Contextual Reference Domains and Verification: What ... - Science Direct

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Reference Domains and Verification: What Is Relevant and What Is Not in Sentence Verification ALLAN B.I.

BERNARDO AND ROBERTJ. STERNBERG Yale University

A contextual reference domain model is proposed to explain situations wherein referents that do not involve the topic of a sentence (or nontopical referents) are judged to be relevant to that sentence’s verification. The model states that decisions about the relevance of referents depend on how the target sentence is understood. The meaning attributed to the sentence constrains the set of objects that can provide proof for the sentence’s verification. This set of objects is referred to as reference domain for veritication and is proposed to vary depending on the contextual factors that affect the meaning of the target sentence. Data supporting the model were found in three experiments with 80 subjects using a verification decision task. The type of relationship (i.e., binary or nonbinary) between the topic of the sentence and the referent was used to prompt more inclusive meanings for the sentence and the reference domains. Nontopical referents were found more likely to be considered relevant in conditions where it was more likely that the target sentence was understood as referring to the nontopical concept, too. The results are discussed in terms of the importance of contextual factors in the sentence verification process. 0 1~~1AC&~~C &SS, 1~.

Consider the following paraphrase conversation once overheard: George. Mario.

George.

of a

I heard you’re gonna buy a new car. Yeah, I’m thinking of getting one of those small imports. Those big American cars are real gas guzzlers . Not so . . . I heard that the Mazda Miata or something is a gas guzzler, too.

This small chunk of the conversation seems to be perfectly normal, but surely some This research was supported in part by a graduate fellowship from Yale University to the primary author and an Army Research Institute contract to the second author. We are grateful to Lynn Okagaki, Richard Gerrig, Joan Miller, and Bob Abelson for comments on previous versions of the manuscript. We are especially thankful to two anonymous reviewers for their very thoughtful and helpful reviews of an earlier version of the article. Requests for reprints should be sent to Robert J. Stemberg, Department of Psychology, Yale University, Box 11A Yale Station, New Haven, CT 06500-7447.

readers already sense that there is something not exactly proper in the exchange. What seems improper is the way George disconfirms or falsifies Mario’s assertion that “big American cars are real gas guzzlers.” George refers to information about a small Japanese car as falsifying evidence for Mario’s assertion. If we ask people what information should we look for in order to verify or falsify a claim about big American cars, people would say we should refer to specific information about big American cars, the topic of the sentence. Information about small Japanese cars, small American cars, big German cars, or Chinese trucks should not and does not say anything about what is or is not true about big American cars and, therefore, should be irrelevant to the sentence’s verification. Homby (1972) found evidence for this idea, saying that the existence of the topic is considered a necessary condition for the truth or falsity of the sentence; if the object with which the sentence is to be verified does not involve the topic, then the sentence is neither true nor false. To the 664

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0 1991 by Academic Press, Inc. of rqmductioo in any form resewed.

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extent that we even briefly accept George’s statement above, it seems this idea is not always true-there should be situations where information about objects other than the topic involved in the sentence would be judged useful for verifying the sentence. The process of verifying the truth or falsity of sentences in reference to some external object or a representation of this object has been investigated in several studies and various theories have been developed to account for the process (see, e.g., Carpenter & Just, 1975; Clark & Chase, 1972; Glucksberg, Trabasso, & Wald, 1973; Greenspan & Segal, 1984; Trabasso, Rollins, & Shaughnessy, 1971). However, none of these analyses consider the factor of whether or not the statement and the referent (i.e., the external object or its representation’) involve the same thing. The focus of these earlier studies was on determining the different parameters that constitute the information processing structure of the task. Although we look at just one new variable, the nature of the referent, the focus of this study is entirely different. The basic purpose of this study is to look into decisions as to which referents will be considered relevant to the verification process. We are not assuming that such a process operates independently of or even just prior to the actual verification process. However, to the extent that people make judgments that some objects are irrelevant to the verification of some sentence, we can assume that people impose constraints on the range of referents that they will consider in the verification process. That is, people seem to have some implicit rule about what referents are probative, or providing proof or evidence, and which are not. ’ The use of the term “referent” to mean a sentence or representation of an object in the environment is not standard (we thank two anonymous reviewers for reminding us about this point). However, our use of the term, particularly in the context of the task involved, still captures the important aspects of the standard usage of the term.

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In this study, we are looking at when and how referents that do not involve the same topic as the sentence are considered relevant to the verification of this sentence (henceforth, we shall refer to such referents as nontopical referents). We focus on such referents because the referents that involve the same topic (i.e., topical referents) are always probative; they always either verify or falsify the sentence. Such is not the case with nontopical referents. Consider the following sentence and nontopical referent: Athletes are physically fit. Stephen Hawking is a scientist and he is not physically fit. The nontopical referent in this case does not seem to be probative. However, consider the following sentence and nontopical referent: Democrats are liberal. Sen. Helms is a Republican liberal.

and he is not

It is conceivable that some people may consider this nontopical referent to be relevant to the verification of the sentence. To account for such situations, we propose a model based on two related ideas. First, whether or not a referent is considered probative depends on whether or not that referent falls within a range of referents implicitly defined as the set of objects that bear information about the sentence to be verified; this set is called the reference domain for verification. Second, what the reference domain shall encompass depends on how the sentence to be verified is understood, particularly, on what a person understands the sentence to refer. The idea is that if a sentence is understood in some way, an appropriate reference domain is defined, and the nontopical referent should be considered relevant; if understood in another way, another reference domain is defined, and the same nontopical referent should be considered irrelevant. The model is discussed in detail in the following sections .

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More often than not, the meaning of a sentence cannot be determined solely by referring to linguistic information. For example, Clark (1983) has shown how a syntactically unambiguous sentence like “Do you know what time it is?” can have several meanings, depending on the pragmatics of the situation. The meaning of any sentence, therefore, seems to be construed with at least some consideration of all or most of the nonlinguistic information available. In the conversation between Mario and George, Mario’s statement that “. . . big American cars are gas guzzlers” may be understood to mean something other than the description of a particular group of cars as inefficient in using fuel. In the context of the conversation, we can reasonably infer that Mario might also have meant that “Small, imported cars are not gas guzzlers.” Thus, he might have explained why he intends to buy one of them. In this context, George’s falsification makes a certain kind of sense. In the proposed model, we assume that sentences have no fixed meaning and that nonlinguistic contextual information infIuences how a sentence is understood. More importantly, this non-linguistic contextual information influences one’s implicit definition of the range of referents which would be considered probative or the reference domain for verification. The reference domain specifies the set of possible referents that will have some confirmatory or disconfirmatory value for a sentence with a particular evoked meaning. Defining the reference domain is based on what one understands the sentence to mean or to refer to. Therefore, the current meaning of a sentence constrains the reference domain for verification. A sentence that has different meanings in varied contexts will, therefore, have different reference domains appropriate to each context. The differences among reference

STERNBERG

domain are probably not extreme; instead, the range of probative referents is merely extended or restricted to suit the meaning. Consider the statement, “Big American cars are gas guzzlers,” for example. Without any reference to a particular context, the reference domain for the sentence will include only the population of big American cars. In the context of the above conversation, however, the reference domain should be expanded to include the population of small imported cars, too. Consequently, the proposed model asserts, our decisions about whether a referent that does not involve the topic of the sentence is or is not relevant to the sentence’s verification will be determined by whether or not that nontopical referent falls within the reference domain specified by the current meaning of the sentence; this meaning is, in turn, specified by various elements of the linguistic and nonlinguistic context. The different elements of the model are described in Fig. 1. But what is it that we mean by “context”? Bransford (1979) very broadly refers to context in comprehension or understanding as all “appropriately activated knowledge.” Such a definition entails that all knowledge structures that may be activated in processing one sentence provide the context in which the sentence is to be understood. This body of knowledge may consist of presuppositions explicitly stated before or after the sentence, or currently available observations about actual objects present or events occurring while the sentence is stated, or stored representations of objects, events, etc., which might be construed as relevant to the sentence. This working definition of context is understandably broad (Clark & Carlson, 198 I), but is nevertheless useful for providing a range of factors, both linguistic and nonlinguistic, to consider in studying the functional elements of context. In this study, to demonstrate the conditions under which nontopical referents will be considered probative, we could focus on

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Senmnce Y: Mcathg

A

Mean& B Meet@

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FIG. 1. Schematic representation of the contextual reference domain model describing how decisions are made about whether or not referents are relevant to the verification process. Referent Y will be considered relevant if the person accepts meanings C and D and their corresponding reference domains. However, it will be. considered irrelevant if meanings A and B are accepted together with their correspoqding reference domains.

elaborate descriptions of the context by embedding the sentence in a meaningful series of sentences similar to the conversation between Mario and George. Instead, we focus on a very simple, even minimal form of context-the set relationship between the topic of the sentence and the nontopical referent. We predict that, even without reference to an elaborate context, a binary relationship between these two elements would lead to the nontopical referent being more likely considered to be relevant in sentence verification. The basis for this prediction is the notion that compared to nonbinary concepts, binary concepts (which could also be called opposites, antonyms, or contradictory concepts) would be more strongly associated with each other. In relation to this point, there would be a greater probability that some information about one concept would be understood as referring as well to the contradictory concept, but in a negative way. For example, recall the following sentence and referent pair involving the nonbinary concepts, “athletes” and “scientists”: AthIetes are physically fit. Stephen Hawking is a scientist and he is not physically fit. It seems rather unlikely that the first sen-

tence would be construed in any way which makes it say anything about scientists. Although it is conceivable that the first sentence might be understood as saying “Athletes, relative to people of other professions or vocations, are physically tit,” nevertheless, the likelihood that the referent would be considered relevant to the verification of the sentence should be low. However, recall the following sentence and referent pair involving the (pragmatically) binary concepts “Democrats” and “Republicans”: Democrats are liberal. Senator Helms is a Republican and he is not liberal. It is not unreasonable to interpret the sentence as saying “Democrats, relative to Republicans, are liberal,” or even “Only Democrats are liberal; Republicans are not.” If the sentence is understood in this broad way, it is more likely that the referent would be considered probative in this case than in the last example. In terms of the contextual reference domain model, the complementary relationship between the concepts “Democrat” and “Republican” creates a context in which it is likely that these more inclusive meanings will be evoked. These meanings would define a reference domain for verification that includes the population of both Democrats

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BERNARDOANDSTERNBERG NON-BINARY CONDITION: Athlew uu phy&xlly fit. AOlbhsuphysWlyfit.

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AWas, mlatlvaa~nonathh8s cur physiesllyfit. -

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sre liberal.

Democrat em ltberul. Dmocnu, nlatlva b nonDameera@(Republtcaxu) am liberal. OR Only DsmcnxauM liberal; non-Dernmau am not.

FIG. 2. Schematic representation of the predictions of the reference domain model with nontopical referents that are either binary or nonbinary concepts to the topic of the target sentence. The thicker lines indicate higher probabilities of accepting a particular meaning of a sentence and its corresponding reference domain. In both conditions the nontopical referent will be considered relevant if the more inclusive meanings are accepted. This is more probable in the binary condition.

and Republicans. Figure 2 illustrates how the two examples are explained by the contextual reference domain model. Note that because there is no actual situational context in which to consider the sentences, the “straightforward” meanings will still be considered most probable in both conditions. The difference lies in how likely it is that the more inclusive meanings will also be evoked and held by the reader. We present and discuss three experiments that demonstrate that the simple set relations between the topic of sentence and the nontopical referent do influence people’s decisions about the relevance of these nontopical referents to verification. We will discuss how that data are consistent with the contextual reference domain model and we shall also address alternative explanations for the data.

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The first experiment was designed to demonstrate that the probability that a nontopical referent is judged to be relevant to the verification process is influenced by the simple contextual variable of set relationship between topic of sentence and nontopical referent. The task used in this and all the other experiments is patterned after the sentence-picture verification task. We call this method the verification-decision task. It involves first presenting simple target sentences like “Democrats are liberal,” which are descriptions of particular groups of people or objects. The description shall be referred to as the comment about the topic. Each sentence is then followed by another sentence, which describes an object or a person in terms of the topic and

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comment in the first sentence, for example, “Sen. Kennedy is a Democrat and he is liberal.” This sentence, which is a representation and characterization of some person or object in the environment, is called the referent. ’ Each target-referent pair forms one verification-decision problem. The task given the subjects is to decide whether the referent confirms, discontirms, or is irrelevant to the verification of the target sentence. The primary independent variable is the type of set relationship between the topic of the target sentence and the nontopical referent, that is, binary or nonbinary. A secondary variable of interest was the polarity of the comment, that is, the description about the topic of the sentence. Considering the target sentence “Democrats are liberal,” a referent that includes “is liberal” is a positive-comment referent, while one that ends with “is not liberal” is a negative-comment referent. This variable is interesting because the most critical and robust finding in earlier studies of sentence verification involving topical referents (i.e., referents that involve the topic of the target sentence) was that it takes longer to respond to negative comment items than to positive ones. This “marking effect” has been explained by invoking cognitive mechanisms in which the default value is to consider the comment as positive and to give a positive response. Thus, a negative comment would require a shift in this value before a negative response can be given (see, e.g., Clark & Chase, 1972). Most explanations of the “marking effect” are variations on this account. The contextual reference domain model does not have any direct predictions regarding the effects of polarity of the comment. That is, because our prediction is that the set relation between the topic and nontopical referent influences how a sentence is understood, the polarity of a comment need not necessarily play any role. However, it is possible that this variable

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adds another element in the minimal context that could influence the decision of whether or not the nontopical referents are probative. Such explanations will be considered a posteriori. The basic design of the experiment is a 2 X 2 (set relation X polarity of comment) completely repeated factorial. This design and example items for each cell are described in the top part of Table 1. In addition to this basic design, several control conditions were added. First, the corresponding topical referent versions (i.e., the referents involve the same topic as the sentence) of all the items in the four experimental cells were also included. These control items were added for two reasons: first, to balance the number of relevant and irrelevant items, and second, to see if the “marking effect” can be replicated in this experiment. The last control condition is another nontopical referent condition, but the referent involves a concept that is very remotely related to the topic of the sentence. These control conditions and example items for each are described in the rest of Table 1. The main dependent variable of interest is the probability that nontopical referents are judged as “irrelevant.” The prediction is that the probability of considering binary concepts “irrelevant” will be lower than it is for non-binary concepts. The probabilities for both these conditions should also be lower than for the remote-relation control condition, where it should be unlikely that the set relation between topic and nontopical referent would prompt consideration of any meaning other than the syntactic one. The probability of considering such nontopical referents as “irrelevant” should be very near or equal to 1.0. Reaction times for producing confirmation decisions are also measured as a secondary index of the dependent variable. For the nontopical referent conditions, the reaction times are not used as indicators of the real-time components of the verifica-

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Topical referent (control) Positive-comment Negative-comment

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T: Athletes are physically fit. R: Jed is a coach and he is physically fit. T: Athletes are physically tit. R: Jeb is a coach and he is not physically fit.

T: Democrats are liberal. R: Sen. Jacob is a Republican and he is liberal. T: Democrats are liberal. R: Sen. Judd is a Republican and he is not liberal.

T: Athletes are physically fit. R: Joe is an athlete and he is physically fit. T: Athletes are physically fit. R: Jim is an athlete and he is not physically fit.

T: Democrats are liberal. R: Sen. Jones is a Democrat and he is liberal. T: Democrats are liberal. R: Sen. James is a Democrat and he is not liberal.

T: Athletes are physically tit. R: Apple II is a computer and it is not physically fit.

Note. T = target sentence; R = referent.

tion-decision task. Instead, they are treated as correlates of the complexity involved in considering alternative meanings of a sentence and making the verification decision. However, for the topical referent control conditions, reaction times should show the benchmark finding of earlier sentence verification research that it will take longer to falsify than to verify a sentence with a topical referent. Method Subjects. Thirty introductory psychology students at Yale University participated in the experiment to fulfill a course requirement. Apparatus. Two IBM personal computers were used to present the instructions and the verification decision problems and to record the verification decisions and reaction times of the subjects. Stimuli. A total of 90 verification decision problems were used in this experiment, 10 problems in each of the experimental and control conditions described in

Table 1. Each item was pretested (using an independent but similar sample of subjects) on how often each target sentence was perceived as true (for the items selected, range of scores on a 0 to 10 scale = 6.17-8.83), and on how confident the subjects were about their ratings on the previous scale (for the items selected, the range of scores on a 0 to 10 scale = 6.67-9.00). This last measure was also intended to remove unfamiliar sentences. For the type of relationship manipulation, 40 contrary (both binary and nonbinary) concepts were generated by the experimenters. The same pretest subjects sorted the different contrary pairs into binary and non-binary pairs, after the distinction between the two types of relationships was clearly defined. At least 70% agreement was required among the sorters before a pair of concepts was used. (See the Appendix for list of items used.) Procedure. Subjects were tested individually. They were told that the study was on the process of confirmation, specifically,

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on the factors that intluence decisions as to whether or not an observation confirms a statement. They were given the instructions for the verification-decision task. With regard to the target sentence in each problem, they were told that it “may or may not be true” but that “like a generalization, it was asserted to be true most of the time but not all the time.” They were also told that the second sentence in the problem was an “observation that is described in terms of the first statement” and that they “should always accept this observation as true.” In each problem, the target sentence was presented first. After reading this sentence, the subject had to press a key to signal the presentation of the referent. The target sentence was not removed from the screen. The subject was to decide whether the observation confirms, dixonfirms, or is irrelevant to the confirmation of the first statement. Subjects were told to indicate their decision by pressing one of the marked keys on the computer keyboard. After typing in their response, they had to press a key to signal the presentation of the next problem. For their response choices, the following definitions were given all the subjects: confirming or verifying observations “provide support for the idea expressed in the first statement”; disconfirming or faIsifying observations “provide support for the idea opposite or contrary to that which is expressed in the first statement”; irrelevant observations do “not provide support for the first idea or its contrary.” Subjects were also told that their responses were being timed, but that their task was not a speeded one. This step was taken so that subjects would know that they should not waste time while doing the problems, and so that they would not perform the task haphazardly for the sake of speed. All subjects were given 20 practice trials to familiarize themselves with the task. They were then given the 90 experimental problems in a randomized sequence.

Results and Discussion Verification decision data. The mean proportion of “irrelevant” responses for the four experimental nontopical conditions and the control nontopical condition are presented in Fig. 3. A series of planned comparisons of means showed that each of the four proportions for the experimental conditions was reliably lower than the proportion for the control (remote relation) condition (t scores ranged from t(29) = 2.28, p < .03, standard error = 0.04; to t(29) = 4.19, p < .OOl, standard error = 0.02). As predicted, the proportion of “irrelevant” responses was reliably lower f&r the binary (X = 0.85) than for the nonbinary (K = 0.93) conditions, subjects: F(1,29) = 3.61, p < .05, items: F(1,36) = 14.53, p < .0005. These results indicate that set relations influence decision about the relevance of nontopical referents. Because the proportions of “irrelevant” responses for the experimental conditions were reliably lower than for the control condition, it seemsthat the effect of set relations has to do with the influence of this variable in how the target sentence is understood. That is, the type of set relation seems to have influenced 1.0

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FIG. 3. Mean proportion of “irrelevant” responses as a function of type of relation and polarity of comment in Experiment 1.

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whether or not the sentence referred only to the topic of the sentence or to the nontopical referent, as well. It was predicted that the likelihood of deriving meanings that include the nontopical referent would be higher for binary concepts, but less likely for the non-binary concepts. These likelihoods correspond to the findings about the different probabilities of judging the nontopical referents in these two conditions as probative. Furthermore, the almost perfect probability for the control items (and the standard deviations of 0.02 over subjects and 0.01 over items) is very highly consistent with the prediction that the remotely related concepts in the verification decision problems would not allow for the interpretation of any alternative meaning of the sentence other than the syntactic meaning and that there should be a near zero probability that the nontopical referent in this condition would be considered probative. There was also a reliable difference in the proportion of “irrelevant” responses due to the polarity of the comment (0.82 vs. 0.87); subjects: F(1,29) = 4.20, p < .05; items: F(1,36) = 6.29, p < .Ol. There was a reliable interaction between the type of set relation and polarity of comment, minF’(1,65) = 4.05, p < .05. A more detailed comparison of the data for each of the conditions indicates that these effects, and probably even the main effect of the type of relationship is due to the data from one condition: the binary, negative-comment condition. A paired comparison of means indicates that the mean for this condition (0.80) is reliably lower than the means for all other conditions (0.91, 0.93, 0.94); t scores ranged from t(29) = 2.32, p < .02, SE = 0.05, to t(29) = 2.46, p < .02, SE = 0.04. But none of the means for the other conditions were different from each other (all 1 scores = .lO; items: F(1,9) = 2.34, p > .lO. As in Experiment 2, the proportion of “irrelevant” responses for the nonbinary condition (E = 0.89) was reliably higher than for both the binary subconditions (nondistinguishing (X = 0.75): t(19) = 2.01, p < -05, SE = 0.10; distinguishing (K = 0.70): t(19) = 2.33, p < .03, SE = 0.11). The two binary subconditions, however, did not differ with respect to this measure (t(19) = 1.04,p > .lO). Also, as in the second experiment, although there was a reliable effect of the type of polarity in the distinguishing binary condition (0.76 vs. 0.64; t(19) = 2.26, p < .04, SE = O&4), the effect was absent in the nonbinary condition (means were both

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FIG. 8. Mean proportion of “irrelevant” and “definitely irrelevant” responses as a function of type of relation and polarity of comment in Experiment 3: ND = nondistinguishing; D = distinguishing.

0.89). There was a difference of 0.06 between the positive- and negative-comment conditions (0.78 vs. 0.72) in the nondistinguishing binary conditions, but this difference was not statistically reliable (t < 1.0). Lastly, the proportion of “irrelevant” responses for the negative-comment conditions in both the binary subconditions were reliably lower than that for the nonbinary conditions, (nondistinguishing (0.72 vs. 0.89): t(19) = 2.13, p < .05, SE = 0.08; distinguishing (0.64 vs. 0.89): t(19) = 3.21,

p < .004, SE = 0.05). The data, except for a few of the differences relevant to the nature of the comment, all replicate those in Experiment 2. Looking at the overall trend of the proportion of “definitely irrelevant” responses, it seems that there is in fact a low probability that the syntactic meaning of the target sentences was accepted when there were nontopical referents. Clearly, the subjects accepted the more inclusive meaning less than 50% of the time; that is, for more than 50% of the time they were considering the more inclusive meaning of the target sentence. Pertinent to this point is the finding that although the proportion of “definitely irrelevant” responses for the closely related nontopical referents was lower than the proportion of “irrelevant” responses; the two proportions were identical for the remote-relation condition (Sr = 0.98). This result is highly consistent with what we have been asserting since early on in the paper-that because of the nature of the remote-relation nontopical referents, no alternative meanings will be considered for sentences in this control condition. There was also a strong main effect of type of relation on the proportion of “definitely irrelevant” responses, minF’(2,48) = 5.01, p < .02. A more detailed comparison of means shows that for this main effect, the proportion of “definitely irrelevant” responses for the nonbinary condition (X = 0.67) was reliably higher than that for both binary subconditions (nondistinguishing (X = 0.46): t(19) = 3.24, p < ,004, SE = 0.10; distinguishing (K = 0.45): t(19) = 2.76, p < .Ol, SE = 0.11). The proportion of “definitely irrelevant” responses for negative-comment referents was also lower for both the binary subconditions compared to the nonbinary condition (nondistinguishing (0.46 vs. 0.67): ~(19) = 2.58;~ < .Ol, SE = 0.08; distinguishing (0.40 vs. 0.67): t(19) = 3.33, p < .003, SE = 0.06). These results strongly replicate the most crucial findings of the previous experiments and therefore support the different ele-

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ments of the contextual reference domain model. The results also indicate that it is improbable that the response options in the previous experiments biased the subjects into giving “relevant” responses. If anything, the data show that the subjects in the previous experiments were forced to give “irrelevant” responses when they were not completely certain this response was correct. GENERAL DISCUSSION

The data from the three experiments provide support for all the major elements of the contextual reference domain model. First, the differences in verification responses, reaction times, and confidence ratings between the conditions where the nontopical referent was remotely related to the topic of the sentence and where it was closely related (binary and nonbinary conditions) suggest that subjects were considering alternative meanings of the target sentence. These alternative meanings were not the syntactic meanings and seem to implicate the nontopical referent, too, therefore making it more likely that the nontopical referent be considered probative. The data also indicate that even without reference to a more complex form of contextual information, set relations between the topic of the sentence and the nontopical referent influence the probability of invoking these alternative meanings. There seems to be a primary effect that a binary relationship between the two elements makes it more likely that the sentence will be understood as referring to the nontopical referent, too. For example, it is more probable that “Democrats are liberal,” will be understood as meaning “Democrats are liberal, whereas Republicans are not,” than “Athletes are physically fit,” will be understood as meaning “Athletes are physically fit, whereas scientists are not.” A secondary effect that seems to add to this primary set relation effect, is that of the nature of the comment. The likelihood of

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accepting an alternative meaning of the sentence seemsto be higher when the polarity of the comment corresponds to the nontopical referent as it is related to the topic of the sentence. For example, it is more likely that “Small cars are fuel-efficient,” will be understood as meaning “Small cars are fuel-efficient, whereas large cars are not,” when the referent is about a large car that is nor fuel-efJicient than when it is about a large car that isfuel-efficient. In particular, when the topic of the sentence and the referent are binary concepts, a negative comment in the referent corresponds to or seems descriptive of the contradictory referent, making the more inclusive meaning more probable (as shown by the most recent example). On the other hand, when the topic and the referent are closely related but are not binary concepts, this correspondence is less likely; that is, the concepts that are contrary to the topic of the sentence may or may not be characteristically described by a particular polarity of the comment. For example, for the sentence “Asian dishes are spicy,” it probably does not make that much of a difference if the referent involved an African dish that is spicy or an African dish that is not spicy. The more inclusive meanings are less probably accepted in this condition. Even when the topic and referent are binary concepts, the likelihood of considering more inclusive meanings is weakened if the negation of the comment does not necessarily correspond to the nontopical referent, as was shown by the veritication data for the nondistinguishing comment, binary conditions. The data show that whether or not a referent is considered to be relevant to the verification of a sentence depends on how the sentence is understood. The particular way in which a sentence is understood entails a corresponding set of objects or referents that will provide useful information for the verification of the sentence. This point was the basis of our claim that the referent is compared to a reference domain for veritication in order to ascertain whether or not it

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is probative. The data from the three experiments show that the probability that a nontopical referent was considered to be relevant to the verification process is a function of the likelihood that the target sentence is understood to refer to a set including the nontopical referents and that the corresponding reference domain is defined to include the nontopical referent, as well. It should be clear, though, that the notion of reference domain is only a descriptive one. We are not claiming that in making a verification decision, people actually make an overt description of the reference domain nor that there is an actual structure in people’s cognitive representations corresponding to the reference domain. Instead, the idea of reference domain is a description of the set of objects or referents that should be considered probative given a particular meaning of a sentence. Hence, we can only speak of reference domains in relation to the meaning of sentences and the constraints this meaning sets upon the range of referents that would be probative. We can, therefore, say that decisions about what referents will be relevant to the vetification of the sentence boil down to what a person understands the sentence to be describing. The data of the experiment demonstrate how minimal contextual factors can influence this understanding and therefore the decision about the relevance of nontopical referents. The findings of this study are significant not only insofar as they strongly challenge the notion that only referents involving the topic of the sentence to be verified are relevant to the verification process.3 By showing some of the conditions in which nontopical referents can be considered relevant, 3 Incidentally, the times when people consider nontopical referents to be relevant is one of the few occasions where the experimental data show that people are reasoning logically. Since the rules of formal logic define every possible thing that exists in the universe and the “universe of discourse” for logical verification or confiiation, it is formally logical to say all referents, topical or nontopical, are always relevant.

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the data also indicate that we should start thinking about the verification process on a broader scale-broader in at least two respects. First, that processing nontopical referents for sentence verification can be studied meaningfully and that it should be. Previous research on sentence verification has not considered processing of nontopical referents because the focus of these studies was on the information processing components of the process and their tasks did not require looking into such factors. Looking at nontopical referents would seem to be a logical extension of such studies, even if only because the real processing components of this type of verification have not been investigated. A second and more important way in which the data indicate how we should broaden our conceptualization of the verification process is by considering the context of verification. In showing that verification decisions are dependent on how target sentences are understood, the data also indicate how very simple set relations can alter the perceived meaning of the target sentence, and therefore, the context in which the verification process takes place. Consistent with van Dijk and Kintsch’s (1983) theories of sentence processing, individuals seem to construct a situational model of the verification problem which is not always similar to the propositional model of the same problem. The situational model of a verification problem would map on to how a person understands the sentence to be verified. People seem to be importing real-world knowledge into constructing these situational models. Hence, the task of sentence verification, which is often referred to as a “simple” problem (Evans, 1982), may not be as straightforward a process as we usually take it to be. Future research should look into what other contextual factors (linguistic or nonlinguistic) bear on people’s representations of the verification problem and which of these factors actually affect their decisions about what objects are probative.

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Public colleges are inexpensive. (Private colleges) ANDNONTOPICALREFERENTS Women are emotionally expressive. (Men) The following list summarizes the critical Black & white movies are old. (Color movmaterials used in the three experiments. ies) Each set includes the target sentences and Introverts are quiet. (Extroverts) the concept used as nontopical referent, the Healthy children are active. (Sickly chillatter enclosed in parentheses. dren) Items in the non-binary condition (used Experienced surgeons are dexterous. (Inin Experiments l-3): experienced surgeons) Birds are tree-dwelling. (Insects) Items in nondistinguishing binary condiHospital volunteers are compassionate. tion (used in Experiments 2-3): (Doctors) Democrats are pro human rights. (RepubliAfrican countries are highly-populated. can) (European countries) Ballet dancers are graceful. (Modem danc- Small cars are foreign-made. (Large cars) Public colleges are crowded. (Private colers) leges) Good playwrights are imaginative. (Actors) Large animals are dangerous. (Small aniTennis pros are competitive. (Tennis mals) coaches) Fathers are authoritative. (Mothers) Asian dishes are spicy. (African dishes) College professors are highly educated. Introverts are introspective. (Extroverts) Good artists are hard-working. (Bad artists) (Lawyers) Athletes are physically fit. (Referees) Illegal drugs are addictive. (Legal drugs) Sky-divers are adventurous. (Pilots) Healthy children are happy. (Sickly children) Ztems in the binary condition (used in Ex- Sweet foods are fattening. (Bitter foods) periment 1): Democrats are liberal. (Republican) REFERENCES Small cars are economical. (Large cars) BRANSFORD, J. D. (1979). Human cognition: LearnPet animals are friendly. (Jungle animals) ing, understanding, and remembering. Belmont, Private colleges are expensive. (Public colCA: Wadsworth. CARPENTER, P. A., & JUST, M. A. (1975). Sentence leges) comprehension: A psycholinguistic processing Women are emotionally expressive. (Men) model of verification. Psychological Review, 82, Extroverts are sociable. (Introverts) 4.5-73. Large animals are vertebrate. (Small ani- CLARK, H. H. (1983). Making sense of nonce sense. In mals) G. B. Flores d’Arcais & R. J. Jarvella (Eds.), The process of language understanding. New York: Cold beverages are refreshing. (Hot beverWiley. ages) H. H., & CARLSON, T. B. (1981). Context for Healthy children are active. (Sickly chil- CLARK, comprehension. In J. Long 8z A. Baddeley (Eds.), dren) Attention andperformance IX. Hillsdale, NJ: ErlExperienced surgeons are dexterous. (Inbaum. experienced surgeons) CLARK, H. H., & CHASE, W. G. (1972). On the pro-

APPENDIX: LISTOFTARGETSENTENCES

Items in the distinguishing binary condition (used in Experiments 2-3):

Democrats are liberal. (Republican) Small cars are fuel-efficient. (Large cars) Wild animals are dangerous. (Pet animals)

cess of comparing sentences against pictures. Cognitive Psychology, 3, 472-517. EVANS, J.ST. B. T. (1982). The psychology of deductive reasoning. London: Routledge & Kegan Paul. GLUCKSBERG, S., TRABASSO, T., & WALD, J. (1973). Linguistic structures and mental operations. Cognitive Psychology, 5, 338-370.

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GREENSPAN, S. L., & SEGAL, E. M. (1984). Reference and comprehension: A topic-comment analysis of sentence-picture verification. Cognitive Psychology, 16, 556-606. HEMPEL, C. G. (1945). Studies in the logic of confirmation. Mind, 54, l-26, 97-121. HORNBY, P. A. (1972). The psychological subject and predicate. Cognitive Psychology, 3, 632-642.

TRABASSO, T., ROLLINS, H., & SHAUGHNESSY, E. (1971). Storage and verification stages in processing concepts. Cognitive Psychology, 2, 239-289. VAN DIJK, T. A., & KINTSCH, W. (1983). Strategies of discourse comprehension. New York: Academic Press. (Received June 3, 1990) (Revision received February 7, 1991)