**Fodor, J. D. 1998. Parsing to learn. Journal of Psycholinguistic Research, 27(3), 339-374.
(6) This in the conclusion: “…in principle it should be possible for Bayesian priors to express the kinds of rich linguistic knowledge that linguists posit for Universal Grammar. It would be extremely interesting to investigate just what a statistical estimator using linguistically plausible parameters might be able to learn.” — Exactly this! I’ve long (vaguely) pondered how to connect the sorts of parameters in, say, a parametric representation of metrical phonology to the kinds of precise mathematical priors Bayesian models use. Somehow, somehow it seems possible…and then perhaps the two uses of “parameter” could be reconciled more precisely.