Decision-Theoretic Semantics: "Even" (@cite{merin-1999} §5) #
@cite{francescotti-1995} @cite{kay-1990} @cite{merin-1999}
Merin's DTS account of the scalar particle "even". The felicity of "A CONJ even(B)" requires B to be more relevant than A, resolving the dispute between Anscombre (argumentative value), Kay (contextual entailment), and Francescotti (surprise) under a single relevance ordering.
Key Definitions #
evenFelicitous(Hypothesis 5): felicity conditions for "A CONJ even(B)"
Main Results #
- Prediction 3 (
but_even_incompatible): "but" and "even" are incompatible — "A but even(B)" is always infelicitous.
Note on the Dispute #
Merin shows that relevance subsumes all three prior analyses:
- Anscombre's "argumentative value" = Bayes factor ordering
- Kay's "contextual entailment" ≈ BF(B) > BF(A) in strong form
- Francescotti's "surprise" ≈ low prior probability ≈ high BF
The DTS account derives all three as special cases of "B is more relevant than A to the current issue."
Hypothesis 5: Felicity conditions for "A CONJ even(B)" with VP-focus.
"A and even B" is felicitous iff: (i) A is positively relevant to some issue H, (ii) B is positively relevant to H, (iii) B is more relevant than A (BF(B) > BF(A)), (iv) H ≠ B (the issue is not B itself — that would collapse to "also").
The key innovation: "even" marks B as the more informative conjunct, not merely "surprising" or "unexpected."
Equations
- One or more equations did not get rendered due to their size.
Instances For
Prediction 3: "But" and "even" are incompatible.
"A but even(B)" is never felicitous: butFelicitous requires B to be
negatively relevant (BF < 1), while evenFelicitous requires B to be
positively relevant (BF > 1). These are contradictory.
DTS Bayes factor ordering as a likelihood ordering for focus particles.
Higher BF = more informative about the issue = less likely a priori =
more surprising. This connects Merin's relevance ordering to the
traditional EVEN presupposition framework in Semantics.FocusParticles.
@cite{merin-1999} subsumes @cite{francescotti-1995}'s "surprise" and @cite{kay-1990}'s "informativeness" as special cases of signed relevance.
Equations
- Theories.DTS.Even.dtsLikelihood ctx a b = (Theories.DTS.bayesFactor ctx a > Theories.DTS.bayesFactor ctx b)