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Emergent and Common Features InfluenceMetaphor InterpretationAngela H. BeckerPublished online: 17 Nov 2009.

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METAPHOR AND SYMBOL, 12(4), 243-259 Copyright O 1997, Lawrence Erlbaum Associates, Inc.

Emergent and Common Features Influence Metaphor Interpretation

Angela H. Becker Indiana University Kokomo

Metaphor interpretations may contain four types of features: common (features included in one's usual representations of both topic and vehicle), vehicle-shared (included in one's representation of the vehicle, but not the topic), topic-shared (included in one's representation of the topic, but not the vehicle), and emergent (not part of one's usual representation of either topic or vehicle). Two groups of partici- pants, each given different instructions, interpreted "A is a B" metaphors. Another group of participants listed features of individually presented topic and vehicle words. Features from metaphor interpretations were compared with features listed for individual words in order to identify the four types of features. Significantly more vehicle-shared and emergent features appeared in interpretations than either common or topic-shared features, regardless of interpretation strategy. Common features were judged as most important to metaphor interpretation and were significantly more important than emergent features. Altering a metaphor's vehicle produced greater changes in emergent content than did altering the topic, suggesting that emergent features were influenced primarily by one's representation of the vehicle.

When a person interprets a novel metaphor such as "A child is a sponge," that interpretation has the potential to contain information from four logically possible sources. One possibility is that attributes or features one usually thinks of only in response to the vehicle (i.e., sponge) will be imported into the interpretation. For example, absorbent is likely to be thought of as a feature of sponges, but not as a feature of children. However, this feature still might be imported into the interpre- tation of "A child is a sponge." Such afeature might be referred to as vehicle-shared because it comes to mind when considering the vehicle as a single word as well as when thinking about the metaphor's interpretation. A second source of information

Requests for reprints should be sent to Angela H. Becker, Social and Behavioral Sciences, Indiana University Kokomo, 2300 S. Washington, P.O. Box 9003, Kokomo, IN 46904-9003. E-mail: abecker@iukfsl .iuk.indiana.edu

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for a metaphor's interpretation is features one usually thinks of only in response to the topic (i.e., child). Small would be a topic-shared feature if it is thought of both in relation to children and when interpreting the metaphor but is not thought of in relation to sponge. Third, common features are thought of when interpreting the metaphor and are also thought of in relation to both the topic and vehicle. For example, dirty is a feature that might come to mind for both children and sponges as well as when interpreting the metaphor. The fourth and most intriguing possi- bility is emergent features. Emergent features are those that appear in a metaphor's interpretation but are not typically thought of in relation to either the topic or the vehicle alone. For example, releases (i.e., sponges release fluid easily when squeezed and children release their emotions openly) might be a feature that results from the interpretation of ' X child is a sponge." However, one would not typically think of this feature in relation either to children or to sponges.

Several models of metaphor make predictions about which of these feature types will occur most frequently in metaphor interpretations. This study examines the predictions of three models: (a) the salience imbalance model (Ortony, 1979), (b) an interactive property attribution model (Glucksberg, McGlone & Manfredi, 1997), and (c) the domain interaction model (Tourangeau & Sternberg, 1982).

The salience imbalance model (Ortony, 1979) proposes that the interpretation of a metaphor is composed primarily of common features (i.e., those shared by topic and vehicle). However, according to Ortony, the interpretation should contain only those common features that are of high salience for the vehicle and of low salience for the topic. For example, "Billboards are warts" makes a good metaphor because the common feature ugly is of high salience for warts, but of low salience for billboards (Ortony, 1979, p. 165). Thus, the vehicle is considered the dominant concept in a metaphor.

In contrast to the feature-matching process described earlier, Glucksberg et al. (1997) proposed that metaphor interpretation occurs through a process of interac- tive property attribution. In this view, a topic suggests "relevant dimensions," and the vehicle provides values on those dimensions that can be applied to the topic. For example, for the metaphor "A child is a sponge," a relevant dimension of child is level of ability to absorb and the value of that dimension provided by sponge is great absorbing ability.

An implication of this model is that features listed in metaphor interpretations are more likely to be vehicle-shared than common. However, not just any feature of the vehicle will do. Only those that can be appropriately applied to some dimension of the topic will be incorporated into the interpretation.

The third model, the domain interaction model (Tourangeau & Sternberg, 1982), proposes that metaphor interpretation involves discovering an analogous relation- ship between the topic within its domain and the vehicle within its domain. To interpret a metaphor, parallels are constructed between features (or relations between features) that exist in the topic domain and features (or relations between

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features) that exist in the vehicle domain. Furthermore, interpretation will often require transformations of both topic and vehicle features in order to locate those that are parallel. (For explanations and examples of several types of transforma- tions, see Tourangeau & Sternberg, 1982.)

Through this process of searching for analogous or parallel features and making transformations, one comes to view the topic, the vehicle, and the topic and vehicle domains in new ways (Kelly & Keil, 1987; Tourangeau & Sternberg, 1982). I suggest that thinking of the objects in these new ways may lead a person to consider as relevant to a metaphoric communication attributes that are not part of the typical representations of those objects outside the context of the metaphor. In other words, the domain interaction theory implies that emergent features should occur quite frequently in metaphor interpretations.

None of the models preclude the occurrence of any of the four kinds of features in metaphor processing. Hence, their rival claims are only about the relative frequency and importance of each of the types of features. For example, the domain interaction model does not preclude the occurrence of common, vehicle-shared, and topic-shared features; it simply suggests they will assume a lesser role in the interpretation. Tourangeau and Sternberg (1982) suggested that distinctive features of the vehicle will be transferred to the topic (i.e., vehicle-shared features) only in cases in which the topic is very unfamiliar. However, even in these cases, they suggested that distinctive vehicle features may not directly apply to the topic. In such cases, knowledge of the topic's domain (rather than knowledge of the topic itself) would have to be used to infer appropriate analogies. The emphasis in this model is on creating parallels among features through transformation (rather than searching for identical or almost identical matches or making simple transfers of features from vehicle to topic or vice versa). This emphasis on transformations should lead to the prediction that emergent features would be more frequent, more important, or both more frequent and more important than any of the other features.

The domain interaction model also proposes that a metaphor's interpretation is most likely to be derived from features that are particularly distinctive for the vehicle and that help differentiate it from other exemplars within its own domain (Tourangeau & Rips, 1991; Tourangeau & Sternberg, 1982). Perhaps the identifi- cation of a distinctive vehicle feature initiates the use of the transformation processes involved in making a novel analogy. If this is the case, one would expect that the precise content of any emerging features would be rather heavily dependent upon the vehicle of the metaphor.

Support for the salience imbalance model comes from experiments in which participants endorsed common features as being more salient for vehicles than for topics of metaphors (Ortony, Vondruska, Foss, & Jones, 1985; Readence, Baldwin, Martin, & O'Brien, 1984). However, support for salience imbalance is not univer- sal. For example, Gentner and Clement (1988) failed to find the low-topickigh-ve- hicle salience pattern in several experiments. Similarly, Tourangeau and Rips's

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(1991) participants rated common features as slightly but not significantly more salient for the vehicle than the topic of a metaphor. The researchers did find, however, that participants rated common features as being highly relevant to metaphor interpretations and participants rated metaphors whose interpretations were high in common features as better, more apt, and more comprehensible than those low in common features.

These findings provide valuable insight into Ortony's prediction of salience imbalance in common features. However, participants in a study by Tourangeau and Rips (1991) interpreted metaphors and also listed features of the metaphors' topics and vehicles. The resulting interpretations included all four feature types described earlier, and emergent features accounted for the largest percentage of interpretation features, as predicted by the domain interaction model. Although the vehicle-shared features also accounted for a large portion of the interpretation (as predicted by the property attribution model), there were far fewer vehicle-shared than emergent features. Common features, emphasized by the salience imbalance approach, and topic-shared features each accounted for only a small percentage of the interpretation. Tourangeau and Rips also showed that interpretation features were rated as being more distinctive for the vehicles than for the topics of metaphors as predicted by the domain interaction model.

My study examined "A is a B" metaphors---copula tropes-and the relation between the frequency and importance of the four types of features in the interpre- tations of the metaphors. Participants were asked to list features for individual words outside the context of metaphors or to interpret metaphors containing those same words. A between-subjects design was used in order to preclude the possibility that emergent features would occur simply because participants would assume they should create different features for metaphor interpretations than they produce for either topic or vehicle alone. This study also contains several other departures from previous work that allow it to address important issues regarding feature types in metaphor interpretation. These departures include (a) use of two different types of instructions in order to elicit different interpretation strategies, (b) ca~nstruction of stimuli in a manner that produced many pairs of metaphors from which to compare the power of the vehicle and topic, and (c) use of an alternative type of metaphor in order to add to the generalizability of previous findings.

The theories may make different predictions about which features should occur most frequently because they make different assumptions about the strategies people use when interpreting metaphors. The interactive property attribution model seems to assume a strategy of attributing some characteristics of the vehicle to the topic, which should result in a large number of vehicle-shared features. The strategy suggested by the salience imbalance model is to search for identical features that are shared by topic and vehicle (i.e., common features) and that offer salience imbalance. If features of the topic and vehicle must be altered a bit to find a "shared"

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EMERGENT AND COMMON FEATURES 247

feature, then they would be the emergent features suggested by the domain interaction model.

In this study, two sets of instructions were given to participants to ensure that any results were not due to a single instructional emphasis on vehicles or shared features that might favor one theoretical strategy over another. Some participants were instructed to list features of the vehicle that are being used to describe or explain the topic. A second set of instructions asked other participants to list features that the topic and vehicle share or have in common.

This study also explored the origin of emergent features by examining whether the content of emergent features was more dependent on the topic or the vehicle of a metaphor. Metaphors were constructed in sets by choosing two words to be used as topics and two to be used as vehicles for each set and then producing all possible combinations of the topics and vehicles within each set. The resulting metaphors were given to two different groups of participants such that each participant responded to each topic and each vehicle only once. This arrangement allowed comparison of (a) responses from metaphors with the same topic but different vehicles and (b) responses from metaphors with the same vehicle but different topics. Thus, I could determine whether people's interpretations (in particular, their use of emergent features) were more similar when the metaphors used the same topic or when they used the same vehicle.

METHOD

Participants

Eighty-eight introductory psychology students were randomly assigned to one of thee conditions. Random assignment resulted in 26 students in the word condition (13 women and 13 men with amean age of 18.62), 29 students in the share condition (17 women and 12 men with a mean age of 18.90), and 33 students in the attribute condition (22 women and 11 men with a mean age of 18.72).

Materials

Ten groups of 4 metaphorical sentences each were constructed for use in the share and attribute conditions (i.e., 40 metaphors in total). The 4 metaphors in each group were created from all possible pairings of two unique topic words with two unique vehicle words. For example, two topics (mind and child) and two vehicles (sponge and closet) were used to create the following group of 4 metaphors: "The mind is a sponge," "The mind is a closet," "A child is a sponge," "A child is a closet." By

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using this method to construct metaphors, each group of 4 metaphors resulted in two pairs of metaphors that had the same topic but different vehicles (e.g., "The mind is a sponge"-"The mind is a closet" and "A child is a spongeM-"A child is a closet") and two pairs of metaphors that had different topics but the same vehicle (e.g., "The mind is a sponge"-"A child is a sponge" and "The mind is a closet "-"A child is a closet"). See Appendix A for a complete list of the 10 metaphor groups. Many of these metaphors have been used elsewhere (see, e.g., Camac & Glucksberg, 1984; Katz, Paivio, Marschark, & Clark, 1988; Lakoff & Johnson, 1980). Words used as topics and vehicles in the metaphors were also used as stimuli in the word condition.

Five qualities of these metaphors were rated by a separate group of 32 students. Half rated the metaphors in Sentence Set 1, and half rated those in Sentence Set 2. The following 7-point scales were used: ease of interpretation (1 = very difJicult, 7 = very easy), degree of metaphoricity (1 = very literal, 7 = veryfigurative), metaphor goodness (1 = very poor metaphor, 7 = very good metaphor), felt familiarity (1 = very unfamiliar, 7 = very familiar), and semantic similarity of topic and vehicle (1 = not at all similar, 7 = very similar). Table 1 presents the mean rating and standard deviation for each scale across all metaphors, as well as the mean ratings for the lowest and highest rated individual metaphors for each scale.

Participants in the main study each received a 20-page booklet containing instructions that described the tasks they were to complete, an example of the task that clarified the written instructions, and the stimulus items for their condition. At the top of each page in the booklet was either a single word (for the word condition) or a metaphorical sentence (for the share and the attribute conditions). Each share and attribute condition booklet contained 20 of the 40 metaphors described pre- viously. Approximately half the participants in each of these two metaphor condi- tions received the 20 metaphors in Sentence Set 1 and half received the 20 metaphors in Sentence Set 2 (see Appendix A). The metaphors were divided into these two sets such that each set contained only 2 metaphors from each of the 10 metaphor groups, with the constraint that these 2 metaphors did not have either the

TABLE 1 Mean Ratings and Standard Deviations for Metaphor Characteristic Scales Across

All Metaphors and Mean Ratings of the Lowest and Highest Rated Individual Metaphors

Scale M SD Lowest Highest --

Ease of interpretation 4.76 1.03 3.06 6.69 Degree of metaphoricity 4.45 .90 2.13 6.13 Metaphor goodness 4.58 1 .OO 2.75 7.00 Felt familiarity 4.32 1.49 1 S O 6.81 Semantic similarity 3.49 1.19 1.63 5.88

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same topic or the same vehicle. In each metaphor, the topic and vehicle were underlined. Word condition booklets contained 20 single words (i.e., one topic and one vehicle from each of the 10 metaphor groups described previously). Approxi- mately half of the participants in the word condition received Word Set 1 and half received Word Set 2 (see Appendix B).

Procedure

Data were collected from small groups of no more than 5 students each. Each participant was given a booklet and was asked to carefully read the metaphoric sentence or single word at the top of the first page, consider its meaning, complete a feature-listing task for that sentence or word, and then go on to the next page.

The feature-listing task differed slightly for each condition. Participants in the attribute condition interpreted each metaphor by listing the characteristics or features of the second underlined word (i.e., the vehicle) that were being used to describe or explain the first underlined word (i.e., the topic). Those in the share condition interpreted the metaphors by listing the characteristics or features that were shared or held in common by the underlined words (i.e., topic and vehicle). Participants in the word condition simply listed the characteristics or features of the single word. Regardless of condition, participants were given 1.5 min per metaphor or word to list as many features as they could think of. Most students finished the feature-listing task well within the time allotted.

After completing the feature-listing task for all 20 stimulus items, participants in all conditions rank ordered the features they listed for each metaphor or word in terms of their importance for that metaphor or word (1 = most important). Rather than provide rank orders immediately after they finished listing features for each stimulus item, participants completed the ranking task after all feature listing for all stimulus items was completed. This was done in order to prevent the participants from dwelling upon the importance of each feature before listing it. The listing task was intended to tap as many features as the participants could think of. Thinking about importance of attributes during the feature-listing task might have prevented participants from listing less important features.

RESULTS

In order to compare features listed across the three conditions within each grouping of four metaphors and their respective topics and vehicles, closely related features were combined. More specifically, synonyms (e.g., scary andfrightening), alter- native spellings and abbreviations (e.g., 0' and oxygen), and differing intensities

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of the same feature (e.g., lots of hair and hair) were accepted as the same feature. If a feature was written as a phrase and contained more than one concept (e.g., bright lights), the phrase was counted as one feature unless both of those concepts also appeared separately. In such cases, the compound was separated and counted twice (e.g., once for bright and once for lights).

This feature combination process was completed by six judges working in pairs. Discrepancies were resolved by discussion and majority vote among judges and by consultation with the author. The result was 10 lists of features (1 for each of the 10 stimulus groupings). For each of the 10 lists, all features that were not given by at least 2 participants in at least one of the conditions were dropped. The analyses that follow were based upon these amended feature lists.

Feature Types

Features listed by participants in the share and attribute conditions were classified as being one of the four types described in the introduction: common, vehicle- shared, topic-shared, or emergent. Thus, common features were those that were listed for the metaphor and were also listed for both the topic and the vehicle as single words. Vehicle-shared features were listed for both the metaphor and for the vehicle as a single word but were not listed for the topic. Topic-shared features were listed for the metaphor and for the topic as a single word, but were not listed for the vehicle. Emergent features were listed only in the metaphor interpretation and were not listed for either the topic or vehicle.

For each metaphor, the frequency of each of the four feature types was counted. This was done separately for both the share and attribute conditions. Features were counted both as types (i.e., counted only once no matter how often the feature was listed) and as tokens (i.e., counted as often as the feature was listed). Thus, if the common feature beautiful was listed five times for the metaphor "stars are diamonds" in the share condition, the type count for common features would be incremented by one, and the token count for common features would be incre- mented by five.

The mean number of common, vehicle-shared, topic-shared, and emergent features for the two instruction conditions are presented in Figure 1 (type counts) and Figure 2 (token counts). As can be seen from the two figures, regardless of whether one counts features as types or as tokens, participants produced more vehicle-shared and emergent features than either topic-shared or common features.

Instruction (share vs. attribute) x feature type (vehicle-shared, topic-shared, common, emergent) analyses of variance (ANOVAs) with metaphors treated as a random factor were conducted for both type and token counts. The type count analysis revealed a significant feature type main effect, F(3,234) = 81.41, p < .05, as well as a significant interaction, F(3,234) = 3.15, p < .05. The instruction main

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Common Vehicle-Shared Topic-Shared

Feature Emergent

FIGURE 1 Mean number of common, vehicle-shared, topic-shared, and emergent features per metaphor in the share and attribute conditions with features counted as types.

0

t 25 V)

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C m a, 0 I Common Vehicle-Shared Topic-Shared Emergent

Feature

FIGURE 2 Mean number of common, vehicle-shared, topic-shared, and emergent features per metaphor in the share and attribute conditions with features counted as tokens.

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effect was not significant. Post hoc analyses (Tukey's HSD) to explore the interac- tion revealed that significantly more vehicle-shared features were produced in the attribute condition than in the share condition (p < .05). Differences between the two instruction conditions for the other three feature types were not significant. Post hocs also indicated that, regardless of instruction condition, there were significantly more emergent and vehicle-shared features than either topic-shared or common features (p < .05) and significantly more topic-shared than common features ( p < .05). However, there was no significant difference between the number of emergent and vehicle-shared features.

The token count analysis produced significant main effects for both instruction, F(1,78) = 12.84, p < .05, and feature type, F(3,234) = 4 0 . 1 0 , ~ < .05, as well as a significant interaction, F(3, 234) = 4.57, p < .05. Post hoc analyses indicated that significantly more vehicle-shared and emergent features were produced in the attribute condition than in the share condition (p < .05). Differences between the two instruction conditions for the other two feature types were not significant. Regardless of instruction condition, there were significantly more vehicle-shared features than either emergent, topic-shared, or common features (p < .05). Also regardless of instruction condition, the difference between the number of topic- shared and common features was not significant. However, some differences between feature types depended on instruction condition. Thus, in the attribute condition, there were significantly more emergent features than either topic-shared or common features (p < .05), but in the share condition, these differences were not significant.

Importance Rankings

Although the sheer number of common features was not high, it is possible that when common features were listed, they were considered extremely important to the metaphor's interpretation. To test this possibility, mean importance rankings of each feature type were calculated for each metaphor from the rankings provided by participants in the share and attribute conditions. The rankings for only those metaphors for which all feature types were present were entered into a condition (share vs. attribute) x feature type ANOVA. The main effect for feature type was significant, F(3, 65) = 3.18, p < .05. Neither the condition main effect nor the interaction was significant. Post hoc analyses of the feature type main effect indicated that common features were considered significantly more important than emergent features (p < .05). All other comparisons of importance rankings between feature types were not significant. Mean importance rankings for each feature type were 2.60 for common, 2.73 for vehicle-shared, 2.84 for topic-shared, and 2.91 for emergent. Note that the lower the mean ranking, the more important the feature type was considered to be.

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Further exploration of the importance rankings given to common features by participants in the word conditions indicated that of the common features in the share and attribute conditions, 58% and 62%, respectively, were ranked as being more important for the vehicle word than for the topic word and thus fit a salience imbalance pattern. This difference between topic and vehicle rankings was signifi- cant for both instruction conditions, F(1,116) = 200.05, p < .05.

Origin of Emergent Features

Of particular interest in this study is the origin of emergent features. Presum- ably, emergent features do not just come out of the blue. It is most likely that these are such low-salient features of the individual topic or vehicle repre- sentations that participants simply fail to list them when considering topics and vehicles as isolated words. The question is, are emergent features influenced primarily by the representation of the topic or primarily by the representation of the vehicle?

To address this question, the specific content of emergent features was compared across metaphor pairs that differed in their topics but had the same vehicle (V-invariantpairs) and across metaphor pairs that differed in their vehicles but had the same topics (T-invariant pairs). For example, "The mind is a sponge" and "A child is a sponge" make a V-invariant pair, whereas "A child is a sponge" and "A child is a closet" make a T-invariant pair. For each metaphor pair, the number of emergent features that were the same across the two interpretations were counted and then divided by the total number of unique emergent features listed across both interpretations. The resulting number represents the percentage of overlapping features across the interpretations of the metaphor pair. This was done separately for both the share and attribute conditions.

If emergent features are influenced primarily by the representation of the vehicle, then there should be greater overlap of emergent features for V-invariant pairs, because they share the same vehicle, than for T-invariant pairs that have different vehicles. If emergent features are influenced primarily by the representation of the topic, there should be greater overlap of emergent features for T-invariant pairs, because they share the same topic, than for V-invariant pairs that have different topics.

The mean percentage of overlapping emergent features for V-invariant pairs was 13.85 for the share condition and 18.90 for the attribute condition. The mean percentage of overlap for T-invariant pairs was 8.85 for the share condition and 8.25 for the attribute condition. An ANOVA confirmed that, regardless of condi- tion, there was greater overlap for V-invariant than for T-invariant pairs, F(l , 76) = 17.50, p < .001. The main effect for condition and the interaction were not significant. Thus, the content of emergent features appeared to be more heavily

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influenced by the representation of the vehicle than the topic of the metaphor, regardless of the type of instructions that participants followed.

DISCUSSION

In this study, metaphor interpretations contained larger numbers of vehicle-shared and emergent features than either topic-shared or common features, regardless of the type of interpretation instructions given and regardless of the manner in which features were counted. The relatively greater frequency of vehicle-shared features than all other feature types when using token counts supports the feature type prediction of the property attribution model. The emergent features that I suggest might result from the transformations presented as part of the domain interaction model also occurred quite frequently. However, even when using the type count data, there were never significantly more emergent than vehicle-shared features. Thus, the frequency data lend a bit more support for the property attribution model than for the domain interaction model.

Analyses regarding the origin of emergent features also supported the property attribution model. The origin analyses indicated that there was greater overlap of emergent feature content for pairs of metaphors that shared the same vehicle than for pairs of metaphors that shared the same topic. Thus, emergents were influenced primarily by the representation of the vehicle rather than the topic. The fact that emergents depend heavily on the vehicle representation, combined with the finding that emergents received the lowest importance ranking of all four feature types, suggests that emergent features are ones that are initially considered very unimpor- tant to the vehicle term's representation. Seeing the word in a metaphor may cause a person to access some of these initially unimportant features and apply them to relevant dimensions of the topic as predicted by the property attribution model.

Evidence supporting the common feature predictions of the salience imbalance model was equivocal. There were relatively few common features, regardless of whether one looked at types or tokens. In fact, share interpretation instructions, which one would expect to boost the frequency of common features in comparison to the attribute instructions, did not produce significantly larger numbers of common features. However, roughly 60% of common features did exhibit salience imbalance. This supports similar findings of salience imbalance of common fea- tures by Readence et al. (1984) and Ortony et al. (1985) and the trend toward salience imbalance found by Tourangeau and Rips (1991). Furthermore, common features were ranked as more important than the other feature types, though the difference was significant only for the comparison with emergent features. Partici- pants in Tourangeau and Rips's study also considered common features to be more relevant than the other three feature types.

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Although the salience imbalance model cannot account for the existence of so few common features, perhaps the property attribution model can. These data indicated that vehicle-shared features occur frequently. An explanation based on the property attribution model is that much of the time, dimensions of enough importance to the vehicle that they are mentioned when describing the vehicle term alone are used to identify topic dimensions. (However, these are dimensions that one does not generally think of in regard to the topic term alone.) Then, the vehicle's values on those dimensions are transferred to the topic. Using a similar line of reasoning, one can elaborate on the property attribution model as currently stated to also explain common features. As before, dimensions of importance to the vehicle are used to identify topic dimensions, and the vehicle's values on those dimensions are transferred to the topic. However, in the case of common features, both the dimensions and values of the vehicle happen to be identical to those of the topic term. If these dimensions and values are important enough for the topic that one generally produces them when thinking of the topic term alone, common features would result. Although such precise identification of dimensions would not be expected to occur often when comparing two things that are not of the same literal category, it is likely to happen occasionally. It is not surprising that when common features do surface, people rate them as highly important to an interpre- tation simply because they are quite sure that others would not question their assertion that the topic and vehicle are similar with respect to such features. In other words, common features may be perceived as important precisely because they appear to present less risk of misinterpretation.

Finally, the two instruction conditions, each intended to encourage different interpretation strategies, produced only a few differences in results. As expected, attribute instructions lead to significantly more vehicle-shared features than did share instructions for both type and token counts. However, contrary to expecta- tions, the share instructions did not produce either significantly more common or emergent features than the attribute instructions. In fact, when using token counts, it was the attribute instructions that produced significantly more emergents than the share instructions. At this time, it is unclear why attribute instructions produced the expected differences in feature type frequency but share instructions did not.

My study and the study by Tourangeau and Rips (1991) provide complementary findings regarding the outcome of metaphor interpretation. For example, Tourangeau and Rips's within-subjects design revealed that emergent features were produced frequently by individuals who were asked to consider both the repre- sentations of individual words as well as the interpretations of metaphors using those same words. My study used a between-subject design to eliminate any possible demand characteristics and still found that emergent features occurred frequently. Although the general outcome of the two studies was similar (i.e., large numbers of vehicle-shared and emergent features in comparison to other feature types), there were some subtle differences in the results. The attribute instructions

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256 BECKER

in my study, which were most similar to Tourangeau and Rips's interpretation instructions, resulted in (a) more vehicle-shared and topic-shared features and fewer emergent features than the previous study for type counts and (b) more vehicle- shared and fewer topic-shared features than the previous study for token counts.

This study also used different stimuli and two different sets of interpretation instructions in order to determine that Tourangeau and Rips's (1991) findings could be generalized to metaphors of different content and structure and to situations in which participants might use somewhat different interpretation strategies. For example, the structure of metaphors used in this study was, "an X is a Y," whereas in the previous study, the topic domain was identified (i.e., "an X is a Y among Z"). Given these variations, the existence of emergent features in metaphor interpreta- tion cannot be dismissed as an artifact of the research design or procedures employed in either study.

The existence of emergent features indicates that providing people with meta- phors to be interpreted might be a way to encourage them to explore familiar concepts and think in ways they otherwise would not. Perhaps engaging in metaphor interpretation would help break mental sets and allow one to refocus on problem characteristics that might otherwise be overlooked. Both sets of instructions used in this study lead to interpretation strategies that produced reasonably large per- centages of emergent features. The subtle differences in percentages of feature types across the attribute and share conditions indicate that one can vary instructions to induce slightly different interpretation strategies. Future research might focus on identifying instruction strategies that encourage even greater production of emer- gent features or that induce people to attribute greater importance to emergent content than they did in this study.

ACKNOWLEDGMENTS

This article is based in part on a doctoral dissertation submitted to Texas A&M University by Angela H. Becker. Portions of this data were presented in May 1994 at the Midwestern Psychological Association Conference in Chicago and in May 1995 at the Creative Concepts Conference in College Station, Texas. I thank Sharon Calhoon, Nadene Keene, Sherry Jones, DonnaMcLean, Sue Sciarne-Giesecke, and Thomas Ward for their helpful comments on this and earlier versions of this article.

REFERENCES

Camac, M. K., & Glucksberg, S. (1984). Metaphors do not use associations between concepts, they are used to create them. Journal of Psycholinguistic Research, 13, 443-455.

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Gentner, D., & Clement, C. (1988). Evidence for relational selectivity in the interpretation of analogy and metaphor. In G. H. Bower (Ed.), The psychology of learning and motivation: Advances in research and theory (Vol. 22, pp. 307-358). New York: Academic.

Glucksberg, S., McGlone, M. S., & Manfredi, D. (1997). Property attribution in metaphor comprehen- sion. Jounurl of Memory and Language, 36,50-67.

Katz, A. N., Paivio, A., Marschark, M., &Clark, J. M. (1988). Normsfor204literaryand260nonliterary metaphors on 10 psychological dimensions. Metaphor and Symbolic Activity, 3. 191-214.

Kelly, M. H., & Keil, F. C. (1987). Metaphor comprehension and knowledge of semantic domains. Metaphor and Symbolic Activity, 2, 33-51.

Lakoff, G., &Johnson, M. G. (1980). Metaphors we live by. Chicago: University of Chicago Press. Ortony, A. (1979). Beyond literal similarity. Psychological Review, 86, 161-180. Ortony, A., Vondruska, R. J., Foss, M. A., &Jones, L. E. (1985). Salience, similes, and the asymmetry

of similarity. Journal of Memory and Language, 24,569-594. Readence, J. E., Baldwin, R. S., Martin, M. A,, & O'Brien, D. G. (1984). Metaphorical interpretations:

An investigation of the salience imbalance hypothesis. Journal of Educational Psychology, 76, 659-667.

Tourangeau, R., & Rips, L. (1991). Interpreting and evaluating metaphors. Journal of Memory and Language, 30,452-472.

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APPENDIX A METAPHOR STIMULI PRESENTED IN THE

METAPHOR CONDITION

Sentence Set I Sentence Set 2

A smile is a knife. Teeth are pearls.

Ideas are fireflies. Stars are diamonds

A sailboat is an arrow. The wind is a cat.

Time is a physician. History is a magnet.

A child is a closet. The mind is a sponge.

Life is a journey. An argument is a game.

Power is penicillin. Money is a lubricant.

Marriage is a joyride. Alcohol is a crutch.

Anger is an ocean. Sleep is a snowstorm.

Love is a sword. Doubt is a net.

A smile is a pearl. Teeth are knives.

Ideas are diamonds. Stars are fireflies.

A sailboat is a cat. The wind is an arrow.

Time is a magnet. History is a physician.

A child is a sponge. The mind is a closet.

Life is a game. An argument is a journey.

Power is a lubricant. Money is penicillin.

Marriage is a crutch. Alcohol is a joyride.

Anger is a snowstorm. Sleep is an ocean.

Love is a net. Doubt is a sword.

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APPENDIX B STIMULUS WORDS PRESENTED IN THE

WORD CONDITION

Word Set I Word Set 2

knife teeth

fueflies stars

arrow wind

physician history

closet mind

life g-e

power lubricant

joyride alcohol

ocean sleep

sword doubt

smile pearls

ideas diamonds

sailboat cat

time magnet

child sponge

journey argument

penicillin money

marriage crutch

anger snowstorm

love net

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