Are Figurative Interpretations of Idioms Directly Retrieved or Compositionally Built?
Evidence from Eye Movement Measures of First and Second Language Reading
Kyle S. Lovseth
Department of Psychology
McGill University, Montreal
Submitted: June, 2012
A thesis submitted to McGill University in partial fulfillment of the requirements of the degree of
M. A. In the Department of Psychology©
Kyle S. Lovseth
ii
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
TABLE OF CONTENTS
ABSTRACT
iv
RÉSUMÉ
v
ACKNOWLEDGEMENTS
vi
CONTRIBUTIONS OF AUTHORS
vii
LIST OF TABLES
viii
LIST OF FIGURES
x
INTRODUCTION
1
What are Idioms?
1
Noncompositional Models of Idiom Processing
2
Compositional Models of Idiom Processing
3
Hybrid Models of Idiom Processing
4
Present Study
6
EXPERIMENT 1
8
Method
8
Participants
8
Stimuli
8
Apparatus
9
Procedure
10
Results
11
First Pass Effects on Phrase-final Nouns
13
Noun FFD
16
Noun GD
17
Disambiguating Region and Subsequent Idiom Effects
17
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
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TABLE OF CONTENTS (CONTINUED)
Disambiguating Region FPGD
20
Idiom Region TRT
21
Idiom Regressions
23
Discussion
23
EXPERIMENT 2
25
Method
27
Participants
27
Stimuli & Apparatus
27
Procedure
27
Results
28
First Pass Effects on Phrase-final Nouns
30
Noun FFD
31
Noun GD
32
Disambiguating Region and Subsequent Idiom Effects
32
Disambiguating Region FPGD
32
Idiom Region TRT
32
Idiom Regressions
34
Discussion
35
GENERAL DISCUSSION
37
REFERENCES
47
APPENDIX: Sentences used in Experiments 1 and 2
55
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
iv
Abstract
Idioms are part of a general class of multiword expressions that convey a figurative
interpretation that is not fully determined through an on-demand compositional (syntactic and
semantic) analysis of their component words (e.g., kick the bucket, save your skin). Idioms are
simultaneously amenable to direct retrieval from memory, and to an on-demand compositional
analysis, yet it is unclear which processes lead to figurative interpretations of idioms during
comprehension. Idioms also pose challenges for second language learners, who may rely less on
direct retrieval than first language users due to reduced L2 experience. In this study, first and second
language users (L1 and L2, respectively) read sentences containing idioms followed by figurative- or
literal-biased disambiguating regions. The results for L1 readers showed that increased familiarity
but not decomposability facilitated comprehension of figurative interpretations. The results for L2
readers showed that cross-language overlap and decomposability facilitated comprehension of
figurative interpretations. Thus, consistent with hybrid or multidetermined idiom processing models
(Titone & Connine, 1999; Libben & Titone, 2008), first language idiom interpretations arise more
from direct retrieval (indexed by familiarity) than compositional analysis. Second language idiom
interpretations, however, arise from both.
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
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Résumé
Les expressions idiomatiques font partie d'une catégorie générale d’expressions à mots
multiples qui confèrent une interprétation figurale qui n'est pas entièrement déterminée par une
analyse compositionnelle sur-demande (syntaxique et sémantique) des mots qui les forment (par
exemple, passer l’arme à gauche, sauver votre peau). Les expressions idiomatiques se prêtent à la
fois à une récupération directe en mémoire, et à une analyse compositionnelle sur-demande.
Cependant, il n'est pas clair quels processus mènent à l’interprétation figurale des idiomes lors de la
compréhension. Les expressions idiomatiques posent également un défi pour les individus apprenant
une langue seconde, individus qui, en raison d’une expérience L2 réduite, se basent possiblement
moins sur la récupération directe que les utilisateurs de langue maternelle. Dans cette étude, des
utilisateurs de langue maternelle et seconde (L1 et L2, respectivement) ont lu des phrases contenant
des idiomes suivis de régions désambiguisantes biaisées figuralement ou littéralement. Pour les
lecteurs L1, les résultats ont montré qu’une plus grande familiarité, mais pas une décomposabilité,
facilite la compréhension des interprétations figurales. Pour les lecteurs L2, les résultats ont montré
que le chevauchement translinguistique et la décomposabilité facilitent la compréhension des
interprétations figurales. Ainsi, conformément aux modèles hybrides ou multidéterminés de
traitement des idiomes (Titone & Connine, 1999; Libben & Titone, 2008), l’interprétation des
idiomes de langue maternelle repose davantage sur la récupération directe (indexée par la familiarité)
que sur l'analyse compositionnelle. Toutefois, l’interprétation des idiomes de langue seconde repose
sur les deux.
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
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Acknowledgments
I would like to start by thanking all of the undergraduate research assistants who helped with
data collection. Japneet Kaur, Monica Bennett, Lauren de la Parra, and Lianne Morier, the time and
effort each of you gave was invaluable and essential to the completion of this thesis. I would also
like to thank my fellow lab members, Veronica Whitford, Irina Pivneva, Naveed Sheikh, Julie
Mercier, and Maya Libben. The way we help and support each other makes our lab one of, if not
THE, very best working environment in the world. It is my pleasure to work alongside each and
every one of you.
Next, I would like to thank all of my co-supervisors during my tenure at McGill: Caroline
Palmer, Michael Wagner, Fred Genesee, and Jelena Ristic. They were always available when I had
questions, and pushed me to do my best work. I owe all of my success to my supervisor, Debra
Titone. Her enthusiasm for what she does is infectious and it has a hand in every facet of my
research. Thank you for taking a chance on me.
Finally, I would like to thank my mother, brother, grandmother, and grandfather to whom this
thesis is dedicated. I hope I have made each of you proud.
This research was supported by funding from the NSERC Create: Training in Auditory
Cognitive Neuroscience Fellowship. In addition, thank you for the support from the Centre for
Research on Language, Mind, and Brain for helping to peak my interest and guide me in exploring
new statistical methods.
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
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Contributions of Authors
This thesis is based on a manuscript submitted to the Journal of Memory and Language. The
first author, Kyle Lovseth, was responsible for experimental design, data collection, statistical
analyses, data interpretation, and writing all sections of the manuscript. The co-author, Debra Titone,
was responsible for providing input on the experimental design and the data interpretation. In
addition, the co –author provide valuable input and revisions to the introduction and discussion of
the manuscript.
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
viii
List of Tables
Table 1
Example Sentences From Id-Id, Id-Lit, and Lit-Lit Conditions
9
Table 2
Minimum Values, Maximum Values, Means, and Standard Deviations
10
for Measurements (Familiarity, L1/L2 Overlap, Decomposability, Literal
Plausibility) of Idiom Normative Values, and Reading Proficiency and
Character Length for Noun and Idiom Phrase in Each Condition (Idiom,
Literal) and Disambiguating Region in Each Condition (Id-Id, Id-Lit,
Lit-Lit)
Table 3
Definitions for Eye Tracking Measures: First Fixation Duration, First
12
Pass Reading Gaze Duration, Total Reading Time, and Idiom Regressions
Table 4
Total Number of Observations, Means, and Standard Deviations Across
14
All Participants for All Eye Movement Measurements (Noun FFD, Noun
GD, Disambiguating FPGD, Idiom TRT, Idiom Regressions) of Native
Language Readers In Each Condition (Idiom, Literal, Id-Id, Id-Lit, Lit-Lit)
for High and Low Levels of Familiarity and Decomposability for Native
English Speakers in Experiment 1
Table 5
Effect Size, Standard Error, and t-Values for Fixed Effects and Variances
for Random Effects Derived From Optimal LMER Models for the
Dependent Variables Noun Region First Fixation Duration and Noun
Region Gaze Duration for Native English Speakers in Experiment 1
16
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
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List of Tables (Continued)
Table 6
Effect Size, Standard Error, and t-Values for Fixed Effects and Variances
19
for Random Effects Derived From Optimal LMER Models for the
Dependent Variables Disambiguating Region First Pass Gaze Duration,
Idiom Region Total Reading Time, and Idiom Region Regressions for
Native English Speakers in Experiment 1
Table 7
Total Number of Observations, Means, and Standard Deviations Across
29
All Participants for All Eye Movement Measurements (Noun FFD, Noun
GD, Disambiguating FPGD, Idiom TRT, Idiom Regressions) of
Non-native Language Readers In Each Condition (Idiom, Literal, Id-Id,
Id-Lit, Lit-Lit) for High and Low Levels of L1/L2 Overlap and
Decomposability for Non-Native English Speakers in Experiment 2
Table 8
Effect Size, Standard Error, and t-Values for Fixed Effects and Variances
30
for Random Effects Derived From Optimal LMER Models for the
Dependent Variables Noun Region First Fixation Duration and Noun
Region Gaze Duration for Non-Native English Speakers in Experiment 2
Table 9
Effect Size, Standard Error, and t-Values for Fixed Effects and Variances
for Random Effects Derived From Optimal LMER Models for the
Dependent Variables Disambiguating Region First Pass Gaze Duration,
Idiom Region Total Reading Time, and Idiom Region Regressions for
Non-Native English Speakers in Experiment 2
33
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
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List of Figures
Figure 1
Noun gaze duration as a function of decomposability for the idiom and
18
literal conditions in native language readers
Figure 2
Disambiguating region first pass gaze duration as a function of familiarity
21
and decomposability for the Id-Id, Id-Lit, and Lit-Lit conditions in native
language readers
Figure 3
Idiom region total reading time as a function of familiarity for the Id-Id,
22
Id-Lit, and Lit-Lit conditions in native language readers
Figure 4
Proportion of regressions to idiom region as a function of familiarity for
23
the Id-Id, Id-Lit, and Lit-Lit conditions in native language readers
Figure 5
Noun first fixation duration as a function of L1/L2 overlap for the idiom
31
and literal conditions in non-native language readers
Figure 6
Idiom region total reading time as a function of decomposability for the
34
Id-Id, Id-Lit, and Lit-Lit conditions in non-native language readers
Figure 7
Proportion of regressions to idiom region as a function of decomposability
for the Id-Id, Id-Lit, and Lit-Lit conditions in non-native language reader
35
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
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Are Idioms Directly Retrieved or Compositionally Built?
Evidence from Eye Movement Measures of First and Second Language Reading
What are Idioms?
Idioms are part of a general class of multiword expressions, which include other elements
of non-literal language such as metaphor, sarcasm, and indirect requests. Idioms are similar to
other forms of non-literal language because they convey a figurative interpretation that is not
fully determined through an on-demand compositional (syntactic and semantic) analysis of their
component words (Chomsky, 1980; Fraser, 1970). Thus, a standard compositional analysis of the
idiom, kick the bucket, does not lead to its figurative interpretation to die, although other idioms
may be relatively more “compositional” (e.g., save your skin, which means, to protect one’s self)
(Nunberg, 1978; Jackendoff, 2002). Idioms differ from other classes of non-literal language,
however, because their figurative meanings are conventional and frequently used within a
language, and also across languages (Wray, 2002). Thus, at some level, idioms must possess
unitary representations that are stored in memory, similar to non-figurative yet over-learned
multiword sequences that also pervade language (e.g., conversational expressions such as How
do you do?). Despite a long-standing body of research, fundamental questions about idiom
processing remain unsettled. In this study, I investigate how first (L1) and second (L2) language
users process idioms using eye movement measures of reading, a method that has the potential to
clarify previously conflicting theoretical accounts of idiom processing.
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
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Noncompositional Models of Idiom Processing
Early models of idiom processing emphasized the lexical and noncompositional nature of
idioms, and thus the direct retrieval of idiomatic meaning. For example, the lexical
representation hypothesis (Swinney & Cutler, 1979) posits that idioms are represented in
memory as lexical entities, and that their pre-compiled figurative meanings are directly retrieved
in a manner similar to that of long compound words (see also Bobrow & Bell, 1973). Support for
the lexical representation hypothesis comes from the widely replicated finding that highly
familiar idioms are processed more rapidly than unfamiliar non-idiomatic phrases or idioms
(e.g., Cronk & Schweigert, 1992; see also Giora, 1997; Libben & Titone, 2008; Schweigert,
1986; Swinney & Cutler, 1979; Tabossi, Fanari, & Wolf, 2009). Facilitative effects of increased
idiom familiarity presumably reflect direct retrieval of pre-compiled figurative meanings, which
is less effortful and faster than on-demand compositional analyses. The configuration model
(Cacciari & Tabossi, 1988) also posits that direct retrieval of stored idiomatic meanings leads to
comprehension, although here idioms are represented as distributed word configurations that are
processed non-idiomatically until enough information is encountered for the configuration to
emerge (Fanari, Cacciari, & Tabossi, 2010; Tabossi, Fanari, & Wolf, 2009; Vespignani et al.,
2010). Within this view, idioms are understood through direct retrieval like any other overlearned word sequence, such as songs or clichés (Tabossi, Fanari, and Wolf, 2009; but see
Molinaro & Carreiras, 2010, and Vespignani et al., 2010, for electrophysiological evidence of
distinct neural responses for idioms vs. non-idiomatic collocations).
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
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Compositional Models of Idiom Processing
In recent years, however, direct retrieval models have fallen out of favor because of work
showing that idioms often behave like compositional word sequences (Nunberg, 1978; Nunberg,
Sag, & Wasow, 1994; Gibbs, Nayak, & Cutting, 1989, Gibbs, 1992). For example, idioms can
retain their figurative meanings when used creatively in syntactically or semantically modified
forms (McGlone, Cacciari, & Glucksberg, 1994; Gibbs & Nayak, 1989; Gibbs, Nayak, Bolton, &
Keppel, 1989; Hamblin & Gibbs, 1999). Accordingly, the figurative meaning of the idiom break
the ice can be understood in a variant form, such as crack the ice. Based on such findings,
Nunberg (1978) posited that idioms are more heterogeneous than previously thought, and Gibbs
and colleagues demonstrated that people process distinct classes of idioms differently. For
example, Gibbs and Nayak (1989, Experiment 2) found that normally decomposable idioms,
whose component words overlap with a figurative meaning (pop the question), retain their
figurative meaning when syntactically modified (the question was popped) more than
nondecomposable idioms, whose component words are distinct from a figurative meaning (the
bucket was kicked).
Moreover, other studies have shown that decomposable idioms have a global processing
advantage over nondecomposable idioms. For example, Gibbs, Nayak, and Cutting (1989) found
that meaningfulness judgments for decomposable idioms were faster than those for
nondecomposable idioms and literal control sentences. As well, nondecomposable idioms were
judged to be meaningful more slowly than literal control sentences. To explain these results,
Gibbs and colleagues suggested that decomposable idioms are understood directly through a
compositional analysis because their idiomatic and literal interpretations are mutually reinforcing
(e.g., question in the idiom pop the question refers directly to its figurative interpretation, to
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
4
propose marriage). By comparison, nondecomposable idioms are disadvantaged because their
idiomatic and literal phrasal meanings are semantically distinct (e.g., kick the bucket can mean to
die suddenly or to strike a bucket with one’s foot) (see also Callies & Butcher, 2007). However,
much of the work showing facilitative effects of decomposability is based on tasks that arguably
reflect off-line rather than on-line processing (e.g., paraphrase judgments), or studies that use
small numbers of idioms that potentially vary in others ways aside from decomposability (e.g.,
literal plausibility, familiarity, etc.).
Hybrid Models of Idiom Processing
Thus, an important but unresolved question is how and when decomposability exerts an
effect on comprehension. Related to this question, Titone and colleagues have also observed
facilitative effects of compositionality on idiom processing but only for later integrative stages of
comprehension, a finding that conflicts with predictions of strict compositional models. In an eye
movement reading study, Titone and Connine (1999) found differences between decomposable
and nondecomposable idioms in reading rates as a function of context. People read sentences
where idioms either preceded or followed a context that supported a figurative (He tried to save
his skin by getting his work done on time) or literal (He tried to save his skin by avoiding the
tanning salons) meaning. Nondecomposable idioms were read more slowly when a biased
(literal or figurative) context preceded the idiom compared to when it followed the idiom,
suggesting that additional time was required to select between one of two active phrase-level
interpretations. Decomposable idioms did not show this slowing, suggesting that semantic
integration was more easily accomplished for idioms with overlapping phrase-level
interpretations that had been activated. Similarly, Libben and Titone (2008) observed facilitative
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
5
effects of familiarity across a wide variety of tasks but only observed facilitative effects of
decomposability for tasks that required people to judge the meaning of idioms as a whole
(similar to the body of work reported by Gibbs and colleagues, but in contrast with Tabossi,
Fanari, & Wolf, 2008, 2009). For example, in a task that required people to read sentences wordby-word for comprehension without any explicit judgments about the meaning of the idiom,
familiarity facilitated reading times but decomposability did not. Thus, decomposability may not
facilitate initial activation of an idiom's figurative meaning, but it might help in selecting
between a simultaneously activated figurative and compositionally generated literal
interpretation of an idiomatic string.
Based on such findings, Titone and Connine (1999) posited a hybrid model of idiom
comprehension that incorporates aspects of both direct retrieval and compositional processing
(see also, Libben & Titone, 2008). Central to this view is that comprehenders simultaneously
follow all paths to comprehension (direct retrieval and compositional analysis), although the
availability of different kinds of information may follow distinct time-courses, and thus affect
comprehension at different stages. Assuming that direct retrieval is a fast process that can be
triggered prior to the phrase-final word, any variable that affects direct retrieval (e.g., idiomatic
status, familiarity, or predictability) should exert effects at the earliest stages of comprehension,
prior to the phrase-final word. In contrast, an on-demand compositional analysis is likely to be
slower and more effortful than direct retrieval, and would certainly require encountering the
phrase-final word to be complete. Thus, variables that affect compositional processing (e.g.,
degree of decomposability) only exert effects after exposure to the phrase-final word (see Prado
& Ullman, 2009, for a similar logic applied to past tense morphology).
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
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Present Study
I investigated three interdependent questions about idiom processing to adjudicate
between direct retrieval models, compositional models, and hybrid models of comprehension.
First, are idioms directly retrieved from memory as lexical-semantic chunks, are they built
compositionally, or do both operations occur simultaneously in a time-dependent fashion?
Second, how do these factors affect the ability to resolve phrase-level ambiguity that arises from
plausible non-idiomatic phrasal interpretations (e.g., when one literally kicks the bucket)?
Finally, how do these processes differ for people with varied linguistic experiences (e.g., when
native or non-native language users encounter idioms)? While prior studies have investigated
similar questions, the literature lacks consensus due to heterogeneity of the idioms tested (both in
terms of structural and other linguistic attributes), the measures used (e.g., lexical decision,
paraphrase judgment, meaningfulness decision, which differentially tap into on-line vs. off-line
processing), and whether people were required to interpret idioms figuratively or literally. Our
goal is to circumvent these issues to the extent possible by studying well-controlled idioms in
sentences using naturalistic eye movement measures of sentence reading (Rayner, 1998, 2009).
In Experiment 1, I investigate how familiarity and decomposability modulate idiom
comprehension when native English users read conventional English idioms. Idioms were
selected that have a consistent grammatical structure (verb-determiner-noun) and length, and that
were normed on several important linguistic dimensions in our prior work (Libben & Titone,
2008). These idioms (and control non-idiomatic literal phrases) were embedded in sentences that
participants read for comprehension while their eye movements were monitored. Within these
sentences, idioms were followed by disambiguating contexts that biased the figurative (Vicki
knew the score well enough not to ask for an extension on the project) or literal (Vicki knew the
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
7
score because she had been following the playoffs closely) interpretation. Structuring the
sentences in this way allowed us to examine reading behavior at two key comprehension points;
the region of the idiomatic phrase prior to contextual information about which meaning was
intended, and after a particular meaning was specified by the subsequent disambiguating context.
Experiment 2 was identical to Experiment 1 except that non-native English speakers were tested
to assess whether reduced participant familiarity with English idioms would increase the
likelihood that a compositional analysis would lead to a figurative interpretation.
I predicted that native English users would read idioms more quickly than literal phrases
on the first pass due to their familiarity with these conventional idioms. I also predicted that
native language users would have more difficulty reading a figuratively biased disambiguating
region for low vs. high familiar idioms, relative to literal control sentences. Regarding
decomposability, consistent with previous work (Titone & Connine, 1999; Libben & Titone,
2008), I predicted that increased decomposability might be important for resolving phrase-level
competition between idiomatic and non-idiomatic interpretations while reading idioms on the
first pass. Because nondecomposable idioms have semantically distinct phrase-level
interpretations (to kick the bucket and die vs. to stub one’s toe) and decomposable idioms have
semantically similar phrase-level interpretations (to save your skin and cover up a transgression
vs. one’s flesh). However, based on predictions of hybrid or multidetermined models, I predicted
that only their familiarity would facilitate reading for later, figuratively biased regions of
sentences.
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
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Experiment 1
Method
Participants
Thirty-six native English users from the McGill and Montreal community participated
for course credit or compensation of $10/hr. All participants had normal or corrected-to-normal
vision and no self-reported history of speech or hearing disorders.
Stimuli
Stimuli consisted of 60 English idioms taken from Libben and Titone (2008). All idioms
had a verb - determiner - noun structure (e.g., had a lark). Non-idiomatic control phrases were
formed by changing the verb in each idiomatic phrase (e.g., saw a lark), thus the nouns were
identical in the idiomatic and non-idiomatic conditions. Across the idiom-bearing sentences and
their non-idiom controls, the verbs matched in both character length (+/-1 character) and word
frequency (+/-5 counts per million, Kucera & Francis, 1967). Each idiom was embedded in one
of three sentence conditions: an idiomatic expression followed by a figurative disambiguating
region (Id-Id) or an idiomatic expression followed by a literal disambiguating region (Id-Lit).
Non-idiomatic phrases were also presented, followed by a supporting context (Lit-Lit). Table 1
presents example sentences from each condition, and the entire set of sentences is listed in the
Appendix.
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
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Table 1.
Example Sentences From Id-Id, Id-Lit, and Lit-Lit Conditions
Condition
Id-Id
Id-Lit
Lit-Lit
Sentence
Ruby had a lark when she switched her family’s sugar to salt as a joke.
Ruby had a lark when she was a child but now wanted a parrot instead.
Ruby saw a lark at the pet store and thought that it was very beautiful.
Independent ratings of familiarity, decomposability, and literal plausibility for each idiom
were obtained from Libben and Titone (2008). Idioms used had a mean familiarity rating of 3.40
on a five-point Likert scale (1 = Low familiarity; 5 = High familiarity), a mean decomposability
proportion of 0.43 (0 = Not decomposable; 1 = Fully decomposable), and a mean literal
plausibility rating of 3.87 on a five-point Likert scale (1 = Low literal plausibility; 5 = High
literal plausibility). Average total reading times (log transformed) were also calculated for all
filler sentences for each subject as a measure of overall reading speed or ability. Finally, total
character lengths were obtained for the noun, idiom, and disambiguating regions. For both the
idiom and disambiguating regions, there were no significant differences in either character length
between any of the specified conditions. Nouns were identical across all conditions. Measures of
familiarity, decomposability, literal plausibility, reading proficiency, and character length are
shown in Table 2.
Apparatus
An Eye-Link 1000 tower mounted system (SR-Research, Ontario, Canada) was used to
record eye movements (1 kHz sampling rate). Viewing was binocular but eye movements were
recorded from the right eye only. Stimuli were presented on a 21” ViewSonic CRT monitor with
a screen resolution of 1024 x 768 pixels, using EyeTrack 7.10 software developed at UMass
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
10
Amherst (http://www.psych.umass.edu/eyelab/software). Text was presented on a single line in
yellow 10-point Monaco font on a black background. Participants’ eyes were positioned 71 cm
from the monitor, thus 1 degree of visual angle comprised of approximately 3 characters of text.
Table 2.
Minimum Values, Maximum Values, Means, and Standard Deviations for Measurements
(Familiarity, L1/L2 Overlap, Decomposability, Literal Plausibility) of Idiom Normative Values,
and Reading Proficiency and Character Length for Noun and Idiom Phrase in Each Condition
(Idiom, Literal) and Disambiguating Region in Each Condition (Id-Id, Id-Lit, Lit-Lit)
Condition
Idiom Normative Values
Reading Proficiency
Noun
Idiom Phrase
Disambiguating Region
Idiom
Literal
Id-Id
Id-Lit
Lit-Lit
Measurement
Familiarity (Exp.1)
L1/L2 Overlap (Exp.2)
Decomposability
Literal Plausibility
log-Total Reading Time (Exp.1)
log-Total Reading Time (Exp.2)
Length (characters)
Length (characters)
Length (characters)
Min
1.60
0.00
0.00
1.50
5.31
7.47
3
11
11
42
43
43
Max
4.80
0.92
0.97
5.00
6.08
8.49
8
20
20
63
62
61
Mean
3.40
0.28
0.43
3.87
5.71
8.07
4.67
15.78
15.68
54.25
53.80
53.42
Procedure
Each participant completed a consent form and online language background
questionnaire. Participants were instructed to read sentences naturally while their eye movements
were recorded. Before each trial, participants were instructed to direct their gaze towards a small
fixation circle, the calibration point, appearing in the center of the monitor. Once the
experimenter noted that the participant’s gaze was fixed upon the calibration point, s/he initiated
the trial. Trials consisted of the appearance of a fixation square in a location equivalent to that of
SD
0.85
0.24
0.24
0.77
0.20
0.25
1.24
2.16
2.13
4.32
4.31
4.15
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
11
the first word of the sentence. Gazing at the fixation square automatically triggered the sentence
for that trial. Participants were instructed to read the sentence at a normal rate for
comprehension, and to press a button on a controller pad once they finished reading and
understood the sentence.
Participants viewed one of three sets of sentences in a fully counterbalanced and
randomized order. Within each set, each idiomatic expression appeared in only one of its
respective conditions. Thus, if a participant saw the idiomatic expression, broke the ice, in the IdId sentence, the next participant would see the same phrase in the Id-Lit sentence, and so on. No
participant saw the same idiomatic expression more than once. In addition to the 60 sentences of
primary interest, each participant read 19 “filler” sentences, 10 practice sentences, and 22
comprehension questions. This resulted in a total of 111 sentences read by each participant.
The filler and practice sentences were similar to non-idiomatic literal sentences. All filler
and practice sentences conveyed literal interpretations and were between 11 and 17 words in
length. Comprehension questions appeared on roughly 20% of trials. Participants responded to
the question by pressing an appropriately labeled controller pad. Overall accuracy on the
comprehension questions was 93%, indicating that participants were attentive during the
experiment.
Results
Linear mixed effects (LME) models were used to analyze all eye movement data. LME
has been used in other reading studies (e.g., Kliegl, Risse, & Laubrock, 2007), and has
advantages in statistical power over separate analyses of variance (ANOVA) across subjects and
items (Baayen, Davidson, Bates, 2008; Quene & van den Bergh, 2008). I used the lme4 package
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
12
(Bates & Sarkar, 2006) implemented for use with the R Project for Statistical Computing (R
Development Core Team, 2006; Baayen, 2008; Baayen, Davidson, Bates, 2008).
Our dependent variables (Table 3) included noun first fixation duration (Noun FFD) and
noun gaze duration (Noun GD) as measures of idiom comprehension prior to encountering the
disambiguating region. Comprehension measures for the disambiguating region included first
pass gaze duration of the disambiguating region (Disambiguating FPGD), total reading time for
the entire idiomatic phrase (Idiom TRT), and proportion of trials in which the idiom was
regressed into from the disambiguating region (Idiom Regressions). First fixation and gaze
duration reflect early cognitive processes, such as lexical access; total reading time and idiom
regression proportion reflect later processes, such as semantic integration (Rayner, 1998, 2009).
Table 3.
Definitions for Eye Tracking Measures: First Fixation Duration, First Pass Reading Gaze
Duration, Total Reading Time, and Idiom Regressions
Eye Tracking Measure
First fixation duration
First pass
gaze duration / Gaze
duration
Total reading time
Idiom regressions
Definition
The length of time the eyes fixate on the target word the first time they land
on it
The sum of all fixation durations following rightward moving saccades
starting the moment the eyes land on the target region until the moment
they move away
The sum of all fixations and refixations on the target region during a given
trial
The proportion of trials in which the target region was regressed into from the
disambiguating region
Likelihood ratio tests (LRTs) were conducted to identify the optimal model for each
dependent variable (Baayen, 2008). The LRTs evaluated goodness of fit for a given model
though a series of iterative log-likelihood ratio comparisons of more complex models (i.e.,
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
13
models with a greater number of fixed effects) to progressively less complex models (i.e.,
models with fewer fixed effects). As such, optimal models for each dependent variable varied as
a function of best fit and contained only fixed effects that significantly improved the fit of the
model. Markov chain Monte Carlo (MCMC) sampling tests were conducted to obtain p-values
for the coefficients of all contrasts included in optimal LME models. Generalized linear mixed
effects models were used for binary dependent variables (i.e., regressions to the idiom region).
Before analysis, 2.2% of the total fixations were removed because of track loss (e.g., eye
blinks) or because fixation durations were less than 80 ms. For each dependent variable, an upper
cutoff of 4 standard deviations above the mean was established to remove extreme outliers. For
Noun FFD and Noun GD, all trials in which the noun was skipped (n = 535, 24.8% of all Noun
FFD and Noun GD trials), or the verb or determiner of the idiom/literal phrase was not fixated
prior to fixating on the noun during the first pass (n = 104, 5% of all Noun FFD and Noun GD
trials) were excluded. For Disambiguating FPGD, Idiom TRT and Idiom Regression data, trials
where the entire idiomatic phrase was skipped on the first pass (n = 20, 1% of all Disambiguating
FPGD, Idiom TRT and Idiom Regression trials) were excluded. Finally, because a participant
could have briefly entered the idiom or disambiguating region before quickly regressing out of
either region, trials from Disambiguating FPGD data if the first pass gaze duration was equal to
the first fixation duration of the disambiguating region for that same trial (n = 170, 7.8% of all
Disambiguating FPGD trials) were removed. Trials in which this was the case would indicate
that only a single fixation occurred for an entire disambiguating region. Subject means and the
number of observations for each dependent variable binned across high and low Familiarity and
Decomposability in each condition are presented in Table 4. These means were included to
facilitate comparison to a traditional F1 ANOVA analysis; they do not reflect the actual analytical
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
14
LME procedure, in which Familiarity and Decomposability were treated as continuous
predictors.
Table 4.
Total Number of Observations, Means, and Standard Deviations Across All Participants for All
Eye Movement Measurements (Noun FFD, Noun GD, Disambiguating FPGD, Idiom TRT, Idiom
Regressions) of Native Language Readers In Each Condition (Idiom, Literal, Id-Id, Id-Lit, LitLit) for High and Low Levels of Familiarity and Decomposability for Native English Speakers in
Experiment 1
Familiarity
Eye-Movement Measure
Noun FFD1
Condition
n
Idiom
1001
Literal
505
1506
All
Idiom
1003
Noun GD1
Literal
502
1505
All
647
Disambiguating FPGD2 Id-Id
Id-Lit
672
Lit-Lit
641
1960
All
Id-Id
703
Idiom TRT1
Id-Lit
711
Lit-Lit
702
2116
All
Id-Id
711
Idiom Regressions
Id-Lit
715
Lit-Lit
707
2133
All
1
Values presented in milliseconds
2
Values presented in milliseconds per character
Note. Standard deviations are listed in parentheses
Condition
Mean
227 (71)
239 (79)
231 (73)
245 (92)
261 (100)
250 (95)
35.1 (14)
36.1 (15)
34.2 (14)
35.1 (15)
737 (422)
710 (384)
741 (405)
729 (404)
30.70%
26.00%
26.70%
27.80%
Low
233 (72)
245 (84)
237 (76)
255 (97)
267 (103)
259 (99)
36.0 (15)
35.7 (15)
34.1 (13)
35.3 (14)
809 (461)
761 (420)
760 (407)
777 (430)
36.80%
27.60%
25.10%
30.00%
High
220 (68)
232 (73)
224 (70)
233 (86)
255 (97)
241 (90)
34.2 (14)
36.4 (15)
34.2 (16)
35.0 (15)
661 (359)
661 (340)
721 (404)
681 (369)
24.00%
24.50%
28.30%
25.60%
Decomposability
Low
232 (75)
239 (77)
235 (76)
258 (103)
263 (99)
260 (102)
35.4 (15)
37.3 (15)
34.4 (14)
35.7 (15)
729 (394)
731 (407)
744 (380)
735 (393)
31.40%
25.90%
26.50%
27.90%
High
221 (66)
238 (81)
227 (71)
232 (77)
259 (102)
241 (87)
34.8 (14)
34.8 (14)
34.0 (14)
34.5 (14)
745 (447)
689 (359)
737 (430)
723 (414)
29.90%
26.20%
26.90%
27.70%
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
15
First Pass Effects on Phrase-final Nouns
I constructed initial LME models with Noun FFD and Noun GD as dependent variables,
and subject and item as random effects. In these models, data from the Id-Id and Id-Lit
conditions were combined to form a single “Idiom” condition, given that these two conditions
were identical prior to the disambiguating region of the sentence. The most complex models
included the interaction between the following theoretically driven predictor variables: Condition
(idiom, literal), Familiarity, and Decomposability. The most complex models also included
several control predictors: Trial (to account for practice or fatigue effects), Literal Plausibility (to
account for phrasal ambiguity), Reading Proficiency (to account for individual differences in
reading speed), and Character Length (to account for item differences in length of any target
region of interest). All predictor variables were continuous except for Condition, which was
categorical. All continuous predictor variables, except for Trial, were centered in an effort to
reduce occurrences of co-linearity, and divided by their standard deviation prior to analysis
(Baayen, 2008). The literal sentence condition was mapped to the intercept (i.e., it was the
baseline). For significant effects, I report differences in means derived from Table 4 and t-values
derived from Table 5. These means are included to facilitate comparison to traditional F1
analyses and do not reflect the actual LME procedure. For control predictor variables, I report
only t-values for significant effects derived from the optimal LME models, also summarized in
Table 5.
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16
Table 5.
Effect Size, Standard Error, and t-Values for Fixed Effects and Variances for Random Effects
Derived From Optimal LMER Models for the Dependent Variables Noun Region First Fixation
Duration and Noun Region Gaze Duration for Native English Speakers in Experiment 1
Noun Region
First Fixation Duration
Gaze Duration
b
SE
t-value
b
SE
t-value
Fixed effects1
Primary Predictors
Condition (Literal, Idiom)2
-10.23 3.82
-2.68**
-15.41
4.81
-3.20**
Familiarity
-7.45 2.31
-3.23**
-10.17
4.06
-2.51*
Decomposability
5.04
5.16
0.98
Condition*Familiarity
Condition*Decomposability
-10.58
4.83
-2.19*
Familiarity*Decomposability
Condition*Familiarity*Decomposability
Control Predictors
Trial
Literal Plausibility
Reading Proficiency
9.92 3.25
3.05**
20.18
3.85
5.24***
Character Length
(Intercept)
237.64 4.43 53.61***
259.41
5.83
44.54***
Random Effects
Variance
Variance
Subject
278.85
482.2
Item
123.47
368.54
Residual
4841.59
7628.36
* Significant at the .05 level
** Significant at the .01 level *** Significant at the .001 level
1
Fixed effects that significantly improved the model where was p<.05 during likelihood ratio tests
2
Model assumes literal condition as the baseline across conditions
Note. All continuous fixed effects are standardized, with the exception of Trial
Noun FFD. The optimal model for Noun FFD included fixed effects of Condition (Idiom
vs. Literal), Familiarity, and Reading Proficiency. There was a significant effect of Condition in
that nouns at the ends of idioms received shorter first fixation durations than nouns at the ends of
literal phrases (-12 ms difference between Idiom and Literal; t = -2.68). There was also a
significant effect of Familiarity in that nouns received shorter first fixation durations as
familiarity increased (-13 ms between high and low familiarity; t = -3.23), although this did not
interact with Condition.
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
17
With respect to our control variables, as Reading Proficiency increased (and thus, total
reading time for filler sentence decreased), nouns received shorter first fixation durations (t =
3.05).
Noun GD. The optimal model for Noun GD included fixed effects of Condition (Idiom
vs. Literal), Familiarity, Decomposability, Reading Proficiency, and the interaction between
Condition and Decomposability. There was a significant effect of Condition in that nouns at the
end of idioms received shorter gaze durations than nouns at the end of literal phrases (-16 ms
difference between Idiom and Literal; t = -3.20). There was also a significant effect of
Familiarity in that all nouns, irrespective of Condition, received shorter gaze durations as
familiarity increased (-18 ms difference between high and low familiarity; t = -2.51). There was
a significant interaction between Condition and Decomposability in that increased
decomposability shortened gaze duration for the idiom condition but not for the literal condition
(Idiom: -26 ms between high and low decomposability, Literal: -4 ms between high and low
decomposability; t = -2.19). Figure 1 depicts this interaction.
With respect to our control variables, again, nouns received shorter gaze durations as
Reading Proficiency increased (t = 5.24).
Disambiguating Region and Subsequent Idiom Effects
I constructed LME models with Disambiguating FPGD, Idiom TRT, and Idiom
Regressions as the dependent variables, and subject and item as random factors. The most
complex models included the interaction between our primary predictor variables; Condition (IdId, Id-Lit, Lit-Lit), Familiarity, and Decomposability. I again included Trial, Literal Plausibility,
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
18
Figure 1. Noun Gaze Duration as a Function of Decomposability for the Idiom and Literal
Conditions in Native Language Readers
Reading Proficiency, and Character Length as control predictors. However, to control for
character length in the Disambiguating FPGD model, I examined FPGD in milliseconds per
character rather than raw values. I did this only for Disambiguating FPGD because it was the
only target region in which length varied by more than three characters between conditions for a
given item. For all models, the Lit-Lit condition was treated as the control condition, and thus
was mapped to the intercept. For significant effects, I report differences in means derived from
Table 4 and t-values derived from Table 6. For control variables, I report only t-values for
significant effects derived from the optimal LME models, summarized in Table 6
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
19
Table 6.
Effect Size, Standard Error, and t-Values for Fixed Effects and Variances for Random Effects Derived From Optimal LMER Models for the Dependent
Variables Disambiguating Region First Pass Gaze Duration, Idiom Region Total Reading Time, and Idiom Region Regressions for Native English
Speakers in Experiment 1
Disambiguating Region
First Pass Gaze Duration
b
SE
t-value
Idiom Region
Total Reading Time
Regressions
b
SE
t-value
b
SE
z-value
Fixed effects1
Primary Predictors
Condition (Lit-Lit, Id-Id)2
0.76 0.64
1.20
-7.64 17.48
-0.44
Condition (Lit-Lit, Id-Lit)2
1.90 0.63
3.02**
-35.94 17.43
-2.06*
Familiarity
0.13 0.54
0.25
0.44 15.25
0.03
Decomposability
-0.43 0.54
-0.79
Condition (Id-Id)*Familiarity
-1.26 0.72
-1.74
-70.31 17.66 -3.98***
Condition (Id-Lit)*Familiarity
1.82 0.71
2.57*
-40.43 17.45
-2.32*
Condition (Id-Id)*Decomposability
0.29 0.71
0.41
Condition (Id-Lit)*Decomposability
-1.36 0.71
-1.93*1
Familiarity*Decomposability
Condition (Id-Id)*Familiarity*Decomposability
Condition (Id-Lit)*Familiarity*Decomposability
Control Predictors
Trial
-0.04 0.01
-2.44*
-1.02 0.41
-2.46*
Literal Plausibility
-0.75 0.31
-2.44*
-24.27 11.38
-2.14*
Reading Proficiency
7.54 0.79
9.55***
180.59 21.16 8.53***
Character Length
58.04 11.30 5.14***
(Intercept)
35.30 1.00 35.25***
774.84 28.03 27.64***
Random Effects
Variance
Variance
Subject
20.20
14384.10
Item
1.64
4540.60
Residual
129.98
106727.70
* Significant at the .05 level
** Significant at the .01 level *** Significant at the .001 level *1 p = 0.53
1
Fixed effects that significantly improved the model where was p<.05 during likelihood ratio tests
2
Model assumes literal condition as the baseline across conditions
Note. All continuous fixed effects are standardized, with the exception of Trial
0.18
-0.04
0.07
-0.44
-0.22
-
0.13
0.13
0.09
0.13
0.13
-
1.45
-0.35
0.70
-3.47***
-1.72
-
0.44 0.13 3.51***
-1.16 0.15 -7.76***
Variance
0.47
0.05
n/a
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
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Disambiguating Region FPGD. The optimal model for Disambiguating FPGD included
fixed effects of Condition (Id-Id vs. Lit-Lit & Id-Lit vs. Lit-Lit), Familiarity, Decomposability,
Trial, Literal Plausibility, Reading Proficiency, the interaction between Condition and
Familiarity, and the interaction between Condition and Decomposability. There were no
significant effects or interactions involving the Id-Id vs. Lit-Lit contrast. However, for the Id-Lit
vs. Lit-Lit contrast, there was a significant effect of Condition in that first pass gaze durations for
disambiguating regions in the Id-Lit condition were longer than first pass gaze durations in the
Lit-Lit condition (1.9 ms/character difference between Id-Lit and Lit-Lit; t = 3.02). There was
also a significant interaction between Condition and Familiarity, in that increased familiarity
slowed first pass gaze durations in the Id-Lit condition compared to increases in familiarity in the
Lit-Lit condition (Id-Lit: 0.7 ms/character difference between high and low familiarity, Lit-Lit:
0.1 ms/character difference between high and low familiarity; t = 2.57). Finally, there was a
significant interaction between Condition and Decomposability in that increased
decomposability facilitated reading for the Id-Lit condition compared to the Lit-Lit condition (IdLit: -2.5 ms/character difference between high and low decomposability, Lit-Lit: -0.4
ms/character difference between high and low decomposability; t = -1.93). All significant
interactions are depicted in Figure 2.
With respect to our control variables, first pass gaze durations for disambiguating regions
were shorter for increases in Trial (t = -2.44), Literal Plausibility (t = -2.44), and Reading
Proficiency (t = 9.55).
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
21
Figure 2. Disambiguating Region First Pass Gaze Duration as a Function of Familiarity and
Decomposability for the Id-Id, Id-Lit, and Lit-Lit Conditions in Native Language Readers
Idiom Region TRT. The optimal model for Idiom TRT included fixed effects of
Condition, Familiarity, Trial, Literal Plausibility, Reading Proficiency, Character Length, and the
interaction between Condition and Familiarity. For the Id-Lit vs. Lit-Lit contrast, there was a
significant effect of Condition in that total reading times for idioms in the Id-Lit condition were
shorter than total reading times for literal phrases in the Lit-Lit condition (-31 ms difference
between Id-Lit and Lit-Lit; t = -2.06). For the Id-Id vs. Lit-Lit contrast, there was a significant
interaction between Condition and Familiarity in that increased familiarity was more facilitative
in the Id-Id condition than in the Lit-Lit condition (Id-Id: -148 ms difference between high and
low familiarity, Lit-Lit: -39 ms difference between high and low familiarity; t = -3.98). For the
Id-Lit vs. Lit-Lit contrast, the interaction between Condition and Familiarity was also significant
in that increased familiarity was more facilitative in the Id-Lit condition than in the Lit-Lit
condition (Id-Lit: -100 ms difference between high and low familiarity, Lit-Lit: -39 ms
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
22
difference between high and low familiarity; t = -2.32). Figure 3 depicts the interactions
between Condition and Familiarity.
With respect to our control variables, total reading times for idioms and literal phrases
were shorter for increases in Trial (t = -2.46), Literal Plausibility (t = -2.14), and Reading
Proficiency (t = 8.53). As well, increased Character Length yielded longer total reading times (t
= 5.14).
Figure 3. Idiom Region Total Reading Time as a Function of Familiarity for the Id-Id, Id-Lit,
and Lit-Lit Conditions in Native Language Readers
Idiom Regressions. The optimal model for Idiom Regressions included fixed effects of
Condition, Familiarity, Reading Proficiency, and the interaction between Condition and
Familiarity. For the Id-Id vs. Lit-Lit contrast, there was a significant interaction between
Condition and Familiarity in that increases in familiarity in the Id-Id condition resulted in fewer
idiom regressions, as compared to increases in familiarity in the Lit-Lit condition (Id-Id: 12.80% difference between high and low familiarity, Lit-Lit: 3.20% difference between high and
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
23
low familiarity; z = -3.47). Figure 4 depicts the interaction between condition (Id-Id vs. Lit-Lit)
and familiarity.
With respect to our control variables, idioms and literal phrases received fewer
regressions as Reading Proficiency increased (i.e., when total reading time decreased) (z = 3.51).
Figure 4. Proportion of Regressions to Idiom Region as a Function of Familiarity for the Id-Id,
Id-Lit, and Lit-Lit Conditions in Native Language Readers
Discussion
Experiment 1 produced several key findings about idiom processing during natural
reading. With respect to first pass reading (first fixation and gaze duration), participants read
phrase-final nouns more quickly when embedded in conventional idiomatic phrases vs. matched
literal phrases. This suggests that native language readers anticipated phrase-final words for
idioms to a greater degree than they did for non-idiomatic sentences, consistent with the view
that people can directly retrieve idioms prior to the phrase-final word. As well, nouns of highly
decomposable idioms were read more quickly than nouns of less decomposable idioms (gaze
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
24
duration only). However, the interpretation of this result must be tempered by what readers did
when they encountered later sentence regions that biased a figurative or literal interpretation of
the idiom. To the extent that increased decomposability led to the on-demand computation of a
figurative meaning, it should also be associated with faster processing of figurative-biased
disambiguating regions, and perhaps even interference for literal-biased disambiguating regions.
To the extent that it did not lead to a figurative interpretation but rather allowed readers to more
easily resolve any phrasal ambiguity occurring at the end of the phrase, one would not expect a
facilitative effect for figurative-biased disambiguating regions. As we will see, the data favor the
second option.
Consider first, the data for sentences where idioms were followed by idiom-biased
contexts (Id-Id) vs. non-idiomatic literal sentences (Lit-Lit). With respect to reading rates of the
disambiguating region, Id-Id sentences were comparable to Lit-Lit sentences, suggesting that
participants read a figurative-biased context after an idiom no differently than what would have
occurred for a non-idiomatic literal sentence. Increased familiarity also yielded significantly
fewer regressions to the idiom region, and significantly shorter total reading times of the idiom
region for Id-Id sentences compared to Lit-Lit sentences. In contrast with familiarity,
decomposability failed to modulate any reading measure for Id-Id sentences relative to Lit-Lit
sentences.
Consider next, the data for sentences where idioms were followed by literal-biased
contexts (Id-Lit) vs. non-idiomatic literal sentences. Reading rates for the disambiguating
regions were significantly shorter for sentences containing idioms than for non-idiomatic literal
sentences, however, idiom facilitation was significantly greater for high vs. low decomposable
idioms. Thus, increased decomposability led to an enhanced (rather than impaired) ability to
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
25
read a literal, non-figurative, context. Increased familiarity was also associated with faster idiom
total reading time.
Taken together, the first pass effects on the noun combined with the later effects starting
at the disambiguating region suggest that people directly retrieve idiomatic configurations during
on-line comprehension, and that direct retrieval leads to comprehension of the figurative
meaning. In contrast, increased decomposability only helped participants to interpret idioms
literally, for example, in the case of the Id-Lit sentences (see also Titone & Connine, 1999).
Thus, the results of Experiment 1 are most consistent with idiom processing models that posit a
time-dependent role for both direct retrieval and compositional processes (see also Titone &
Connine, 1999; Libben & Titone, 2008).
Experiment 2
Experiment 2 extended the results of Experiment 1 by investigating how non-native
language users, specifically French-English bilinguals for whom English is a second language,
read the identical materials under the same conditions as Experiment 1. Second language
research demonstrates that non-native language users, especially those who acquired their L2 as
an adult, experience great difficulty comprehending and producing idioms in a native-like
manner (Conklin & Schmitt, 2008; Nekrasova, 2009; Tabossi, Wolf, & Koterle, 2009; Weinart,
1995; Wood, 2006). For example, Siyanova-Chanturia, Conklin, Schmitt (2011) had native and
non-native English users read paragraphs containing idiomatic expressions or literal phrases
while their eye movements were recorded. They found that participants read L1 idioms
significantly faster than literal phrases, while there was no difference between idioms and literal
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
26
phrases for L2 reading. However, Siyanova-Chanturia et al. did not explicitly examine the effects
of linguistic dimensions on comprehension.
Of relevance here, L2 idiom processing has been show to be particularly affected by
linguistic dimensions such as compositionality and cross-language overlap (Abel, 2003; Irujo,
1993; Laufer, 2000; Steinel, Hulstijn, & Steinel, 2007). Abel showed that non-native English
users were more likely to rate English idioms as semantically decomposable compared to our
prior study of native English users (Titone & Connine, 1994a; see also, Bortfield, 2003).
Presumably, L2 users rely more heavily on compositional processes to interpret idioms
figuratively because they have less overall familiarity with L2 idioms, which precludes direct
retrieval from memory. Interestingly, however, direct retrieval during L2 idiom processing may
still occur to the extent that an L2 idiom has an L1 counterpart. For example, Irujo (1993)
showed that cross-language similarity (the degree to which an idiom existed in multiple
languages) was a better predictor of whether Spanish idioms would be translated into English
than phrasal frequency or decomposability (see also Charteris-Black, 2002; Laufer, 2000).
Thus, Experiment 2 addresses two unresolved questions about idiom processing. First, do
idioms still exhibit the same processing advantage over literal phrases for L2 readers who are
globally less familiar with English idioms? Second, and most importantly, do compositional
processes play a more prominent role during idiom comprehension for L2 users, for whom
familiarity with English idioms is lower and direct retrieval is less likely? Finally, to what extent
does the cross-language similarity of idioms modulate comprehension for L2 users?
Regarding the first question, I predicted that idiom-final nouns would lose their
processing advantage over nouns embedded in non-idiomatic sentences for L2 users, and may
actually incur a processing cost. Regarding the second question, I predicted that increased
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
27
decomposability would exert a significant role in appreciating an idiom's figurative meaning, in
contrast with the findings of Experiment 1 with L1 users. Regarding the final question, I
predicted that L2 idiom processing (for French L1 users) would be easier to the extent that
English idioms overlapped with French idioms (e.g., play with fire and jouer avec le feu).
Method
Participants
Thirty-seven non-native English users from the McGill and Montreal community, whose
first language was French, participated for course credit or compensation of $10/hr. Participants
completed a survey assessing both French and English language history and ability. All
participants reported French as the first acquired language and their dominant language used
daily. They also had normal or corrected-to-normal vision and no self-reported history of speech
or hearing disorders.
Stimuli & Apparatus
The stimuli and apparatus were identical to those used in Experiment 1.
Procedure
The procedure was identical to that used in Experiment 1 except that after the reading
task, participants completed a survey involving the 60 idioms used in the experiment. For each
idiom, participants indicated whether they knew of an equivalent idiom in French. If an
equivalent expression existed, participants wrote the equivalent French expression. From this
procedure, a set of L1/L2 cross-language similarity ratings (L1/L2 Overlap) was amassed, to be
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
28
used as predictors in subsequent analyses. Again, comprehension questions occurred on 20% of
trials, and accuracy across all participants was 86%, indicating that participants were attentive
during the experiment.
Results
The analytic procedure was identical to Experiment 1, except that L1/L2 Overlap ratings
were used rather than L1 Familiarity ratings as a predictor for two important reasons. First,
native English familiarity ratings from Libben and Titone (2008) would be invalid indicators of
idiom familiarity for non-native English users. Second, ratings of L1/L2 Overlap would allow us
to test hypotheses about cross-language idiom processing effects. The L1/L2 Overlap measure is
summarized in Table 2.
Before analysis, 2.7% of total fixations were removed because of track loss or fixation
durations less than 80 ms. Again, an upper cutoff of 4 standard deviations above the mean for
each DV was established. When analyzing Noun FFD and Noun GD, all trials in which the noun
was skipped (n = 528, 23.8% of all Noun FFD and Noun GD trials), or the verb or determiner of
the idiom/literal phrase was not fixated prior to fixating on the noun during the first pass (n = 70,
3.0% of all Noun FFD and Noun GD trials) were excluded. When analyzing Disambiguating
FPGD, Idiom TRT, and Idiom Regression data, I again excluded any trials in which the entire
idiomatic phrase was skipped on the first pass (n = 12, 0.5% of all Disambiguating FPGD, Idiom
TRT, and Idiom Regression trials). Finally, I again removed trials from Disambiguating FPGD
data if the first pass gaze duration was equal to the first fixation duration of the disambiguating
region for that same trial (n = 166, 7.5% of all Disambiguating FPGD trials). Similar to
Experiment 1, subject means and the number of observations for each dependent variable binned
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
29
across high and low L1/L2 Overlap and Decomposability in each condition are presented in
Table 7. These means were included to facilitate comparison to traditional F1 analyses; they do
not reflect the actual LME procedure, in which L1/L2 Overlap and Decomposability were treated
as continuous predictors.
Table 7.
Total Number of Observations, Means, and Standard Deviations Across All Participants for All
Eye Movement Measurements (Noun FFD, Noun GD, Disambiguating FPGD, Idiom TRT, Idiom
Regressions) of Non-native Language Readers In Each Condition (Idiom, Literal, Id-Id, Id-Lit,
Lit-Lit) for High and Low Levels of L1/L2 Overlap and Decomposability for Non-Native English
Speakers in Experiment 2
Eye-Movement Measure
1
Condition
n
Idiom
1097
Literal
516
1613
All
Idiom
1093
Noun GD1
Literal
517
1610
All
681
Disambiguating FPGD2 Id-Id
Id-Lit
673
Lit-Lit
681
2035
All
Id-Id
730
Idiom TRT1
Id-Lit
729
Lit-Lit
732
2191
All
Id-Id
735
Idiom Regressions
Id-Lit
735
Lit-Lit
735
2205
All
1
Values presented in milliseconds
2
Values presented in milliseconds per character
Note. Standard deviations are listed in parentheses
Noun FFD
Condition
Mean
249 (85)
239 (79)
246 (84)
271 (107)
266 (108)
270 (107)
41.2 (15)
41.5 (16)
41.4 (15)
41.4 (15)
874 (460)
856 (447)
825 (411)
852 (440)
40.00%
36.90%
37.30%
38.00%
L1/L2 Overlap
Decomposability
Low
High
Low
High
252 (88)
230 (70)
245 (83)
274 (111)
264 (111)
271 (111)
40.4 (15)
42.6 (16)
41.1 (15)
41.4 (15)
937 (488)
887 (463)
846 (425)
890 (460)
45.10%
38.30%
40.40%
41.30%
246 (83)
246 (85)
246 (84)
268 (103)
268 (107)
268 (104)
41.9 (16)
40.6 (15)
41.5 (14)
41.4 (15)
819 (426)
829 (430)
807 (398)
818 (418)
35.50%
35.60%
34.50%
35.20%
248 (87)
239 (79)
245 (84)
275 (114)
272 (112)
274 (113)
41.0 (16)
42.5 (17)
42.3 (15)
42.0 (16)
930 (481)
884 (468)
821 (392)
878 (451)
45.00%
40.10%
37.50%
40.90%
250 (84)
238 (79)
246 (83)
267 (100)
261 (104)
265 (101)
41.5 (15)
40.5 (14)
40.4 (14)
40.8 (15)
818 (430)
828 (422)
830 (429)
825 (427)
35.10%
33.50%
37.00%
35.20%
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
30
First Pass Effects on Phrase-final Nouns
I constructed initial LME models identical to those used in Experiment 1, with the
exception that L1/L2 Overlap replaced Familiarity as a primary predictor. For significant effects,
I report differences in means derived from Table 7 and t-values derived from Table 8. For
control predictor variables, I report only t-values for significant effects derived from optimal
LME models, summarized in Table 8.
Table 8.
Effect Size, Standard Error, and t-Values for Fixed Effects and Variances for Random Effects
Derived From Optimal LMER Models for the Dependent Variables Noun Region First Fixation
Duration and Noun Region Gaze Duration for Non-Native English Speakers in Experiment 2
Noun Region
First Fixation Duration
Gaze Duration
b
SE
t-value
b
SE
t-value
Fixed effects1
Primary Variables
Condition (Literal, Idiom)2
9.42 4.09
2.30*
L1/L2 Overlap
5.23 3.6
1.45
Decomposability
Condition*L1/L2 Overlap
-10.19 4.12
-2.47*
Condition*Decomposability
L1/L2 Overlap*Decomposability
Condition*L1/L2 Overlap*Decomposability
Control Variables
Trial
Literal Plausibility
-6.05 2.21
-2.74**
-11.65
3.55
-3.28**
Reading Proficiency
16.39 5.18
3.17**
26.58
5.57
4.77***
Character Length
10.69
3.57
2.99**
(Intercept)
239.51 5.94 40.30***
268.95
6.08 44.21***
Random Effects
Variance
Variance
Subject
839.56
913.28
Item
70.21
374.27
Residual
5791.20
9468.48
* Significant at the .05 level
** Significant at the .01 level *** Significant at the .001 level
1
Fixed effects that significantly improved the model where was p<.05 during likelihood ratio tests
2
Model assumes literal condition as the baseline across conditions
Note. All continuous fixed effects are standardized, with the exception of Trial
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
31
Noun FFD. The optimal model for Noun FFD included Condition (Idiom vs. Literal),
L1/L2 Overlap, Literal Plausibility, Reading Proficiency, and the interaction between Condition
and L2 Overlap. There was a significant effect of Condition in that nouns at the ends of idioms
received longer first fixation durations than nouns at the ends of literal phrases (10 ms difference
between Idiom and Literal; t = 2.03). There was a significant interaction between Condition and
L1/L2 Overlap, in that increased L1/L2 Overlap facilitated first fixation durations in the idiom
condition more than it did in the literal condition (Idiom: -6 ms between high and low L1/L2
Overlap, Literal: 16 ms between high and low L1/L2 Overlap; t = -2.47). The interaction
between Condition and L1/L2 Overlap is depicted in Figure 5.
With respect to our control predictors, first fixation durations were shorter as Literal
Plausibility increased (t = -2.74) and as Reading Proficiency increased (t = 3.17).
Figure 5. Noun First Fixation Duration as a Function of L1/L2 Overlap for the Idiom and Literal
Conditions in Non-Native Language Readers
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
32
Noun GD. The optimal model for Noun GD included fixed effects of Literal Plausibility,
Reading Proficiency, and Character Length. Gaze durations for nouns were shorter as Literal
Plausibility (t = -3.28) and Reading Proficiency (t = 4.77) increased, and as Character Length
increased (t = 2.99).
Disambiguating Region and Subsequent Idiom Effects
I again constructed LME models identical to those used in Experiment 1 except that
Familiarity was replaced with L1/L2 Overlap. Again, for significant effects, I report differences
in means derived from Table 7 and t-values derived from Table 9. For control predictor
variables, I report only t-values for significant effects, summarized in Table 9.
Disambiguating Region FPGD. The optimal model for Disambiguating FPGD included
only the fixed effect of Reading Proficiency. Disambiguating regions received shorter first pass
gaze durations as reading proficiency increased (t = 3.97).
Idiom Region TRT. The optimal model for Idiom TRT included fixed effects of
Condition, Decomposability, Trial, Literal Plausibility, Reading Proficiency, Character Length,
and the interaction between Condition and Decomposability. The Id-Lit vs. Lit-Lit contrast was
not significant alone or in any interaction. However, for the Id-Id vs. Lit-Lit contrast, total
reading times for idioms in the Id-Id condition were longer than those for literal phrases in the
Lit-Lit condition (49 ms difference; t = 2.49). There was also a significant interaction between
Condition and Decomposability in that increased decomposability was more facilitative in the IdId condition than in the Lit-Lit condition (Id-Id: -112 ms difference between high and low
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
33
Table 9.
Effect Size, Standard Error, and t-Values for Fixed Effects and Variances for Random Effects Derived From Optimal LMER Models for the Dependent
Variables Disambiguating Region First Pass Gaze Duration, Idiom Region Total Reading Time, and Idiom Region Regressions for Non-Native
English Speakers in Experiment 2
Disambiguating Region
First Pass Gaze Duration
b
SE
t-value
Idiom Region
Total Reading Time
b
SE
t-value
b
Fixed effects1
Primary Variables
Condition (Lit-Lit Id-Id)2
47.07
2
Condition (Lit-Lit Id-Lit)
30.87
L1/L2 Overlap
Decomposability
6.14
Condition (Id-Id)*L1/L2 Overlap
Condition (Id-Lit)*L1/L2 Overlap
Condition (Id-Id)*Decomposability
-66.19
Condition (Id-Lit)*Decomposability
-26.09
L1/L2 Overlap*Decomposability
Condition (Id-Id)*L1/L2 Overlap*Decomposability
Condition (Id-Lit)*L1/L2 Overlap*Decomposability
Control Variables
Trial
-1.88
Literal Plausibility
-32.14
Reading Proficiency
8.34 0.87
9.56***
208.21
Character Length
69.23
(Intercept)
41.39 0.91 45.69***
884.17
Random Effects
Variance
Subject
25.81
Item
3.39
Residual
134.06
* Significant at the .05 level
** Significant at the .01 level *** Significant at the .001 level
1
Fixed effects that significantly improved the model where was p<.05 during likelihood ratio tests
2
Model assumes literal condition as the baseline across conditions
Note. All continuous fixed effects are standardized with the exception of Trial
18.88
18.89
15.97
18.91
18.88
-
2.49*
1.63
0.38
-3.50***
-1.38
-
0.45 -4.19***
11.82
-2.72**
17.45 11.93***
11.66
5.94***
26.34 33.57***
Variance
9136.20
4659.50
130143.70
0.14
-0.02
-0.15
0.01
-0.33
-0.07
-
Regressions
SE
z-value
0.12
0.17
0.06
0.09
0.12
0.12
-
1.17
-0.15
-2.32*
0.09
-2.82**
-0.63
-
0.56 0.14
3.97***
-0.65 0.16
-4.15***
Variance
0.62
0.05
n/a
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
34
decomposability, Lit-Lit: 9 ms difference between high and low decomposability; t = -3.50). The
interaction between Condition (Id-Id vs. Lit-Lit) and Decomposability is depicted in Figure 6.
With respect to our control variables, total reading times for idioms and literal phrases
were shorter as Trial (t = -4.19), Literal Plausibility (t = -2.72), and Reading Proficiency (t =
11.93) increased, and as Character Length decreased (t = 5.94).
Figure 6. Idiom Region Total Reading Time as a Function of Decomposability for the Id-Id, IdLit, and Lit-Lit Conditions in Non-Native Language Readers
Idiom Regressions. The optimal model for Idiom Regressions included fixed effects of
Condition, L1/L2 Overlap, Decomposability, Reading Proficiency, and the interaction between
Condition and Decomposability. There was a significant effect of L1/L2 Overlap in that idioms
and literal phrases were regressed into less often as L1/L2 Overlap increased (-6.10% difference
between high and low L1/L2 Overlap; z = -2.32). For the Id-Id vs. Lit-Lit contrast, there was a
significant interaction between Condition and Decomposability in that increases in
decomposability in the Id-Id condition resulted in fewer idiom regressions than that found for the
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
35
Lit-Lit condition (Id-Id: -9.90% difference between high and low familiarity, Lit-Lit: 0.05%
difference between high and low decomposability; z = -2.82). The Condition and
Decomposability interaction is depicted in Figure 7.
With respect to our control predictors, as Reading Proficiency increased, idioms and
literal phrases received fewer regressions (z = 3.97).
Figure 7. Idiom Region Total Reading Time as a Function of Decomposability for the Id-Id, IdLit, and Lit-Lit Conditions in Non-Native Language Readers
Discussion
Experiment 2 produced several key findings regarding L2 idiom comprehension. First, in
contrast with native English users (Experiment 1), non-native English users read idiom-final
nouns more slowly than nouns occurring at the ends of literal phrases. This suggests that L2
readers did not directly retrieve the phrase-final words of English idioms, but rather they
experienced comprehension difficulty when idiom-final nouns were encountered. However, the
costs associated with idiom-final nouns were significantly modulated by whether the idiom in
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
36
question also existed in French, their L1. In particular, phrase-final nouns for uniquely English
idioms were read more slowly than phrase-final nouns of literal sentences, whereas phrase-final
nouns for English idioms that also existed in French were read more quickly than phrase-final
nouns of literal sentences. Thus, similar to prior work for idioms (e.g., Irujo, 1993), and also for
single words (Duyck, van Assche, Drieghe, Hartsuiker, 2007; Libben & Titone, 2009; Van
Assche et al., 2011), idioms that have cross-language similarity are easier for readers to
comprehend in their L2.
A second important finding was that L2 users had difficulty processing figurative biased
contexts when they encountered the disambiguating region. That is, L2 users spent more total
time reading idiomatic expressions than literal phrases when the idioms were followed by
figurative contexts. However, difficulty processing figurative-biased contexts was mediated by
the decomposability of the idioms. As idioms increased in decomposability, L2 users made fewer
regressions and spent less total time reading idioms after reading figurative-biased contexts.
Thus, unlike Experiment 1, where increased decomposability facilitated comprehension of a
literal interpretation of idioms, increased decomposability in Experiment 2 facilitated
comprehension of a figurative interpretation for L2 readers. Presumably this is because nonnative language users are less familiar with idioms in their L2, and are less likely to directly
retrieve them from memory (Abel, 2003; Irujo, 1993; Laufer, 2000; Tabossi, Wolf, & Koterle,
2009). Consequently, they must rely on compositional analyses to lead them towards an
understanding of the idioms’ figurative meaning.
Taken together, the results of Experiment 2 build upon those of Experiment 1, and
provide support for models of idiom comprehension that incorporate both direct retrieval and
compositional processes in the L1, as well as the L2.
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
37
General Discussion
I examined the degree to which L1 and L2 readers directly retrieved or compositionally
constructed the figurative meanings of idioms during natural reading. In two experiments, native
English (Experiment 1) and non-native English (Experiment 2) participants read sentences
containing idioms or matched literal phrases, followed by subsequent contexts that specifically
biased their figurative or literal meanings. In both experiments, several eye movement measures
were analyzed that reflected both early and late stages of comprehension.
In Experiment 1, L1 readers processed idiom-final nouns more easily than literal phrasefinal nouns on the first pass. This early comprehension advantage for idioms over literal phrases
is similar to that reported in previous studies (e.g., Cronk & Schweigert, 1992; Gibbs, 1980,
McGlone, Cacciari, & Glucksberg, 1994; Swinney & Cutler, 1979). While increased familiarity
significantly facilitated reading times for nouns in the L1, the amount of facilitation did not differ
between idioms and their literal counterparts as a function of familiarity. In contrast, increased
decomposability had a facilitative effect on early reading times for idiom-final nouns as
compared to literal phrase-final nouns. This result could have arisen for at least two different
reasons.
One possibility is that increased decomposability facilitates a compositional analysis
leading to a figurative interpretation an idiomatic string, in agreement with the work of Gibbs
and colleagues (e.g., Gibbs, Nayak, & Bolton, & Keppel, 1989). A second possibility is that
increased decomposability leads to reduced phrasal or lexical ambiguity for idioms (see Titone &
Connine, 1999; Colombo 1998). In this view, nondecomposable idioms would be analogous to
homographs that possess semantically distinct meanings, whereas decomposable idioms would
be analogous to polysemous words that possess semantically overlapping meanings. Thus, like
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
38
what has been found for homonyms and polysemous words, nondecomposable idioms may elicit
processing difficulty because people must select between two distinct meanings, whereas
decomposable idioms do not elicit processing difficulty because the directly retrieved figurative
meaning and literal interpretation of the phrase are semantically compatible (see Frazier &
Rayner, 1990; Klepousniotou, Titone, & Romero, 2008, for evidence of easier comprehension
for polysemous vs. homonymous words).
Indeed, the pattern of data for later measures as a function of decomposability and the
particular interpretation instantiated by a sentence context was most consistent with the latter
option. Native English readers processed subsequent figurative-biased portions of Id-Id
sentences no differently than non-idiomatic literal sentences, however, they were less likely to
regress to the idiom region for Id-Id sentences to the extent that an idiom was familiar. In
contrast, increased decomposability exerted no effect on L1 reading for Id-Id sentences. The
increased tendency to regress to earlier portions of the sentence for low familiar idioms was also
reflected in terms of reduced total reading time on the idiom region. Thus, it appears that the
early facilitative effect of decomposability in the L1 was due to the figurative and literal meaning
of idioms being more-or-less polysemous, or phrasally ambiguous for decomposable vs.
nondecomposable idioms (e.g., Titone & Connine, 1999; Colombo, 1998). Accordingly, when
L1 readers directly retrieve idiomatic meanings when first encountering the phrase-final word, if
an idiomatic meaning conflicts with a normal compositional (i.e., literal) analysis of the string,
comprehension will be relatively slow. In contrast, if a directly retrieved figurative meaning is
semantically compatible with a normal compositional (i.e., literal) analysis of the string,
comprehension will be relatively fast.
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
39
The effects of decomposability and familiarity, however, were quite different for Id-Lit
sentences compared to Id-Id sentences. Here, the effect of condition interacted with both
familiarity and decomposability but in opposite ways. Consider first, the effects of familiarity.
Increased familiarity slowed reading times for disambiguating contexts in Id-Lit sentences,
consistent with the view that direct retrieval of idiomatic representations leads to a figurative
interpretation. However, increased familiarity did not increase regressions to the idiom region for
Id-Lit sentences. This pattern contrasts with the effect of familiarity for Id-Id sentences, where
increased familiarity did not affect reading rates for the disambiguating region but did affect
whether people regressed to the idiom from the disambiguating region (i.e., people regressed
significantly more for low familiar idioms). Thus, when an idiom is high familiar, and its
figurative meaning is relatively more dominant than its literal phrasal meaning, readers directly
retrieve its figurative meaning such that a subsequent context that is literally biased is harder but
not impossible to read (i.e., it slows reading but does not cause a regressive eye movement).
This pattern of data suggests that the literal phrasal meaning must be available to some degree,
even for highly familiar idioms (see also Peterson, Burgess, Dell, & Eberhard, 2001). In
contrast, when an idiom is not familiar, and a subsequent context is figuratively biased, reading
is fully disrupted in that regressive eye movements occur. Thus, the relative amount of
figurative vs. literal meaning dominance may not be perfectly symmetrical for high vs. low
familiar idioms. Specifically, the figurative meaning of high familiar idioms does not fully
trump a literal interpretation of the phrase, whereas the literal phrase meaning of low familiar
idioms does fully trump a figurative interpretation of the phrase, presumably because the reader
does not have the figurative meaning represented in memory. Thus, idiom processing may have
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
40
other similarities to how lexically ambiguous words are processed with respect to the effects of
meaning dominance (see Simpson, 1981; Simpson & Burgess, 1985).
Consider next, the effects of decomposability on Id-Lit sentences. To the extent that
decomposability leads to a figurative interpretation, one would expect that literally biased
disambiguating regions of highly decomposable idioms would be more difficult to read, similar
to the effects of increased familiarity. However, this was not the case, and in fact, the reverse
was true. Specifically, increased decomposability facilitated reading times for disambiguating
contexts in Id-Lit sentences. Thus, consistent with the results and conclusions of Titone and
Connine (1999), it appears that decomposability may have more to do with the reanalysis of an
idiom’s interpretation, and in particular, when a figurative meaning must be suppressed to make
way for an intended literal phrasal interpretation. It would not, however, be involved in
generating a figurative interpretation as there was no significant effect of decomposability on
how people read figuratively biased disambiguating regions (i.e., Id-Id sentences).
Although the design of Experiments 1 and 2 were not identical, non-native English L2
readers in Experiment 2 yielded a different overall pattern of effects than native English L1
readers for both early and late measures when reading English idioms. First, regarding early
reading measures, L2 readers demonstrated overall difficulty comprehending idioms vs. literal
sentences, which most likely arose from a lack of familiarity with figurative meanings of
English, L2 idioms (but see Siyanova-Chanturia, Conklin, & Schmitt, 2011). Interestingly,
however, L2 idiom processing was less difficult when L2 idioms possessed L1 translation
equivalents (i.e., the English idiom he broke the ice has the French equivalent il a brisé la glace,
whereas the English idiom she had a lark has no French equivalent), consistent with other L2
learning studies (e.g., Irujo, 1993; Laufer, 2000). This effect is also intriguing when one
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
41
considers the large body of literature showing facilitation for words that overlap in form and
semantics across language (i.e., cognates - words that overlap both orthographically and
semantically between the L1 and L2; see Dijkstra et al., 2010; Duyck et al., 2007; Libben &
Titone, 2009; Schwartz & Kroll, 2006; Titone, Libben, Mercier, Whitford, & Pivneva, in press).
At the word level, cognate facilitation presumably arises from convergent lexical activation
across the L1 and L2, given that bilingual language processing is overwhelmingly non-selective
in nature (De Groot, 2011; Dijkstra et al., 2010). Our data suggest the same is true for idioms.
However, the remarkable difference between word and “phrasal” cognates is that for phrases,
component words may not be identical across languages, although their phrasal relation to each
other may be highly similar.
Regarding late-stage reading measures for Experiment 2, L2 readers again had difficulty
computing the figurative meaning of English idioms, consistent with the pattern of early effects,
as well as previous work on L2 idiom comprehension (e.g., Abel, 2003; Wray 2002). However,
in contrast with what was found for L1 readers in Experiment 1, increased decomposability now
facilitated reading for Id-Id sentences. Specifically, L2 readers generated fewer regressions to
the idiom region when reading the disambiguating region of Id-Id sentences, to the extent that an
idiom was decomposable. Similarly, L2 readers spent less total reading time on the idiom region
to the extent that an idiom was decomposable. Thus, unlike L1 readers, for whom the figurative
interpretations of conventional English idioms are generally represented in memory and directly
retrieved during comprehension, L2 readers have no choice but to compositionally construct
figurative interpretations of idioms. Thus, when an idiom is decomposable, and the products of a
compositional analysis are semantically close to a figurative interpretation, comprehension is
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
42
easy. However, when an idiom is nondecomposable, and the products of a compositional
analysis are semantically distant from a figurative interpretation, comprehension is difficult.
Taken together, the results of Experiments 1 and 2 are key for adjudicating between
different models of idiom comprehension. In contrast with the predictions of strict direct
retrieval models (e.g., Swinney & Cutler, 1979; Cacciari & Tabossi, 1988), increased
decomposability does indeed play a role during both L1 and L2 idiom comprehension. For L1
idiom processing, increased decomposability reduces phrasal ambiguity when an idiom is
initially read, and it also helps in reanalyzing an idiom literally should a subsequent context call
for that interpretation. However, in contrast with strict compositional models (Gibbs, Nayak, &
Bolton, & Keppel, 1989), increased decomposability does not directly lead to a figurative
interpretation of idioms during L1 idiom processing, rather figurative interpretations of
conventional idioms appear instead to be directly retrieved from memory. Of note, when the
same idioms are read by L2 readers, for whom English L1 idioms are less known or familiar as a
group, both cross-language overlap, an index of direct retrieval for L2 readers, and increased
decomposability facilitates idiom processing.
Thus, the overall pattern of findings best supports a hybrid or multidetermined model of
comprehension (Titone & Connine, 1999; Libben & Titone, 2008), according to which people
simultaneously use all available information during comprehension (resulting from direct
retrieval and compositional analysis); different kinds of information may be available at different
time-courses; and different classes of information interact over time. Because all sources of
information interact, if the products of direct retrieval are particularly strong or salient, they may
overwhelm and functionally terminate the products of compositional processes. In contrast, if the
products of direct retrieval are weak, as they might be for low familiar idioms, an ongoing
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
43
compositional analysis might instead dominate. Consistent with this view, and the data presented
here, our prior work shows that non-idiomatic literal word meaning activation is reduced for
highly predictable and literally implausible idioms, and that figurative meanings of highly
predictable idioms are retrieved prior to encountering their phrase-final words (Titone &
Connine, 1994b). Conversely, in other work, it was found that increased decomposability
facilitated meaningfulness judgments for unfamiliar idioms but not highly familiar idioms
(Libben & Titone, 2008). Thus, this study and our prior work contribute to the growing body of
results that favor hybrid models of idiom processing such as that proposed by Titone and
Connine (1999), and subsequently by others (Abel, 2003; Caillies and Butcher, 2007; Smolka,
Rabanus, & Rosler, 1997; Sprenger, Levelt, & Kempen, 2006).
An important corollary of the hybrid, or multidetermined approach, is that any factor that
independently modulates direct retrieval or compositional processes should also modulate
figurative meaning generation and integration during comprehension; these include individual
differences among idioms or people. Thus, in this study I used this model to make predictions
about second language learners, and many further untested predictions remain. For example, it is
unclear whether the same pattern of familiarity and compositionality effects on idiom processing
would hold when disambiguating contexts precede idioms during sentence comprehension. Prior
contexts generally facilitate idiom processing (e.g., Fanari, Cacciari, & Tabossi, 2010; Mueller &
Gibbs, 1987; Titone & Connine, 1999), however, it is still unclear whether it does so be aiding
direct retrieval, compositional processing, or both. While the effects of a prior context would
most likely arise from pre-activation of an idiomatic form in memory, it is possible that a prior
context would make the semantic relation between an idiom’s figurative meaning and component
words more salient on the first pass, thus increasing the likelihood that the figurative
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
44
interpretation is partially built compositionally as well as directly retrieved. A prior context that
is figuratively biased might also cause relatively more suppression of a literal phrasal
interpretation than what was found in the present study. These are important issues for further
study, which are more easily characterized by a hybrid model of idiom processing compared to
pure direct retrieval or compositional models.
Another target for future research concerns the nature of the direct retrieval process with
respect to idiom processing. One important issue here concerns what is directly retrieved during
idiom processing. Direct retrieval could involve a linguistic form representation independent of
a phrasal meaning, as well as the meaning-based interpretation linked in memory to a particular
form. This distinction is particularly salient for idioms in that idiom-final words might be easier
to process than phrase-final words for non-idiomatic phrases simply on the basis of high word
co-occurrence for idioms vs. non-idioms, or differences among idioms in their structural
fixedness. Regarding the latter point, classes of idioms other than verb-determiner-noun phrases,
such as verb-particle constructions, are more syntactically promiscuous and may take any
number of nouns as their direct objects (carry out the project, carry the project out) (e.g.,
Jackendoff, 2002, 2003; Konopka & Bock, 2009). Thus, direct retrieval for verb-particle idioms
may also involve provisions about their structural flexibility, which interact with word cooccurrence patterns. Moreover, compositional processes may in fact play more of a role for
these structurally flexible idiomatic forms. Finally, beyond the lexical form level, as seen here,
idiomatic phrases have stored meaning-based interpretations that can be retrieved, and that may
conflict with an ongoing literal (compositional) analysis of the string. Thus, one question is
whether the semantic level of representation for idioms is in fact distinct from the lexical form
level representation. Recent electrophysiological work posits different event related potentials
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
45
for idiom form vs. meaning activation (Vespignani et al., 2010; Molinaro & Carreiras, 2010),
however, differences among idiomatic and non-idiomatic collocations in phrasal ambiguity in
these studies preclude a straightforward interpretation of the ERP effects.
In addition to questions about what is directly retrieved during idiom processing, a
second issue concerns how the direct retrieval process may transpire. One option is that direct
retrieval during idiom processing is a kind of template-matching process where comprehenders
compare an unfolding input to fixed canonical form of a particular idiom in memory. This
approach may be overly rigid, however, and unable to account for data showing that people
readily comprehend and produce idioms outside of their canonical forms (e.g., Gibbs & Nayak,
1989; Gibbs & O’Brien, 1990; McGlone, Cacciari, & Glucksberg, 1994). Moreover, given the
structurally flexibility of many idioms, it is unclear whether it would be possible to identify a
single canonical form or template for a large proportion of idioms, and indeed, perhaps all
idioms. A second option, however, is that direct retrieval is a kind of anticipatory or prediction
process (e.g., Vespignani et al., 2010), where people generate lexical and semantic expectations
about upcoming words as language unfolds. This view has substantial advantages over a rigid
template-matching view, in that it can more easily account for the comprehension of idiom
variants, and it more naturally integrates the processing of idioms with what we do normally to
comprehend all forms of language. These data do not distinguish between these two options, as I
only presented idioms in relatively canonical forms. However, it is possible that future studies of
how the structural characteristics of idioms alter the relative balance of direct retrieval vs.
compositional processing during comprehension would be better suited to this aim.
To conclude, consistent with hybrid or multidetermined models of comprehension (e.g.,
Titone & Connine, 1999; Libben & Titone, 2008), idiom processing appears to arise from both
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
46
direct retrieval and compositional processes, which follow different time-courses for L1 and L2
readers (e.g., Libben & Titone, 2008). For L1 readers, increased familiarity leads to fast direct
retrieval of the figurative meanings, although compositional processes may help for interpreting
an idiom literally (Titone & Connine, 1999). For L2 readers, direct retrieval, via L1 knowledge,
and compositional processes both increase the figurative interpretation of idioms. Whether such
a view extends to all language contexts, to language production, or to all idiomatic forms
remains open questions for future work.
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
47
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Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
55
Appendix
Sentences used in Experiments 1 and 2
Idiom
lost his seat
knew the score
packed his bags
hit the books
got the message
flooded the market
wore the trousers
smelled a rat
Familiarity
Rating
2.7
3.8
4.43
4.73
4.57
2.5
3
3.6
Decomposability
Proportion
L1/L2
Overlap
0.74
0.514
0.76
0.85
0.76
0.95
0.63
0.32
0.3
0.189
0.703
0.027
0.676
0.054
0.486
0.216
Condition
Sentence
Id-Id
Otto lost his seat on the council after he was caught embezzling funds.
Id-Lit
Otto lost his seat at the football game when he got up to get some beer.
Lit-Lit
Otto left his seat unoccupied when he left quickly to use the bathroom.
Id-Id
Vicki knew the score well enough to not ask for an extension on the essay.
Id-Lit
Vicki knew the score because she had been following the playoffs closely.
Lit-Lit
Vicki told the score to the young fans who had just arrived at the game.
Id-Id
Bernie packed his bags when he became disillusioned with the company's ethics.
Id-Lit
Bernie packed his bags when he realized his plane was leaving in half an hour.
Lit-Lit
Bernie emptied his bags as soon as he returned home from the long vacation.
Id-Id
Penelope hit the books only two weeks before the dreaded final examination.
Id-Lit
Penelope hit the books with her hand when she sat down quickly at the desk.
Lit-Lit
Penelope put the books on the shelf when she returned home from the library.
Id-Id
Rona got the message when her friends refused to talk to her after the breakup.
Id-Lit
Rona got the message on the answering machine when she arrived home from school.
Lit-Lit
Rona put the message on the fridge so she wouldn't forget to call her mother.
Id-Id
Rupert flooded the market with his over-abundant soybean crop last year.
Id-Lit
Rupert flooded the market while fixing a leak in the store's plumbing.
Lit-Lit
Rupert entered the market determined to buy only the items on his list.
Id-Id
Cindy wore the trousers in her family in the weeks after her father died.
Id-Lit
Cindy wore the trousers after deciding it was too cold to wear the skirt.
Lit-Lit
Cindy gave the trousers to her son after she was finished hemming them.
Id-Id
Myrna smelled a rat when her coworker wouldn't look her in the eye yesterday.
Id-Lit
Myrna smelled a rat the moment she entered the cluttered and dirty pet store.
Lit-Lit
Myrna trapped a rat in the garage after she saw it eating the bag of birdseed.
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
used his head
cleared the air
smacked her lips
had a lark
passed the buck
covered her tracks
scratched his head
showed her cards
hit a wall
got the picture
4.57
3.23
2.83
1.57
2.83
4.3
3.87
2.93
3.87
4.67
0.9
0.71
0.25
0.1
0.36
0.98
0.67
0.77
0.75
0.74
0.784
0.189
0.162
0.000
0.081
0.459
0.459
0.649
0.667
0.216
56
Id-Id
Ben used his head to outsmart his opponents even though they were stronger.
Id-Lit
Ben used his head to bump the ball straight into the opposing team's net.
Lit-Lit
Ben hurt his head when he sat up too quickly and struck the top bunk bed.
Id-Id
Royce cleared the air by completely explaining why he was late coming home.
Id-Lit
Royce cleared the air by opening the window and turning the exhaust fan on.
Lit-Lit
Royce forced the air into the flat tire before it could deflate itself again.
Id-Id
Alice smacked her lips at the thought of the pay raise she had been promised.
Id-Lit
Alice smacked her lips to feel the texture of the lipstick she had purchased.
Lit-Lit
Alice traced her lips in the mirror as she tried on a new shade of lipstick.
Id-Id
Ruby had a lark when she switched her family's sugar to salt as a joke.
Id-Lit
Ruby had a lark when she was a child but now wanted a parrot instead.
Lit-Lit
Ruby saw a lark at the pet store and thought that it was very beautiful.
Id-Id
Taylor passed the buck when she was accused of losing the major account.
Id-Lit
Taylor passed the buck when her friend didn't have enough cash for lunch.
Lit-Lit
Taylor saved a buck when she brought in her coupon at the grocery store.
Id-Id
Stacey covered her tracks so that she wouldn't be caught embezzling money.
Id-Lit
Stacey covered her tracks so that she couldn't be followed through the snow.
Lit-Lit
Stacey cleared her tracks from the garden once she was finished weeding it.
Id-Id
Niles scratched his head when he could not determine where his dog was hiding.
Id-Lit
Niles scratched his head when he returned from camp covered in mosquito bites.
Lit-Lit
Niles examined his head when he returned from camp covered in mosquito bites.
Id-Id
Norah showed her cards when she invited the handsome man to the wedding party.
Id-Lit
Norah showed her cards to the other poker players to show that she had bluffed.
Lit-Lit
Norah counted her cards to determine who had more points when the game ended.
Id-Id
Marge hit a wall in her renovations when she realized she was out of materials.
Id-Lit
Marge hit a wall while digging her garden too close to the house's foundation.
Lit-Lit
Marge fit a wall in between the gazebo and the path around the garden's pond.
Id-Id
Eric got the picture when his blind date didn't show up after 40 minutes.
Id-Lit
Eric got the picture when his mother finally mailed it to him overnight.
Lit-Lit
Eric put the picture on the mantelpiece as a reminder of his fun vacation.
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
bought the farm
changed her tune
made a bundle
lined his pockets
dropped a bundle
bit the bullet
followed his nose
trimmed his sails
took the veil
dropped a line
2.53
3.8
3.87
2.93
2.47
4.2
3.23
2.03
1.67
4.03
0.05
0.8
0.7
0.16
0.5
0.28
0.5
0.12
0.52
0.31
0.000
0.216
0.054
0.108
0.000
0.135
0.324
0.081
0.162
0.270
57
Id-Id
Harry bought the farm unexpectedly after developing lung cancer late in life.
Id-Lit
Harry bought the farm from his uncle after inheriting a large sum of money.
Lit-Lit
Harry loved the farm and always enjoyed visiting his uncle there on holidays.
Id-Id
Maggie changed her tune and supported the policy when she recognized its benefits.
Id-Lit
Maggie changed her tune to a livelier melody when the audience was unresponsive.
Lit-Lit
Maggie hummed her tune happily as she returned from a successful choir practice.
Id-Id
Hank made a bundle over the summer working full time at the community pool.
Id-Lit
Hank made a bundle out of his towels before stuffing them in his suitcase.
Lit-Lit
Hank gave a bundle of clothes to the Salvation Army at least once a year.
Id-Id
Keith lined his pockets with the money he got for selling the stolen stereos.
Id-Lit
Keith lined his pockets with fleece after he got frostbite on his fingertips.
Lit-Lit
Keith sewed his pockets when he started losing change through several holes.
Id-Id
Jane dropped a bundle when she stayed in a five-star hotel for her vacation.
Id-Lit
Jane dropped a bundle when she tried to carry too much laundry up the stairs.
Lit-Lit
Jane carried a bundle of clothes down the street to the local Laundromat.
Id-Id
Larry bit the bullet and bought diamond earrings for his wife's birthday.
Id-Lit
Larry bit the bullet to verify the quality of the casings on his ammunition.
Lit-Lit
Larry hid the bullet so the police would not find the crucial evidence.
Id-Id
Billy followed his nose when hiring rather than checking applicant references.
Id-Lit
Billy followed his nose to the kitchen where his mother was baking apple pies.
Lit-Lit
Billy splashed his nose with cold water in an effort to relieve the swelling.
Id-Id
Blake trimmed his sails after he started paying for his own tuition fees.
Id-Lit
Blake trimmed his sails in preparation for the local yacht competition.
Lit-Lit
Blake raised the sails in preparation for the local yacht competition.
Id-Id
Rosemary took the veil because she had always wanted to devote her life to God.
Id-Lit
Rosemary took the veil because she didn't want to forget it before the wedding.
Lit-Lit
Rosemary tore the veil accidentally because the gauzy material was too fragile.
Id-Id
Hal dropped a line to his old roommate after remembering it was his birthday.
Id-Lit
Hal dropped a line to see if the fish were biting this early in the season.
Lit-Lit
Hal printed a line in colored ink to find out if the ink cartridge was full.
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
kicked the bucket
held the fort
missed the mark
pulled David's leg
buried the hatchet
faced the music
hedged her bets
blew a fuse
lost the thread
skimmed the cream
2.97
3.23
3.37
4.23
3.7
3.23
2.13
4.03
1.67
1.86
0.17
0.41
0.85
0.15
0.38
0.24
0.55
0.31
0.44
0.3
0.108
0.405
0.250
0.162
0.378
0.243
0.000
0.730
0.514
0.108
58
Id-Id
Mary kicked the bucket after suddenly becoming seriously ill on the weekend.
Id-Lit
Mary kicked the bucket when it was blocked from her view by the chair.
Lit-Lit
Mary tipped the bucket to sprinkle fertilizer into her new flower garden.
Id-Id
Haden held the fort by taking care of his brother while their mom was at work.
Id-Lit
Haden held the fort high above the table while his Lego armies battled below.
Lit-Lit
Haden left the fort because he no longer wanted to work there in the summer.
Id-Id
Steve missed the mark when he claimed the Yankees won a World Series in 1960.
Id-Lit
Steve missed the mark when his shoulder slipped from the weight of the rifle.
Lit-Lit
Steve placed the mark at the place where the runners began the city marathon.
Id-Id
Bailey pulled David's leg because he was great fun to joke around with.
Id-Lit
Bailey pulled David's leg because he was stuck halfway down the slide.
Lit-Lit
Bailey rubbed David's leg to increase blood flow to his frozen feet.
Id-Id
Yvonne and Lucy buried the hatchet after both forgot why they were fighting.
Id-Lit
Yvonne and Lucy buried the hatchet after stealing it from the hardware store.
Lit-Lit
Yvonne and Lucy threw the hatchet at the approaching bear hoping to scare it.
Id-Id
Regan faced the music when her parents caught her returning home after curfew.
Id-Lit
Regan faced the music when she wanted to determine which speaker was loudest.
Lit-Lit
Regan hated the music and stayed out of the house when his brother practiced.
Id-Id
Carol hedged her bets by double majoring in computer science and accounting.
Id-Lit
Carol hedged her bets at the horse races by wagering on all the favorites.
Lit-Lit
Carol changed her bets when she learned that one of the horses hurt its leg.
Id-Id
Sarah blew a fuse when the material she had studied most wasn't on the test.
Id-Lit
Sarah blew a fuse when her bedside lamp had a severe electrical malfunction.
Lit-Lit
Sarah fixed a fuse that always failed when she used the plug beside the sink.
Id-Id
Charlie lost the thread of the story and couldn't grasp its conclusion.
Id-Lit
Charlie lost the thread when he dropped the sewing needle on the floor.
Lit-Lit
Charlie made the thread out of cotton fibers he got at the fabric store.
Id-Id
Heather skimmed the cream by only hiring the top graduating students for the job.
Id-Lit
Heather skimmed the cream by dragging a big spoon through the fresh jug of milk.
Lit-Lit
Heather spilled the cream when she reached across the table for the sugar bowl.
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
cleared the decks
broke the ice
got the sack
spilled the beans
straddled the fence
dropped a bomb
spread the word
turned the tables
showed his teeth
went to town
2.9
4.43
2.77
4.37
2.57
4.1
4.8
4.03
2.7
3.77
0.16
0.26
0.15
0.45
0.27
0.5
0.95
0.44
0.32
0.15
0.054
0.919
0.000
0.162
0.054
0.216
0.486
0.054
0.459
0.162
59
Id-Id
Jeff cleared the decks by finishing his project before undertaking a new one.
Id-Lit
Jeff cleared the decks by sweeping away the leaves before his guests arrived.
Lit-Lit
Jeff cleaned the decks so they would be spotless for his party at the marina.
Id-Id
Bruce broke the ice by quickly introducing himself to everyone at the wedding.
Id-Lit
Bruce broke the ice by driving his snowmobile directly onto the thawing lake.
Lit-Lit
Bruce stored the ice in his cooler so he could bring it to the holiday party.
Id-Id
Derek got the sack after showing up late for work and having a bad attitude.
Id-Lit
Derek got the sack that had been hidden behind boxes in the kitchen pantry.
Lit-Lit
Derek put the sack in the pantry when he was finished peeling the potatoes.
Id-Id
Dolan spilled the beans when he mentioned the surprise party to his friend.
Id-Lit
Dolan spilled the beans when he tried to pour too many into the soup pot.
Lit-Lit
Dolan cooked the beans before he started adding vegetables to the soup pot.
Id-Id
Dolores straddled the fence as she couldn't decide which position to believe.
Id-Lit
Dolores straddled the fence as she climbed over it into her neighbor's yard.
Lit-Lit
Dolores destroyed the fence before building a new one with fresh cedar rails.
Id-Id
Winston dropped a bomb on his parents when he announced his engagement.
Id-Lit
Winston dropped a bomb on the enemy's base as his plane flew overhead.
Lit-Lit
Winston planted a bomb in the enemy's headquarters early that morning.
Id-Id
Bailey spread the word about the party to all her friends by sending an email.
Id-Lit
Bailey spread the word across the top of her poster to use up all the space.
Lit-Lit
Bailey feared the word that her strict father was about to say to her was no.
Id-Id
Jade turned the tables on his opponent by using the new tennis technique.
Id-Lit
Jade turned the tables upside down so that they could be easily dismantled.
Lit-Lit
Jade washed the tables after the customers had left the Thai restaurant.
Id-Id
Pete showed his teeth when he caught the local boys bullying his sister.
Id-Lit
Pete showed his teeth when his mother asked if he had brushed that morning.
Lit-Lit
Pete cleaned his teeth when his mother reminded him for the third time.
Id-Id
Alice went to town on the preparations for her son's elaborate wedding.
Id-Lit
Alice went to town to buy decorations for her son's elaborate wedding.
Lit-Lit
Alice came to town to visit her relatives over the Christmas holidays.
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
missed the bus
bore his cross
lost his shirt
hit the ceiling
father forced her
licked her wounds
paved the way
gave her word
hit the roof
bit her lip
3.97
2.5
3.47
2.97
2.77
2.86
4.2
4.6
3.97
4.03
0.47
0.5
0.56
0.18
0.7
0.45
0.85
0.91
0.16
0.74
0.459
0.162
0.270
0.216
0.514
0.162
0.216
0.703
0.162
0.541
60
Id-Id
Yvette missed the bus when she didn't hand in her application on time.
Id-Lit
Yvette missed the bus when she forgot to set her alarm Monday morning.
Lit-Lit
Yvette drove the bus from the high-school to drop off the students.
Id-Id
Josh bore his cross the entire flight and didn't complain about the snoring man.
Id-Lit
Josh bore his cross down the center aisle of the church during the passion play.
Lit-Lit
Josh lost his cross when he dropped it in the grass on the way home from church.
Id-Id
Brian lost his shirt when his new hobby shop went bankrupt last winter.
Id-Lit
Brian lost his shirt when it blew off the clothesline during the storm.
Lit-Lit
Brian left his shirt at the Laundromat when he had to leave in a hurry.
Id-Id
Sally hit the ceiling when the course she'd prepared for was cancelled.
Id-Lit
Sally hit the ceiling when she tried to jump on her trampoline indoors.
Lit-Lit
Sally lit the ceiling on fire when the Christmas tree lights overheated.
Id-Id
Kaitlyn's father forced her hand by telling her where to attend high school.
Id-Lit
Kaitlyn's father forced her hand away from the stove before she was burned.
Lit-Lit
Kaitlyn's father pushed her hand away from the stove before she was burned.
Id-Id
Rose licked her wounds after being defeated badly in the tennis championship.
Id-Lit
Rose licked her wounds since there was no clean water available to wash them.
Lit-Lit
Rose washed her wounds with peroxide so that they would not become infected.
Id-Id
Jerry paved the way for his son by setting up a trust fund for the university.
Id-Lit
Jerry paved the way for his son so he wouldn't trip over the gravel again.
Lit-Lit
Jerry found the way to the top of the mountain without the help of a guide.
Id-Id
Vicki gave her word to Jack that she would help him paint his room the next day.
Id-Lit
Vicki gave her word to Jack when he started finding the scrabble game difficult.
Lit-Lit
Vicki felt her word was too strong for the context and regretted saying it.
Id-Id
Sam hit the roof when he discovered someone had taken his new golf clubs.
Id-Lit
Sam hit the roof to check the condition of the old and crumbling shingles.
Lit-Lit
Sam cut the roof into pieces with his saw after he dismantled the old barn.
Id-Id
Roxy bit her lip and tried to keep the plans for the surprise party a secret.
Id-Lit
Roxy bit her lip as she rushed through breakfast in a hurry to get to school.
Lit-Lit
Roxy cut her lip on a branch when she climbed too high up the cedar tree.
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
got the axe
pulled the plug
3.37
3.4
0.19
0.69
0.027
0.216
61
Id-Id
Ramona got the axe after being repeatedly warned not to be late for work.
Id-Lit
Ramona got the axe after being asked to help chop kindling for the fire.
Lit-Lit
Ramona had the axe that she borrowed from her neighbor to chop fire wood.
Id-Id
Dara pulled the plug on her brother's money when she caught him gambling.
Id-Lit
Dara pulled the plug of the bathtub when the water began to get very cold.
Lit-Lit
Dara removed the plug from the bathtub when the water began to get cold.
Running Head: FIRST AND SECOND LANGUAGE IDIOM PROCESSING
62