A study on scalar implicatures and gradable adjectives. - corpora ...

“Can a decent student get into Harvard” A <strong>study</strong> on scalar implicatures and gradable
adjectives.
Andrea Beltrama and Ming Xiang
University of Chicago
According to Horn [1], scalar implicatures (SIs) are often triggered by lexical items on a scale
ordered by monotonic entailment-based logical strength. For instance, on a quantity scale, “some”
triggers the pragmatic inference that the negation of a stronger term “all” is true. Scalar implicatures of
this kind, i.e. the assertion of a weaker term negates the corresponding stronger term on the same scale,
have been widely discussed for quantifiers, number terms and conjunction/disjunction, but little has
been studied for gradable adjectives, which naturally form a scale. In fact, it has been shown that
pragmatic inferences on scalar adjectives, e.g. “warm” pragmatically implies “not hot”, are not readily
available to people, unless the alternatives in the context was made more salient to them [2].
In this <strong>study</strong>, we look at SIs triggered by gradable adjectives. We hypothesize that a key factor
to trigger SIs is the degree of contrast in informativity between the expression and the situation that it
describes. Gradable adjectives provide a perfect testing ground to investigate the causal relationship
between degrees of informativity and the generation of SIs because multiple adjectives can be ordered
on a scale across a continuum. In a given context, adjectives exhibiting a high degree of
underinformativity could make alternatives on the same scale more salient, and consequently facilitate
the calculation of scalar implicatures. The other goal of this <strong>study</strong> is to look at the time course of the
processing of SIs. Previous research has found mixed results: some argued that the calculation of SIs is
a delayed process [3]; while others found that SIs are processed by people as soon as possible after they
encounter the scalar term that could trigger SIs [4].
Twenty-four adjective scales were created in Italian, each of which contained three adjectives: a
weak one (i.e, “decent”), an intermediate one (“good”), a strong one (“excellent”). For each adjective
scale, a two-sentence scenario was created in which the strong adjective was the most informative
choice, and the weak and the intermediate adjectives were less informative. In addition, a fourth control
condition was created with an adjective on the same scale, which would lead to a contradiction. An
example is shown below (the original was in Italian):
(1) a. Mark is a decent student. That’s why he has been accepted to Harvard… (weak)
b. Mark is a good student. That’s why he has been accepted to Harvard…. (intermediate)
c. Mark is an excellent student. That’s why he has been accepted to Harvard… (strong)
d. Mark is a bad student. That’s why he has been accepted to Harvard… (contradiction)
Twenty-four sets of stimuli were distributed into 4 lists with a Latin Square design, such that each
participant only saw one condition from each item. In addition, 30 filler sentences were mixed with the
critical items. Each participant performed a self-paced-reading task. The first sentence of each scenario
was read as a chunk, and the second sentence was read word-by-word. The critical word (CW) in the
second sentence (“Harvard” above) was never the last word of the sentence. At the end of each
scenario, participants were also instructed to provide a score of acceptability for the scenario, ranging
from 1 (completely unacceptable) to 5 (perfectly acceptable).
Our predictions are the following: 1) if degrees of contrast in informativity matter for
calculating SIs, the more underinformative sentences will generate more SIs and hence also receive
lower scores in the rating task. This predicts a rating order of “weak”< “intermediate”< “strong”; (2) if
SIs are calculated as fast as possible, there should be a reading time (RT) difference at the CW, such
that the more underinformative sentences will lead to bigger processing cost and hence longer RTs:

“weak” > “intermediate” > “strong”. For both of these predictions, the contradiction condition serves as
a control baseline.
The Preliminary results from 16 native speakers of Italian are shown in Table 1. Regarding the
acceptability judgment, sentences containing weak adjectives are rated significantly lower than those
with intermediate and strong adjectives (all ps.5). This suggests that SI calculations were not immediately
available to people when they first encounter the SI triggers. This supports the view that SI processing,
being pragmatic in nature, is a delayed process.
Table 1 Acceptability judgment response and RT results (n=16)
Condition
Weak Intermediate Strong Contradictory
Response (1-5) 3.15 4.13 4.24 1.50
Response time 3602.0 3766.4 3296.4 2572.8
(ms)
RT at the CW
(ms)
649.4 659.4 669.2 739.9
Reference
[1] Horn, Laurence. 1984. "A new taxonomy for pragmatic inference: Q-based and R-based
implicature." In D. Schiffrin (ed.), Meaning, Form and Use in Context (GURT '84), 11-42.
[2] Doran, Ryan, Rachel Baker, Yaron McNabb, Meredith Larson, and Gregory Ward, 2008,“On the
Non-Unified Nature of Scalar Implicature: An Empirical Investigation,” in International Review of
Pragmatics 1:1-38.
[3] Bott, L. & Noveck, I.A. (2004). Some utterances are underinformative: The onset and time course
of scalar inferences. Journal of Memory and Language, 51(3), 437-457.
[4] Nieuwland, M.; Ditman, T. & Kuperberg, G. 2010. On the incrementality of pragmatic processing:
An ERP investigation of informativeness and pragmatic abilities. Journal of Memory and Language.
63:324-346.