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Comprehension of negation with quantification
JOURNAL OF VERBAL LEARNING AND VERBAL BEHAVIOR 10,
244-253 (1971)
Comprehension of Negation with Quantification MARCEL ADAM JUST AND PATRICIAANN CARPENTER1
Stanford University, Stanford, California 94305 Three experiments were carried out to compare the processingof three kinds of affirmative and negative sentences. In the first experiment, Ss were timed while they read a sentence, looked at a dot array, and then judged the sentence true or false with respect to the picture. The results showed that explicit syntacticnegatives (e.g., None of the dots are red) and implicit syntactic negatives (e.g., Few., .) were processed differently than semantic negatives which were referentially equivalent to few (e.g., A minority...). All three types of negatives took longer to verify than affirmatives. Two further experiments confirmed that Ss coded the arrays accompanying the imphcit syntactic negatives (few) and semantic negatives (a minority) in terms of the larger and smaller subsets of dots, respectively, thus accounting for the difference in processing.
The present paper reports a series of experiments designed to study how people process different kinds of negatives. Psychological research has previously shown that negatives with not (e.g., Seven is not an even number) are processed differently from affirmative sentences. For instance, the studies of Wason (1959, 1961, 1965), Wason and Jones (1963), and Gough (1965, 1966) all indicate that reaction time (RT) to such negative sentences is longer than to affirmative sentences, whether the task is verifying or completing sentences. However, negation exists in more forms than just the explicit not morpheme. For instance, Klima (1964) presented three criteria that defined a class of what he called negative preverbs. By Klima's criteria of either-conjunction, negative-appositive tag formation, and negative-question tag formation, a sentence with the word f e w or scarcely any is as negative as a sentence with
the word not. As an example, sentences with not and f e w can be either-conjoined whereas affirmative sentences cannot: John does not go to class, and Mary does not go either. * John goes to class, and Mary goes either. Few boys go to class, and few girls go either. * Many boys go to class, and many girls go either.
While previous studies have illustrated differences between affirmative and negative sentences with the not morpheme, the present study was designed to test whether such processing differences exist when negation is implicit, as with the word few. There is another difference between words hke not and those like few. Sentences with the negative particle, for example, not, none, no, negate a proposition about an entire set, as None o f the apples is good, whereas syntacticThe order of authors was decided by the toss of a ally negative sentences with quantifiers, for coin. The studies were a completelycollaborative effort. example, few, scarcely any, seldom, may be The first author was supported by a Canada Council considered to negate a proposition about a Fellowship, while the secondauthor was supported by a proper subset, as Few o f the apples are good. National Science Foundation Fellowship while these studies were being conducted. The authors express Processing differences may exist between fulltheir appreciation to Dr. Herbert Clark for his con- set negation, such as none, and subset negation, structive advice throughout the project. such as few. 244
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COMPREHENSION OF NEGATION A n o t h e r a i m of this research was to study the sentences that have the same reference as f e w a n d yet do n o t share the same syntactic properties. Sentences with the phrase a minority or a small proportion m a y refer to the same s i t u a t i o n as a sentence w i t h f e w , b u t sentences with a minority are n o t syntactically negative. F o r example, such sentences c a n n o t be eitherconjoined: * A m i n o r i t y of boys go to class, a n d a m i n o r ity of girls go either. The psychological question is whether such sentences are processed similarly to syntactic negatives with the same reference. F u r t h e r more, are such terms as a minority or a small proportion processed as t h o u g h they are negative with respect to phrases such as a majority a n d a large proportion ? These questions can be studied by e x a m i n i n g how people decode a n d i n t e r n a l l y represent sentences a n d pictures in verification tasks. These tasks require the c o m p a r i s o n o f two sources o f i n f o r m a t i o n leading to a decision o f true or false. A model p r o p o s e d by Clark (1969) a t t e m p t e d to characterize R T in verification tasks by m a k i n g the a s s u m p t i o n that a c o m p a r i s o n between two similar representations is easier t h a n a c o m p a r i s o n between two different representations. F o r the time being, the n a t u r e of a sentence's or a picture's intern a l representation will n o t be specified, except that such representations will be considered as
p r o p o s i t i o n s in which the person codes the i n f o r m a t i o n from the sentence or picture. Clark's model will be used to m a k e inferences as to the n a t u r e of these representations a n d the influence of n e g a t i o n a n d quantification on them. EXPERIMENT I
Method The experiment was a verification task in which the S was timed while he read a sentence, looked at a picture, and then decided whether the sentence was true or false with respect to the picture. Half of the sentences used are presented in Table 1. The other half were identical except the adjective black appeared in place of the adjective red. The three syntactic categories, listed in Table 1, are defined by the linguistic properties of their negative forms. They were: SYN-NOT, syntactic negatives (by Khma's criteria) with the negative particle; SYN, syntactic negatives without the negative particle; SEM, semantic negatives with the same reference as few, but not syntactically negative. Table 1 shows the three exemplars for each category of negation, along with their corresponding affirmative exemplars. Each sentence was accompanied by a 4 x 4 array of dots. For SYN-NOT, all 16 dots were the same color. For example, a picture that was true for The dots are red had 16 red dots. The picture that falsified the sentence had all black dots. A picture that made the negative sentence, The clots aren't red, true had all black dots. To falsify the sentence, the picture had all red dots. For both SYN and SEM, the arrays consisted of either 14 red and 2 black dots or the reverse. For example, the picture that was true for Many of the dots are red had 14 red and 2 black dots. The picture that
TABLE 1 EXEMPLAR SENTENCES IN THE THREE SYNTACTIC CATEGORIES
Category SYN-NOT
SYN
SEM
Affirmatives
Negatives
The dots are red All of the dots are red There are red dots
The dots aren't red None of the dots are red There are no red dots
Many of the dots are red Most of the dots are red Lots of the dots are red A majority of the dots are red About 14 of the 16 dots are red A large proportion of the dots are red
Few of the dots are red Scarcely any of the dots are red Hardly any of the dots are red A minority of the dots are red About 2 of the 16 dots are red A small proportion of the dots are red
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falsified the sentence had 14 black and 2 red dots. The picture that made the negative sentence, Few of the dots are red, true had 14 black and 2 red dots. To falsify the sentence the picture had 14 red and 2 black dots. The final design included three syntactic categories, three exemplars per category, affirmative and negative sentences, two truth values, and two color predicates, for a total of 72 different sentence-picture combinations. Each sentence was typed on a 4 x 8-in. stimulus card, and the corresponding dot array, ½-in. square, was drawn with a felt pen immediately to the right of the sentence. The card was viewed in a Cambridge Tachistoscope at a distance of 16 in. The S pushed a switch when he was ready for a trial, and 1 sec later a stimulus card was presented. The S was timed (in hundredths of a second) from stimulus onset while he read the sentence, then examined the dot array and decided whether the sentence was true or false with respect to the array. His decision was made using a twobutton decision apparatus, with a balanced assignment of dominant hand to true button across Ss. During the practice session, which consisted of 10 cards selected at random from the deck, the S was told when his response was incorrect. After the practice, all 72 cards were shuffled and the Swent through all the cards twice, with a 5-min rest in between the two runs. The entire session lasted about 50 min. The Ss were 20 nativeEnglish speaking Stanford undergraduates who participated as part of an Introductory Psychology requirement. Results
The R T d a t a was a n a l y z e d b y c o l l a p s i n g over the two runs a n d the two adjectives " r e d " a n d " b l a c k . " The R T s for e r r o n e o u s responses were disregarded, a n d the S was assigned a m e a n score based only on his correct responses for each exemplar. The analysis o f variance t r e a t e d the three e x e m p l a r s p e r c a t e g o r y as replications. F i g u r e 1 presents the m e a n R T for each o f the three syntactic categories as a function o f affirmation-negation (called Aff-Neg) a n d t r u t h value. I n the categories S Y N - N O T a n d SYN, true-affirmative sentences h a d a s h o r t e r R T t h a n false-affirmatives, while true-negative sentences h a d a longer R T t h a n false-negatives. These interactions in S Y N - N O T a n d S Y N were strong e n o u g h to result in an overall i n t e r a c t i o n o f A f f - N e g × T r u e - F a l s e , F ( 1 , 19) = 9.64, p < .01. The m o s t n o t a b l e result was
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FIG. 1. Mean RT for the three syntactic categories in Experiment I, when stimulus sentences and pictures were presented on the same card. t h a t the i n t e r a c t i o n was a b s e n t for S E M , where b o t h affirmative a n d negative sentences h a d shorter R T s when they were true t h a n when they were false. The absence o f the Aff-Neg × True-False interaction from one category ( S E M ) resulted in a t h r e e - w a y interaction o f C a t e g o r y × A f f - N e g × T r u e - F a l s e , F ( 2 , 38) = 5.52, p < .01. A posterlori, two o r t h o g o n a l c o n t r a s t s were used to test the pairwise differences in Aff-Neg × T r u e - F a l s e i n t e r a c t i o n a m o n g the three syntactic categories. The first test exa m i n e d the hypothesis t h a t the i n t e r a c t i o n was different in S Y N - N O T a n d S Y N . As F i g u r e 1 m i g h t suggest, the test was n o t significant, F(1, 38) < 1. The A f f - N e g × T r u e - F a l s e intera c t i o n present in S Y N - N O T a n d S Y N was significantly different f r o m the l a c k o f intera c t i o n in S E M , F(1, 38) = 10.35, p < .05, by a Scheff6 test. The m e a n R T to negative sentences was greater t h a n to affirmative sentences in all three categories F(1, 1 9 ) = 122.41, p < .01. N e g a t i o n time is o b t a i n e d by collapsing over true a n d false, a n d s u b t r a c t i n g R T to affirmative sentences f r o m the R T to negative sentences. The m e a n n e g a t i o n time was 280 msec for S Y N - N O T , 328 msec for S Y N , a n d 176 msec for SEM. These n e g a t i o n times were significantly different f r o m each other, F(2, 38) = 6.17, p < .01, a l t h o u g h the smallest n e g a t i o n time, in S E M , was still significantly different f r o m zero, t(19) = 5.46, p < .01.
COMPREHENSION OF NEGATION
False sentences had a longer RT overall than true, F(1, 19) = 13.06, p < .01. The difference in RT between true and false sentences did not differ significantly across the three syntactic categories: 68 msec for SYN-NOT, 64 msec for SYN, and 128 msec for SEM, F(2, 38) = 1.47. Overall, RTs increased from SYN-NOT (1603 msec) to SYN (1755 msec) to SEM (1892 msec), F(2, 38) = 43.22, p < .01. Within each syntactic category, all exemplar pairs showed the same pattern of RTs with respect to the Aff-Neg × True-False interaction (or lack of it), although there was some variability in negation times. The errors were distributed similarly across the three syntactic categories, with an overall error rate low enough (5.5 ~) to indicate that counting RT only for correct responses did not bias the data. More errors were made to negative than to affirmative sentences, with truenegative sentences accounting for the majority of errors. Discussion
It will be argued that syntactic negation referring to subsets (SYN) is processed analogously to syntactic negation with the negative particle (SYN-NOT). These two negatives focus the S's attention on the larger subset (in the case of SYN) or the entire set (in the case of SYN-NOT) of the accompanying array. On the other hand, SEM negatives focus the S's attention on the smaller subset. The Aff-Neg x True-False interaction in SYN-NOT, essentially a replication of previous results (Wason, 1961), may be explained in terms of a processing model proposed by Clark (1969). The essence of the model is the principle of congruence which asserts that a comparison between two pieces of information (e.g., a sentence and a picture) is easier when the representations of the two pieces of information are similar (congruent) and harder when the two representations are different (incongruent). For example, the information in the affirmative sentence The
247
dots are red may be represented in propositional form like (Dots be red). An array of 16 red dots, which verifies the sentence, may also be represented as (Dots be red). The comparison between these congruent representations results in a short RT to true-affirmatives. Incongruence between the sentence representation and the representation of 16 black dots results in a longer RT for false-affirmatives. A negative sentence, The dots aren't red, may be represented as a negation operator that denies an embedded proposition: (Neg (Dots be red)). A picture of 16 red dots falsifies the sentence, but because its representation has the color red, RT is relatively short for falsenegatives. Incongruence between the sentence representation and the representation of 16 black dots results in a longer RT for true-negatives. The model gives a reasonable explanation of the Aff-Neg × True-False interaction in SYN-NOT. Therefore, the model will be assumed as a basis of inference for the main interest of this experiment: the representations in SYN and SEM. The identical Aff-Neg × True-False interaction in SYN-NOT and SYN means that there were congruent sentence and picture representations for true-affirmatives and falsenegatives in both categories. In SYN-NOT, the interaction was predictable because Ss had no choice but to code the one color of the accompanying array. In SYN, where the array had 14 dots of one color and 2 dots of the other color, the interaction must have resulted because Ss coded the color of the larger subset. For example, Many of the dots are red includes the information that the larger subset is referenced and that the color of this subset is red, which may be represented as (Many (Dots be red)). This sentence representation will be congruent with the representation of the larger subset for true-affirmatives and incongruent for false-affirmatives. A SYN negative (e.g., Few o.f the dots are red) also focuses on the larger subset by denying that the larger subset is red. This concept may be represented as a negation operator and a
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doubly embedded proposition: (Neg (Many out the not marker, are more difficult to recog(Dots be red))). This sentence representation is nize than Wason's not-morpheme negatives. more congruent with the picture representa- A control group of 10 Ss, instructed to convert tion for false-negatives than it is with the pic- both SYN and SEM negatives, corroborated ture representation for true-negatives. Thus, these arguments by reporting great difficultyin the inference that the S coded the color of the performing the conversions. In addition, the larger subset for SYN sentences completely instruction to convert negatives increased accounts for the Aff-Neg x True-False inter- negation time by 225 msec for both SYN and SEM over negation time without conversion. action. The RT pattern for SEM indicates that Therefore, the hypothesis that SEM negatives affirmatives were interpreted as statements were converted to affirmatives was rejected. about the larger subset. The affirmative A The hypothesis that remains is that the difmajority of the dots are red may be repre- ference between SYN and SEM is due to the sented as (Majority(Dots be red)). The stra- effect of the two syntactic categories on how tegy of coding the color of the larger subset Ss coded the accompanying picture. The again results in congruence for true-affirma- hypothesis was tested in Experiment II by tives and incongruence for false-affirmatives. presenting the picture first and then removing However, the RT for SEM negatives indicates the picture before presenting the sentence. This that the S coded the color of the smaller subset procedure eliminated any possible different after reading a negative. For example, the effects SYN and SEM might have had on how sentence A minority of the dots are red could a picture is coded. be represented as information about the Another important result of Experiment I smaller subset: (Minority(Dots be red)). was the longer RT to negative than to affirmaCoding the color of the smaller subset results tive sentences found for all three categories. in congruence for true-negatives and incon- Negatives take longer to read than affirmagruence for false-negatives. Therefore, the tives, but even with reading time controlled, inference from this experiment is that the syntactic negatives take longer to verify than Aff-Neg x True-False interaction, or lack of affirmatives (Trabasso, Rollins, & Shaughinteraction, is the result of the way Ss coded nessy, in press). This psychological preference the arrays accompanying the sentences. In for affirmative over negative sentences can be particular, they seem to have coded the color related to the more general principle of markof the larger subset after reading a SYN nega- ing, which states that within certain pairs of tive and the color of the smaller subset after bipolar linguistic entities, one member of the a SEM negative. pair is preferred or unmarked and the other is Another possible explanation of the differ- unpreferred or marked. Greenberg (1966) ence between SYN and SEM negatives might noted that in all languages, full-set negation is be that Ss converted SEM negatives into linguistically marked (i.e., more complex) affirmatives before coding the picture (e.g., because "The negative always receives overt A minority of the dots are red into A majority expression, while the positive usually has zero of the dots are black), as Wason (1961) reported expression [p. 50]." In addition, he noted that some of his Ss did with not morpheme nega- many languages have no separate word for tives. However, conversion of SEM negatives few, and express the concept as the linguisticseems implausible because, contrary to the ally marked not many while no language exresults, such a strategy should have increased presses many as not few. The fact that affirmanegation time for SEM more than for SYN tives are unmarked and negatives are linguis(due to the added time to convert SEM nega- tically marked is completely correlated with tives). Furthermore, negatives in SEM, with- the finding in this study and previous studies
COMPREHENSIONOF NEGATION that affirmatives are psychologically less complex than negatives. Greenberg's linguistic data further suggest the generalization across languages that all syntactic negatives are psychologically m o r e difficult to process than corresponding affirmatives. A further interesting finding was that SEM negatives also have longer RTs than SEM affirmatives. It is already k n o w n that small is linguistically m a r k e d with respect to large. However, there are no linguistic data which would predict that minority would be less preferred than majority. Furthermore, there is no linguistic evidence that 2 out of 16 is marked with respect to 14 out of 16. Presumably all quantifiers referring to small quantities (or exceptions) are psychologically less preferred than quantifiers referring to larger quantities (or generalities). This preference relation between large and small quantities does not necessarily imply that the preferred entity constitutes the basis o f the unpreferred during processing. The R T pattern indicates, for example, that smatlproportion is not processed as not large proportion. Thus, the m a j o r difference between syntactic negation (SYNN O T and SYN) and the semantic negation o f S E M is that syntactic negatives are processed in terms o f their affirmatives, while S E M negatives are not, although S E M negatives still are m o r e difficult to process than their affirmatives.
EXPERIMENT II
Method The main innovation in Experiment II was that the presentation of the dot array was completed prior to the presentation of the stimulus sentence. The dot arrays and stimulus sentences were on separate cards presented through two channels of an Iconix tachistoscope. The dot arrays were 1½in. square. The sentences were typed on separate cards in large print on an IBM Executive Directory typewriter with an average sentence length of 3 in. and were viewed at a distance of 4 ft. The S initiated the trial by closing a switch with a 500-msec delay interval, after which time the dot array was presented for 1500 msec, followed by a 250-msec
249
blank interval, and finally followed by the presentation of the sentence alone. The S's response was recorded, with RT measured from the onset of the stimulus sentence. The S went through all 72 stimulus cards once, except for those trials on which he made an error or did not respond within 4 sec, in which case the response but not the RT was recorded, and the stimulus card was replaced among the remaining unused stimulus cards. Thus there was a correct response RT to all stimuli. The procedure was otherwise identical to Experiment I. The 11 Ss were from the same S pool as in Experiment I, although none had participated in Experiment I.
Results Experiment II was designed to test the hypothesis that the difference between S Y N and SEM was due to differences in h o w the S coded the picture after reading the sentences f r o m each category. The RTs were based only on correct responses with a low overall error rate o f 7.2 ~ . The data were analyzed, collapsing over red and black adjectives. A g a i n the three exemplars per category were treated as three replications in the analysis o f variance.
20
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FIG. 2. Mean RT for the three syntacUc categories an Experiment II, when pictures were presented prior to stimulus sentences.
Figure 2 presents the mean RTs o f the 11 Ss for the three syntactic categories as a function o f Aff-Neg and True-False. The twoway interaction o f Aff-Neg × True-False was n o t significant overall, F(1, 10) < l, because
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the interaction was only present for SYNNOT. This difference in the presence of the interaction among syntactic categories was significant, F(2, 20)=10.21, p < . 0 1 . In Experiment I, SYN had an Aff-Neg x TrueFalse interaction, whereas it was absent from SEM. The change in experimental manipulation in Experiment II, requiring the S to code the picture prior to the sentence presentation, eliminated the Aff-Neg × True-False interaction from SYN. A method of contrasts test showed that SYN and SEM did not differ significantly as a function of Aff-Neg and True-False, F(1, 20) < 1. The orthogonal contrast test showed the Aff-Neg x True-False interaction present in SYN-NOT differed significantly from the lack of interaction in SYN and SEM, using the Scheff6 test, F(1, 20) = 19.58, p < .01. Negative sentences took significantly longer than affirmative sentences in Experiment II as in Experiment I, F(1, 10)= 40.67, p < .01. Negation times across the three syntactic categories were 247 msec for SYN-NOT, 312 msec for SYN, and 138 msec for SEM, but these negation times were not significantly different from each other, F(2, 20) = 2.23. False sentences took longer than true sentences in all categories, F(1, 10)= 19.90, p < .01. This difference between true and false sentences increased significantly from SYNNOT to SYN to SEM, from 4 to 96 to 201 msec, respectively, F(2, 20)= 6.27, p < .01, with the latter two values significantly different from zero, F(1, 10) = 5.96, p < .05, and F(1, 10) = 26.14, p < .01. As in Experiment I, there was a significant overall increase in RT going from SYN-NOT (1384 msec) to SYN (1716 msec) to SEM (1777 msec), F(2, 20) = 26.98, p < .01. There was an overall decrease in RT of 125 msec between Experiment I and Experiment II, with means of 1759 msec and 1624 msec, respectively. The decrease was probably due to the procedural change in Experiment II, which gave the S a chance to code the picture before the timing started.
Discussion Presenting the picture first eliminated the effect of the SYN and SEM categories on picture coding and, therefore, made the RT patterns for SYN and SEM similar. On the other hand, the Aff-Neg x True-False interaction was predictably present for SYNNOT, since the S could only code the one color in the picture and compare this ~epresentatlon with the representation of the subsequent sentence. The question might be raised as to what strategy Ss used in SYN and SEM when presented with a dot array made of two subsets. One possibihty is that because the S did not know the kind of sentence to follow, he used the 1500-msec display time to redundantly code both subsets of the array (e.g., larger subset--red, smaller subset--black). When the sentence was displayed, the S used the referenced quantity (larger or smaller subset) in the comparison process and checked whether the color adjective in the picture representation matched that of the sentence. Certainly the kind of sentence did not dictate the picture coding strategy, as in Experiment I where the sentence preceded the picture array. Whatever the strategy, in this experiment Ss were not differentiating between SYN and SEM when they coded the picture prior to seeing the sentence. Individual S data also showed that the RT patterns for SYN and SEM were similar within Ss. Clearly, the next step was to control exactly how the picture was coded prior to the sentence presentation.
EXPERIMENT III Method The main change from Experiment II to Experiment III was the introduction of two instructions which told the Ss how to represent the dot array to themselves while they were waiting for the sentence to be presented. One instruction was to code the array in terms of its larger subset color. For example, 14 red and 2 black dots would be coded as "many red" or "majority
red" or some equivalent form which stressed the preeminenceof the larger subset. The alternate instruction was to code the array in terms of its smaller subset color.
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COMPREHENSION OF NEGATION
Each of three Ss was tested m four 1-hr sessions on four consecutive days, with one instruction per day, counterbalanced across days. Stimuli from only categories SYN and SEM were used, each session consisting of two runs through the 48 sentence-picture combinations. The remainder of the procedure was identical to Experiment II. The three Ss were the two authors as well as one paid, naive Sfrom the pool of the Introductory Psychology course.
Ss' coding strategies were not controlled. The inference from Experiment I, that Ss coded the color of the larger subset after reading a syntactically negative sentence, is supported by these data.
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Results and Discussion
~18
This experiment was designed to test the hypothesis that the nature of the Aff-Neg x True-False interaction could be determined by controlling the picture coding. The RT data, collapsed over the three Ss, are presented in Figures 3 and 4. The RT patterns were highly similar across Ss, a finding consistent with the hypothesis that some of the variance in group data is the result of differences in individual S's strategies for picture coding. Separate analyses of variance were done for the data of each S.
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TRUE FALSE TRUE FALSE FIG. 3. Mean RT for the two syntactic categories in Experiment III with the instruction to code the larger subset of the picture.
As Figure 3 shows for both SYN and SEM, an instruction to code the color of the larger subset made true-affirmatives easier than falseaffirmatives, but true-negatives were harder than false-negatives. An important feature of the data is that this interaction, under the instruction to code the color of the larger subset, is the same type of interaction found for SYN-NOT and SYN in Experiment I, when lO
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TRUE FALSE TRUE FALSE FIG. 4. Mean RT for the two syntactic categories in Experiment III with the instruction to code the smaller subset of the picture.
The opposite Aff-Neg x True-False interaction resulted when the S was instructed to code the smaller subset color, as shown in Figure 4. The difference in Aff-Neg x TrueFalse interactions with the two instructions was highly significant for all three Ss, F(1, 23) = 40.91, 41.77, and 6.132, respectively, p < .01. Different coding instructions result in opposite Aff-Neg x True-False interactions, confirming the maj6r hypothesis that the way a picture is coded determines where congruence between sentences and pictures will occur, and hence determines the nature of the interaction. One unexpected finding was that with the instruction to code the smaller subset, negative sentences in SEM had a shorter RT than affirmative sentences for all Ss, F(I, 23) < 1, and F(1, 23) = 18.87, 56.55, p < .01. This was not the case for SYN, where negative sentences took longer than affirmative sentences for two Ss, F ( l , 23) < l~andF(1, 23) = 48.66, p < .01, but negative sentences had a slightly shorter RT than affirmatives for the third S, F(1, 23) =2.91, n.s. Over Ss, the instruction to code the smaller subset resulted in negation times for SEM (-130 msec) and for SYN (123 msec) that were equal in magnitude but opposite in direction. Therefore, the instruc-
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JUST AND CARPENTER
tion to code the smaller subset had an overall zero negation time. Negation time with the instruction to code the larger subset was 284 msec for SEM and 285 msec for SYN, a mean negation time of 284 msec. The difference in mean negation times of the two instructions resulted in a significant interaction of Instruction × Aff-Neg, F(1,23) = 58.94, 10.77,p < .01, and F(1, 23) = 7.54, p < .05, for the three Ss, respectively. The reversal of negation time when coding the smaller subset with SEM sentences can possibly be accounted for in terms of the marking relation between negatives and affirmatives. SEM negatives, referring to small quantities, are normally unpreferred, but if the S attends to small quantities the usual preference relation is reversed. Thus, with the instruction to code the smaller subset, small quantities become preferred, and, hence, SEM negatives are easier than "affirmatives. The decrease of negation time for SYN with the instruction to code the smaller subset is due to this same attentional constraint. With no coding instructions, SYN negatives are unpreferred in two ways: (a) with respect to syntactic negation (as are SYN-NOT negatives); and (b) with respect to smaller quantities (as are SEM negatives). The instruction to code the smaller subset does not affect the syntactic negation for SYN, but it reverses the quantity preference relation for SYN as it did for SEM. In fat*. negation time decreases for SYN from 28:, to .23 msec with the instruction to code the larger subset and smaller subset, respectively. It seems that the quantity marking is susceptible to attention changes, while syntactic negation marking is not. Though this experiment was not designed to test a theory about the double marking of negation and quantity in SYN, the data are compatible with such an interpretation. GENERALDISCUSSION These experiments were originally conceived as investigating a continuum of negat on from
none to few to a small proportion. An alternative way of conceptualizing the problem is to distinguish two factors: scope of negation (full set vs. subset) and syntax (syntactic negation vs. semantic analogues). In such a scheme, none, few, and a small proportion are full syntactic, subset syntactic, and subset semantic negation, respectively. The fourth cell would be full semantic negation, for example, The dots are absent. The Aff-Neg × True-False interaction should occur with the full-set semantic negation, since there is no choice (as in SYN) in picture coding. Clark (personal communication) has obtained this result for absent. Both full and subset syntactic negatives focus on the larger subset or entire set because they are negating a proposition about those sets. This is obvious in None of the dots are red, which may be represented as (Neg(All(Dots be red))), with the focus on all. Few of the dots are red includes this syntactic negative property, as well as possibly a quantification marking. This may be represented as (Neg(Many(Dots be red))) with the focus on many, plus an implicit marking (smaller quantity red). All negatives are unpreferred, but the essence of their negativity is that they are dependent on their affirmative for focus. This argues for the generalization that all syntactic negatives may have the same basic internal representation as their corresponding affirmatives, but with an additional negation operator. SEM negatives, on the other hand, do not focus on the larger subset and are marked only with respect to quantity. The demonstrated marking of relatively small quantities in SEM may explain Wason's (1965) failure to confirm the ratio hypothesis in "The context of plausible denial." Wason's ratio hypothesis was: "Given two sets of stimuli which differ considerably in magnitude, it is more plausible to deny that the smaller set possesses a property of the larger set than to deny the converse [p. 8]." That is, Exactly one (of eight) circles is not red is a more plausible expression than Exactly seven (of
COMPREHENSION OF NEGATION
eight) circles are not blue. The reason the ratio hypothesis was not confirmed was probably because the former sentence contained, in fact, a "double negatwe". It contained both an unpreferred quantifier (smaller subset, similar to 2 out of 16) as well as an explicit negative (not), while the "less plausible" sentences only contained the explicit negative. REFERENCES
CLARK, H. H. Linguistic processes In deductive reasoning. Psychological Review, 1969, 76, 387404. GotJ~H, P. B. Grammatical transformations and speed of understanding. Journal o f Verbal Learning and Verbal Behavior, 1965, 4, 107-111. GOUGH,P. B. The verification of sentences: The effects of delay on evidence and sentence length. Journal o f Verbal Learning and Verbal Behavior, 1966, 5, 492-496.
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GREENBERG, J. H. Language universals. The Hague: Mouton, 1966. KLIMA,E. S. Negation in English. In J. A. Fodor and J. J. Katz (Eds.), The structure of language. Englewood Cliffs, N.J.: Prentice-Hall, 1964. TRABASSO, T., ROLLINS, H., & SHAUGHNESSY, E. Storage and verification stages in processing concepts. Cognitive Psychology (in press). WASON, P. C. The processing of positive and negative information. Quarterly Journal of Experimental Psychology, 1959, l l , 92-107. WASON, P. C. Response to affirmative and negative binary statements. British Journal o f Psychology, 1961, 52, 133-142. WASON,P. C. The contexts of plausible denial. Journal o f Verbal Learning and Verbal Behavior, 1965, 4, 7-11. WASON,P. C. & JONES, S. Negatives: Denotation and connotation. British Journal of Psychology, 1963, 54, 299-307. (Received October 7, 1970)
244-253 (1971)
Comprehension of Negation with Quantification MARCEL ADAM JUST AND PATRICIAANN CARPENTER1
Stanford University, Stanford, California 94305 Three experiments were carried out to compare the processingof three kinds of affirmative and negative sentences. In the first experiment, Ss were timed while they read a sentence, looked at a dot array, and then judged the sentence true or false with respect to the picture. The results showed that explicit syntacticnegatives (e.g., None of the dots are red) and implicit syntactic negatives (e.g., Few., .) were processed differently than semantic negatives which were referentially equivalent to few (e.g., A minority...). All three types of negatives took longer to verify than affirmatives. Two further experiments confirmed that Ss coded the arrays accompanying the imphcit syntactic negatives (few) and semantic negatives (a minority) in terms of the larger and smaller subsets of dots, respectively, thus accounting for the difference in processing.
The present paper reports a series of experiments designed to study how people process different kinds of negatives. Psychological research has previously shown that negatives with not (e.g., Seven is not an even number) are processed differently from affirmative sentences. For instance, the studies of Wason (1959, 1961, 1965), Wason and Jones (1963), and Gough (1965, 1966) all indicate that reaction time (RT) to such negative sentences is longer than to affirmative sentences, whether the task is verifying or completing sentences. However, negation exists in more forms than just the explicit not morpheme. For instance, Klima (1964) presented three criteria that defined a class of what he called negative preverbs. By Klima's criteria of either-conjunction, negative-appositive tag formation, and negative-question tag formation, a sentence with the word f e w or scarcely any is as negative as a sentence with
the word not. As an example, sentences with not and f e w can be either-conjoined whereas affirmative sentences cannot: John does not go to class, and Mary does not go either. * John goes to class, and Mary goes either. Few boys go to class, and few girls go either. * Many boys go to class, and many girls go either.
While previous studies have illustrated differences between affirmative and negative sentences with the not morpheme, the present study was designed to test whether such processing differences exist when negation is implicit, as with the word few. There is another difference between words hke not and those like few. Sentences with the negative particle, for example, not, none, no, negate a proposition about an entire set, as None o f the apples is good, whereas syntacticThe order of authors was decided by the toss of a ally negative sentences with quantifiers, for coin. The studies were a completelycollaborative effort. example, few, scarcely any, seldom, may be The first author was supported by a Canada Council considered to negate a proposition about a Fellowship, while the secondauthor was supported by a proper subset, as Few o f the apples are good. National Science Foundation Fellowship while these studies were being conducted. The authors express Processing differences may exist between fulltheir appreciation to Dr. Herbert Clark for his con- set negation, such as none, and subset negation, structive advice throughout the project. such as few. 244
245
COMPREHENSION OF NEGATION A n o t h e r a i m of this research was to study the sentences that have the same reference as f e w a n d yet do n o t share the same syntactic properties. Sentences with the phrase a minority or a small proportion m a y refer to the same s i t u a t i o n as a sentence w i t h f e w , b u t sentences with a minority are n o t syntactically negative. F o r example, such sentences c a n n o t be eitherconjoined: * A m i n o r i t y of boys go to class, a n d a m i n o r ity of girls go either. The psychological question is whether such sentences are processed similarly to syntactic negatives with the same reference. F u r t h e r more, are such terms as a minority or a small proportion processed as t h o u g h they are negative with respect to phrases such as a majority a n d a large proportion ? These questions can be studied by e x a m i n i n g how people decode a n d i n t e r n a l l y represent sentences a n d pictures in verification tasks. These tasks require the c o m p a r i s o n o f two sources o f i n f o r m a t i o n leading to a decision o f true or false. A model p r o p o s e d by Clark (1969) a t t e m p t e d to characterize R T in verification tasks by m a k i n g the a s s u m p t i o n that a c o m p a r i s o n between two similar representations is easier t h a n a c o m p a r i s o n between two different representations. F o r the time being, the n a t u r e of a sentence's or a picture's intern a l representation will n o t be specified, except that such representations will be considered as
p r o p o s i t i o n s in which the person codes the i n f o r m a t i o n from the sentence or picture. Clark's model will be used to m a k e inferences as to the n a t u r e of these representations a n d the influence of n e g a t i o n a n d quantification on them. EXPERIMENT I
Method The experiment was a verification task in which the S was timed while he read a sentence, looked at a picture, and then decided whether the sentence was true or false with respect to the picture. Half of the sentences used are presented in Table 1. The other half were identical except the adjective black appeared in place of the adjective red. The three syntactic categories, listed in Table 1, are defined by the linguistic properties of their negative forms. They were: SYN-NOT, syntactic negatives (by Khma's criteria) with the negative particle; SYN, syntactic negatives without the negative particle; SEM, semantic negatives with the same reference as few, but not syntactically negative. Table 1 shows the three exemplars for each category of negation, along with their corresponding affirmative exemplars. Each sentence was accompanied by a 4 x 4 array of dots. For SYN-NOT, all 16 dots were the same color. For example, a picture that was true for The dots are red had 16 red dots. The picture that falsified the sentence had all black dots. A picture that made the negative sentence, The clots aren't red, true had all black dots. To falsify the sentence, the picture had all red dots. For both SYN and SEM, the arrays consisted of either 14 red and 2 black dots or the reverse. For example, the picture that was true for Many of the dots are red had 14 red and 2 black dots. The picture that
TABLE 1 EXEMPLAR SENTENCES IN THE THREE SYNTACTIC CATEGORIES
Category SYN-NOT
SYN
SEM
Affirmatives
Negatives
The dots are red All of the dots are red There are red dots
The dots aren't red None of the dots are red There are no red dots
Many of the dots are red Most of the dots are red Lots of the dots are red A majority of the dots are red About 14 of the 16 dots are red A large proportion of the dots are red
Few of the dots are red Scarcely any of the dots are red Hardly any of the dots are red A minority of the dots are red About 2 of the 16 dots are red A small proportion of the dots are red
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falsified the sentence had 14 black and 2 red dots. The picture that made the negative sentence, Few of the dots are red, true had 14 black and 2 red dots. To falsify the sentence the picture had 14 red and 2 black dots. The final design included three syntactic categories, three exemplars per category, affirmative and negative sentences, two truth values, and two color predicates, for a total of 72 different sentence-picture combinations. Each sentence was typed on a 4 x 8-in. stimulus card, and the corresponding dot array, ½-in. square, was drawn with a felt pen immediately to the right of the sentence. The card was viewed in a Cambridge Tachistoscope at a distance of 16 in. The S pushed a switch when he was ready for a trial, and 1 sec later a stimulus card was presented. The S was timed (in hundredths of a second) from stimulus onset while he read the sentence, then examined the dot array and decided whether the sentence was true or false with respect to the array. His decision was made using a twobutton decision apparatus, with a balanced assignment of dominant hand to true button across Ss. During the practice session, which consisted of 10 cards selected at random from the deck, the S was told when his response was incorrect. After the practice, all 72 cards were shuffled and the Swent through all the cards twice, with a 5-min rest in between the two runs. The entire session lasted about 50 min. The Ss were 20 nativeEnglish speaking Stanford undergraduates who participated as part of an Introductory Psychology requirement. Results
The R T d a t a was a n a l y z e d b y c o l l a p s i n g over the two runs a n d the two adjectives " r e d " a n d " b l a c k . " The R T s for e r r o n e o u s responses were disregarded, a n d the S was assigned a m e a n score based only on his correct responses for each exemplar. The analysis o f variance t r e a t e d the three e x e m p l a r s p e r c a t e g o r y as replications. F i g u r e 1 presents the m e a n R T for each o f the three syntactic categories as a function o f affirmation-negation (called Aff-Neg) a n d t r u t h value. I n the categories S Y N - N O T a n d SYN, true-affirmative sentences h a d a s h o r t e r R T t h a n false-affirmatives, while true-negative sentences h a d a longer R T t h a n false-negatives. These interactions in S Y N - N O T a n d S Y N were strong e n o u g h to result in an overall i n t e r a c t i o n o f A f f - N e g × T r u e - F a l s e , F ( 1 , 19) = 9.64, p < .01. The m o s t n o t a b l e result was
SYN
SYN-NOT,
SEM o
2.0 o v
o 1.8 E
i= g t.6 o
or14
oN-.~EC°
:j I
."
<-
-2Y"
0-
I
I
I
I
I
TRUE FALSE TRUE FALSE TRUE FALSE
FIG. 1. Mean RT for the three syntactic categories in Experiment I, when stimulus sentences and pictures were presented on the same card. t h a t the i n t e r a c t i o n was a b s e n t for S E M , where b o t h affirmative a n d negative sentences h a d shorter R T s when they were true t h a n when they were false. The absence o f the Aff-Neg × True-False interaction from one category ( S E M ) resulted in a t h r e e - w a y interaction o f C a t e g o r y × A f f - N e g × T r u e - F a l s e , F ( 2 , 38) = 5.52, p < .01. A posterlori, two o r t h o g o n a l c o n t r a s t s were used to test the pairwise differences in Aff-Neg × T r u e - F a l s e i n t e r a c t i o n a m o n g the three syntactic categories. The first test exa m i n e d the hypothesis t h a t the i n t e r a c t i o n was different in S Y N - N O T a n d S Y N . As F i g u r e 1 m i g h t suggest, the test was n o t significant, F(1, 38) < 1. The A f f - N e g × T r u e - F a l s e intera c t i o n present in S Y N - N O T a n d S Y N was significantly different f r o m the l a c k o f intera c t i o n in S E M , F(1, 38) = 10.35, p < .05, by a Scheff6 test. The m e a n R T to negative sentences was greater t h a n to affirmative sentences in all three categories F(1, 1 9 ) = 122.41, p < .01. N e g a t i o n time is o b t a i n e d by collapsing over true a n d false, a n d s u b t r a c t i n g R T to affirmative sentences f r o m the R T to negative sentences. The m e a n n e g a t i o n time was 280 msec for S Y N - N O T , 328 msec for S Y N , a n d 176 msec for SEM. These n e g a t i o n times were significantly different f r o m each other, F(2, 38) = 6.17, p < .01, a l t h o u g h the smallest n e g a t i o n time, in S E M , was still significantly different f r o m zero, t(19) = 5.46, p < .01.
COMPREHENSION OF NEGATION
False sentences had a longer RT overall than true, F(1, 19) = 13.06, p < .01. The difference in RT between true and false sentences did not differ significantly across the three syntactic categories: 68 msec for SYN-NOT, 64 msec for SYN, and 128 msec for SEM, F(2, 38) = 1.47. Overall, RTs increased from SYN-NOT (1603 msec) to SYN (1755 msec) to SEM (1892 msec), F(2, 38) = 43.22, p < .01. Within each syntactic category, all exemplar pairs showed the same pattern of RTs with respect to the Aff-Neg × True-False interaction (or lack of it), although there was some variability in negation times. The errors were distributed similarly across the three syntactic categories, with an overall error rate low enough (5.5 ~) to indicate that counting RT only for correct responses did not bias the data. More errors were made to negative than to affirmative sentences, with truenegative sentences accounting for the majority of errors. Discussion
It will be argued that syntactic negation referring to subsets (SYN) is processed analogously to syntactic negation with the negative particle (SYN-NOT). These two negatives focus the S's attention on the larger subset (in the case of SYN) or the entire set (in the case of SYN-NOT) of the accompanying array. On the other hand, SEM negatives focus the S's attention on the smaller subset. The Aff-Neg x True-False interaction in SYN-NOT, essentially a replication of previous results (Wason, 1961), may be explained in terms of a processing model proposed by Clark (1969). The essence of the model is the principle of congruence which asserts that a comparison between two pieces of information (e.g., a sentence and a picture) is easier when the representations of the two pieces of information are similar (congruent) and harder when the two representations are different (incongruent). For example, the information in the affirmative sentence The
247
dots are red may be represented in propositional form like (Dots be red). An array of 16 red dots, which verifies the sentence, may also be represented as (Dots be red). The comparison between these congruent representations results in a short RT to true-affirmatives. Incongruence between the sentence representation and the representation of 16 black dots results in a longer RT for false-affirmatives. A negative sentence, The dots aren't red, may be represented as a negation operator that denies an embedded proposition: (Neg (Dots be red)). A picture of 16 red dots falsifies the sentence, but because its representation has the color red, RT is relatively short for falsenegatives. Incongruence between the sentence representation and the representation of 16 black dots results in a longer RT for true-negatives. The model gives a reasonable explanation of the Aff-Neg × True-False interaction in SYN-NOT. Therefore, the model will be assumed as a basis of inference for the main interest of this experiment: the representations in SYN and SEM. The identical Aff-Neg × True-False interaction in SYN-NOT and SYN means that there were congruent sentence and picture representations for true-affirmatives and falsenegatives in both categories. In SYN-NOT, the interaction was predictable because Ss had no choice but to code the one color of the accompanying array. In SYN, where the array had 14 dots of one color and 2 dots of the other color, the interaction must have resulted because Ss coded the color of the larger subset. For example, Many of the dots are red includes the information that the larger subset is referenced and that the color of this subset is red, which may be represented as (Many (Dots be red)). This sentence representation will be congruent with the representation of the larger subset for true-affirmatives and incongruent for false-affirmatives. A SYN negative (e.g., Few o.f the dots are red) also focuses on the larger subset by denying that the larger subset is red. This concept may be represented as a negation operator and a
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doubly embedded proposition: (Neg (Many out the not marker, are more difficult to recog(Dots be red))). This sentence representation is nize than Wason's not-morpheme negatives. more congruent with the picture representa- A control group of 10 Ss, instructed to convert tion for false-negatives than it is with the pic- both SYN and SEM negatives, corroborated ture representation for true-negatives. Thus, these arguments by reporting great difficultyin the inference that the S coded the color of the performing the conversions. In addition, the larger subset for SYN sentences completely instruction to convert negatives increased accounts for the Aff-Neg x True-False inter- negation time by 225 msec for both SYN and SEM over negation time without conversion. action. The RT pattern for SEM indicates that Therefore, the hypothesis that SEM negatives affirmatives were interpreted as statements were converted to affirmatives was rejected. about the larger subset. The affirmative A The hypothesis that remains is that the difmajority of the dots are red may be repre- ference between SYN and SEM is due to the sented as (Majority(Dots be red)). The stra- effect of the two syntactic categories on how tegy of coding the color of the larger subset Ss coded the accompanying picture. The again results in congruence for true-affirma- hypothesis was tested in Experiment II by tives and incongruence for false-affirmatives. presenting the picture first and then removing However, the RT for SEM negatives indicates the picture before presenting the sentence. This that the S coded the color of the smaller subset procedure eliminated any possible different after reading a negative. For example, the effects SYN and SEM might have had on how sentence A minority of the dots are red could a picture is coded. be represented as information about the Another important result of Experiment I smaller subset: (Minority(Dots be red)). was the longer RT to negative than to affirmaCoding the color of the smaller subset results tive sentences found for all three categories. in congruence for true-negatives and incon- Negatives take longer to read than affirmagruence for false-negatives. Therefore, the tives, but even with reading time controlled, inference from this experiment is that the syntactic negatives take longer to verify than Aff-Neg x True-False interaction, or lack of affirmatives (Trabasso, Rollins, & Shaughinteraction, is the result of the way Ss coded nessy, in press). This psychological preference the arrays accompanying the sentences. In for affirmative over negative sentences can be particular, they seem to have coded the color related to the more general principle of markof the larger subset after reading a SYN nega- ing, which states that within certain pairs of tive and the color of the smaller subset after bipolar linguistic entities, one member of the a SEM negative. pair is preferred or unmarked and the other is Another possible explanation of the differ- unpreferred or marked. Greenberg (1966) ence between SYN and SEM negatives might noted that in all languages, full-set negation is be that Ss converted SEM negatives into linguistically marked (i.e., more complex) affirmatives before coding the picture (e.g., because "The negative always receives overt A minority of the dots are red into A majority expression, while the positive usually has zero of the dots are black), as Wason (1961) reported expression [p. 50]." In addition, he noted that some of his Ss did with not morpheme nega- many languages have no separate word for tives. However, conversion of SEM negatives few, and express the concept as the linguisticseems implausible because, contrary to the ally marked not many while no language exresults, such a strategy should have increased presses many as not few. The fact that affirmanegation time for SEM more than for SYN tives are unmarked and negatives are linguis(due to the added time to convert SEM nega- tically marked is completely correlated with tives). Furthermore, negatives in SEM, with- the finding in this study and previous studies
COMPREHENSIONOF NEGATION that affirmatives are psychologically less complex than negatives. Greenberg's linguistic data further suggest the generalization across languages that all syntactic negatives are psychologically m o r e difficult to process than corresponding affirmatives. A further interesting finding was that SEM negatives also have longer RTs than SEM affirmatives. It is already k n o w n that small is linguistically m a r k e d with respect to large. However, there are no linguistic data which would predict that minority would be less preferred than majority. Furthermore, there is no linguistic evidence that 2 out of 16 is marked with respect to 14 out of 16. Presumably all quantifiers referring to small quantities (or exceptions) are psychologically less preferred than quantifiers referring to larger quantities (or generalities). This preference relation between large and small quantities does not necessarily imply that the preferred entity constitutes the basis o f the unpreferred during processing. The R T pattern indicates, for example, that smatlproportion is not processed as not large proportion. Thus, the m a j o r difference between syntactic negation (SYNN O T and SYN) and the semantic negation o f S E M is that syntactic negatives are processed in terms o f their affirmatives, while S E M negatives are not, although S E M negatives still are m o r e difficult to process than their affirmatives.
EXPERIMENT II
Method The main innovation in Experiment II was that the presentation of the dot array was completed prior to the presentation of the stimulus sentence. The dot arrays and stimulus sentences were on separate cards presented through two channels of an Iconix tachistoscope. The dot arrays were 1½in. square. The sentences were typed on separate cards in large print on an IBM Executive Directory typewriter with an average sentence length of 3 in. and were viewed at a distance of 4 ft. The S initiated the trial by closing a switch with a 500-msec delay interval, after which time the dot array was presented for 1500 msec, followed by a 250-msec
249
blank interval, and finally followed by the presentation of the sentence alone. The S's response was recorded, with RT measured from the onset of the stimulus sentence. The S went through all 72 stimulus cards once, except for those trials on which he made an error or did not respond within 4 sec, in which case the response but not the RT was recorded, and the stimulus card was replaced among the remaining unused stimulus cards. Thus there was a correct response RT to all stimuli. The procedure was otherwise identical to Experiment I. The 11 Ss were from the same S pool as in Experiment I, although none had participated in Experiment I.
Results Experiment II was designed to test the hypothesis that the difference between S Y N and SEM was due to differences in h o w the S coded the picture after reading the sentences f r o m each category. The RTs were based only on correct responses with a low overall error rate o f 7.2 ~ . The data were analyzed, collapsing over red and black adjectives. A g a i n the three exemplars per category were treated as three replications in the analysis o f variance.
20
SYN-NOT _
SYN
SEM o
N
A
~°18 E i.xl6
g
O,o NEG
/ j° B,"~FF • A~FF °
./ 1.2
I I I I TRUE FALSE TRUE FALSE TRUE FALSE
FIG. 2. Mean RT for the three syntacUc categories an Experiment II, when pictures were presented prior to stimulus sentences.
Figure 2 presents the mean RTs o f the 11 Ss for the three syntactic categories as a function o f Aff-Neg and True-False. The twoway interaction o f Aff-Neg × True-False was n o t significant overall, F(1, 10) < l, because
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JUST AND CARPENTER
the interaction was only present for SYNNOT. This difference in the presence of the interaction among syntactic categories was significant, F(2, 20)=10.21, p < . 0 1 . In Experiment I, SYN had an Aff-Neg x TrueFalse interaction, whereas it was absent from SEM. The change in experimental manipulation in Experiment II, requiring the S to code the picture prior to the sentence presentation, eliminated the Aff-Neg × True-False interaction from SYN. A method of contrasts test showed that SYN and SEM did not differ significantly as a function of Aff-Neg and True-False, F(1, 20) < 1. The orthogonal contrast test showed the Aff-Neg x True-False interaction present in SYN-NOT differed significantly from the lack of interaction in SYN and SEM, using the Scheff6 test, F(1, 20) = 19.58, p < .01. Negative sentences took significantly longer than affirmative sentences in Experiment II as in Experiment I, F(1, 10)= 40.67, p < .01. Negation times across the three syntactic categories were 247 msec for SYN-NOT, 312 msec for SYN, and 138 msec for SEM, but these negation times were not significantly different from each other, F(2, 20) = 2.23. False sentences took longer than true sentences in all categories, F(1, 10)= 19.90, p < .01. This difference between true and false sentences increased significantly from SYNNOT to SYN to SEM, from 4 to 96 to 201 msec, respectively, F(2, 20)= 6.27, p < .01, with the latter two values significantly different from zero, F(1, 10) = 5.96, p < .05, and F(1, 10) = 26.14, p < .01. As in Experiment I, there was a significant overall increase in RT going from SYN-NOT (1384 msec) to SYN (1716 msec) to SEM (1777 msec), F(2, 20) = 26.98, p < .01. There was an overall decrease in RT of 125 msec between Experiment I and Experiment II, with means of 1759 msec and 1624 msec, respectively. The decrease was probably due to the procedural change in Experiment II, which gave the S a chance to code the picture before the timing started.
Discussion Presenting the picture first eliminated the effect of the SYN and SEM categories on picture coding and, therefore, made the RT patterns for SYN and SEM similar. On the other hand, the Aff-Neg x True-False interaction was predictably present for SYNNOT, since the S could only code the one color in the picture and compare this ~epresentatlon with the representation of the subsequent sentence. The question might be raised as to what strategy Ss used in SYN and SEM when presented with a dot array made of two subsets. One possibihty is that because the S did not know the kind of sentence to follow, he used the 1500-msec display time to redundantly code both subsets of the array (e.g., larger subset--red, smaller subset--black). When the sentence was displayed, the S used the referenced quantity (larger or smaller subset) in the comparison process and checked whether the color adjective in the picture representation matched that of the sentence. Certainly the kind of sentence did not dictate the picture coding strategy, as in Experiment I where the sentence preceded the picture array. Whatever the strategy, in this experiment Ss were not differentiating between SYN and SEM when they coded the picture prior to seeing the sentence. Individual S data also showed that the RT patterns for SYN and SEM were similar within Ss. Clearly, the next step was to control exactly how the picture was coded prior to the sentence presentation.
EXPERIMENT III Method The main change from Experiment II to Experiment III was the introduction of two instructions which told the Ss how to represent the dot array to themselves while they were waiting for the sentence to be presented. One instruction was to code the array in terms of its larger subset color. For example, 14 red and 2 black dots would be coded as "many red" or "majority
red" or some equivalent form which stressed the preeminenceof the larger subset. The alternate instruction was to code the array in terms of its smaller subset color.
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COMPREHENSION OF NEGATION
Each of three Ss was tested m four 1-hr sessions on four consecutive days, with one instruction per day, counterbalanced across days. Stimuli from only categories SYN and SEM were used, each session consisting of two runs through the 48 sentence-picture combinations. The remainder of the procedure was identical to Experiment II. The three Ss were the two authors as well as one paid, naive Sfrom the pool of the Introductory Psychology course.
Ss' coding strategies were not controlled. The inference from Experiment I, that Ss coded the color of the larger subset after reading a syntactically negative sentence, is supported by these data.
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Results and Discussion
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This experiment was designed to test the hypothesis that the nature of the Aff-Neg x True-False interaction could be determined by controlling the picture coding. The RT data, collapsed over the three Ss, are presented in Figures 3 and 4. The RT patterns were highly similar across Ss, a finding consistent with the hypothesis that some of the variance in group data is the result of differences in individual S's strategies for picture coding. Separate analyses of variance were done for the data of each S.
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TRUE FALSE TRUE FALSE FIG. 3. Mean RT for the two syntactic categories in Experiment III with the instruction to code the larger subset of the picture.
As Figure 3 shows for both SYN and SEM, an instruction to code the color of the larger subset made true-affirmatives easier than falseaffirmatives, but true-negatives were harder than false-negatives. An important feature of the data is that this interaction, under the instruction to code the color of the larger subset, is the same type of interaction found for SYN-NOT and SYN in Experiment I, when lO
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TRUE FALSE TRUE FALSE FIG. 4. Mean RT for the two syntactic categories in Experiment III with the instruction to code the smaller subset of the picture.
The opposite Aff-Neg x True-False interaction resulted when the S was instructed to code the smaller subset color, as shown in Figure 4. The difference in Aff-Neg x TrueFalse interactions with the two instructions was highly significant for all three Ss, F(1, 23) = 40.91, 41.77, and 6.132, respectively, p < .01. Different coding instructions result in opposite Aff-Neg x True-False interactions, confirming the maj6r hypothesis that the way a picture is coded determines where congruence between sentences and pictures will occur, and hence determines the nature of the interaction. One unexpected finding was that with the instruction to code the smaller subset, negative sentences in SEM had a shorter RT than affirmative sentences for all Ss, F(I, 23) < 1, and F(1, 23) = 18.87, 56.55, p < .01. This was not the case for SYN, where negative sentences took longer than affirmative sentences for two Ss, F ( l , 23) < l~andF(1, 23) = 48.66, p < .01, but negative sentences had a slightly shorter RT than affirmatives for the third S, F(1, 23) =2.91, n.s. Over Ss, the instruction to code the smaller subset resulted in negation times for SEM (-130 msec) and for SYN (123 msec) that were equal in magnitude but opposite in direction. Therefore, the instruc-
252
JUST AND CARPENTER
tion to code the smaller subset had an overall zero negation time. Negation time with the instruction to code the larger subset was 284 msec for SEM and 285 msec for SYN, a mean negation time of 284 msec. The difference in mean negation times of the two instructions resulted in a significant interaction of Instruction × Aff-Neg, F(1,23) = 58.94, 10.77,p < .01, and F(1, 23) = 7.54, p < .05, for the three Ss, respectively. The reversal of negation time when coding the smaller subset with SEM sentences can possibly be accounted for in terms of the marking relation between negatives and affirmatives. SEM negatives, referring to small quantities, are normally unpreferred, but if the S attends to small quantities the usual preference relation is reversed. Thus, with the instruction to code the smaller subset, small quantities become preferred, and, hence, SEM negatives are easier than "affirmatives. The decrease of negation time for SYN with the instruction to code the smaller subset is due to this same attentional constraint. With no coding instructions, SYN negatives are unpreferred in two ways: (a) with respect to syntactic negation (as are SYN-NOT negatives); and (b) with respect to smaller quantities (as are SEM negatives). The instruction to code the smaller subset does not affect the syntactic negation for SYN, but it reverses the quantity preference relation for SYN as it did for SEM. In fat*. negation time decreases for SYN from 28:, to .23 msec with the instruction to code the larger subset and smaller subset, respectively. It seems that the quantity marking is susceptible to attention changes, while syntactic negation marking is not. Though this experiment was not designed to test a theory about the double marking of negation and quantity in SYN, the data are compatible with such an interpretation. GENERALDISCUSSION These experiments were originally conceived as investigating a continuum of negat on from
none to few to a small proportion. An alternative way of conceptualizing the problem is to distinguish two factors: scope of negation (full set vs. subset) and syntax (syntactic negation vs. semantic analogues). In such a scheme, none, few, and a small proportion are full syntactic, subset syntactic, and subset semantic negation, respectively. The fourth cell would be full semantic negation, for example, The dots are absent. The Aff-Neg × True-False interaction should occur with the full-set semantic negation, since there is no choice (as in SYN) in picture coding. Clark (personal communication) has obtained this result for absent. Both full and subset syntactic negatives focus on the larger subset or entire set because they are negating a proposition about those sets. This is obvious in None of the dots are red, which may be represented as (Neg(All(Dots be red))), with the focus on all. Few of the dots are red includes this syntactic negative property, as well as possibly a quantification marking. This may be represented as (Neg(Many(Dots be red))) with the focus on many, plus an implicit marking (smaller quantity red). All negatives are unpreferred, but the essence of their negativity is that they are dependent on their affirmative for focus. This argues for the generalization that all syntactic negatives may have the same basic internal representation as their corresponding affirmatives, but with an additional negation operator. SEM negatives, on the other hand, do not focus on the larger subset and are marked only with respect to quantity. The demonstrated marking of relatively small quantities in SEM may explain Wason's (1965) failure to confirm the ratio hypothesis in "The context of plausible denial." Wason's ratio hypothesis was: "Given two sets of stimuli which differ considerably in magnitude, it is more plausible to deny that the smaller set possesses a property of the larger set than to deny the converse [p. 8]." That is, Exactly one (of eight) circles is not red is a more plausible expression than Exactly seven (of
COMPREHENSION OF NEGATION
eight) circles are not blue. The reason the ratio hypothesis was not confirmed was probably because the former sentence contained, in fact, a "double negatwe". It contained both an unpreferred quantifier (smaller subset, similar to 2 out of 16) as well as an explicit negative (not), while the "less plausible" sentences only contained the explicit negative. REFERENCES
CLARK, H. H. Linguistic processes In deductive reasoning. Psychological Review, 1969, 76, 387404. GotJ~H, P. B. Grammatical transformations and speed of understanding. Journal o f Verbal Learning and Verbal Behavior, 1965, 4, 107-111. GOUGH,P. B. The verification of sentences: The effects of delay on evidence and sentence length. Journal o f Verbal Learning and Verbal Behavior, 1966, 5, 492-496.
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GREENBERG, J. H. Language universals. The Hague: Mouton, 1966. KLIMA,E. S. Negation in English. In J. A. Fodor and J. J. Katz (Eds.), The structure of language. Englewood Cliffs, N.J.: Prentice-Hall, 1964. TRABASSO, T., ROLLINS, H., & SHAUGHNESSY, E. Storage and verification stages in processing concepts. Cognitive Psychology (in press). WASON, P. C. The processing of positive and negative information. Quarterly Journal of Experimental Psychology, 1959, l l , 92-107. WASON, P. C. Response to affirmative and negative binary statements. British Journal o f Psychology, 1961, 52, 133-142. WASON,P. C. The contexts of plausible denial. Journal o f Verbal Learning and Verbal Behavior, 1965, 4, 7-11. WASON,P. C. & JONES, S. Negatives: Denotation and connotation. British Journal of Psychology, 1963, 54, 299-307. (Received October 7, 1970)