
I’m no biblical studies expert, but I’d like to think I’m an informed amateur, and in my readings and podcasts I’ve run across a few reasoning habits and approaches from biblical studies folks that tweak me a bit in terms of the proper use of probabilities.
- Unknown unknowns, not rhetorically taking into account the probability space, and statistically overfitting the data
Maybe Moses had a pet named Joshua. Maybe Mary had a bad relationship with her second cousin who defrauded her out of a lamb. Any one of these has a very small chance of happening, but if we take the vast space of all the very small possibilities added up altogether it’s clear that what we have is an infinitesimal fraction of the lived experiences of biblical figures. Of course, it’s not biblical scholars’ jobs to speculate about all the unknown unknowns, but rhetorically at least scholars sometimes tend to speak about biblical events and figures as if they exclusively consist of the strung together sequences of paltry evidence and theories derived from those shards of evidence, instead of a big mass of unknowns of which the rare in-the-ground or on-the-text evidence describes a small part. Again, this isn’t a criticism of their actual processes, but rather a matter of rhetorical emphasis and framing. The evidence is so sparse that they tend to overfit the data they do have, when in reality much of reality probably has nothing to do with any data that we have and will never have.
I’m not trying to subtly flip the onus of justification, as if they have to prove that Mary didn’t have a bad relationship with her cousin, Russell’s teapot on all that, but rather making the point that when speaking about biblical figures and events we tend to speak less in terms of a vast unknown and more as if the entire event or person was triangulated within our theory. This leads to more confidence about things like personality and such than is warranted.
And of course, people have to sell books when a more honest appraisal of the situation would list the “second best bed,” and a handful of confirmed details and leave it mostly at that, but instead some people have a tendency to layer conjecture on top of conjecture to fill out a word count. To talk about Jesus the revolutionary or Jesus the rabbi, or this or that take on Jesus, when by any secular historiographic standards we really have very little idea outside of revealed religious truths. To paraphrase Joseph Smith, while there are consensuses, for big-picture issues so many scholars interpret the same piece of evidence in such drastically different ways so as to destroy all confidence by an appeal to the data.
- Assuming probability of .8= probability of 1.
Cognitively we don’t handle probabilities very well and we tend to round up or down. We saw this during the first Trump election when people assumed that Nate Silver’s probability of 20% or so for a Trump victory was essentially zero. I also a recall an anecdote from a book (can’t remember which one) where an economic adviser quoted President Obama a 40% chance of something happening, and Obama said, “so a coin flip…,” and the adviser had to specify no, 40% isn’t a coin clip, it’s 40%. (Not to disparage Obama on this, it’s a common thing most of us do.)
In much the same way consensus biblical positions are often rhetorically treated as givens. For example, the Markan priority, the idea that the book of Mark was written first, has some strong evidence for it last time I did a deep dive, so let’s place its probability at, say, a 90% chance of being valid. That’s pretty high; it is probably true. However, not believing in the Markan priority is not the equivalent of, say, thinking the earth is flat, and believing that the woman taken into adultery actually represents an older, more authentic tradition is not the same thing probabilistically as 9/11 being an inside job, but sometimes everything on the other side of a strong consensus is lumped together as a fringe theory when they really don’t belong in the same categories.
- Chained Probabilities
Some theories take the position that given X (say the Markan priority), we can infer Y. There’s no problem with that, but we essentially have two different probabilities, the probability of X, and then the probability of Y given X. If we chain these probabilities together the overall chance of it being wrong increases. Is it a reasonable estimate given the evidence? Yes. But if we have more interconnected hypotheses, no matter how reasonable any given one is, then the chained probabilities decrease the chance that the whole web is accurate. If we have three linearly interrelated, contingent facts that each have an 80% chance of being true, that is only slightly more than a 50% chance that the entire system is true. Again, nothing wrong with that, but chained probabilities add up and that 10% chance that there is no Q source or that the documentary hypothesis is wrong should not be completely ignored when building theoretical edifices on them.
- Confidence Intervals
Given all of the above and the sheer paucity of clear evidence for most biblical episodes, If you look at the evidence you have there’s a tendency to zoom in on that and to ignore the size of your confidence intervals on either side of your peripheral vision. This is an old back-and-forth among academic disciplines. Physicists demanded a p-value (the chance that they got those results by chance) of 0.00000059 before declaring the Higgs boson discovered. To them social scientists’ threshold of p=.05 it has the rigor of mud. Most disciplines can criticize other disciplines about how their thresholds are looser, but biblical studies and ancient history is near the bottom of that pile. People try to draw conclusions about prehistoric monuments from some ochre, burial sites, and neolithic monuments, when a paper about modern-day Presbyterians or whatever drawn from the same amount and quality of evidence would get laughed out of the room.
Again, that is not to bag on ancient historians. While I am sure they would love to unearth a large-N survey on clay tablets in a Babylonian library, they have to deal with the data they have, not the data they want, and they’re probably doing an excellent job with the data they have.
However, every once in a while it’s nice to take a step back and realize how broad the confidence intervals are when you’re basing your judgments on a very small amount of evidence. And yes, the physicists would say the same thing about survey-based social science; there’s always a bigger bully in the room, and that’s not to say that every discipline that can’t possibly get to five-sigma confidence should just wrap up and go home, but just because they’re dealing with inherent limitations does not mean that those limitations should be ignored when talking about the bigger picture.

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