Tesis doctoral en la redInfoling 9.30 (2019)
A predicate is understood distributively if it is inferred to be individually true of each member of a plural subject, nondistributively if not. 'Alice and Bob smiled conveys that Alice smiled and Bob smiled (distributive); 'Alice and Bob met conveys that they met jointly (nondistributive); 'Alice and Bob opened the window' can describe a situation in which they each did so (distributive), or one in which they did so only jointly (nondistributive).
These facts raise a compositional semantics question and a lexical semantics question. The compositional semantics question has been discussed widely: how should these sentences be represented semantically? To what extent should such representations capture inferences about distributivity? The lexical semantics question has received less attention: which predicates are understood in which ways? Certainly these inferences are grounded in the events described by these predicates (smile is distributive because people have their own faces); but which further predicates behave like smile, like meet, or like open the window, and why?
To make progress, this dissertation presents the Distributivity Ratings Dataset, over 2300 verb phrases (built from the verbs of Levin 1993) rated for their distributivity potential by online annotators. This dataset provides evidence consistent with a series of hypotheses: that predicates describing the action of an individual body or mind (smile) are distributive given that individuals have their own bodies and minds; that predicates describing inherently multilateral actions (meet) are nondistributive given that individuals cannot carry out these actions unilaterally; that causative predicates (open a window, describing an action where the subject causes the object to change) can (but need not) be nondistributive given that multiple individuals’ actions may be jointly but not individually sufficient to cause a result; and finally, that predicates with incremental objects (objects whose parts correspond to the parts of the event described by the predicate, as in eat a pizza) can also be nondistributive, given that each member of a plural subject might carry out the verb event on a different portion of the object, only jointly adding up to the whole.
Turning from verb phrases to adjectives, the dissertation draws on tools from measurement theory to argue that a gradable adjective’s potential for distributivity depends on the nature of the scale associated with it. An adjective can be understood nondistributively (as when ''the boxes are heavy'' conveys that the boxes are jointly but not individually heavy) if the scale associated with the adjective behaves ''positively'' with respect to concatenation: if the weight of two boxes together exceeds the weight of each one. That way, the contextual standard for what counts as ''heavy'' can be set in such a way that two boxes together exceed it, while each box individually falls short of it — nondistributive.
Turning to the compositional semantics question, the dissertation advocates for an underspecified semantics in which a predicate is true of each cell of a contextually supplied cover (set of subparts) of its plural subject. All inferences about distributivity are framed as inferences about which cover(s) to entertain, given what is known about the event or property described by the predicate. This semantic analysis does not explain anything on its own, but becomes explanatory when combined with a predictive analysis of which predicates can be understood in which ways.
More info: https://purl.stanford.edu/st374mm5103
1.1 What is distributivity?
1.2 Plan of attack
1.2.1 Main questions
1.2.2 Preview of claims
1.2.3 Guiding principles
1.2.4 Distinguishing linguistic and non-linguistic knowledge
1.3.1 Types of subjects
1.3.2 Arguments other than the subject
1.3.3 The effect of the object of a transitive verb
1.3.4 What’s possible versus what’s preferred
1.4 Outline of the dissertation
2 ‘Collective’ vs. ‘cumulative’
2.2 Should ‘collective’ be separate from ‘cumulative’?
2.2.1 For and against defining collectivity positively
2.2.2 For and against a collective / cumulative distinction
2.3 Cumulativity of verbs and thematic roles
2.4 Evidence from predicates with incremental objects
2.5 Chapter summary
3 Semantic representation
3.2 Data to capture
3.3 A cover analysis
3.3.1 Schwarzschild’s formulation
3.3.2 Analysis advocated here
3.3.3 Capturing the ‘collective’ / ‘cumulative’ data on the proposed analysis
3.4 Alternative analyses from the literature
3.4.1 One source: an operator
3.4.2 One source: meaning postulates
3.4.3 Two sources: meaning postulates and an operator
3.5 Chapter summary
4 Verb phrases
4.1.1 Literature motivating the current study
4.1.2 Where the current work fits in
4.2 Distributivity Ratings Dataset
4.2.1 Choosing objects for transitives
4.2.2 Study design
4.3 Motivating and testing hypotheses
4.3.1 Full models including all predictors
4.3.2 Transitive / intransitive asymmetry
4.3.3 Body / mind predicates
4.3.4 Multilateral predicates
4.3.6 Predicates with incremental objects
4.4 Chapter summary
5.2 Literature on the distributivity of adjectives
5.2.1 A pragmatic explanation for heavy versus tall
5.2.2 Open questions
5.3 Background on gradable adjectives and measurement theory
5.4 Explaining the distributivity potential of adjectives
5.5 Chapter summary
6.2 Open questions
6.3 Zooming out
Búsquedas a partir del año 1998: