asked as a young educated man what a Jewish mystery religion would look like, based on what I knew of the common features of mystery cult and the strongest features of Judaism, I could have described Christianity to you in almost every relevant particular—before it was even invented. It would involve the worship of a mythical-yet-historicized personal savior, a son of god, who suffered a death and resurrection, by which he obtained salvation for those who communed with his spirit, thereby becoming a fictive brotherhood, through baptism and the sharing of sacred meals. How likely is it that I could predict that if that wasn’t in fact how it came to pass? Influence is the only credible explanation. To propose it was a coincidence is absurd. (OHJ, 611)
It is very easy to predict the current state of the evidence that has been with us from the beginning. Prediction in hindsight is easy. It is so easy to know what to have expected after the event. We only have to compare the many predictions that the recent US elections would be a tight race between Kamala Harris and Donald Trump. After the election it was easy to look back and see what we “should have expected” and why.
Jesus either existed or he did not. If he existed it was not with a probability of less than 1. If he existed he existed 100%. If we can’t be sure he existed then we are not sure or we cannot know. If we cannot know we cannot say he may have existed at a 30% probability. That would make no sense if he existed. If the historian does not know for sure then the historian does not know. The historian may say it is likely or not likely he existed, but that still leaves the question unanswered. Those are the fundamental options with respect to any historical event — it either happened or it didn’t or we have no evidence or at best ambiguous evidence for it happening.
Thomas Bayes (Wikimedia)
Don’t get me wrong. I like Bayes’ theorem. It is a brilliant tool at doing what it was designed to do. But historical research is not a science and few historians, maybe a few die-hard stubborn empiricist historians, would claim it is a science that can predict what will be found in the sources or even sometimes what will happen in the future. Historical events are unique. The justified historical approach to the question of Jesus is to study the Jesus bequeathed to us in the surviving sources. Whether a historical figure behind the myth and theology historically existed is an unknown and unknowable question, and, I think, ultimately irrelevant.
Carrier, Richard. On the Historicity of Jesus: Why We Might Have Reason for Doubt. Sheffield Phoenix, 2014.
Doherty, Earl. The Jesus Puzzle: Did Christianity Begin with a Mythical Christ? Canadian Humanist Publications, 1999.
Rank, Otto, Raglan, and Alan Dundes. In Quest of the Hero. Mythos. Princeton University Press, 1990.
It’s been a long while since I wrote about Jesus mythicism. I hope what I write now will present a slightly different and useful perspective.
Should not Christian apologists be thrilled with Richard Carrier’s widely known conclusion and welcome it:
In my estimation the odds Jesus existed are less than 1 in 12,000. . . .
There is only about a 0% to 33% chance Jesus existed.
(On the Historicity of Jesus, 600, 607)
Doesn’t that indicate that Jesus was a truly exceptional figure according to the best conclusions of the atheist scholar? Don’t believing Christians want Jesus to be unique, to be different from anyone else, to bring about an unlikely event by normal human standards? A 1 in 12,000 figure is surely bringing Jesus down too close to normality, isn’t it? Shouldn’t Jesus be a unique figure in history? So if historical tools as understood and used by Richard Carrier conclude that Jesus is not to be expected in the annals of normal human history and left no record comparable to the records of other mortals for historians to ponder, should not apologists take comfort from such findings?
I want to address what appears to me to be a widespread misconception about historical knowledge across various social media platforms and in some published works where this question is discussed.
Too often I hear that historians can never be absolutely certain about anything in the past and that they always, of necessity, can only speak of “what probably happened”. (When I speak of historians I have in mind the main body of the historical guild in history departments around the world. I am not talking about biblical scholars and theologians because their methods are very often quite different.)
So let’s begin with Part 1 of the question of probability in historical research. Richard Carrier is widely known for reducing the entire question of Jesus’ existence to a matter of probabilities. I agree with much of Carrier’s approach but I also disagree on some major points. A fundamental point on which I disagree with Carrier is the claim that the most a historian can say about any historical event is that it is “probably” true. Carrier writes:
All claims have a nonzero epistemic probability of being true, no matter how absurd they may be (unless they’re logically impossible or unintelligible), because we can always be wrong about anything. And that entails there is always a nonzero probability that we are wrong, no matter how small that probability is. And therefore there is always a converse of that probability, which is the probability that we are right (or would be right) to believe that claim. This holds even for many claims that are supposedly certain, such as the conclusions of logical or mathematical proofs. For there is always a nonzero probability that there is an error in that proof that we missed. Even if a thousand experts check the proof, there is still a nonzero probability that they all missed the same error. The probability of this is vanishingly small, but still never zero. Likewise, there is always a nonzero probability that we ourselves are mistaken about what those thousand experts concluded. And so on. The only exception would be immediate experiences that at their most basic level are undeniable (e.g., that you see words in front of you at this very moment, or that “Caesar was immortal and Brutus killed him” is logically impossible). But no substantial claim about history can ever be that basic. History is in the past and thus never in our immediate experience. And knowing what logically could or couldn’t have happened is not even close to knowing what did. Therefore, all empirical claims about history, no matter how certain, have a nonzero probability of being false, and no matter how absurd, have a nonzero probability of being true.
(Proving History, 24f – my bolding in all quotations)
A little further on Carrier raises again the exception of a “trivial” event like an “uninterpreted [direct personal] experience”:
The only exceptions I noted are claims about our direct uninterpreted experience (which are not historical facts) and the logically necessary and the logically impossible (which are not empirical facts).17 Everything else has some epistemic probability of being true or false.
17. Of course “historical facts” do include direct uninterpreted experience, because all observations of data and of logical and mathematical relations reduce to that, but no fact of history consists solely of that; and “the logically necessary and the logically impossible” are empirical facts in the trivial sense that they can be empirically observed, and empirical propositions depend on them, and logical facts are ultimately facts of the universe (in some fashion or other), but these are not empirical facts in the same sense as historical facts, because we cannot ascertain what happened in the past solely by ruminating on logical necessities or impossibilities. Logical facts are thus traditionally called analytical facts, in contrast to empirical facts. Some propositions might combine elements of both, but insofar as a proposition is at all empirical, it is not solely analytical (and thus has some nonzero epistemic probability of being true or false), and insofar as it is solely analytical, it is not relevantly empirical (and thus cannot affirm what happened in the past, but only what could or couldn’t have).
(Proving History, 62, 302)
And again, in pointing out that historians can never be absolutely certain about any “substantive claim”,
Such certainty for us is logically impossible (at least for all substantive claims about history . . . )
(Proving History, 329)
Not even God can avoid reducing all knowledge of the past to “what probably happened”:
A confidence level of 100% is mathematically and logically impossible, as we never have access to 100% of all information, i.e., we’re not omniscient, and as Gödel proved, no one can be, for it’s logically necessary that there will always be things we won’t know, even if we’re God . . .
I have to disagree. We don’t need “100% of all information” or to be “omniscient” in order to be absolutely certain about certain facts of the past. Historians are indeed certain about basic facts. We know for a fact that the U.S. dropped atomic bombs on Japan in 1945, that Japan attacked Pearl Harbor a few years before that event, that Europeans migrated to and settled in the Americas, Africa, Australasia in the sixteenth to the nineteenth centuries, that King John signed the Magna Carter in 1215, that Rome once ruled the Mediterranean, that the Jerusalem temple was destroyed in 70 CE.
Historical events are unique and unrepeatable and our knowledge of many of them can often be absolutely certain. Witness the “History Wars” around the world — the Americas, India, Australia. In Australia, for instance, the arguments over the killing of aborigines and removing children from their families is not about what “probably” happened but what the evidence tells us did actually happen — with no room for any doubt at all. The 1992 Holocaust trial of David Irving was not about what probably happened but what can be known as an indisputable fact to have happened.
To be certain about such events does not require us to possess 100% of all the related information. Further, being certain about such events does not mean we are certain about all the details. There are grey areas where probability does enter the picture but the core events themselves cannot be legitimately doubted.
* The quoted phrases are from Hindess, Barry, and Paul Q. Hirst. Pre-Capitalist Modes of Production. London: Routledge & Kegan Paul, 1975, page 2, in reference to Willer & Willer’s book, Systematic Empiricism: Critique of a Pseudo-Science.
A “brilliant and devastating critique”* of the probability approach to historical facts (in fact to the entire area of theoretical empiricism that once typically “characterised the academic social sciences and history”) was published in the 1972 book Systematic Empiricism: Critique of a Pseudo-Science by David and Judith Willer. The chapter that specifically addresses probability in this context was written by the sociologist Dr Cesar Hernandez-Cela. Here is what he says about probability in the context being discussed in this post:
A relative frequency is a probability only if the number of events taken into account is infinite. But when the number of instances is finite . . . the ratio is a relative frequency but not a probability. . . . . A relative frequency is a description, but a probability is a calculation. Although we may calculate a theoretical probability value of 1/2 for a universe in which A and B are equally represented when the number of instances approaches infinity, the most that can be said about the number of heads that will turn up when tossing a coin twenty times is that there will be a particular frequency which is unknown until we toss the coin. In other words, the assignment of a value of 1/2 simply because the coin has two sides is an error because we do not know that each side will be equally represented in any empirical case. Equal representation in probability is a mathematical assumption which is violated in finite empirical cases. . . . We may instead find that tossing a die results in a successive run of fives . . . .
The theory of probability . . . can be used in scientific theories, but it cannot be used to associate observables. Sociological statistical procedures are concerned with observables and therefore violate the conditions under which probability calculations may be legitimately used. But they are so often used that they are frequently accepted (in spite of their obvious absurdity) without question. We are told that the probability of rain tomorrow is 60 percent when, in fact, it will either rain or it will not. Such statements are unjustified, wrong, and misleading.
(Systematic Empiricism, 97f – italics in the original)
One is reminded here of Richard Carrier’s discussion of the “Rank-Raglan hero class”, a category of ancient figures — most of whom are mythical — who share certain mythical attributes.
This is a hero-type found repeated across at least fifteen known mythic heroes (including Jesus) — if we count only those who clearly meet more than half of the designated parallels (which means twelve or more matches out of twenty-two elements), which requirement eliminates many historical persons, such as Alexander the Great or Caesar Augustus, who accumulated many elements of this hero-type in the tales told of them, yet not that many.
The twenty-two features distinctive of this hero-type are:
1. The hero’s mother is a virgin. 2. His father is a king or the heir of a king. 3. The circumstances of his conception are unusual. 4. He is reputed to be the son of a god. 5. An attempt is made to kill him when he is a baby. 6. To escape which he is spirited away from those trying to kill him. 7. He is reared in a foreign country by one or more foster parents. 8. We are told nothing of his childhood. 9. On reaching manhood he returns to his future kingdom. 10. He is crowned, hailed or becomes king. 11. He reigns uneventfully (i.e., without wars or national catastrophes). 12. He prescribes laws. 13. He then loses favor with the gods or his subjects. 14. He is driven from the throne or city. 15. He meets with a mysterious death. 16. He dies atop a hill or high place. 17. His children, if any, do not succeed him. 18. His body turns up missing. 19. Yet he still has one or more holy sepulchers (in fact or fiction). 20. Before taking a throne or a wife, he battles and defeats a great adversary (such as a king, giant, dragon or wild beast).
and
21. His parents are related to each other. 22. He marries a queen or princess related to his predecessor.
Many of the heroes who fulfill this type also either (a) performed miracles (in life or as a deity after death) or were (b) preexistent beings who became incarnated as men or (c) subsequently worshiped as savior gods, any one of which honestly should be counted as a twenty-third attribute. . . .
1. Oedipus (21) 2. Moses (20) 3. Jesus (20) 4. Theseus (19) 5. Dionysus (19) 6. Romulus (18) 7. Perseus (17) 8. Hercules (17) 9. Zeus (15) 10. Bellerophon (14) 11. Jason (14) 12. Osiris (14) 13. Pelops (13) 14. Asclepius (12) 15. Joseph [i.e., the son of Jacob] (12)
This is a useful discovery, because with so many matching persons it doesn’t matter what the probability is of scoring more than half on the Rank-Raglan scale by chance coincidence. Because even if it can happen often by chance coincidence, then the percentage of persons who score that high should match the ratio of real persons to mythical persons. In other words, if a real person can have the same elements associated with him, and in particular so many elements (and for this purpose it doesn’t matter whether they actually occurred), then there should be many real persons on the list—as surely there are far more real persons than mythical ones. . . .
So there is no getting around the fact that if the ratio of conveniently named mythical godmen to conveniently named historical godmen is 2 to 1 or greater, then the prior probability that Jesus is historical is 33% or less.
(On the Historicity of Jesus, 229-231, 241 – italics original)
First, we have fewer than a quarter of 100 instances in our group so a per centum figure is misleading. The total number Raglan studied was twenty.
Second, on what basis can we validly decide to count only those figures who score more than half of the listed attributes? Carrier identifies ten of the twenty-two listed features as applicable to Alexander the Great and acknowledges (though disputes) the possibility of assigning him thirteen. Half seems to be an arbitrary cut-off point (or at least tendentious insofar as it excludes the exceptions, historical persons who would spoil the point being made) especially when we know that Raglan himself said that his list of twenty-two was an arbitrary number. Other scholars of mythical “types” produced different lists:
Von Hahn had sixteen incidents, Rank did not divide his pattern into incidents as such, and Raglan had twenty-two incidents. Raglan himself admitted that his choice of twenty-two incidents (as opposed to some other number of incidents) was arbitrary (Raglan 1956:186).
(In Quest of the Hero, 189. — Raglan’s words were: I have taken twenty-two, but it would be easy to take more. Would a more complete list reduce the other figures to matching fewer than half….? So we begin to see the arbitrariness of Carrier’s deciding to focus only on those with more than half of the attributes in the Raglan list of 22.)
Alexander the Great and Mithridates are not the only ancient figures to whom “hero attributes” were attributed in the literature. Sargon and Cyrus were also studied in the same context by other scholars:
Raglan wrote in complete ignorance of earlier scholarship devoted to the hero, and he was therefore unaware of the previous studies of von Hahn and Rank, for example. Raglan was parochial in other ways too. For one thing, the vast majority of his heroes came exclusively from classical (mostly Greek) sources. The first twelve heroes he treats are: Oedipus, Theseus, Romulus, Heracles, Perseus, Jason, Bellerophon, Pelops, Asclepios, Dionysos, Apollo, and Zeus. Raglan could have strengthened his case had he used some of the same heroes used by von Hahn and Rank and other scholars, e.g., such heroes as Sargon and Cyrus.
(In Quest of the Hero, 187 – my bolding)
One might even argue that the further east one went from Greece the more likely it was that historical persons matched the mythical hero reference class! Much fun can be had with statistics.
Let’s continue with Hernandez-Cela’s discussion of probability as it applies to the social sciences and history:
Social empiricists, when presenting numerical values such as the “probability” of churchgoers giving alms to the poor, might state that only in 5 percent of cases would an association as large as 60 percent or larger not obtain when instances are randomly selected. But, observing individuals, we may only say that they either do or do not give alms. In the first observation we may find that 60 percent of the total sample gave alms, but in succeeding observations this value may differ. We cannot, in fact, have any expectations of probability of giving alms to the poor, no matter how many samples we take. If, on the other hand, the sample approaches or is equal to the total population of churchgoers, then the figure represents a simple proportion, a frequency, not a probability. On the other hand, specification that only 5 percent of samples will not result in the .60 or more is meaningless. If we chose several samples all of the same size, and found that in only 5 percent of them the figure was under .60, then we still can draw no conclusions, for we know nothing about the empirical conditions prevailing in future samples. Such a claim has no basis either in theory or in observation. What the claim means is that if there were an infinite number of cases whose composition was on the average like that of the sample, then in only 5 percent of them would the percentage be smaller than .60. But, we cannot assume that any other empirical cases are on the average like the sample studied, and we cannot assume that they are infinite in number. Theoretical cases can be infinite in number, but empirical ones cannot. Such statistical claims, of course, cannot be violated empirically because they are not probability statements at all but disguised frequencies obtained by observation. Future observations cannot verify or falsify frequencies but only slightly modify their numerical value in the light of new cases. Furthermore, the statistical procedures themselves are not open to any kind of empirical verification or falsification . . .
(Systematic Empiricism, 99)
So a sample of a score of mythical heroes cannot be the basis for predicting the likelihood of any particular figure being historical or not.
The statement, “All As are Bs,” . . . . really means no more than “As have been observed with Bs.” But this statement is not a universal statement, but limited to a population. . . . Consequently no empirical generalization can act as a major premise in a deductive explanation, and empirical generalizations can never be used deductively to explain or predict.
(Systematic Empiricism, 130 — no longer from Hernandez-Cela’s chapter; italics original)
An illustration of the fallacy is set out thus:
Premise A: The probability of recovery from a streptococcus infection when treated by penicillin is close to 1.
Premise B: John Jones was treated with large doses of penicillin.
Conclusion: The probability that John Jones will recover from his streptococcus infection is close to 1.
(Systematic Empiricism, 130)
One might rephrase this as:
Premise A: The probability of a figure in the hero-class being non-historical is close to 0.
Premise B: Jesus is a figure in the hero-class.
Conclusion: The probability that Jesus is non-historical is close to 0.
But as D. and J. Willer observe,
Predictions and explanations cannot be made from [such a statement]. John Jones either does or does not recover. If he does recover the probability value of statement A is slightly increased by his case, and if he does not the probability value decreases. . . . [T]he event itself cannot be predicted with any certainty. Furthermore, if John Jones either recovers or does not, he does not recover with a probability of close to 1.
Individual facts either occur or they do not. Certain facts cannot be explained by uncertain statements. Even in ordinary everyday practical empiricism we do not make that error.
(Systematic Empiricism, 131, 135)
No two historical events are ever exactly alike. People and societies are not like that. There are always variables that make each historical event unique. Of course there are common experiences such as war or economic depression but no two wars or depressions are the same. Human events are not governed by laws in the same way geological forces or the weather are governed by scientific laws. Historians do not observe the results of “laws” in the historical data. They cannot make predictions about a unique historical event or person — all historical events and persons are unique in some respect — on the basis of limited samples with variable (“arbitrary”) attributes. Generalizations can be made about the impacts of technologies on various kinds of social groups but particular historical events are each unique in some way. But generalizations cannot predict what a historian will find in the sources.
The most that probability (in the context of Richard Carrier’s discussion) can tell us about the likelihood of Jesus having existed is that Jesus was one of a few historical exceptions (or even the only exception) to general notions about mythical persons.
In the next post I’ll show what historians say about the certainty or otherwise of “their basic facts”.
Carrier, Richard. On the Historicity of Jesus: Why We Might Have Reason for Doubt. Sheffield: Sheffield Phoenix Press Ltd, 2014.
Carrier, Richard. Proving History: Bayes’s Theorem and the Quest for the Historical Jesus. Amherst, N.Y: Prometheus Books, 2012.
Hindess, Barry, and Paul Q. Hirst. Pre-Capitalist Modes of Production. London: Routledge & Kegan Paul Books, 1975.
Raglan, Lord. The Hero: A Study in Tradition, Myth and Drama. Mineola, N.Y: Dover Publications, 2011.
Rank, Otto, Raglan, and Alan Dundes. In Quest of the Hero. Mythos (Princeton, N.J.). Princeton, N.J.: Princeton University Press, 1990.
Willer, David, and Judith Willer. Systematic Empiricism: Critique of a Pseudoscience. Englewood Cliffs: Prentice-Hall, 1973.
0:15:13.8 SC: . . . . the idea that the election was stolen was made by a whole bunch of partisan actors, but it was also, I think, importantly, taken up as something worth considering, even if not necessarily true, by various contrarian, centrist pundits, right?
0:16:32.1 SC: . . . . So the answer I would have put forward is, “No. [chuckle] It was never worth taking that kind of claim seriously.” . . . . We like to talk here about being Bayesian, and in fact, it’s almost a cliche in certain corners of the internet talking about being good Bayesians, and what is meant by that is, for a set of propositions like the election was stolen, the election was not stolen. Okay, two propositions mutually exclusive, so you assign prior probabilities or prior credences to these propositions being true. So you might say,
“Well, elections are not usually stolen, so the credence I would put on that claim my prior is very, very small.
And the credence I would put on it not being stolen is very large.”
So we collect the data that will help us assess which proposition is the more likely. If the data is not what we would expect if X were true, then we revise our estimation that X really did happen. If the data we collect is exactly what we would expect to find if X were true, then we can be confident that X is indeed most likely true.
0:18:51.0 SC: . . . . So in a case like this where a bunch of people are saying, “Oh, there was election fraud, irregularities, the counting was off by this way or that way. It all seems suspicious.” You should ask yourself, “Did I expect that to happen?” The point is that if you expected exactly those claims to be made, even if the underlying proposition that the election was stolen is completely false, then seeing those claims being made provides zero evidence for you to change your credences whatsoever. Okay? So to make that abstract statement a little more down to earth, in the case of the elections being stolen, how likely was it that if Donald Trump did not win the election, that he and his allies would claim the election was stolen independent of whether it was, okay? What was the probability that he was going to say that there were irregularities and it was stolen?
0:20:19.6 SC: Well, a 100%, roughly speaking, 99.999, if you wanna be little bit more meta-physically careful, but they announced ahead of time that they were going to make those claims, right? He had been saying for months that the very idea of voting by mail is irregular and was going to lead to fraud, and they worked very hard to make the process difficult, both to cast votes and then to count them, different states had different ways of counting, certain states were prohibited from counting mail in ballots ahead of time. The Democrats were much more likely to vote by mail than the Republicans were, they slowed down the postal service, trying to make it take longer for mail-in votes to get there. There’s it’s a whole bunch of things going on in prior elections in the primaries, Trump had accused his opponents of rigging the election and stealing votes without any evidence.
0:21:15.3 SC: So your likelihood to function, that you would see these claims rise up even if the underlying proposition was not true, is basically, 100%. And therefore, as a good Bayesian, the fact that people were raising questions about the integrity of the election means nothing. It’s just what you expect to happen.
Oh someone claimed that something’s going on, therefore it’s my job to evaluate it and wait for more evidence to come in.
The data we need to see in order to take the claims of fraud seriously:
If you really want to spend any effort at all taking a claim like this seriously, you have to go beyond that simple thing, “Oh someone claimed that something’s going on, therefore it’s my job to evaluate it and wait for more evidence to come in.”
You should ask further questions, “What else should I expect to be true if this claim was correct?” For example, if the Democrats had somehow been able to get a lot of false ballots, rig elections, you would expect to see certain patterns, like Democrats winning a lot of elections, they had been predicted to lose different cities where or locations more broadly, where the frauds were purported to happen would be ones where anomalously large percentages of people were voting for Biden rather than Trump.
0:22:28.3 SC: In both cases, in both the idea that you would predict Democrats winning elections, they had been predicted lose and places where fraud was alleged to have happened would be anomalously pro-Biden it was the opposite. And you could instantly see that it was the opposite, right after election day.
The Democrats lost elections for the House of Representatives and the Senate that they were favored to win.
So they were very bad at packing the ballots, if that’s really what they were trying to do.
In cities like Philadelphia where it was alleged that a great voter fraud was taking place, Trump did better in 2020 than he did in 2016.
So right away, without working very hard, you know this is egregious bullshit, there is no duty to think, to take seriously, to spend your time worrying about the likely truth of this outrageous claim, all of which is completely compatible with every evidence, the falsity of which is completely compatible with all the evidence we have.
0:23:32.2 SC: So just to make it dramatic, let me spend a little bit of time here… Let me give you an aside, which is my favorite example of what I mean by this kind of attitude because it is very tricky. You should never, and I’m very happy to admit, you should never assign zero credence to essentially any crazy claim. That would be bad practice as a good Bayesian because if you assign assigned zero credence to any claim, then no amount of new evidence would ever change your mind. Okay? You’re taking the prior probability multiplying it with the likelihood, but at if the prior probability is zero, then it doesn’t matter what the likelihood is, you’re always gonna get zero at the end. And you should be open to the idea that evidence could come in that this outrageous claim is true, that the election was stolen, it’s certainly plausible that such evidence would come in.
0:24:21.9 SC: Now it didn’t, right, when actually they did have their day in court, they were laughed … out of court because they had zero evidence, even all the way up to January 6th when people in Congress were raising a stink about the election not being fair, they still had no evidence. The only claim they could make was that people were upset and people had suspicions, right? Even months later, so there was never any evidence that it was worth taking seriously. But nevertheless, even without that, I do think you should give some credence and therefore you have to do the hard work of saying, “Well, I’m giving it some non-zero credence, but so little that it’s not really worth spending even a minute worrying about it.” That’s a very crucial distinction to draw, and it’s very hard to do.
Another Thompson aphorism: ‘When everyone is agreed on something, it is probably wrong’. In other words, as Thompson has also put it, ‘in our fields, if all are in agreement, it signifies that no one is trying to falsify the theory: an essential step in any scientific argument’. — Doudna 2020
That’s not being perverse. It’s about pausing when “things seem too good to be true” and taking time out to ask if “there has probably been a mistake”. (Gunn, @ 2 mins)
[U]ntil the Romans ultimately removed the right of the Sanhedrin to confer death sentences, a defendant unanimously condemned by the judges would be acquitted [14, Sanhedrin 17a], the Talmud stating ‘If the Sanhedrin unanimously find guilty, he is acquitted. Why? — Because we have learned by tradition that sentence must be postponed till the morrow in hope of finding new points in favour of the defence’.
That practice could be interpreted as the Jewish judges being intuitively aware that suspicions about the process should be raised if the final result appears too perfect . . .
[I]f too many judges agree, the system has failed and should not be considered reliable. (Gunn et al 2016)
Or even more simply,
They intuitively reasoned that when something seems too good to be true, most likely a mistake was made. (Zyga, 2016)
See Interview 1 and Interview 2 with Thomas L. Thompson. All Vridar blog posts on Thompson’s work are archived here. I expect to begin posting my thoughts on Biblical Narratives, Archaeology & Historicity: Essays in Honour of Thomas L. Thompson fairly soon.
I thought of what I have come to call Thompson’s Rule when I encountered this scientific study showing that, as counterintuitive as it sounds, unanimous agreement actually does reduce confidence of correctness in conclusions in a wide variety of disciplines (Gunn et al. 2016).
Is it possible for a large sequence of measurements or observations, which support a hypothesis, to counterintuitively decrease our confidence? Can unanimous support be too good to be true? The assumption of independence is often made in good faith; however, rarely is consideration given to whether a systemic failure has occurred. Taking this into account can cause certainty in a hypothesis to decrease as the evidence for it becomes apparently stronger. We perform a probabilistic Bayesian analysis of this effect with examples based on (i) archaeological evidence, (ii) weighing of legal evidence and (iii) cryptographic primality testing. In this paper, we investigate the effects of small error rates in a set of measurements or observations. We find that even with very low systemic failure rates, high confidence is surprisingly difficult to achieve . . . .
Sometimes as we find more and more agreement we can begin to lose confidence in those results. Gunn begins with a simple example in a presentation he gave in 2016 (link is to youtube video). Here is the key slide:
With a noisy voltmeter attempting to measure a very small voltage (nanovoltage) one would expect some variation in each attempted measurement. Without the variation, we can conclude something is wrong rather than that we have a precise measurement.
Another example:
The recent Volkswagen scandal is a good example. The company fraudulently programmed a computer chip to run the engine in a mode that minimized diesel fuel emissions during emission tests. But in reality, the emissions did not meet standards when the cars were running on the road. The low emissions were too consistent and ‘too good to be true.’ The emissions team that outed Volkswagen initially got suspicious when they found that emissions were almost at the same level whether a car was new or five years old! The consistency betrayed the systemic bias introduced by the nefarious computer chip. (Zyga 2016)
From https://www.cagle.com/arend-van-dam/2015/09/smart-vw-cars
Then there was the Phantom of Heilbronn or the serial killer “Woman Without a Face“. Police spent eight to fifteen years searching for a woman whom DNA connected to 40 crime scenes (murders to burglaries) in France, Germany and Austria. Her DNA was identified at six murder scenes. A three million euro reward was offered. It turned out that the swabs used to collect the DNA from the crime scenes had been inadvertently contaminated at their production point by the same woman.
Consider, also, election results. What do we normally suspect when we hear of a dictator receiving over 90% of the vote?
We have all encountered someone who has argued that “all the evidence” supports their new pet hypothesis to explain, say, Christianity’s origins. I have never been able to persuade them, as far as I know, that reading “all the evidence” with a bias they either cannot see or think is entirely valid.
Ironically, scholars like Bart Ehrman who attempt to deny a historical and even slightly significant “Jesus myth” view among scholars are doing their case a disservice. By insisting that there is and that there has been no valid or reasonable contrary view ever raised, such scholars are undermining confidence in the case for the historicity of Jesus. If they could accept the challenges from serious thinkers over the past near two centuries, and acknowledge the ideological pressure inherent in “biblical studies” for academics to conform within certain parameters of orthodox faith, then they could begin to not look quite so like those politicians who claim 90% of the vote, or like those police chasing a phantom woman serial killer for eight years across Europe, of the dishonest VW executives . . . . Continue reading ““When everyone is agreed on something, it is probably wrong” — Thompson’s Rule”
Note: I wrote this post a few years back and left it lying in the draft pile, unable to come up with a satisfactory conclusion until earlier this year. Our forecast calls for snow tomorrow (something those of us who live in RVs would rather not see), so a post about precipitation and weather prediction might be apt. –TAW
Yellow umbrella in bad weather (Photo credit: Wikipedia)
[This post begins our hard look at Chapter 6, “The Hard Stuff” in Carrier’s Proving History. — specifically, the section entitled “Bayesianism as Epistemic Frequentism.”]
In the 1980s, the history department building on the University of Maryland’s College Park campus had famous quotations painted on its hallway walls. Perhaps they still do.
The only quote I can actually still remember is this one:
“The American people never carry an umbrella. They prepare to walk in eternal sunshine.” — Alfred E. Smith
I used to enjoy lying to myself and say, “That’s me!” But the real reason I never carry an umbrella is not that I’m a naive Yankee optimist, but rather because I know if I do, I will leave it somewhere. In this universe, there are umbrella receivers and umbrella donors. I am a donor.
Eternal sunshine
So to be honest, the reason I check the weather report is to see if I should take a jacket. I’ve donated far fewer jackets to the universe than umbrellas. But then the question becomes, what does it actually mean when a weather forecaster says we have a 20% chance of rain in our area this afternoon? And what are we supposed to think or do when we hear that?
Ideally, when an expert shares his or her evaluation of the evidence, we ought to be able to apply it to the situation at hand without much effort. But what about here? What is our risk of getting rained on? In Proving History, Richard Carrier writes:
When weathermen tell us there is a 20% chance of rain during the coming daylight hours, they mean either that it will rain over one-fifth of the region for which the prediction was made (i.e., if that region contains a thousand acres, rain will fall on a total of two hundred of those acres before nightfall) or that when comparing all past days for which the same meteorological indicators were present as are present for this current day we would find that rain occurred on one out of five of those days (i.e., if we find one hundred such days in the record books, twenty of them were days on which it rained). (Carrier 2012, p. 197)
These sound like two plausible explanations. The first sounds pretty “sciency,” while the second reminds us of the frequentist definition of probability, namely “the number of desired outcomes over the total number of events.” They’re certainly plausible, but do they have anything to do with what real weather forecasters do?
In historical research, we evaluate the plausibility of hypotheses that aim to explain the occurrence of a specific event. The explanations we develop for this purpose have to be considered in light of the historical evidence that is available to us. Data functions as evidence that supports or contradicts a hypothesis in two different ways, corresponding to two different questions that need to be answered with regard to a hypothesis:
1. How well does the event fit into the explanation given for its occurrence?
2. How plausible are the basic parameters presupposed by the hypothesis?
. . . . .
[A]lthough this basic structure of historical arguments is so immensely important and its disregard inevitably leads to wrong, or at least insufficiently reasoned, conclusions, it is not a sufficient condition for valid inferences. Historical data does not come with tags attached to it, informing us about (a) how – or whether at all – it relates to one of the two categories we have mentioned and (b) how much plausibility it contributes to the overall picture. The historian will never be replaced by the mathematician.23
23 This becomes painfully clear when one considers that one of the few adaptations of Bayes’s theorem in biblical studies, namely Richard Carrier, On the Historicity of Jesus: Why We Might Have Reason for Doubt (Sheffield: Sheffield Phoenix, 2014), aims to demonstrate that Jesus was not a historical figure.
Heilig, Christoph. 2015. Hidden Criticism?: The Methodology and Plausibility of the Search for a Counter-Imperial Subtext in Paul. Tübingen: Mohr Siebeck. pp. 26f
Last night I chanced to turn on the TV half way through a program trying to show viewers how interesting maths was. Yeh, okay. But I watched a little as they demonstrated how they do searches at sea for missing persons. Then it suddenly got interesting. Bayes’ theorem was introduced as their way of handling new information that came to them as they conducted their search. And the presenter, a maths wiz (I have seen her magical maths brain at work on another show), Lily Serner, explained it all without the maths. Move the red button forward to the 44:54 mark:
I argue that the interpretation of Bayesianism that I present here is the best explanation of the actual practices of historians.
— Tucker, Aviezer. 2009. Our Knowledge of the Past: A Philosophy of Historiography. Reissue edition. Cambridge University Press. p. 134
Aviezer Tucker
I have posted aspects of Aviezer Tucker’s discussion of how Bayesian reasoning best represents the way historians conduct their research but here I want to post a few details in Tucker’s chapter that I have not covered so far.
(Interjection: it is not strictly fair to call Aviezer Tucker a “Bayesian historian” because, as is clear from the opening quote, what he argues is that all historians, at least at their best and overall, employ Bayesian logic without perhaps realizing it.)
Tucker includes discussion of biblical criticism in his book but in his chapter on Bayesian methods he unfortunately contradicts himself. The contradiction can best be explained, I think, by appealing to the power of the Christian story to implant unquestioned assumptions into even the best of scholars. I could call that my hypothesis and suggest that the prior probability for it being so in many historians is quite high.
There have been attempts to use the full Bayesian formula to evaluate hypotheses about the past, for example, whether miracles happened or not (Earman, 2000, pp. 53–9). Despite Earman’s correct criticism of Hume (1988), both ask the same full Bayesian question:
“What is the probability that a certain miracle happened, given the testimonies to that effect and our scientific background knowledge?”
But this is not the kind of question biblical critics and historians ask. They ask,
“What is the best explanation of this set of documents that tells of a miracle of a certain kind?”
The center of research is the explanation of the evidence, not whether or not a literal interpretation of the evidence corresponds with what took place.
(Tucker, p. 99)
One explanation for the documents relating the miracles is that the miracles happened and were recorded. Other explanations can also come to mind.
No doubt because the question focused on miracles it was very easy for Tucker and countless others before and since to think of alternative hypotheses to explain the stories of miracles that have survived for our reading entertainment today.
Analytic thinking:
(the degree to which people use words that suggest formal, logical, and hierarchical thinking patterns)
82.22%
32.85%
55.17%
Authenticity:
(when people reveal themselves in an authentic or honest way)
49.57%
34.39%
39.55%
Clout:
(the relative social status, confidence, or leadership that people display through their writing)
38.59%
47.75%
48.82%
Tone:
(the higher the number, the more positive the tone)
92.86%
16.55%
13.75%
Anger:
0.22%
0.56%
0.88%
.
Tone
Unfortunately when one reads McGrath’s Two Truths post one soon sees that his very positive tone (over 92% positive) is in fact an indication of overconfidence with the straw-man take-down.
But but but….. Please, Richard, please, please, please! Don’t fall into McGrath’s trap. Sure he sets up a straw man and says all sorts of fallacious things but he also surely loves it when he riles you. It puts him on the moral high ground (at least with respect to appearances, and in the real world, despite all our wishes it were otherwise, appearances do seriously count).
But see how McGrath then followed with a lower tone — and that’s how it so easily can go in any debate on mythicism with a scholar who has more than an academic interest in the question.
Anger
Ditto for anger.
This variable was measured by the following words:
Clearly a more thorough and serious analysis would need to sort words like “argument” between their hostile and academic uses.
Analytic thinking style
James McGrath began the discussion in a style that conveyed a serious analytical analysis of Carrier’s argument. Of course anyone who has read Carrier’s works knows McGrath’s target was a straw man and not the actual argument Carrier makes at all. (Interestingly when Carrier pointed out that it appeared McGrath had not read his actual arguments McGrath at best made inferences that he had read Carrier’s books but fell short of saying that he had actually read them or any of the pages where Carrier in fact argued the very opposite of what McGrath believed he had.) Nonetheless, McGrath’s opening gambit conveyed a positive approach for anyone unfamiliar with Carrier’s arguments.
But look what happened to McGrath’s analytical style after meeting Carrier’s less analytical style: he followed Carrier’s lead.
Carrier has chosen to write in natural language style which is fine for informal conversation but the first impression of an outsider unfamiliar with Carrier’s arguments would probably be that McGrath was the more serious analyst of the question. (I understand why Carrier writes this way but an overly casual style, I suspect, would appeal more to the friendly converted (who are happy to listen rather than actively share the reasoning process) than an outsider being introduced to the ideas.
In actual fact, Carrier uses far more words that do indeed point to analytic thinking than does McGrath. Carrier uses cognitive process words significantly more frequently than does McGrath (24% to 16%/19%). But his sentences are far less complex and shorter.
Other
There are many other little datasets that a full LIWC analysis reveals. One is a comparative use of the personal singular pronoun. A frequent use of “I” can indicate a self-awareness as one speaks and this can sometimes be a measure of some lack of confidence. Certainly the avoidance of “I” is often a measure of the opposite, of strong confidence and serious engagement in the task at hand. Carrier’s use of I is significantly less than McGrath’s.
Another progression one sees is the use of “he”. As the debate progressed it became increasingly focused on what “he” said: e.g. McGrath1: 0.45%; Carrier 1.65%; McGrath2 2.06%.
McGrath sometimes complains about the length of Carrier’s posts. But more words are linked to cognitive complexity and honesty.
—o—
Of course I could not resist comparing my own side-line contribution:
A Roman Catholic historian who thinks he’s a Bayesian walks into the secret Vatican archives. There he discovers a document that might have significance for rewriting the origins of Christianity. I have reproduced a facsimile:
The historian is stunned. His faith has taught him that James was only a cousin or half-brother. If he was wrong about that, he wonders, how can he even be sure Jesus existed at all?
Reeling in doubts, the historian is nonetheless conscientious and no fool. He knows he has to test this document for its authenticity. So he snips off a corner of it and sends it to the laboratory to determine the age and provenance of the material. As an extra check he sends a high definition copy to a paleographer.
The results come back. The material is dated between 40 AD and 60 AD and the paleographic analysis confirms that the style to what was typical of the year 50 AD.
Next, he asks if the letter is genuinely by Paul. His colleagues tell him it sounds just like the Paul they know so that is confirmed.
Since this is evidently an autograph questions of the contents of the letter being altered during the process of copying do not arise.
But how reliable are its contents as historical evidence? Our historian asks if we can verify that this particular James really was known to be the literal brother of Jesus.
He consults the latest scholarship on the book of Acts and discovers that it is now established “beyond doubt” that the first chapters, 1-15, were written in the year 45 AD and that the original text said that James was not only the head of the church but was also the junior brother of Jesus, one year younger to be precise. The contents of Paul’s letter are confirmed!
But our historian is more thorough still. Did anyone else in the early church know anything of this letter and its contents? He pores through Tertullian’s writings and sees that Tertullian quotes the passage about meeting James to refute Marcion’s heresy that Jesus was not really a flesh and blood human being born of a woman on earth.
That clinched it! The letter and its contents sure seemed to be genuine and known to be genuine by the venerable Fathers.
But our historian is a Bayesian. At least he thinks he is. He read half of a blurb on the back cover of a book that had Bayes written on its front cover and is confident that he got the hang of it from that.
If he was wrong about Jesus having brothers how can he be sure Jesus even existed? The historian pauses to think of all the unbelievable stories about Jesus. Could such a person really have existed in the first place? So he puts on what he thinks is his Bayesian cap that looks very much like one of those conical dunce caps and sets to work.
He weighed the evidence. He took all the stories that were mythical and set them against the evidence for the reality of Jesus and here’s what he found:
McGrath does not tell his readers in the post we are addressing what he has in mind as the “clear-cut” evidence for the historicity of Jesus but from previous posts and comments I am convinced that it is the “brother of the Lord” passage in Galatians 1:19 that he has in mind. If I am wrong then someone will no doubt inform me.
I ought to have made that point clearer in my original post.
If someone can direct me to where McGrath recently made the point about that Galatians passage (was it in response to the reddit discussion about Vridar?) I would much appreciate it.
James McGrath in a recent post, Jesus Mythicism: Two Truths and a Lie, made the following criticism of the use of Bayes’s theorem in the Jesus Mythicism debate:
. . . . as I was reminded of the problematic case that Richard Carrier has made for incorporating mathematical probability (and more specifically a Bayesian approach) into historical methods. . . .
If one followed Carrier’s logic, each bit of evidence of untruth would diminish the evidence for truth, and each bit of evidence that is compatible with the non-historicity of Jesus diminishes the case for his historicity.
The logic of this argument is based on a misunderstanding of the nature of historical inquiry and how a historian is expected to apply Bayesian logic. (It also misconstrues Carrier’s argument but that is another question. I want only to focus on a correct understanding of how a historian validly applies Bayesian reasoning.)
In support of my assertion that James McGrath’s criticism is misinformed I turn to a historian and philosopher of history, Aviezer Tucker (see also here and here), author of Our Knowledge of the Past: A Philosophy of Historiography. He treats Bayesian reasoning by historical researchers in depth in chapter three. I quote a section from that chapter (with my own formatting):
There have been attempts to use the full Bayesian formula to evaluate hypotheses about the past, for example, whether miracles happened or not (Earman, 2000, pp. 53–9).
We may compare McGrath’s criticism. He is of the impression that the Bayesian formula is used to evaluate the hypothesis that Jesus did exist. This is a common misunderstanding. If you are confused, continue to read.
Despite Earman’s correct criticism of Hume (1988), both ask the same full Bayesian question:
“What is the probability that a certain miracle happened, given the testimonies to that effect and our scientific background knowledge?”
We may compare McGrath’s criticism again. He is of the impression that the historian using Bayesian logic is asking what is the probability that Jesus existed, given the testimonies to that effect and our background knowledge. If you are still confused then you share McGrath’s misunderstanding of the nature of historical inquiry. So continue with Tucker:
But this is not the kind of question biblical critics and historians ask. They ask,
“What is the best explanation of this set of documents that tells of a miracle of a certain kind?”
The center of research is the explanation of the evidence, not whether or not a literal interpretation of the evidence corresponds with what took place.
(Tucker, p. 99)
In other words, biblical critics and historians ask (Tucker is assuming the biblical critic and historian is using Bayesian logic validly and with a correct understand of the true nature of historical research) what is the best explanation for a document that, say, purports to be by Paul saying he met the James, “the brother of the Lord”.
I use that particular example because — and someone correct me if I am mistaken — Jame McGrath and others believe that passage (Galatians 1:19) makes any questioning of the historicity of Jesus an act of “denialism”. (McGrath does not tell his readers in the post we are addressing what he has in mind as the “clear-cut” evidence for the historicity of Jesus but from previous posts and comments I am convinced that it is the “brother of the Lord” passage in Galatians 1:19 that he has in mind. If I am wrong then someone will no doubt inform me.)
No one, I am sure, would mean to infer that the late and highly respected Philip R. Davies was guilty of denialism when he suggested that the historical methods he applied to the Old Testament should also be applied to the New — a method I have sought to apply to the study of Christian origins ever since I read Davies’ groundbreaking book.
Back to the question. It is the question of what is the best explanation for the passage in our version of Galatians that I have attempted to address several times now.
That is the question that the historian needs to ask. Every decent book I have read for students about to undertake advanced historical studies has stressed, among many other duties, the necessity for the researcher to question the provenance, the authenticity, of the documents he or she is using, and to know all the questions related to such questions from a thorough investigation of the entire field. My several posts have attempted to introduce such questions that should be basic to any historical study.
