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The impact of focus particles on the recognition and rejection of contrastive alternatives

Published online by Cambridge University Press:  22 January 2016

NICOLE GOTZNER*
Affiliation:
ZAS and Humboldt-Universität zu Berlin
ISABELL WARTENBURGER
Affiliation:
Universität Potsdam
KATHARINA SPALEK
Affiliation:
Humboldt-Universität zu Berlin
*
†Address for correspondence: Nicole Gotzner, ZAS, Schützenstr. 18, 10117 Berlin, Germany. e-mail: gotzner@zas.gwz-berlin.de>
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Abstract

The semantics of focus particles like only requires a set of alternatives (Rooth, 1992). In two experiments, we investigated the impact of such particles on the retrieval of alternatives that are mentioned in the prior context or unmentioned. The first experiment used a probe recognition task and showed that focus particles interfere with the recognition of mentioned alternatives and the rejection of unmentioned alternatives relative to a condition without a particle. A second lexical decision experiment demonstrated priming effects for mentioned and unmentioned alternatives (compared with an unrelated condition) while focus particles caused additional interference effects. Overall, our results indicate that focus particles trigger an active search for alternatives and lead to a competition between mentioned alternatives, unmentioned alternatives, and the focused element.

Information

Type
Research Article
Copyright
Copyright © UK Cognitive Linguistics Association 2016 
Figure 0

Fig. 1. Mean pitch contour of focused element in the critical sentences across particle conditions. The fundamental frequency was averaged at five equidistant interval parts on the entire word.

Figure 1

Fig. 2. Mean RT across unrelated items, mentioned alternatives, and unmentioned alternatives broken by particle condition (Experiment 1). Error bars represent standard errors (SEM). Means are calculated based on the statistical model presented in Table C2.

Figure 2

Fig. 3. Mean RT across unrelated items, mentioned alternatives, and unmentioned alternatives (Experiment 2). Error bars represent standard errors (SEM). Means are calculated based on the statistical model presented in Table C4.

Figure 3

table A1. Items used in Experiments 1 and 2

Figure 4

table B1. Word length and frequency of mentioned alternatives, unmentioned alternatives and unrelated items

Figure 5

table C1. Accuracy across probe/target types and particle conditions

Figure 6

table C2. Results of mixed model for probe recognition experiment 1 (n = 3429, log-likelihood = 1160) including estimates, confidence intervals, and p-values based on MCMC sampling

Figure 7

table C3. Accuracy across target types and particle conditions (Experiment 2)

Figure 8

table C4. Results of mixed model for lexical decision experiment 2 (n = 1888, log-likelihood = 532.8) including estimates, confidence intervals, and p-values based on MCMC sampling