1,721,022 research outputs found
A D-type Theory Solution to the Proportion Problem
No full textThere are currently two major theories offering an analysis of donkey sentences: Dynamic Semantics (e.g. Kamp 1981, Heim 1982) and D-type theory (e.g. Heim 1990, Elbourne 2005). In their standard implementation, both theories generate so-called strong symmetric readings for donkey sentences. However, the literature also notes asymmetric readings of donkey sentences that have usually as their Q-adverb (the ‘proportion problem’). Recently, Chen (2012) has argued that Dynamic Semantics have an advantage over D-type theory as they can solve the proportion problem by giving up unselective binding; in contrast, the most recent proposal for a D-type theory, Elbourne (2005), offers no solution to the problem. In this paper, I argue that Elbourne’s system can straightforwardly be extended to solve the proportion problem. This will also provide a natural solution to the problem of weak readings, which allows us to reconsider the relationship between the weak/strong and the symmetric/asymmetric distinction
Counterfactual Donkey Sentences: A Strict Conditional Analysis
Full text linkWe explore a distinction between \u27high\u27 and \u27low\u27 readings in counterfactual donkey sentences and observe three open issues in the current literature on these sentences: (i) van Rooij (2006) and Wang (2009) make different empirical predictions with respect to the availability of \u27high\u27 donkey readings. We settle this question in favour of van Rooij’s (2006) analysis. (ii) This analysis overgenerates with respect to weak readings in so-called \u27identificational\u27 donkey sentences. We argue that pronouns in these sentences should not be analysed as donkey pronouns, but as concealed questions or as part of a cleft. (iii) The analysis also undergenerates with respect to NPI licensing in counterfactual antecedents. We propose a strict conditional semantics for counterfactual donkey sentences that derives the correct licensing facts
High and low readings in indicative donkeys
No full textIn this paper, we extend existing accounts of high and low readings in counterfactual donkey sentences (van Rooij 2006, Walker and Romero 2015) to indicative donkey sentences. First, we generalize the account to indicative donkey sentences featuring modals that employ ordering sources. Then, we turn to indicative donkey sentences with adverbs of quantification. We discuss the relationship between high and low readings arising when a similarity measure is involved and symmetric and asymmetric readings arising with adverbs of quantification (Kadmon 1987) and present tentative data that suggests that they are two closely related phenomena
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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