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The notion focus affinity refers to the likelihood that a grammatical role (e.g., subject, object) is the narrow focus of a sentence. There is evidence that such differences exist at the level of distributional data. For example, subjects are less often focal and more often topical as compared to direct objects. However, it is not obvious whether focus affinity is genuinely related to grammatical roles. Focus affinity could be an epiphenomenon of various other linguistic and pragmatic processes or their interactions (e.g., direct objects are more often indefinite, less often animate, more often new than subjects). In our controlled experimental study, we investigate the focus affinity of three adjunct types (instruments, locatives, depictive secondary predicates) in Spanish and provide evidence that these grammatical roles indeed differ with respect to focus affinity. Depictives show the highest degree of focus affinity, followed by instruments and finally locatives. These effects are robust and stable even if we account for a number of possible alternative explanations. Thus, we suggest that focus affinity is a property sufficiently closely associated with grammatical roles to justify more attention both in theoretical linguistic and psycholinguistic literature. • Focus affinity is an understudied information structural concept. • Focus affinities of three adjunct types have been experimentally investigated. • Focus hierarchy: Depictives > Instruments > Locatives. • Differences between grammatical roles are robust even if we consider alternative explanations (e.g., probabilities). [ABSTRACT FROM AUTHOR]

Highlights • We find an inverse S-shape in stated subjective probabilities in a novel experiment. • Prelec's (1998) conditional invariant model provides the best fit. • We find a large degree of individual heterogeneity. Abstract We examine the nature of stated subjective probabilities in a complex, evolving context in which participants are not told what the actual probability is: we collect information on subjective expectations in a computerized car race game wherein participants must bet on a particular car but cannot influence the odds of winning once the race begins. In our setup, the actual probability of the good outcome (a win) can be determined based on computer simulations from any point in the process. We compare this actual probability to the subjective probability stated by participants at three different points in each of six races. In line with previous research in which participants have direct access to actual probabilities, we find that the inverse S-shaped curve relating subjective to actual probabilities is also evident in our far more complex situation, and that there is only a limited degree of learning through repeated play. We show that the model in the inverse S-shaped function family that provides the best fit to our data is Prelec's 1998 conditional invariant model. We also find that individuals who report a greater degree of ambiguity are more pessimistic and less responsive to actual changes in real probabilities. [ABSTRACT FROM AUTHOR]