The Jesus Process Begins

A while back, Joseph Hoffmann announced a new project with the title “The Jesus Process.” It has now produced its first few offerings, in the form of the following online essays:

Maurice Casey, “Mythicism: A Story of Bias, Incompetence and Falsehood”

Stephanie Louise Fisher, “An Exhibition of Incompetence: Trickery, Dickery, Bayes”

R. Joseph Hoffmann, “Controversy, Mythicism, and the Historical Jesus”

See also Hoffmann’s very recent blog post on the use of Bayes’ Theorem by Richard Carrier and other mythicists, and Steph Fisher’s guest post on Jim West’s blog about the interpretation of Albert Schweitzer. Joel Watts also interacted with Neil Godfrey and Steph Fisher’s response to him. Tim Widdowfield expressed appreciation to Steph Fisher for her responses to two of his blog posts at Vridar, coining the cute term “serf review” since he is not a peer!


Stay in touch! Like Religion Prof on Facebook:
Many Jesuses?
Heroes of the Bible
Mark 7:27-28 for the Birds
Happy Mothers' Day!
  • David Evans

    Hoffmann says in his recent blog post  “Carrier thinks he is justified in this by making historical uncertainty (i.e., whether an event of the past actually happened) the same species of uncertainty as a condition that applies to the future”

    I think Carrier actually is justified here. Bayes’ theorem itself contains only tenseless probabilities, and can just as well apply to the past as to the future, whenever there is uncertainty.

    • Paul Regnier

      David, from my admittedly limited understanding of what Hoffmann is talking about, I don’t think the problem is when the event takes place. He’s contrasting events where we can know probabilities involved with ones where we cannot. 

      Hoffmann gives the example of Marie’s wedding. The use of Bayes’ theorem here seems to depend on us knowing how likely it is to rain in this desert on a any given day, and how accurate the weatherman is. Both of these probabilities would be fairly easy to calculate if we have the meteorological record for this particular desert, and had a record of how successful this particular weatherman had been (produced by comparing his predictions with the actual meteorological record). As long as we have these of course, it doesn’t really matter if we’re calculating the probability of it raining on Marie’s wedding were it taking place tomorrow, or if we’re calculating the probability of it having rained if Marie’s wedding had taken place a year ago. 

      But, would this still work if the event we’re trying to calculate the probability of an event having taken place 2,000 years ago? Suppose we found an ancient letter where Mariam, a bride to be, complains that the local soothsayer has predicted rain on her wedding day, would Bayes’ theorem work as neatly then? I don’t think it would. 

      Firstly, we would have to know about the average number of days’ rain in previous years in the desert where the wedding took place to enable us to calculate the probability of it raining on a given day. Would such meteorological records survive, if they ever existed? Probably not…

      Secondly, how could we begin to estimate how the accuracy of the soothsayer who forecasted rain on the day of Mariam’s wedding? If we had no meteorological record and no record of other predictions he had made, how could we possibly calculate the accuracy of his forecasts to give us a figure to stick into our equation?

      Thirdly, what if there were gaps in our knowledge about Mariam’s wedding? Suppose Mariam didn’t say in her letter exactly where her wedding was going to take place, because the person who she was writing to already knew (high-context culture and all that)? If other locations with different climates now become possibilities, what would that do to our calculations? 

      No doubt we could come up with some numbers to crunch to keep Bayes happy, based on our best guess at where the wedding was taking place, available data about what the climate might have been at the time, and our assessment of the meteorological skills of ancient soothsayers, but I think what Hoffmann is saying is that at this point, we’re just giving our own assumptions or existing conclusions numerical values and doing some Maths with them to make them look cool. 

      Incidentally, even the Marie’s wedding example seems a bit simplistic to me. It tells us whether it will rain on the day of Marie’s wedding, but the site Hoffmann is using seems to equate “raining on the day of Marie’s wedding” with “Marie getting rained on during her wedding”. Presumably, this only works if we assume that on days that it rains, it rains for the whole day and/or Marie’s wedding last the whole day? If both the rain and Marie’s wedding each last only then hour then the chances of the rain and Marie’s wedding coinciding are fairly small.

      For example, I used to live in Kuwait where it probably only rained 5 days a year, but the rain almost always happened in the evening. So if Marie was planning on getting married in the middle of the dessert at noon in Kuwait, I don’t think she’d have to worry about getting wet, even if the forecast of rain on that day were accurate.  Heat stroke would be another matter.

      PS: I don’t know much about Maths (see the Jesus Denial and other Bunk around the blogosphere thread where I had to get a Maths teacher to help me cope with Vinny’s fairly small number of James’s) so I apologise in advance if the above is complete gibberish :-)

      • David Evans

        Having re-read Hoffman I see that he is not saying exactly what I thought. He may well be right about Carrier’s book (which I have not read) and his criticism of Swinburne is spot-on.

  • Paul Regnier

    PS: For any other Maths dummies out there, Radio 4’s In Our Time has quite a good episode on probability: