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Abstract:
Two sentence completion experiments will be
reported in which participants had to generate German equivalents
of "the servant of the actress who " (NP of NP RC)
constructions. Target fragments (where subjects were free
to produce either high- or low-attached relative clauses, cf. 1)
were preceded by structurally similar prime fragments triggering
either high attachment of the relative clause (2a), low
attachment of the relative clause (2b), or the generation of a
structure that did not contain a relative clause (baseline
condition, 2c).
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(1)
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Target: Der Pensionär
schimpfte über die Verfasserin der Flugblätter, die
...
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The pensioner railed about the
author [fem, sing] of the fliers [neut, plur] that [?]
...
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(2)
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Primes:
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a.
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Die Assistentin verlas den
Punktestand der Kandidatin, der ...
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The assistant announced the
score [masc, sing] of the candidate [fem, sing] that
[masc, sing] ...
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b.
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Die Assistentin verlas den
Punktestand der Kandidatin, die ...
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The assistant announced the
score [masc, sing] of the candidate [fem, sing] that
[fem, sing] ...
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c.
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Die Assistentin verlas den
Punktestand der Kandidatin, bevor ...
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The assistant announced the
score [masc, sing] of the candidate [fem, sing] before
...
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Experiment 1 (showing a baseline bias towards
low-attached target RCs) obtained reliably more high-attached
target RCs after high attachment primes, but only marginally
more low-attached target RCs after low attachment primes.
Experiment 2 employed a different set of items (resulting in a
baseline bias towards high-attached target RCs) and obtained
significantly more low-attached target RCs after low attachment
primes, but only marginally more high-attached target RCs after
high attachment primes. The results are interpreted as
evidence for a tendency of language producers to retain
sequences of generative rule applications from one trial to the
next. (Note that the results cannot be explained in terms
of the context-free rules themselves, as in, e.g., Pickering
& Branigan, 1998). Furthermore, a quantitative model
is developed (and backed up by additional data from the
literature) that allows for the prediction of priming
magnitudes in terms of how much information is conveyed by the
relevant primes, given a certain bias in the baseline. The
model explains why priming is weaker after primes that are of
the same type as the preferred baseline response than after
primes of the alternative (non-preferred) type.
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