Križ & Spector (2021): Interpreting Plural Predication #
@cite{kriz-spector-2021}
Interpreting Plural Predication: Homogeneity and Non-Maximality. Linguistics and Philosophy, 44, 1131-1178.
Core Contribution #
Križ & Spector 2021 refine @cite{kriz-2016}'s pragmatic mechanism for non-maximality. Where Križ 2016 used "Addressing an Issue" (no QUD cell straddles the true/false boundary), K&S replace this with strong relevance filtering: a candidate interpretation is relevant only if its truth predicate is constant on each cell of the QUD partition.
Bridge Theorems #
This file proves the correspondence between the two accounts:
bivalent_addressing_iff_stronglyRelevant: For bivalent sentences (those modified byall), Križ 2016's Addressing constraint is equivalent to Križ & Spector 2021's strong relevance of the truth predicate to the QUD.all_addressing_iff_relevant: Specialization toall-sentences: Addressing the QUD ↔allSatisfyis strongly relevant.
These theorems connect two independently formalized mechanisms:
Semantics.Homogeneity.addressesIssue(from Križ 2016)Semantics.Lexical.Plural.Distributivity.isStronglyRelevantProp(from K&S 2021)
showing they agree on the bivalent fragment.
For bivalent sentences, the two pragmatic constraints are equivalent. Križ 2016's Addressing says no QUD cell has both true and false worlds. K&S 2021's strong relevance says the truth predicate is constant on each cell. For bivalent sentences these coincide: if the predicate varies within a cell, one world must be true and the other false (there is no gap).
For bivalent sentences, Addressing ↔ strong relevance of the truth predicate.
The Addressing condition says no cell has both true and false worlds. Strong relevance says the truth predicate is constant on each cell. For bivalent sentences these are equivalent: if the predicate varies within a cell, one world must be true and the other false (there is no gap to break the dichotomy).
For all-sentences, the bridge specializes further: Addressing ↔
allSatisfy is strongly relevant to the QUD. This connects directly to
nonMaximality_from_coarse_qud in Distributivity.lean: when the QUD groups
an all-true world with a not-all-true world, the all-sentence fails to
address the issue, so all cannot be used non-maximally.
For all-sentences, Addressing ↔ allSatisfy is strongly relevant.
This bridges Križ 2016's pragmatic mechanism (Addressing) to K&S 2021's filtering mechanism (strong relevance) for the specific case of universal quantification over pluralities.
The two independently developed mechanisms for non-maximality — pragmatic
(communicatedContent from Križ 2016) and semantic (candidate conjunction from
K&S 2021) — are connected by this bridge: communicatedContent is exactly the
set of worlds where the conjunction of strongly relevant candidates is usable.
For simple cases (single plural DP, distributive predicate), the candidate
conjunction reproduces pluralTruthValue. The pragmatic filtering via
strong relevance then determines the communicated content by selecting which
candidates matter.
The candidate conjunction matches pluralTruthValue when all candidates
are included (before relevance filtering). This is the central
correspondence of @cite{kriz-spector-2021} §3: the simple trivalent
semantics IS truth-on-all-readings applied to the full candidate set.
This is a restatement of pluralTruthValue_eq_candidateSemantics in
terms of the candidate conjunction operator.
The H-parameter framework from Distributivity.lean provides a deeper
derivation of the same trivalent semantics. Here we connect the three
characterizations:
pluralTruthValue(supervaluation over atoms)fullCandidateSet+ conjunction (truth on all readings)allViaForallH(∀H quantification)
All three agree: they are three views of the same trivalent denotation.
The ∀H characterization of all agrees with allSatisfy, which agrees
with allPluralTV_eq_removeGap. This closes the triangle:
∀H ↔ allSatisfy ↔ removeGap(barePluralTV).
@cite{kriz-spector-2021} §2.2.3, §3.1: The enriched candidate set correctly handles plural definites in non-monotonic contexts like "Exactly one student read the books." Unlike the two-candidate approach (Krifka 1996), the full candidate set ensures that the conjunction of candidates captures both "one student read all" AND "the others read none."
We demonstrate this with a concrete model: 2 students, 2 books, 4 worlds.
| World | Mary reads | John reads | "Exactly one read the books" |
|---|---|---|---|
| maryAll | a, b | ∅ | TRUE (intended) |
| bothAll | a, b | a, b | FALSE |
| maryAllJohnA | a, b | a | GAP (underdetermined) |
| noneRead | ∅ | ∅ | FALSE |
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Did this student read this book in this world?
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- Phenomena.Plurals.Studies.KrizSpector2021.nmRead Phenomena.Plurals.Studies.KrizSpector2021.NMStudent.mary x✝ Phenomena.Plurals.Studies.KrizSpector2021.NMWorld.maryAll = true
- Phenomena.Plurals.Studies.KrizSpector2021.nmRead Phenomena.Plurals.Studies.KrizSpector2021.NMStudent.mary x✝ Phenomena.Plurals.Studies.KrizSpector2021.NMWorld.bothAll = true
- Phenomena.Plurals.Studies.KrizSpector2021.nmRead Phenomena.Plurals.Studies.KrizSpector2021.NMStudent.mary x✝ Phenomena.Plurals.Studies.KrizSpector2021.NMWorld.maryAllJohnA = true
- Phenomena.Plurals.Studies.KrizSpector2021.nmRead Phenomena.Plurals.Studies.KrizSpector2021.NMStudent.mary x✝ Phenomena.Plurals.Studies.KrizSpector2021.NMWorld.noneRead = false
- Phenomena.Plurals.Studies.KrizSpector2021.nmRead Phenomena.Plurals.Studies.KrizSpector2021.NMStudent.john x✝ Phenomena.Plurals.Studies.KrizSpector2021.NMWorld.maryAll = false
- Phenomena.Plurals.Studies.KrizSpector2021.nmRead Phenomena.Plurals.Studies.KrizSpector2021.NMStudent.john x✝ Phenomena.Plurals.Studies.KrizSpector2021.NMWorld.bothAll = true
- Phenomena.Plurals.Studies.KrizSpector2021.nmRead Phenomena.Plurals.Studies.KrizSpector2021.NMStudent.john x✝ Phenomena.Plurals.Studies.KrizSpector2021.NMWorld.noneRead = false
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The singleton candidate {a} for John IS a candidate in the full set.
That singleton candidate is TRUE at maryAllJohnA (John did read book a).
But the maximal candidate is FALSE (John didn't read all books).
The gap for John arises from candidate disagreement: some candidates are true (singleton {a}) and some are false (maximal {a,b}). This is precisely the K&S diagnosis of homogeneity as candidate disagreement.
@cite{kriz-spector-2021} §3.3, Appendix: Upward homogeneity arises when a predicate is true of a super-plurality containing x but not of x itself. For example, "The soldiers of my brigade didn't surround the castle" is false if the brigade together with other soldiers surrounded the castle.
The existing generalisedTV in Homogeneity.lean captures this via the
overlaps relation. Here we prove the connection: when an overlapping
super-plurality satisfies P, the sentence about x is gapped, not false.
Upward homogeneity: if P is false of x but true of some overlapping super-plurality in the domain, then the generalised truth value is GAP, not FALSE. The predicate's truth "leaks upward" through overlap.
This captures @cite{kriz-spector-2021} §3.3: "The soldiers of my brigade didn't surround the castle" is undefined (not false) when the brigade participated with other soldiers in surrounding the castle.