The multidetermined nature of idiom processing - Springer · such as familiarit y. In contrast,...

Idioms are classically defined as phrases whose figura-tive meanings are distinct from their component words,for example, kick the bucket, spill the beans, be on cloud nine, and others (Abel, 2003; Cacciari & Glucksberg, 1991; Gibbs, Nayak, & Cutting, 1989; Nunberg, 1978;Titone & Connine, 1999). In the psycholinguistic litera-ture, three classes of theories have been proposed to ex-pplain how idioms are represented and processed duringcomprehension. One class of theory holds that idioms arerepresented as long words (Bobrow & Bell, 1973; Swin-ney & Cutler, 1979), thus adhering to the classic noncom-ppositional view. A second class of theory holds that anlidiom’s internal semantic structure is necessary for under-standing idiomatic meaning, thus taking a compositionalapproach (Abel, 2003; Gibbs, Nayak, & Cutting, 1989;Hamblin & Gibbs, 1999; Nunberg, 1978). A third classof theory adopts a hybrid approach that incorporates fea-tures of both noncompositional and compositional theo-ries (Cacciari & Tabossi, 1988; Titone & Connine, 1999). Accordingly, idioms have unitary representations that may bbe directly retrieved when idioms are familiar or predict-able, but they may also be compositionally analyzed dur-ing comprehension, especially in the case of unfamiliar or unpredictable idioms. The present study tests predictionsof these different views of idiom processing using severaloffline and online comprehension measures.

Compositional theories of idiom processing have gained much ground in recent years (e.g., Gibbs & Nayak, 1989;Gibbs, Nayak, Bolton, & Keppel, 1989; Gibbs, Nayak, &

tCutting, 1989; Hamblin & Gibbs, 1999). The notion thatd idioms are compositionally analyzed was first introduced

m by Nunberg (1978), who proposed a method of idiomclassification that emphasized the interaction betweenan idiom’s literal and figurative meanings (see also Cac-ciari & Glucksberg, 1991; Geeraerts, 1995; Gibbs, Nayak,

& Cutting, 1989; Nunberg, Sag, & Wasow, 1994). Thisclassification scheme asserts that idioms vary in their se-mantic decomposability, and that there are different types

fof decomposability relations. For example, the words of normally decomposable idioms bear a direct relation to

the figurative meaning (e.g., question in pop the questionrefers to a marriage proposal), whereas the words of abnor-mally decomposable idioms bear a metaphorical relationto the figurative meaning (e.g., maker inr rmeet your makermetaphorically refers to a deity). Thus, decomposability is defined as the extent to which the words independentlycontribute to the figurative interpretation.

nWith respect to comprehension, the main predictionr of compositional models is that an idiom will be easier

to comprehend if its words are related, in any way, to itsfigurative meaning. Furthermore, this advantage for de-

d composable idioms over nondecomposable idioms shouldoccur at the earliest stages of comprehension (i.e., as soon

as the figurative meaning accrues activation). Accordingly,the comprehension of decomposable idioms such as popthe question or meet your maker twould be faster than thatrof nondecomposable idioms such as kick the bucket. Thiswould occur because the idioms’ words are semantically

1103 Copyright 2008 Psychonomic Society, Inc.

The multidetermined nature of idiom processing

MAYA R. LA IBBEN AND DEBRARR A. TITONEMcGill University, Montreal, Canada

Models of idiom comprehension differ in their predictions concerning compositionality: Some claim that idi-omatic meaning is the result of compositional analysis initiated at the earliest stages of comprehension, whereas others claim that compositional analysis occurs only at late stages, subsequent to direct retrieval—especially

ffor idioms that are highly familiar. We evaluated these alternatives in four experiments by using a variety of online and offline comprehension measures. In Experiment 1, we analyzed the normative characteristics of 219 idioms with respect to these predictions. Dimensions of interest included several measures of decomposability, familiarity, and word frequency of the idioms’ verbs and nouns. In Experiments 2 through 4, we determined how

dthese dimensions relate to several online measures of idiom comprehension. High familiarity was associated dwith good comprehension across all experiments; however, facilitative effects of decomposability were found f only for tasks that required an overt semantic judgment. Word frequency, but not semantic decomposability offthe idiom-initial verb, was associated with comprehension for some measures. These data support a model of fidiom comprehension, according to which figurative meaning arises from the time-dependent availability of multiple linguistic constraints, and in which decomposability plays a limited role in the earliest stages of idiom comprehension. Normative data for 210 of the idiomatic phrases may be downloaded from the Psychonomic

y p y gSociety Web archive at www.psychonomic.org/archive/.

Memory & Cognition2008, 36 (6), 1103-1121doi: 10.3758/MC.36.6.1103

D. A. Titone, [email protected]

11041104 LIBBENIBBEN ANDAND TITONEONE

& Connine, 1994b) and do not affect comprehension (Ta-bossi et al., 2008). Other studies find a role of decompos-ability that is limited in scope. For example, Titone and Connine (1999) tested whether decomposability affected comprehension in an eye movement study of reading.They presented sentences containing idioms to partici-pants and monitored their eye movements as the partici-pants read normally, thus studying first-pass effects onidiom processing in a highly natural task situation. They found no difference in reading speed between decompos-able and nondecomposable idioms that were embedded inrelatively unbiased linguistic contexts. However, when aprior context biased a dominant interpretation of an idiom(either figurative or literal), Titone and Connine (1999)found that decomposable idioms were read more quickly than were nondecomposable idioms. Thus, semantic de-composability facilitated idiom processing at a later stage of comprehension—that is, when a specific phrasal mean-ing needed to be integrated into a specific context. Fi-nally, a recent sentence-priming study showed enhanced priming for decomposable idioms that emerged quickly during comprehension (Caillies & Butcher, 2007). In that study, sentence primes were presented visually and in their entirety for relatively long durations; thus, it is unclear whether these results reflected the first-pass products of comprehension (given that portions of the sentences could have been reread), and targets may have been seen quite late in the comprehension process.

Another consideration when reviewing previous stud-ies involves the use of global measures of idiom decom-posability that are based on assessments of idiomatic se-quences as a whole. Global measures of decomposabilitymay not be sensitive enough to capture decomposabilityeffects on comprehension. A recent study by Hamblin and Gibbs (1999) addressed this concern by emphasizing the individual parts of the idiom—in particular, the constitu-ent verb of semantically nondecomposable idioms. In a series of ratings experiments, Hamblin and Gibbs found that when participants encountered phrases such as kick the bucket, in which the verb (kick) is associated with a kkfast action, they consistently reported the figurative mean-ing to be better captured by a phrase that was semantically consistent with the idiom’s main verb (e.g., to die suddenlyvs. to die slowly; see also McGinnis, 2004, for a linguistic treatment of this issue). In addition, participants were morelikely to rate idioms as belonging to discourse contexts thatendorsed the preferred interpretation of the verb. That is, idioms received higher appropriateness ratings when they were presented within the context of a story that was con-sistent with the semantics of the idiom’s main verb (e.g., a story about someone dying quickly vs. one about someone dying slowly). These results are intriguing, especially giventhat only globally nondecomposable idioms were studied.

A final area of interest is that idioms differ with re-spect to the frequency of their component words. Word frequency effects on idiom retrieval have received little at-tention, although they have been of great importance in other areas of psycholinguistics, in which there is similar tension between direct retrieval and compositional pro-

consistent with a figurative interpretation for decompos-able idioms but inconsistent with a figurative interpreta-tion for nondecomposable idioms. However, it is also possible that decomposable idioms may not differ fromnondecomposable idioms with respect to comprehension, or that nondecomposable idioms might actually be easier to comprehend. These two options would be inconsistentwith compositional models. Indeed, to the extent that non-decomposable idioms such as kick the bucket are easier tto understand than decomposable idioms such as pop the question, one may infer that direct retrieval of a completeidiomatic meaning is faster than a full compositional anal-ysis of the string that generates the idiomatic meaning.

Other models assert that idioms undergo both simul-taneous compositional analysis and direct retrieval when their component words constitute a familiar and recog-nizable configuration (Cacciari & Tabossi, 1988; Titone& Connine, 1999), although the configuration model(Cacciari & Tabossi, 1988) does not make specific claimsabout the effects of decomposability. Rather, Cacciari and Tabossi (1988; see also Tabossi, Fanari, & Wolf, 2005, 2008) emphasize the dimension of predictability (i.e., the extent to which an idiom is completed idiomaticallywhen its final word is omitted), which gates access to the idiomatic configuration, independently of other variablessuch as familiarity. In contrast, others (Titone & Connine, 1994b) view predictability effects as being partially de-termined by other variables such as subjective familiarity. For example, Titone and Connine (1994b) found a strong positive relationship between predictability and familiarity ratings for a relatively large set of English idioms. Another difference between the two approaches is that accordingto the hybrid view, facilitative effects of semantic decom-posability should be modulated by familiarity. Thus, when comprehenders encounter highly familiar idiomatic se-quences, idiomatic meanings will be directly retrieved and integrated into the ongoing discourse representation (seealso Giora, 1997), irrespective of whether the componentwords bear any relation to the figurative meaning. In con-trast, when idiomatic sequences are not highly familiar or predictable, direct retrieval prior to phrase offset will be more difficult, and comprehension will be dependenton ongoing compositional analysis. In this way, when idi-oms are not familiar, the predictions of the hybrid model should approach those of decomposable models (i.e., fa-cilitative effects of compositionality).

Empirical demonstrations of compositionality effects on idiom processing have been mixed. Several studies byGibbs and colleagues (e.g., Gibbs, 1992; Gibbs & Nayak,1989; Gibbs, Nayak, Bolton, & Keppel, 1989; Gibbs, Nayak, & Cutting, 1989) show that decomposable idiomsare read more quickly than nondecomposable idioms, thus supporting the view that compositionality facilitatesidiom processing. However, it is difficult to determine whether decomposability effects are the products of first-pass comprehension operations or of those occurring wellafter idioms are initially retrieved. Other studies suggestthat comprehenders’ intuitions about decomposability areoften unreliable (Abel, 2003; Tabossi et al., 2008; Titone

MULTIDETERULTIDETERMINEDINED NNATUREATURE OFOF IDIODIOM PROCESSINGROCESSING 11051105

oms of a controlled length and phrasal structure, which in-cludes several types of decomposability ratings.

Experiments 2 through 4 extended the results of Experi-ment 1 by utilizing online measures of reading speed and accuracy, as a function of the normative characteristics of these idioms, again focusing on familiarity and the variousdecomposability measures. In Experiment 2, participantsmade speeded meaningfulness judgments for idioms pre-sented in whole sentences. In Experiment 3, participants made speeded meaningfulness judgments of idioms pre-sented word by word at an experimenter-controlled rate. In Experiment 4, participants read sentences containing idioms and matched literal phrases for comprehension at their own pace in a moving-window paradigm. Thus, un-like in the other experiments, in Experiment 4, we did not require participants to make any overt semantic judgment. Multiple regression analyses were used in all experiments, to determine whether the ways in which idioms differ af-fected comprehension. Indeed, multivariate approachesmay lead to a more nuanced understanding of idiom pro-cessing, as compared to traditional parametric approaches,which are limited due to stimulus selection constraints.

EXPERIMENT 1

The purpose of Experiment 1 was to collect normative data on a large set of English idioms that had a similar phrasal structure (e.g., she stole the show, he lost his cool,it hit the spot, she made a killing, he cleared his name,she hit the sack, she drove him nuts, etc.) and to examine the effects of familiarity and decomposability on offline judgments of idiom meaningfulness. A range of norma-tive characteristics were collected (global decomposabil-ity, verb and noun decomposability, familiarity, mean-ingfulness, literality, predictability, and frequency of the idioms’ component words). Measures of decomposability included normal–abnormal decomposability ratings, as well as two separate measures of global decomposabil-ity; this allowed us to investigate the effect of instruction wording on participant ratings.

MethodParticipants. One hundred sixty undergraduate students attend-

ing McGill University participated for course credit or for compen-sation at a rate of C$10/hour. All participants were native speakers of English and had normal or corrected-to-normal vision.

Stimuli. The experimental materials consisted of 219 idiomaticexpressions chosen from the Penguin Dictionary of English Idioms(Gulland & Hinds-Howell, 1994) and NTC’s Dictionary of American Slang and Colloquial Expressions (Spears, 2000). All stimuli had a“She verbed x noun” structure, where x could be an article, preposi-tion, or determiner (e.g., she kicked the bucket, he took a beating,he used his head, etc.). Our objective in adopting these criteria was to control for phrasal complexity and length. We also included 30nonidiomatic literal phrases (e.g., he drove the van) to help anchor responses for the different ratings.

Because many of the idioms’ component words are absent fromstandard word frequency corpora (e.g., Ku era & Francis, 1967), es-pecially the verbs in their past-tense form, frequency of the idioms’component verbs and nouns was assessed using Yahoo page countvalues divided by 1,000,000. Given that this measure of word fre-quency is somewhat nonstandard, we conducted a normative analysis

cesses. For example, within the morphological processingliterature, the extent to which polymorphemic words (e.g.,humbug, firefly, doorknob) are compositionally processed during comprehension has been investigated by examining the factors that facilitate the comprehension of constituent morphemes, such as stem frequency (e.g., Baayen, Dijk-stra, & Schreuder, 1997; Bertram, Schreuder, & Baayen,2000; Bradley, 1979; Burani & Caramazza, 1987; Burani,Salmaso, & Caramazza, 1984; Colé, Beauvillain, & Segui,1989; Schreuder & Baayen, 1997; Taft, 1979, 2004). Al-though questions concerning storage and computation remain under active investigation, with respect to mor-phology (e.g., Burani & Caramazza, 1987; Burani & Lau-danna, 1992; Caramazza, Laudanna, & Romani, 1988), the analogy between polymorphemic words and idioms maybe instructive. Specifically, a compositional approach toidioms presumes that idiomatic meaning is built directlyfrom its component words and word meanings. Accord-ingly, any factor that facilitates lexical access and word meaning retrieval should, in turn, facilitate composition of the idiomatic meaning. Inasmuch as idioms are compo-sitionally analyzed on the basis of their parts, the analogywith morphological effects in word processing implies thatincreased frequency of an idiom’s component words should facilitate the comprehension of its figurative meaning.

To our knowledge, the only study examining the effects of component word frequency on idiom comprehensionwas conducted by Cronk, Lima, and Schweigert (1993), and their study did not support the prediction that increased word frequency leads to improved understanding of idi-oms. In a word-by-word reading study, Cronk et al. found an interaction between idiom familiarity and Ku era–Francis (KF, 1967) word frequency (averaged across allwords of the idiom) on moving-window reading times. High-familiar idioms (e.g., it slipped her mind, he kicked the bucket, he cracked a joke) were read more quickly than were low-familiar idioms (e.g., he rushed his fences, shecurled her lip, she took the veil), but this familiarity effectwas larger for low-frequency idioms with low-frequencyconstituent words than for idioms with high-frequencyconstituent words, as can be seen from the data presented in their Figure 5. It is interesting that the most quickly read condition was that for high-familiar idioms that were of a low, rather than high, word frequency.

The present study examines the effects of familiarity, de-composability, and other measures, such as word frequency, on idiom processing for a large set of idioms, using both on-line and offline comprehension measures. In Experiment 1,we report data on the normative characteristics of 219 idi-oms, which include ratings of familiarity, global decom-posability, normal and abnormal decomposability, verb and noun decomposability, and other relevant linguistic features (e.g., literal plausibility, predictability of the phrase-finalword, frequency of the idioms’ component words). Usingthese ratings, we examined the effects of familiarity and decomposability on people’s offline judgments of idiommeaningfulness. Normative data on idioms have been re-ported before (e.g., Titone & Connine, 1994b). However,there is potential value in an updated set of norms for idi-


pants to make, in effect, normal decomposability judgments rather than global decomposability judgments. Thus, in the present study, one group of participants was presented with instructions fromTitone and Connine (1994b), and another group was presented with instructions that had been used by Gibbs and colleagues (Gibbs & Nayak, 1989; Gibbs, Nayak, & Cutting, 1989). Finally, we also col-lected normal and abnormal decomposability ratings, with which to determine the relationship to global decomposability ratings.

Across all dimensions, phrases used as examples in the instruc-tions were not included in the stimulus set. Examples of the ratingformat for each scale are provided in Appendixes A–C. Dimensions were separated among test groups to prevent carryover effects be-tween the rating scales that were most likely to interfere or mutually influence each another (e.g., global decomposability and verb and noun relatedness). Table 1 presents the stimulus subdivisions withinand across Test Booklets 1, 2, and 3.

Test Booklet 1 consisted of a fill-in-the-blank task measuring final-word predictability and a rating task for measuring global de-composability (i.e., the degree to which the component words are related to the figurative meaning). The booklet was administered to a total of 30 participants, each of whom provided ratings for all 219 idioms. Three versions of Test Booklet 1 were created, having differ-ent random orders of stimuli. The predictability phrase-completionquestions always preceded the decomposability judgments, so that participants would not be cued by having previously seen the idioms during phase completions. Thirty literal phrases (e.g., she drove thevan, she tied her shoe) were also included within the predictability section. After completion of the predictability section, participantswere presented with the global decomposability section.

In Test Booklet 2, participants were asked to sort idioms into twoclasses according to the idioms’ degree of global compositionality (i.e., decomposable or nondecomposable). Instructions for the com-positionality ratings were directly taken from those used by Gibbsand Nayak (1989) and Gibbs, Nayak, and Cutting (1989). Note thatthe instructions provided in Part 1 of the Test Booklet 2 were almost identical to those provided in Test Booklet 1 and in Titone and Con-nine (1994b), except the one mention of literally related was omitted dfrom the sentence An example of a decomposable idiom would be the phrase cover up your tracks, which has two words that are related to the idiomatic meaning. On completion of the global decomposabil-ity ratings, participants were asked to further classify decomposable idioms as being either normally decomposable (in which a part of the idiom is used literally) or abnormally decomposable (in which the referents of an idiom’s parts can be identified metaphorically).Instructions for abnormal/normal classifications were identical to those used by Gibbs and Nayak (1989) and Gibbs, Nayak, and Cutting (1989). Test Booklet 2 contained all 219 idioms and their paraphrases. Two versions of the booklet were created, having two random orders of items.

in order to check its validity as a measure of word frequency. First,a total of 1,165 words for which KF frequency was known were ob-tained from the MRC lexical database (Wilson, 1988) . These wordswere then automatically searched on Yahoo, and page count valuesfor each word were generated. The parametric Pearson correlationbetween KF frequency and Yahoo page count (divided by 1,000,000)was .60, and the nonparametric Spearman rho correlation was .82. Thus, there was a strong relationship between KF word frequency and Yahoo page count, validating the latter as a good proxy indicator of word frequency (see also Blair, Urland, & Ma, 2002).

Procedure. Participants received one of three test booklets. Ineach booklet, participants were asked to rate idiomatic phrases ac-cording to a subset of nine possible dimensions: familiarity, mean-ingfulness, predictability, literal plausibility, global decomposability, normal decomposability, abnormal decomposability, verb related-ness, and noun relatedness. Instructions for the first four scales weretaken from Titone and Connine (1994b).

Familiarity is operationally defined as the subjective frequencywith which comprehenders encounter an idiom in its written or spo-ken form, regardless of their familiarity with the actual meaning of the phrase. Meaningfulness is taken to represent the comprehenders’confidence in their understanding of what the phrase actually means. As applied to idioms, predictability is defined as the probability of completing an incomplete phrase idiomatically (e.g., He kicked the______). Literality refers to an idiom’s potential for a literal inter-pretation. For example, some idioms, such as bite the bullet, have awell-formed literal meaning, whereas other idioms, such as break her word, only have a meaningful idiomatic interpretation. As pre-viously discussed, global decomposability refers to how an idiom’swords make independent semantic contributions to the overall fig-urative meaning. Idioms considered to be globally decomposablemay be further classified as normally decomposable or abnormallydecomposable. Normally decomposable idioms are expressions in which a part of the idiom is used literally (e.g., the question in thephrase pop the question). Abnormally decomposable idioms are ex-pressions in which the referents of an idiom’s parts can be identified metaphorically (e.g., maker in r meet your maker, which metaphori-cally refers to a deity). Finally, we operationally define verb and noun relatedness as the extent to which the constituent verb and/or noun is related to the overall figurative meaning of the phrase.

In the case of global decomposability, we collected two sets of rat-ings in order to investigate a methodological issue within the exist-ing literature. Specifically, the instructions for Titone and Connine’s(1994b) global decomposability ratings were virtually identical tothose used previously by Gibbs and colleagues (Gibbs & Nayak, 1989; Gibbs, Nayak, & Cutting, 1989), except Titone and Connine referred to a literal relation between the component words and the idiomatic meaning, whereas Gibbs and colleagues did not. This is aconcern because the term literally related may have biased partici-d

Table 1Organization of the Three Test Booklets Used in Experiment 1

Versions Across No. of Idiomatic Randomization Total No. of Total No. of Test Which Stimuli Stimuli Presented of Stimulus Participants Who Ratings on Each

Booklet Rating Sections Were Divided per Rating Order Completed Version of the 219 Idioms

1 Predictability, global N/A 219 Ver. 1 10 30 decomposability Ver. 2 10

Ver. 3 10

2 Global decomposability, N/A 219 Ver. 1 20 40normal/abnormal Ver. 2 20decomposability

3 Familiarity, Ver. 1 73 Sub-ver. A 15 30meaningfulness, Sub-ver. B 15literal plausibility, Ver. 2 73 Sub-ver. A 15verb/noun relatedness Sub-ver. B 15

Ver. 3 73 Sub-ver. A 15Sub-ver. B 15

MUULTIDETERMINEDINED NNATAA UREURE OFOF IDIODIOM PROCESSINGROCESSING 11071107

composability ratings, based on 70 participants per item, were used in all subsequent analyses.

The normative data collected for the 210 idiomatic phrases can be downloaded from the Psychonomic Society’sNorms, Stimuli, and Data Archive at www.psychonomic.org/archive/. In order to examine the associations among the dimensions and measures, Spearman rho correlationswere computed between the following variables: global decomposability proportion (combined), verb decompos-ability, noun decomposability, normal decomposabilityproportion, familiarity, meaningfulness, literality, predict-ability, verb word frequency, and noun word frequency. Spearman rho was chosen over Pearson’s r, to minimize the effect of outliers and linearize the data (Bobko, 2001). The correlation matrix is presented in Table 2.

Global decomposability correlated significantly and positively with all dimensions except literality—for whichthere was a significant negative correlation—and verb fre-quency—for which there was no correlation. Thus, whereasidioms were judged to be more decomposable, their verband noun constituents were judged to be more semanticallyrelated to the figurative meaning; they were judged to be more familiar, meaningful, and predictable; and the word frequency of the noun was high. Although the negative cor-relation between global decomposability and literality may initially seem counterintuitive—given that all literal phrasesare, by nature, decomposable—this relationship highlights the unique properties inherent to idiomatic phrases. Spe-cifically, unlike literal sentences, globally decomposable idioms do not necessarily have to be literally plausible (e.g.,she pocketed her pride), and literally plausible idioms donot have to be decomposable (e.g., he kicked the bucket). tGlobal decomposability judgments were positively corre-lated with normal decomposability proportions (and thus negatively correlated with abnormal decomposability pro-portions). This was also true when the decomposability pro-portions ascertained exclusively from Test Booklet 2 were analyzed alone. Thus, using the identical instructions as were used by Gibbs and colleagues (Gibbs & Nayak, 1989; Gibbs, Nayak, & Cutting, 1989), global decomposability judgments were more associated with normal decompos-ability than with abnormal decomposability. Because the

Test Booklet 3 consisted of ratings for five scales (i.e., familiar-ity, meaningfulness, literal plausibility, verb relatedness, and noun relatedness) and was administered to a total of 90 participants.The five scales were grouped into three rating sections: Familiar-ity (frequency with which a comprehender encounters an idiom)and meaningfulness (familiarity with the idiom’s meaning) were grouped together (as in Titone & Connine, 1994b), and literal plausi-bility (an idiom’s potential for a literal interpretation) and verb–noun relatedness (the degree to which the constituent verb and/or noun are related to the overall figurative meaning) were grouped separately. Idioms were counterbalanced across these three sections, so that participants within a section rated the same subset of idioms, and individual participants rated different idioms across sections. Thus, the 219 idioms were divided into three groups, each consisting of 73 idioms, and were counterbalanced across sections for the three versions of Test Booklet 3. Finally, item order was randomized in two sub-versions for each of the three counterbalanced versions, resulting in a total of six versions of Test Booklet 3.

In Test Booklet 3, rating sections were always ordered as follows: familiarity, meaningfulness, literal plausibility, verb relatedness, and noun relatedness.

Results and DiscussionNine idioms with familiarity ratings lower than 1.5 were

omitted from the present analysis and from all subsequent experiments. We first evaluated whether the difference ininstructions between Test Booklet 1 and Test Booklet 2affected the global decomposability ratings. The correla-tion between the global decomposability proportions inthe two experiments was positive and extremely high (r.89, p .01). Thus, the single mention of the word literalin Test Booklet 1 did not affect participants’ sorting be-havior any more than did its absence from Test Booklet 2.This finding has implications for previous studies of com-positionality effects on idiom processing. In particular,it demonstrates that the ratings used by Gibbs and col-leagues (Gibbs & Nayak, 1989; Gibbs, Nayak, & Cutting,1989) are comparable to those used by Titone and Con-nine (1994b) and those used in the present study. In other words, global decomposability has been operationallydefined by Gibbs and colleagues in the same way as byTitone and Connine (1994b) and here. We consequently combined the global decomposability ratings from Test Booklets 1 and 2, which had 30 and 40 participant re-sponses per item, respectively. The combined global de-

Table 2Spearman Rho Correlation Matrix Between Global Decomposability Proportion

(Combined) (GD), Verb Decomposability (VD), Noun Decomposability (NnD), NormalDecomposability Proportion (NrD), Familiarity (FAM), Meaningfulness (MNG),

Literality (LIT), Predictability (PRED), Verb Word Frequency (VF),RRand Noun Word Frequency (NF)

VD NnD NrD FAM MNG LIT PRED VF NF

GD .52* .72* .72* .40* .41* .21** .14** .00 .37*

VD 1.00 .07 .31* .14* .16** .02 .04 .12 .21*

NnD 1.00 .69* .33* .36* .38* .09 .04 .31*

NrD 1.00 .40* .39* .23* .17** .06 .34*

FAM 1.00 .95* .11 .41* .21* .28*

MNG 1.00 .15** .38* .13 .24*

LIT 1.00 .03 .12 .07PRED 1.00 .20* .17*

VF 1.00 .11NF 1.00*p .05. **p .01.


and Titone and Connine’s (1994b), predictability was sig-nificantly positively correlated with idiom familiarity.

To examine the specific effects of decomposability and familiarity, and to test predictions of compositional, non-compositional, and hybrid models of idiom processing, we conducted a series of multiple regression analyses, using meaningfulness ratings and final word predictability as thedependent variables. We designated meaningfulness ratings as a dependent variable because, for those ratings, we spe-cifically asked participants to assess how much meaningeach phrase carried, irrespective of how they arrived at that meaning (i.e., direct retrieval or compositional analysis). We designated predictability as another dependent variable, be-cause this variable indicates how primed idiomatic comple-tions of sentences are given their initial words. We used eachregression model to evaluate the main effect of familiarity, the main effect of the decomposability rating of interest (i.e.,global decomposability, noun relatedness, or verb related-ness), and the two-way interaction between familiarity and the decomposability variable of interest. Moreover, in eachof the models, literal plausibility, verb frequency, and noun frequency were entered as independent variables in order to account for their contributions to idiom comprehension.

With respect to the dependent variable of idiom mean-ingfulness ratings, we evaluated three separate models in-volving global decomposability proportion, verb related-ness, and noun relatedness, the results of which are reported in Table 3. Each model showed a significant main effect of familiarity. In addition, the models assessing global decom-posability and noun decomposability showed a significanttwo-way interaction between familiarity and noun decom-

correlation between global decomposability and normalor abnormal decomposability was not reported in previousstudies, it is impossible to determine whether all previous studies showed the same bias. In the remainder of this ar-ticle, analyses using normal decomposability proportions are excluded, since they should be comparable to the resultsfor global decomposability proportions.

All decomposability ratings correlated positively with each other except verb and noun relatedness, which were uncorrelated. Familiarity correlated positively with mean-ingfulness and predictability, but negatively with literalplausibility. Meaningfulness also correlated positivelywith verb and noun relatedness. Finally, literal plausibilitycorrelated negatively with all decomposability measures,as well as with idiom meaningfulness.

The pattern of results for frequency of the idioms’ verbs and nouns was also noteworthy. Verb frequency correlated with only two variables (idiom familiarity and idiom pre-dictability), in opposite directions. There was a positiverelationship between verb frequency and idiom familiar-ity, whereas there was a negative correlation between verbfrequency and idiom predictability. This pattern of datais intriguing, given that idiom familiarity and predict-ability were positively correlated themselves. In contrast with verb frequency, noun frequency correlated positively with all variables except literality and verb frequency, for which the variables were uncorrelated.

These results suggest that verb word frequency and noun word frequency may play two very different rolesduring idiom processing. Increased verb frequency pre-cludes (rather than enhances) idiom predictability and is uncorrelated with all decomposability variables. Thus,rare verbs are more predictive of idiomatic sequences thancommon verbs are, irrespective of their semantics. On theother hand, the reverse effect of word frequency is found for nouns, suggesting that they play a stronger semantic role than verbs. Noun frequency was positively correlated with all other variables except literal plausibility and verbfrequency; thus, this variable appears to facilitate idiomactivation. Moreover, the positive correlation between verb frequency and idiom familiarity, but not betweenverb frequency and meaningfulness, suggests that par-ticipants based their idiom familiarity decisions on a fre-quency dimension to a greater extent than they based their meaningfulness decisions. Thus, although familiarity and meaningfulness were highly correlated themselves, only familiarity was related to another frequency measure.

The correlations presented in Table 2 replicate and ex-tend those found in Titone and Connine (1994b). A subset (n 35) of the verb-x-noun idioms used in the presentstudy were also used in Titone and Connine (1994b), thusfacilitating a direct comparison of ratings for the sameitems across the two studies. Results from the correlation analysis revealed significant positive correlations betweenmeasures of global decomposability (r .51, p .01),familiarity (r .76, p .01), meaningfulness (r .71,p .01), and literal plausibility (r .89, p .01). Onlypredictability ratings were uncorrelated, likely the result of the highly skewed distribution and high variability for these data in both studies. Nevertheless, in both this study

Table 3Results From Three Multiple Regression Models

(Experiment 1), Where Percentage MeaningfulnessJudgments Is the Dependent Variable

(Scaled) SE F RatioF Prob F

Model 1: R2 (Adjusted) .88, RMS 0.30, F RatioF 250.7, p .01

Familiarity 1.49 0.04 1,108.00 .01**

Global decomposability 0.07 0.04 2.49 .11Familiarity global decomp. 0.36 0.08 21.03 .01**

Literality 0.04 0.04 1.13 .29Verb frequency 0.07 0.05 2.13 .15Noun frequency 0.02 0.07 0.05 .83


Familiarity 1.53 0.04 1,247.00 .01**

Verb decomposability 0.08 0.05 2.45 .12Familiarity verb decomp. 0.11 0.10 1.26 .26Literality 0.03 0.04 0.73 .39Verb frequency 0.11 0.05 4.15 .04*

Noun frequency 0.04 0.08 0.25 .61


Familiarity 1.51 0.04 1,205.00 .01**

Noun decomposability 0.07 0.05 2.39 .12Familiarity noun decomp. 0.34 0.08 17.00 .01**

Literality 0.03 0.04 0.60 .44Verb frequency 0.08 0.05 2.71 .10Noun frequency 0.01 0.07 .01 .95*p .05. **p .01.


The results suggest that decomposability has differ-ent effects on idiom processing, as reflected by offline meaningfulness and final-word predictability judgments. As might be expected, global decomposability exerted arobust effect on offline meaningfulness judgments, and this effect was greater for low-familiar idioms. The samepattern of results was found for noun decomposability,whereas verb decomposability exerted no effect on idiom meaningfulness judgments. None of the decomposabilitymeasures was associated with final-word predictability;however, as in the correlation results, verb frequency was inversely related to predictability.

The different pattern of decomposability and verb fre-quency effects for overt meaningfulness judgments and final-word predictability ratings led us to several conclu-sions regarding the role of decomposability during idiom processing. First, decomposability effects are more likelyto arise in a task that encourages attention to be focused atthe semantic level (i.e., meaningfulness judgments) than at the lexical level (i.e., predictability of the phrase-final word). Second, when decomposability effects are found, they are attenuated by high phrasal familiarity, suggest-ing that there may be two routes to comprehension—one

posability. Finally, when modeling the effect of verb de-composability, we found a significant inverse effect of word frequency of the verb. This effect was in a similar direction,but it was nonsignificant in the other models.

The significant two-way interactions between the vari-ous decomposability measures (except verb decompos-ability) and familiarity are illustrated in Figures 1 and 2.The figures depict average meaningfulness judgments,as a function of the different ratings. High, medium, and low subsets for each dimension were determined by split-ting the items into approximate thirds; we took care not to allow the same values to straddle categories. The resultingsubsets are included in order to aid interpretation of the in-teractions; they were not used in the regression analysis.

With respect to the dependent variable of idiom predict-ability, we again evaluated three separate models, involv-ing global decomposability proportion, verb relatedness,and noun relatedness, the results of which are reported inTable 4. All three models showed significant main effectsof familiarity and verb frequency. Specifically, increasesin familiarity and decreases in verb frequency were as-sociated with increased idiom predictability. Across thethree models, no other effects were significant.

Mea

nin

gfu

lnes

s R

atin

gs

5

4

3

2

1

Low Familiarity Moderate Familiarity High Familiarity

Low decomposability

Moderate decomposability

High decomposability

Figure 2. Mean idiom meaningfulness ratings, as a function of noun decom-posability and familiarity.

Mea

nin

gfu

lnes

s R

atin

gs

5

4

3

2

1


Low decomposability



Figure 1. Mean idiom meaningfulness ratings, as a function of global decom-posability and familiarity.


Procedure. Experiment 2 was implemented using E-Prime soft-ware (Schneider, Eschman, & Zuccolotto, 2002). Sentences were pre-sented visually in the center of a computer screen. Participants wererequired to judge, as quickly as possible, whether each sentence wasmeaningful, by pressing an appropriately labeled button on a buttonbox. The sentence remained on the screen until the participant madea response. To prevent stereotyped responding, the intertrial intervalsvaried randomly between 1,000 msec and 1,250 msec, during whichparticipants saw a white fixation cross. All participants received a practice block of 15 trials before beginning the test session.

Results and DiscussionSummary data for correct RTs and error proportions

are presented in Table 5. Responses to idioms were sig-nificantly slower [F1(1,54) 7.59, p .01; F2FF (1,239)3.59, p .01] and significantly less accurate [F1(1,54)11.74, p .01; F2FF (1,239) 5.10, p .01] than responsesto literal sentences. Responses to nonsense sentences were significantly slower than those made to idioms [F1(1,54)10.04, p .01; F2FF (1,329) 6.01, p .01] and to literal sentences [F1(1,54) 8.14, p .01; F2FF (1,149) 3.66, p .01] and were significantly more accurate than idiom responses [F1(1,54) 7.13; p .01; F2FF (1,329) 3.67,p .01], but not more accurate than literal sentences.

We used multiple regression analyses to examine theeffects of familiarity and decomposability on idiom com-prehension. The dependent variables were the speed and accuracy of participants’ meaningfulness judgments, and the independent variables included familiarity, literalplausibility, a decomposability variable of interest, and the two-way interaction between familiarity and the rele-vant decomposability measure. Each model was evaluated once with the proportion of errors in the meaningfulness judgment task as the dependent variable, and once withcorrect RT as the dependent measure. The models and sta-tistical results are presented in Tables 6 and 7.

Familiarity facilitated semantic judgment responses significantly in all models, and global decomposability marginally facilitated semantic judgment responses in theerror proportion data only. None of the interactions be-tween familiarity and decomposability was significant.Increased literal plausibility facilitated semantic judg-ment responses only for error proportions. These results are similar to those found for the offline meaningfulnessjudgments in Experiment 1, with the exceptions that in Experiment 2, the decomposability effects were less ro-bust, and literal plausibility was associated with facili-tated responding in the error proportion data.

However, one possible limitation with Experiment 2 isthat although the whole sentence reading time task is argu-ably more indicative of online processing than are paper-

that involves direct retrieval for high-familiar idioms, and one that relies more on decomposition for low-familiar idioms. Third, the semantics of the noun appear to play a greater role in offline meaningfulness judgments than dothe semantics of the verb. Finally, people are more likelyto think of idiomatic completions in the context of a rareor low-frequency verb than of a high-frequency verb.

In Experiment 2, we examined whether these factors would affect idiom processing when people processed idioms in a more online fashion. Thus, we conducted asecond experiment, in which a new set of participants made speeded meaningfulness judgments for the same 210 idioms, along with 210 nonsense phrases, presented as whole sentence units. As in Experiment 1, we predicted that familiarity and decomposability would again interact in their influence on both the accuracy and the correct re-sponse times (RTs) of online meaningfulness judgments.

EXPERIMENT 2

MethodParticipants. Fifty-five undergraduate students attending McGill

University participated for course credit or for monetary compensa-tion at a rate of C$10/hour. All participants were native speakers of English and had normal or corrected-to-normal vision.

Stimuli. The experimental materials consisted of the same 210idiomatic expressions and 30 literal phrases used in Experiment 1,as well as 240 nonsense phrases created by combining constituentverbs and nouns from different idioms in our stimulus list (e.g., Sheran the cloud ). Stimuli were randomly assigned to two possible listsconsisting of 240 phrases (105 idioms, 15 literal phrases, and 120nonsense phrases). Participants were randomly assigned to one of the two list conditions.

Table 4Results From Three Multiple Regression Models(Experiment 1), Where Final-Word Predictability

Is the Dependent Variable


Model 1: R2 (Adjusted) .17,RMS 0.21, F RatioF 8.0, p .01

Familiarity 0.19 0.03 37.24 .01**

Global decomposability 0.01 0.03 0.25 .62Familiarity global decomp. 0.05 0.05 0.83 .36Literality 0.01 0.03 0.13 .71Verb frequency 0.12 0.03 11.49 .01**

Noun frequency .01 0.05 .01 .10

Model 2: R2 (Adjusted) .17RMS 0.21, F RatioF 8.3, p .01

Familiarity 0.18 0.03 41.05 .01**

Verb decomposability 0.05 0.03 2.46 .12Familiarity verb decomp. 0.03 0.06 0.23 .64Literality 0.01 0.03 0.19 .66Verb frequency 0.11 0.03 9.57 .01**

Noun frequency 0.01 0.05 0.03 .86


Familiarity 0.18 0.02 37.37 .01**

Noun decomposability 0.01 0.03 0.03 .87Familiarity noun decomp. 0.06 0.05 1.41 .24Literality 0.01 0.03 0.18 .67Verb frequency 0.12 0.03 11.45 .01**

Noun frequency .01 0.05 0.01 .93*p .05. **p .01.

Table 5Summary Data for Participant Response Times (RTs, inRR

Milliseconds) and Error Proportions (EPs) DuringWhole-Sentence Reading in Experiment 2

RT EP

M SD M SD

Idioms (n 210) 1,279.9 308.9 0.15 0.19Literal sentences (n 30) 1,211.2 214.1 0.14 0.07Nonsense sentences (n 120) 1,321.8 221.8 0.15 0.07

MULTIDETERULTIDETERMINEDINED NNATUREATURE OFOF IDIODIOM PROCESSINGROCESSING 1111

same phrasal structure and length, we had the opportunityto further investigate online mechanisms by employing two different word-by-word reading tasks.

Thus, the goal of Experiments 3 and 4 was to deter-mine whether the results of Experiment 2 would extend to two reading tasks in which the words of each sentencewere presented in sequence, and in which participants could not reread portions of the sentence. In Experi-ment 3, words were presented one at a time at a fixed rate, and again participants made forced-choice sensi-bility judgments. In Experiment 4, however, the reading task was more natural. Here, words were presented one at a time at a participant-determined rate, in a moving-window reading paradigm (see, e.g., Just, Carpenter, & Woolley, 1982). No overt decision was required in Ex-periment 4, although comprehension questions were pre-sented intermittently to ensure that participants actually read the sentences for comprehension, and to determinewhether participants were interpreting idioms figura-tively or literally.

EXPERIMENT 3

MethodParticipants. Forty-three undergraduate students attending

McGill University participated for course credit or for compensa-tion at a rate of C$10/hour. All participants were native speakers of English and had normal or corrected-to-normal vision.

Stimuli. The experimental materials were the same as those used in Experiment 2.

Procedure. The procedure was the same as that used in Ex-periment 2, except that participants saw the four words of each ex-perimental sentence presented one at a time at a fixed rate. Each word was presented in the center of the screen for 300 msec, with a 200-msec interval between words. Three red question marks ap-peared below the fourth (final) word of each sentence, which re-mained on the screen until the participant provided a “yes” or “no” (meaningfulness) response, using the button box.

Results and DiscussionSummary statistics, including means and standard devi-

ations of the constituent word response measures, are pre-sented in Table 8. Responses to idioms were significantly slower [F1(1,42) 9.23, p .01; F2FF (1,239) 4.89, p.01] and significantly less accurate [F1(1,42) 7.90, p.01; F2FF (1,239) 4.12, p .05] than those to literal sen-tences. Responses made to nonsense sentences were sig-nificantly slower than those made to idioms [F1(1,42)6.92, p .05; F2FF (1,329) 6.12, p .01] and to literal sen-tences [F1(1,42) 11.23, p .01; F2FF (1,149) 3.12, p.01], and they were significantly more accurate than idiom

and-pencil ratings (as in Experiment 1), it may still berelatively insensitive to online processing, in that partici-pants have time to ruminate over the sentence before mak-ing a response. Because all of the sentence stimuli had the

TableTT 6Results From Three Multiple Regression Models (Experiment 2:

Whole-Sentence Presentation), Where Response Error Proportion Is the Dependent Variable



Familiarity 0.20 0.02 90.64 .01**

Global decomposability 0.04 0.02 3.59 .06Familiarity global decomp. 0.01 0.04 0.11 .74Literality 0.15 0.02 61.59 .01**

Verb frequency .01 0.02 0.02 .89Noun frequency 0.02 0.03 0.27 .60


Familiarity 0.22 0.02 118.80 .01**

Verb decomposability 0.03 0.02 1.28 .26Familiarity verb decomp. 0.01 0.04 0.09 .77Literality 0.14 0.02 58.22 .01**

Verb frequency .01 0.02 0.01 .93Noun frequency 0.02 0.04 0.19 .66


Familiarity 0.21 0.02 108.10 .01**

Noun decomposability 0.02 0.02 0.50 .48Familiarity noun decomp. 0.05 0.04 1.50 .22Literality 0.15 0.02 56.35 .01**

Verb frequency .01 0.02 0.01 .93Noun frequency 0.01 0.04 0.16 .69*p .05. **p .01.

TableTT 7Results From Three Multiple Regression Models (Experiment 2:

Whole-Sentence Presentation), Where Correct Response Time Is the Dependent Variable



Familiarity 247.00 41.0 36.41 .01**

Global decomposability 52.60 40.6 1.68 .20Familiarity global decomp. 45.10 71.9 0.39 .53Literality 38.80 36.1 1.15 .28Verb frequency 76.80 45.9 2.81 .09Noun frequency 121.00 67.5 3.22 .07


Familiarity 227.00 38.1 35.74 .01**

Verb decomposability 27.60 44.9 0.38 .54Familiarity verb decomp. 34.40 85.2 0.16 .69Literality 44.60 35.6 1.57 .21Verb frequency 84.50 46.0 3.37 .07Noun frequency 118.00 67.7 3.04 .08


Familiarity 241.00 39.6 36.97 .01**

Noun decomposability 57.80 43.1 1.80 .18Familiarity noun decomp. 7.55 74.8 0.01 .92Literality 27.20 38.2 0.51 .47Verb frequency 81.00 45.7 3.14 .08Noun frequency 118.00 67.1 3.08 .08*p .05. **p .01.

TableTT 8Summary Statistics for Participant MeaningfulnessResponse Times (RTs, in Milliseconds) and Error

Proportions (EPs) for the Phrase-Final Word During Fixed-Rate Presentation in Experiment 3

RT EP

M SD M SD

Idioms (n 210) 917.7 150.8 0.15 0.17Literal sentences (n 30) 886.7 145.0 0.10 0.15Nonsense sentences (n 120) 996.2 148.1 0.08 0.13


with the instructions in Experiment 2, rereading portionsof the sentence is not possible using the moving-windowmethod. Unlike in the previous experiments that required participants to make overt meaningfulness judgments,

responses [F1(1,42) 10.52, p .01; F2FF (1,329) 4.67, p .01], but not more accurate than literal sentences.

As in Experiment 2, we conducted multiple regression analyses on the data. The statistical results are presented in Tables 9 and 10.

Error proportions declined to the extent that idioms were familiar, which was similar to the results of Experi-ment 2. However, unlike Experiment 2, error proportions were lower for idioms that were rated as being more liter-ally plausible, and to the extent that verb frequency was low (similar to the effects on predictability in Experi-ment 1). None of the decomposability variables exerted a significant effect on participants’ error proportions. However, correct meaningfulness judgment latencies de-clined to the extent that idioms were globally decompos-able. The main effects of verb and noun decomposability were not significant, although the main effect of verb de-composability trended toward significance in the latencydata. The data for correct RTs, plotted as a function of the main effects of global decomposability and familiarity,are presented in Figure 3. In addition, increased familiar-ity, literal plausibility, and decreased verb frequency weresignificantly associated with increased judgment speed of the sentence-final word.

The results of Experiment 3 suggest that increased fa-miliarity, literal plausibility, and global decomposabilityfacilitate idiom processing; however, increased verb fre-quency again impedes idiom processing when compre-henders read idiomatic sentences word by word at a fixed presentation rate. It is possible that the increased com-prehension demands associated with Experiment 3, com-pared with those associated with Experiment 2, account for the difference in results. When people make semanticjudgments about idioms presented in whole sentences, such as in Experiment 2, they can reread portions of thesentence before making their response. In contrast, when participants read sentences word by word at a fixed rate, they can neither reread portions of the sentence nor take asmuch time as they might like in order to read a particular word (except the last word in this task). Thus, given theincreased task demands of Experiment 3, it is likely that any linguistic variable that would help one make this deci-sion might become more salient. This would again includefamiliarity, but now also includes global decomposability, literal plausibility, and verb frequency.

One potential limitation with Experiment 3 is that thefixed rate presentation may not generalize to normal read-ing, in which comprehenders decide how long to spend encoding each word, and in which they read for com-prehension, rather than with the explicit requirement of making a semantic judgment. In Experiments 1 (with theexception of predictability ratings), 2, and 3, attention wasfocused explicitly on sentence meaningfulness judgments. Consequently, Experiment 4 was designed to test whether the results of Experiment 3 would hold for a task that used a self-paced, moving-window presentation, and was thus more natural (e.g., Just et al., 1982). This method involves word-by-word presentation of each sentence. Participantsinitiate the onset of each new word, and only one word can be seen at a time in its normal sentence position. As

Table 9Results From Three Multiple Regression Models (Experiment 3:

Fixed-Rate Sentence Presentation), Where Response ErrorProportion Is the Dependent Variable



Familiarity 0.22 0.01 166.90 .01**

Global decomposability 0.02 0.02 1.80 .18Familiarity global decomp. 0.02 0.03 0.68 .41Literality 0.10 0.02 44.34 .01**

Verb frequency 0.04 0.02 5.15 .02*

Noun frequency 0.03 0.03 1.09 .30


Familiarity 0.23 0.02 209.20 .01**


Verb frequency 0.05 0.02 6.74 .01**

Noun frequency 0.03 0.03 1.19 .28


Familiarity 0.23 0.02 191.70 .01**

Noun decomposability 0.01 0.02 0.06 .87Familiarity noun decomp. 0.01 0.03 0.04 .84Literality 0.10 0.02 37.91 .01**

Verb frequency 0.05 0.02 5.80 .02Noun frequency 0.03 0.03 0.78 .38*p .05. **p .01.

Table 10Results From Three Multiple Regression Models (Experiment 3:

Fixed-Rate Sentence Presentation), Where Correct ResponseTime Is the Dependent Variable



Familiarity 155.00 17.6 77.21 .01**

Global decomposability 44.40 17.4 16.50 .01**

Familiarity global decomp. 16.00 30.9 10.27 .60Literality 53.70 15.5 11.99 .01**

Verb frequency 55.90 19.7 18.05 .01**

Noun frequency 0.13 29.0 .01 .10


Familiarity 170.00 16.4 107.00 .01**


Verb frequency 63.70 19.8 110.30 .01**

Noun frequency 2.88 29.2 110.01 .92


Familiarity 172.00 17.3 99.34 .01**

Noun decomposability 0.23 18.8 .01 .99Familiarity noun decomp. 0.87 32.6 .01 .98Literality 47.40 16.6 8.09 .01**

Verb frequency 59.80 19.9 8.99 .01**

Noun frequency 10.40 29.3 0.13 .72*p .05. **p .01.


sentences and 30 for their matched literal sentences. Comprehension questions for the idiomatic phrases specifically targeted the figu-rative interpretation of the phrase; for example, after having read He kicked the bucket, participants were asked, Did he die? Giventhe two counterbalanced lists, we had comprehension question data for a total of 60 idioms and 60 matched literal sentences across allparticipants.

Participants were given the following instructions:

When you press the red button, the first word of the sentencewill appear. Each subsequent time that you press the red button,the next word of the sentence will appear, and the prior word will disappear. In this way, you will make progress through eachsentence. Although this way of reading is somewhat strange,please try to read as naturally as possible, much as you would read a magazine or a newspaper. Your task is to understand eachsentence in the shortest amount of time.

Results and DiscussionThe reading speeds for each word of the idiomatic and

matched literal sentences are presented in Table 11. Read-ing speed for the idiomatic and matched literal sentences did not significantly differ across all 210 idioms. The relatively high accuracy on idiom-related comprehensionquestions (87%) suggests that people tended to interpretidioms figuratively, rather than literally. The difference in comprehension question accuracy between idioms and matched literal sentences was not significant.

Because sentences containing idioms were matched to literal sentences with the same sentence-final words, and because this was counterbalanced across participants,we were able to compute a difference score indicative of the overall benefit in reading associated with idioms

participants in Experiment 4 were instructed only to read for comprehension.

We also increased the number of literal phrases in Ex-periment 4, to decrease the proportion of idioms presented to participants. The purpose of this change was to addressa possible concern about the design of Experiment 3, thatthe high proportion of idioms may have caused participantsto engage in unnatural comprehension strategies. Finally,a quarter of the trials included comprehension questions,which probed the figurative meaning of sentences contain-ing idioms. Thus, we could evaluate to some extent whether participants were interpreting idioms figuratively.

EXPERIMENT 4

MethodParticipants. Forty undergraduate students attending McGill

University participated for course credit or monetary compensationat a rate of C$10/hour. All participants were native speakers of En-glish and had normal or corrected-to-normal vision.

Stimuli. The experimental materials consisted of the same 210 idi-omatic expressions used in the previous experiments, as well as 330 verb-x-noun literal sentences. To control for final-word length and frequency effects, 210 of the literal phrases were individually matched with specific idiomatic phrases, so that they possessed the same final word. For example, the literal phrase She told a lie was created, based on the idiomatic phrase She lived a lie. Additional examples include the following: She cleaned his ears/She boxed his ears, They tightened the knot/They tied the knot, and so on. We also included 120 additional, nonmatched literal phrases, in order to decrease the proportion of idi-omatic phrases vis-à-vis Experiment 3. Thus, in this experiment, the percentage of sentences containing idioms decreased from approxi-mately 44% to approximately 32%. Idioms were randomly assigned to two possible lists consisting of 330 phrases (105 idioms, 105 matched literal phrases, and 120 “extra” nonmatched literal phrases). Idiomsand their matched literal sentences were counterbalanced across the two lists, so that each participant saw either the idiom or its matched literal phrase, but not both. Participants were randomly assigned toone of the two list conditions.

Procedure. Participants first saw four dashes in the center of the screen, indicating where the words would appear. Participantspressed a button to reveal the first word of the phrase. Each sub-sequent buttonpress revealed the next word and replaced the previ-ous word with dashes. Sixty yes/no comprehension questions wererandomly presented throughout the experiment: 30 for idiomatic

Rea

ctio

n T

ime

(mse

c)

1,100

1,050

1,000

750

700

650

600


Low decomposability



950

900

850

800

Figure 3. Correct response time of idiom-final word for fixed-rate presenta-tion, as a function of global decomposability and familiarity.

Table 11Experiment 4: Self-Paced Reading Speeds (in Milliseconds)

for Each Word of the Idiomatic and Matched LiteralSentences, As Well As Accuracy Percentages (ACC %)

for Presented Comprehension Questions

RT

W1 W2 W3 W4 ACC %

Idioms (n 210) 325.6 326.8 331.0 439.3 87.3Literal sentences (n 210) 325.9 327.4 333.1 436.4 91.6


efit in reading rate for the last word of idiom-bearing sentences than for the last word of literal sentences.Similarly, decreases in verb frequency were also associ-ated with a greater benefit in reading the last word of sentences containing idioms. None of the decompos-ability variables was associated with facilitated idiomprocessing. Thus, when one considers the absence of decomposability effects, the results of Experiment 4were most similar to those of the predictability ratingsin Experiment 1 as compared with that of the other com-prehension measures, for which the instructions overtly inquired about phrase meaningfulness.

GENERALRR DISCUSSION

The purpose of this study was to test predictions of three idiom processing models that differ concerningthe effects of semantic decomposability on idiom com-prehension. To this end, one group of participants rated a relatively large set of idiomatic expressions on a num-ber of psycholinguistic dimensions, including familiar-ity, global decomposability, noun decomposability, verbdecomposability, and literal plausibility (Experiment 1). We then used these ratings, verb word frequencies, and noun word frequencies as independent variables in sev-eral offline and online idiom comprehension experiments with new groups of participants. Dependent variables in these studies included offline meaningfulness judgments(Experiment 1); online, whole-sentence meaningfulness judgments (Experiment 2); word-by-word, fixed-rate meaningfulness judgments (Experiment 3); and word-by-word, self-paced reading (Experiment 4). A potentialvirtue of this multivariate approach is that we were able to examine the simultaneous effects of many predictor vari-ables, some of which were correlated themselves. A sum-mary of the regression results across all four experiments (for models including global decomposability ratings) is provided in Table 13.

As can be seen in Table 13, idiom familiarity exerted a facilitative effect on comprehension across all experi-

compared with that with literal sentences (i.e., averagefinal-word RT for idiom sentences minus average final-word RT for literal sentences). We conducted multiple regression analyses using this difference score as the de-pendent variable. Trials that had comprehension questionsthat were responded to incorrectly were omitted. The sta-tistical results are presented in Table 12.

As can be seen in Table 12, the results were extremelyconsistent across the three regression models. Increasesin idiom familiarity were associated with a greater ben-

Table 12Results From Three Multiple Regression Models (Experiment 4: Moving-Window Reading), Where Idiom Facilitation (Sentence-

Final Word Reaction Time for Idiomatic Sentences Minus Reaction Time for the Literal Sentences) Is

the Dependent Variable



Familiarity 26.80 12.4 4.66 .03*

Global decomposability 11.40 12.3 0.86 .35Familiarity global decomp. 0.76 21.8 .01 .97Literality 13.40 10.9 1.49 .22Verb frequency 30.50 13.9 4.83 .03*

Noun frequency 0.22 20.5 .01 .99


Familiarity 31.90 11.5 7.68 .01**

Verb decomposability 0.15 13.5 .01 .99Familiarity verb decomp. 31.80 25.7 1.54 .22Literality 10.70 10.7 1.00 .32Verb frequency 32.60 13.9 5.51 .02*

Noun frequency 4.84 20.4 0.06 .81


Familiarity 30.10 12.0 6.27 .01**

Noun decomposability 2.65 13.1 0.04 .84Familiarity noun decomp. 15.00 22.7 0.44 .50Literality 11.50 11.6 0.98 .32Verb frequency 30.20 13.9 4.78 .03*

Noun frequency 3.67 20.3 0.03 .86*p .05. **p .01.

Table 13Summary of the Results Across All Four Experiments for Regression Models,

Including Global Decomposability As an Independent Variable

Global Global Decomp. Literal Verb Noun Familiarity Decomp. Familiarity Plausibility Frequency Frequency

Experiment 1: Offline Ratings

Meaningfulness Positive – Positive – – –Predictability Positive – – – Negative –

Experiment 2: Whole-Sentence Speeded Meaningfulness Judgments

Error proportion Positive – – Positive – –Correct RT Positive – – – – –

Experiment 3: Fixed-Rate Speeded Meaningfulness Judgments

Error proportion Positive – – Positive Negative –Correct RT Positive Positive – Positive Negative –

Experiment 4: Moving-Window Reading

Idiom facilitation Positive – – – Negative –

Note—Positive— indicates that increases in the relevant dimension are associated with facilitated idiom processing; Negative indicates that increases in the relevant dimension are associated with impaired idiom processing.


McGinnis (2002) argues that the aspectual properties of verbs in idiomatic expressions obey exactly the same rulesoperative in literal expressions. For example, both literaland idiomatic language adheres to the general rule thattelic (finite duration) verbs, but not atelic (ongoing activ-ity) verbs, can be modified by in, whereas atelic verbs, but not telic verbs, can be modified by for. Thus, consistent with the views of Hamblin and Gibbs, one can readily kick the bucket in an hour, but cannot as readily kick the bucket for months. It is possible that experiments that place idioms in such contexts may be necessary for examining how the temporal properties of verbs affect idiom comprehension.The present study, at the very least, suggests that idiomslike pay through the nose, whose verbs make direct refer-ence to figuratively associated actions, are not understood more readily than idioms like chew the fat, whose verbsdo not.

In addition to familiarity and decomposability, there were also effects of other variables. Literal plausibility exerted a facilitative effect in both Experiments 2 and 3;however, this likely occurred because participants’ mean-ingfulness judgments could be based on either a figurative or a nonidiomatic literal interpretation of the string. More interesting were the effects for word frequency associated with the constituent verbs and nouns of the idioms. Tothe extent that idioms are compositionally analyzed, we expected increased word frequency of an idiom’s parts to be positively related to comprehension of that idiom as a whole, similar to the logic employed in the morpho-logical processing literature on polymorphemic words (e.g., Baayen et al., 1997; Bertram et al., 2000; Bradley,1979; Burani & Caramazza, 1987; Burani et al., 1984;Colé et al., 1989; Schreuder & Baayen, 1997; Taft, 1979,2004). However, we found no effect of word frequencyof the noun in any experiment, and negative relationships between word frequency of the verb and several measures of comprehension.

High-frequency verbs were associated with reduced idiom processing in predictability judgments (Experi-ment 1); fixed-rate, speeded meaningfulness judgments (Experiment 3); and moving-window reading (Experi-ment 4). The inverse frequency correlation likely arose because infrequent verbs (e.g., twiddled ) are more pre-dictive of idiomatic completions than are frequent verbs (e.g., hit); thus, they facilitate processing of the idiomaticstring as a whole. High-frequency verbs may be less pre-dictive, because they occur in many different contexts and are highly polysemous (Gentner & France, 1988). In con-trast, low-frequency verbs are more bound to idiomaticconfigurations, are likely to be less polysemous, and are, perhaps, more concrete than high-frequency verbs. Thus, idioms with low-frequency verbs have higher cloze prob-ability than do idioms with high-frequency verbs. Indeed,in this study, the correlation between verb frequency and final-word predictability (a cloze probability measure) was significant (r .41).1 It is also noteworthy that frequency,but not compositionality, of the verb was associated withfacilitated idiom processing. This suggests that facilita-tion due to a low-frequency verb may be lexical, rather

ments and dependent measures, consistent with previouswork (Cronk & Schweigert, 1992; Gibbs, 1980; Nippold & Taylor, 2002; Schweigert, 1986; Titone & Connine, 1994b). Given that familiarity is a likely indicator of howidiomatic strings are configured in memory, we take this result to be evidence that idiomatic sequences are directly retrieved to some extent during comprehension.

In contrast with familiarity, the decomposability vari-able and its interaction with familiarity exerted less consis-tent effects on comprehension. There was some evidence of facilitative effects of decomposability in tasks that re-quired a semantic judgment about the meaningfulness of the idiomatic string, but no effect of decomposability onthe two measures that were less likely to direct attentionto idiomatic meanings as a whole (i.e., predictability rat-ings in Experiment 1, and moving-window reading in Ex-periment 4). Moreover, global decomposability exerted a greater effect on paper-and-pencil meaningfulness ratings (Experiment 1) than on idioms, which were less familiar. With respect to decomposability of the constituent words of idioms, the only reliable evidence was a facilitative ef-fffect of noun decomposability in the meaningfulness ratings of Experiment 1. Thus, decomposability had a facilitative influence on comprehension, but only when attention was focused on the meaningfulness of the phrase.

The absence of verb decomposability effects contrasts with a previous study that examined the semantic contri-bution of the verb in comprehending nondecomposable idioms (Hamblin & Gibbs, 1999; see also McGinnis,2004). One possibility is that the discrepancy betweenthe present results and those of Hamblin and Gibbs arose from methodological differences between the studies. Hamblin and Gibbs (Experiment 1) presented idiomaticphrases with either their preferred definitions (e.g., kick the bucket to die quickly), or their dispreferred defini-tions (e.g., kick the bucket to die slowly), in a forced-choice rating task. Participants in this task read each idiomand circled the definition they believed best captured the figurative meaning. They found that comprehenders cir-cled the preferred interpretation more frequently than they did the less preferred interpretation, consistent with the view that the semantics of the verb affects comprehension. Subsequent experiments demonstrated a similar patternof results. However, it is possible that participants based their decisions on metalinguistic judgments, because at-tention was explicitly focused on the relationship betweenthe verb and the figurative meaning of the phrase. Thus, participants may have attended more to semantics of the verb than they normally would during comprehension. Inaddition, given the offline nature of the task, participants would certainly have had enough time to contemplatethe semantic relationships between constituent verbs and figurative meanings and to choose from the two options explicitly provided.

However, it is possible that to observe the kinds of verbeffects reported by Hamblin and Gibbs (1999) in an onlinesituation, one would have to create an experiment that ex-plicitly manipulates aspectual (i.e., event structure) proper-ties of the verbs involved. Similar to Hamblin and Gibbs,


2007; Thibodeau & Durgin, 2008), whereas others do not (Glucksberg, Brown, & McGlone, 1993; Keysar & Bly,1999; McGlone, 2007).

However, given the open-ended nature of our global decomposability instructions, it is likely that the decom-posability assessment in this study, as well as in previous studies (e.g., Titone & Connine, 1994b), does not precludethese other characterizations. Rather, inspection of theidioms rank-ordered on the global decomposability vari-able reveals that participants may have been somewhatsensitive to these variables, but confused about how tomake categorizations that respect crisply defined psycho-linguistic categories. Thus, in the range of decomposabil-ity agreement between 45% and 55%, we find normallydecomposable idioms (e.g., He popped the question; He hammered a beer), abnormally decomposable idioms (e.g., She spilled the beans; She walked a tightrope), and metonymically based or nonisomorphic idioms (e.g., He knit his brow; She hit the sack). The same pattern holdskkfor the 85% to 95% decomposability agreement range. Yet again, we find normally decomposable idioms (e.g., She covered her tracks; She changed her mind ), abnormallydecomposable idioms (e.g., He overshot the mark; They spread the word ), and metonymically based or noniso-morphic idioms (e.g., She packed her bags; She turned his head ). Moreover, a similar pattern would hold if we were to focus exclusively on normal decomposability ratings, rather than on global decomposability ratings. Therefore, different conceptions of compositionality were not uni-formly classified as being nondecomposable in the con-text of this study. Rather, participants expressed their sen-sitivity to these different conceptions of decomposability in their offline ratings, but nevertheless failed to show dramatic or consistent decomposability effects during on-line comprehension. Thus, consistent with Abel (2003),Tabossi et al. (2008), and Titone and Connine (1994b), thesubdivisions of idiom decomposability seem to be moredifficult for comprehenders to make in practice than they are for psycholinguists to make in theory.

Taken together, the results of this study suggest that when people encounter the verb of verb-x-noun idioms,they generate simultaneous activation for the semanticrepresentation of its normal literal interpretation, and they may also begin to accrue activation for a configured figu-rative representation of the idiom. When comprehendersencounter subsequent portions of the idiom, the processes initiated at the verb continue, although now it is morelikely that the figurative activation begins to increase, be-cause more of the configuration is revealed. Finally, when comprehenders encounter the final word of the idiom (i.e., the noun, in the present study), both the idiomatic mean-ing and the products of a literal compositional analysis of the string are available, and at this point, a specific mean-ing or interpretation must be selected or integrated into the unfolding discourse context.

Thus, when one considers idiomatic processing as a whole, a variety of factors modulate comprehension from the start, and all sources of information interact in a time-dependent fashion. For example, if an idiom is highly fa-

than semantic, in nature. The result is therefore consistentwith the tenets of the configuration model (e.g., Cacciari& Tabossi, 1988; Tabossi et al., 2005), according to whichidiomatic meanings are retrieved only after recognition of the idiom as a configuration takes place.

This issue touches on a debate in corpus research on fixed expressions, which include phrasal idioms of the kind studied here (e.g., Fellbaum, 2007; Moon, 1998). For example, Cowie (1999) discusses Moon’s corpus study, inwhich only approximately 40% of the fixed expressions studied occur at a rate better than chance, thus undermin-ing any frequency-based view of idioms. Rather, Cowie argues that it is the structural or lexical invariance of idi-oms that is more associated with the “fixedness” of fixed expressions than the number of times such expressions areencountered in ongoing language. Although the conclu-sions of corpus studies are dependent on characteristicsof the corpus under investigation, it is possible that the fa-miliarity effect observed here and in previous studies may have something to do with lexical invariance or structuralproperties of idioms other than frequency. Indeed, most,if not all, studies of idiom familiarity or frequency are based on subjective ratings of familiarity. Thus, if multiplefactors give rise to subjective impressions of familiarity,those factors will be represented in any set of ratings. In the context of the present study, this implies that the fa-miliarity ratings obtained may have been based not only on participants’ impressions of how frequently they en-counter the idioms presented, but also of how often thoseparticular words within the idiom configuration occur to-gether as an invariant unit.

One potential limitation with the present study is its re-liance on the notion of compositionality and decompos-ability proposed by Nunberg (1978) and Gibbs and col-leagues (Gibbs & Nayak, 1989; Gibbs, Nayak, & Cutting,1989), when other conceptualizations are available. For example, Geeraerts (1995) proposed that idioms may becompositional, even if their parts have nothing to do withthe figurative meaning directly (e.g., saw logs). Thus, theNunberg classification scheme may not be adequate, be-cause it does not account for this indirect conceptual link. As an alternative, Geeraerts proposes the orthogonal con-structs of motivatedness and isomorphicity for character-izing differences in compositionality among idioms. Ac-cording to this scheme, the idiom saw logs (meaning to“sleep” or “snore”) is motivated, in that one can appreciatewhy the idiom refers to its figurative meaning; however it lacks isomorphicity because the parts saw and logs donot map directly to the act of sleeping. Similarly, Gibbs (1995) argues that idioms may bear metonymic relations to their figurative meanings, as in the idiom bite the dust, in which dust metonymically refers to what happens to dead tbodies over time. Idiomatic meaning may also be based on tacit knowledge of conceptual metaphors, such as the mind as a container, which are assumed to clarify the mapping of idioms such as spill the beans to their figura-tive interpretations, although there is mixed evidence thatsuch conceptual metaphors directly affect comprehension. Some studies find positive evidence (Gong & Ahrens,


normal compositional analysis of the string (e.g., Titone& Connine, 1999). Furthermore, the fact that idiomatic meanings are creatively extended and syntactically modi-fied during production requires that people be sensitive to the individual words and their relation to the figurative meaning of the phrase as a whole (Gibbs & Nayak, 1989;Gibbs & O’Brien, 1990; McGlone, Glucksberg, & Cac-ciari, 1994). However, it is also clear that idioms enjoy acomprehension advantage over newly encountered literal or nonliteral sequences, presumably because they are fre-quently encountered and tend to be used in structurallylimited ways. Indeed, a number of previous studies haveshown that when one breaks the formal structure of idi-oms by changing their syntactic form, replacing compo-nent words with synonyms, or inserting new lexical items within the configuration, the idioms’ processing advan-tage over nonidiomatic language is reduced or lost (Gibbs & Nayak, 1989; Gibbs & O’Brien, 1990; McGlone et al., 1994; Van de Voort & Vonk, 1995). Thus, manipulations that disrupt the processing of the idiom as a configured unit and call attention to the phrase as a compositional en-tity can impair comprehension of the idiom, presumably by impeding direct retrieval.

Thus, idioms are represented and retrieved as units that can interact with an ongoing compositional analysis and other relevant constraints in a temporally dynamic way.In this study, we offer concrete examples of the kinds of simultaneous constraints that may be important (e.g., fa-miliarity, compositionality, word frequency, and literal plausibility), as well as suggestions about the differenttime courses according to which each are operable (e.g.,effects of familiarity or word frequency at the point of thefirst word; effects of global decomposability by the end of the string). The application of general theoretical ap-proaches to nonliteral language may facilitate new ways of studying idiom processing. For example, factors tradi-tionally emphasized by constraint-based models of normal comprehension (e.g., verb subcategorization preferences, contextual effects) are relevant to idioms, yet there is cur-rently little contact between the sentence processing and idiom processing literatures. A constraint-based view of idioms might also encourage the development of compu-tational simulations that incorporate idiomatic language. Such approaches would invigorate our understanding of idioms and emphasize their status as normal componentsof language that must be embraced by normal models of comprehension.

In summary, the results of this study suggest that peo-ple make use of several relevant sources of information incomprehending idiomatic expressions, and that decom-posability is just one of many factors that can influence comprehension under certain circumstances. For English phrasal idioms, global decomposability exerts a facilita-tive influence on comprehension when an experimen-tal task focuses attention overtly on phrase meaning, or when postaccess integration is necessary (see, e.g., Titone& Connine, 1999). In contrast, variables such as phrasefamiliarity and verb frequency are related to initial re-trieval of idiomatic configurations as lexicalized units.

miliar, and thus more configured in memory, activation of the idiom representation accrues sooner and with greater strength than if the idiom is not familiar. This is evidenced by the many observations of robust familiarity on idiomcomprehension (Cronk & Schweigert, 1992; Gibbs, 1980; Nippold & Taylor, 2002; Schweigert, 1986; Titone & Con-nine, 1994b). However, idiom activation may begin to ac-crue early for low-familiar idioms whose verbs are rare and more uniquely identifiable within the idiomatic context. If an idiom is literally plausible and the word constituents donot bear any relation to the figurative meaning, it may be more difficult to select and integrate the idiomatic mean-ing than if the idiom is literally implausible (e.g., Titone & Connine, 1994a; Titone, Holzman, & Levy, 2002). If the idiom is not familiar, and thus direct retrieval of aconfigured meaning is difficult or impossible, the final interpretation will result from the ongoing compositionalanalysis exclusively, or to a large extent. This is illustrated by the facilitative effects of increased decomposability for low-familiar idioms (the present study), children who arejust learning idioms (e.g., Caillies & Le Sourn-Bissaoui,2006; Nippold & Taylor, 2002), and second-languagelearners (e.g., Abel, 2003).

In this way, a hybrid view of idiom comprehensionmight be more aptly described as a multidetermined, or constraint–satisfaction, process (e.g., MacDonald, Pearl-mutter, & Seidenberg, 1994; MacDonald & Seidenberg,2006; St. John & McClelland, 1990) that is no differentfrom what occurs normally during language compre-hension, but with the three specific provisions: Familiar idiomatic sequences are represented as units in memory,their semilexicalized figurative meanings may be acti-vated prior to the end of the sequence, and these phrasal meanings may interact with the ongoing compositionalanalysis of phrasal meaning. Within such a model, it isalso important to consider that different sources of infor-mation may become available according to different timecourses; thus, there may be temporal constraints on how information interacts during comprehension. For example, although the semantics of the individual words are avail-able as they are encountered (or shortly thereafter), globaldecomposability at a phrase level cannot be determined definitively until the last word is encountered and inte-grated with previous words, for most verb-x-noun idioms.Thus, differences between decomposable and nondecom-posable idioms may be most likely to occur at later stagesof processing—that is, at the offset of the phrase or later.

There are advantages of a constraint-based view of idiom processing, as other authors have noted for non-literal sequences, such as proverbs and metaphors (e.g.,Gibbs, 2006; Katz & Ferretti, 2001, 2003). First, they ac-commodate much of the psycholinguistic data, with re-spect to all dimensions known to affect idiom processing.It is clear from both the psycholinguistic and linguistic literatures that idioms cannot be thought of merely as ar-bitrary, noncompositional sequences (i.e., the standard definition of idioms). Compositionality can facilitate idiom processing after a figurative meaning has been re-trieved and competes for selection or integration with a


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It is noteworthy that similar conclusions have emerged in the growing literature on the production of idiomatic expressions (Cutting & Bock, 1997; Sprenger, Levelt, & Kempen, 2006). Thus, we propose a model that is con-sistent with a hybrid approach to idiom processing (e.g.,Cacciari & Tabossi, 1988; Titone & Connine, 1999) and with general constraint-based approaches (e.g., MacDon-ald et al., 1994; MacDonald & Seidenberg, 2006; St. John& McClelland, 1990) that have been previously applied to figurative language (Gibbs, 2006; Katz & Ferretti, 2001, 2003). Given the recent focus on idioms within linguis-tics (e.g., Jackendoff, 2002; Marantz, 2005), future work ought to probe more deeply to determine how compre-hension data on idioms might adjudicate between gen-eral linguistic frameworks of language representation and process.

AUTAA HOR NOTE

We gratefully acknowledge support from the Natural Sciences and Engineering Research Council of Canada in the form of a doctoral grantto the first author and a discovery grant to the second author; the Canada Research Chairs Program; and the Canadian Foundation for Innovation.We thank Kristine Onishi for comments on the manuscript. Correspon-dence concerning this article should be addressed to D. Titone, Depart-ment of Psychology, McGill University, 1205 Dr. Penfield Ave., Mon-treal, QC, H3A1B1 Canada (e-mail: [email protected]).

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NOTE

1. Some comments regarding predictability are relevant here. In thisexperiment, we considered predictability to be an outcome variable; thus,it was treated as a dependent variable only in Experiment 1. We did notconsider predictability to be an independent variable in Experiments 2 through 4 due to its highly skewed distribution and significant positiverelationship with familiarity and verb word frequency.

ARCHIVED MATERIALS

The following materials associated with this article may be accessed through the Psychonomic Society’s Norms, Stimuli, and Data archive,www.psychonomic.org/archive/.

To access these files, search the archive for this article using the journalname (Memory & Cognition(( ), the first author’s name (Libben), and the publication year (2008).

FILE: Libben-M&C-2008.zipDESCRIPTION: The compressed archive file contains three files:LibbenTitone-ReadMe.txt, information for the user.LibbenTitone-Norms.txt, normative data for 210 idiomatic phrases.LibbenTitone-Norms.xls, the above information in Excel format.

AUTHOR’S E-MAIL ADDRESS: [email protected]

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APPENDIX ATest Booklet 1

Instructions for Predictability Ratings

On the following pages you will find a list of sentence fragments. Your task is to complete these sentenceswith the first word that comes to mind and to write your answer on the line at the end of each fragment. For example, you may get an incomplete sentence such as The boy swung the _______. In this case, the firstword that might come to mind is bat. If this were so, you would write the word bat in the space provided.tThis would complete the phrase as The boy swung the bat.

Instructions for Global Decomposability Ratings (Based on Titone & Connine, 1994b)

In the following section you will make a judgment as to the “decomposability” of various idiomatic phrases. Decomposable idioms are defined as phrases whose individual components contribute to their overall meanings. Idioms whose individual words do not make such a contribution are called nondecomposable.


APPENDIX BTest Booklet 2

Instructions for Global Decomposability Ratings and Normal/Abnormal Ratings(Based on Gibbs & Nayak, 1989, and Gibbs, Nayak, & Cutting, 1989)

PART 1

For each of the idioms on the following pages you will need to make two judgments. First, you must sort allthe idioms into two categories: idioms whose words make some unique contribution to the phrase’s figura-tive meaning (decomposable idioms) and idioms whose individual words do not make such a contribution(nondecomposable idioms).

An example of a decomposable idiom would be the phrase “cover up your tracks” which has two wordsthat are related to the idiomatic meaning. The word “cover” is closely related to the idea “hide,” whilethe word tracks refers to “evidence of your actions.” Another example of a decomposable idiom is “can’t believe my ears” where, again it is apparent how the individual words map onto the figurative meaning(“unable to believe what is being said”).

An example of a nondecomposable idiom would be “be the cat’s whiskers.” This idiom means to “be thebest” and would be called nondecomposable because the component words do not directly relate to theoverall meaning of the idiom.

Please mark an X on the appropriate line (Decomposable or Nondecomposable) to indicate your choice.For now you can ignore the bottom section that says “Normal” and “Abnormal.” This will only be relevantin the second part of the experiment. Please take your time to make the best possible answers.

PART 2

Now that you have sorted all the idioms into these two categories, you will go back only to the idiomsthat you have decided are decomposable and sort them into two groups, normally and abnormallydecomposable.

Some decomposable idioms have words whose meanings directly related to their figurative interpretations.Again we will use the example of “cover up your tracks” which has two words that are closely related totheir individual figurative meanings. The word cover is closely related to the idear hide, while the word tracks refers to evidence of your actions. Idiom phrases like this are called “normally decomposable.”

On the other hand, there are idioms that are decomposable but whose individual words have a more meta-phorical relation to their figurative meanings. Thus, the phrase “meet your maker” means “to die.” Herethere is a metaphorical relationship in which “maker” is referring to God, and therefore when you “meetyour maker” you have died. Idioms such as meet your maker are called “abnormally decomposable.” An-rother abnormally decomposable idiom would be to button your lips which means “not to speak.” Here thereis a metaphorical relationship between “buttoning” and “closing” your lips so as not to speak.

Please return to the beginning of the booklet and for each of the idioms that you marked as “Decompos-able” mark an X next to either “Normal” or “Abnormal” to indicate your choice. Nondecomposable idiomsdo not need to be subdivided into “Normal” and “Abnormal” categories.

APPENDIX A (Continued)An example of a decomposable idiom would be the phrase “cover up your tracks” which has two words thatare literally related to the idiomatic meaning. The word cover is closely related to the idear hide, while theword tracks refers to evidence of your actions. Another example of a decomposable idiom is can’t believemy ears where, again it is apparent how the individual words map onto the figurative meaning (unable tobelieve what is being said ).

An example of a nondecomposable idiom would be “be the cat’s whiskers.” This idiom means to “be thebest” and would be called nondecomposable because the individual word meanings do not directly relateto the overall meaning of the idiom. Please read each phrase and its overall meaning (presented in paren-theses) and then indicate whether you feel the phrase is decomposable or nondecomposable by markingan X on the appropriate line.


APPENDIX CTest Booklet 3

Instructions for Meaningfulness and Familiarity Ratings

For each of the phrases on the following pages you will need to make two judgments. First, decide howfrequently you have seen, heard or used the phrase without consideration of whether or not you know itsmeaning. Make your ratings on a scale of 1 to 5, with 5 signifying that you see or hear the phrase veryfrequently and 1 signifying you have never or almost never heard or seen the phrase. At the midpoint of the scale, a rating of 3 would indicate that you have come across the phrase moderately often. Please usethe full range of the scale in making your decisions.

After you make your familiarity judgment, you will rate the same phrases on a scale of 1 to 5, dependingon how well you know the meaning of the phrase. A rating of 1 would mean that you have absolutely noidea what the phrase means. A 3 means that you are moderately certain of what it means, and a 5 would indicate that you are 100% certain of the phrase’s meaning and could easily put it into your own words. Besure to use the full scale when making your judgments.

Instructions for Literality Ratings

For each of the idioms on the following pages you will need to make a literality judgment. While all of theidioms have a meaningful idiomatic or figurative interpretation, only some of them have a well-formed literal meaning. For example, the idiom let the cat out of the bag figuratively means,g to reveal a secret and literally means, to release a cat. However, the idiom to give the cold shoulder, which figuratively meansto ignore, does not have a clear literal meaning (if any at all) as compared to let the cat out of the bag (e.g.,git is unclear what it means to literally give a cold shoulder).

Your task in rating these idioms is to decide if there is a possible literal interpretation, and if so, how plau-sible it is on a 5-point scale. That is, rate the idioms based on how likely the literal meaning of the phrase is(if you believe one exists). A rating of 1 would indicate that an idiom definitely does not have any possibleliteral interpretation and therefore is completely implausible literally. A rating of 5 would indicate thatthe idiom definitely has a clear and well-formed literal interpretation that is very plausible. Intermediatevalues of the scale should reflect your judgments of the plausibility of these phrases interpreted literally.Please try to use the entire scale when doing your ratings.

Instructions for Verb/N// oun Relatedness Ratings

For each of the following phrases (in bold letters) you will need to make two judgments. These judgmentsinvolve relating each phrase to its figurative meaning, which is paraphrased in brackets.

First you will rate how well the verb of each phrase (the first underlined word) relates to the entire mean-ing of the phrase. A rating of 5 means that the verb is highly related to the overall meaning of the phrasewhile a rating of 1 means that the verb is completely unrelated to the overall meaning of the phrase. Arating of 3 means that the verb is somewhat related to the overall meaning of the phrase. An example of acase in which the verb is highly related to the overall meaning of the phrase is save your skin. In this casethe word save is related to the overall phrase meaning (to protect yourself ) and therefore, this verb would get a high rating.

The second rating that you will perform will follow the same procedure as outlined above, but will bebased on how well the noun (the second underlined word) relates to the overall meaning of the phrase. Anexample of a phrase in which the noun is not very related to the overall meaning of the phrase is chew thefat. In this case it is unclear how the word fat is related to the overall meaning of the phraset to gossip and,therefore, would get a lower rating. As with the verbs, a rating of 5 means that the noun is highly related to the figurative meaning of the phrase while a rating of 1 means that the noun is completely unrelated tothe phrase. A rating of 3 means that the noun is somewhat related to the figurative meaning of the phrase.An example of a phrase in which the noun would be related somewhere in the middle of the scale is wasteyour breath in which the word breath is somewhat related to the action of speaking and therefore partiallycontributes to the overall meaning of the phrase (to speak to no avail ).

(Manuscript received February 26, 2006; revision accepted for publication March 24, 2008.)

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