“Meta-Criteria of Theory Testing” (the Science of Historicity/Forensics).

In following critical methods (criteria) of assessing the probability of improvable truths (such as historical propositions), we must assess the potency of its:

  • plausibility1
  • explanatory power
  • explanatory scope
  • predictive power
  • simplicity2
  • nesting3
  • track record4
  • fruitfulness5
  • accord with accepted beliefs
  • superiority to rival hypotheses
  • dis-confirmed by fewer accepted beliefs
  • low chance of an incompatible post-hypotheses

Scholarly lists of disiderata use these methods to determine an inference to the best explanation. These criterion have epistemic value that make the theory “truth-tending” (or more likely to be true than not).

1 As put by Ratzsch as “internal consistency and compatibility with well-grounded metaphysical beliefs.” Could also be stated as including “mathematical validity.”
2 Or, “Occam’s Razor”–finding the explanation with the least hypotheses. Elsewhere stated as “limiting ad hoc-ness.” Something is ad hoc when it is an unnecessary additional hypothesis created to save a given theory.
3 Retention of a past working theory whose contents have been emptied of everything but the most necessary datum.
4 Ratzsch puts it, “how successful it has been in handling problems in the past.”
5 “A theory giving rise to unexpected discoveries … [and] fruitful in suggesting new lines of research or new experiments…” (Ibid.)

Sources:

Craig, William Lane. “Visions of Jesus: A Critical Assessment of Gerd Ludemann’s Hallucination Hypothesis” ReasonableFaith.org. N.p., n.d. Web. 16 July 2015. .

Ratzsch, Delvin Lee. “The Competence of Science.” Science & Its Limits: The Natural Sciences in Christian Perspective. Downers Grove, IL: InterVarsity, 2000. 90. Print.

See also:

McCullagh, C. Behan (1984) Justifying Historical Descriptions. Cambridge: Cambridge University Press.

https://en.wikipedia.org/wiki/Historical_method#Statistical_inference and https://en.wikipedia.org/wiki/Historical_method#Argument_from_analogy

Hume’s Abject Failure: The Argument Against Miracles by John Earman for the probability calculus (Bayes’ Theorem). Craig presents it here.

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