Answering questions about negative conditionals

25.691-709

JOURNALOFMEMORYANDLANGUAGE

(1986)

Answering Questions about Negative Conditionals P. WRIGHTAND A.J. HULL Medical

Research

Council

Applied

Psychology

Unit,

Cambridge

Two studies explored readers’ mental representations of declarative sentences containing and IF NOT. Errors and reading times showed that people represented IF NOT as a positive action and negative condition. Performance with IF NOT was unaffected by the order of condition and action in the text but was better if subsequent information referred to the condition rather than to the action. Three rules governing readers’ representations are proposed to account for performance with IF NOT. An additional rule is needed for UNLESS, which was sometimes represented as a negative action and positive condition. Choice of representation for UNLESS varied with the writer’s order of mentioning action and condition information. D 1986 Academic Press. Inc. UNLESS

Reading is a strategic activity in that people read texts for many purposes. Variation in reading strategy is reflected in many aspects of reading performance. For example, modifying the reading purpose from “recall” to “answering questions” will change where readers pause (e.g., Aaronson and Scarborough, 1976) and can also influence readers’ representation of the information in the text (Aaronson, 1976). In spite of the evidence that readers have alternative representation strategies available, there is not yet a clear understanding of the principles governing when particular strategies will be selected. Among the factors likely to influence strategy selection are (1) syntax (e.g., readers may prefer to represent main and subordinate clauses in particular ways), (2) pragmatics (e.g., where temporal sequences are involved, readers may choose to reflect these sequences in their representation), (3) processing complexity (e.g., people may prefer to allocate more difficult proWe are extremely grateful to Dr. Geoffrey Leech of the University of Lancaster, U.K., for making the frequency data available to us, and to Marcel Just for his incredible patience with earlier versions of this work. Reprint requests should be addressed to Dr. P.Wright, MRC Applied Psychology Unit, 15 Chaucer Rd.. Cambridge CB2 2EF, England.

cessing to a particular segment of the representation), and (4) lexis (i.e., atypical representations may be associated with certain lexical items). Because all four factors are potentially relevant to readers’ choice of representation for negative conditionals, the present studies will examine how readers represent information from declarative sentences containing IF NOT and UNLESS. These conditionals both involve temporal contingencies, and they both signal the start of a subordinate clause. The similarities in the syntax, pragmatics, and negativity give rise to the expectation that readers will represent IF NOT and UNLESS in similar ways. However, these conditionals differ at the lexical level in terms of the explicitness of the negation. Sherman (1973) has shown that people find it harder to process explicit negatives (e.g., not happy) than implicit negatives (e.g., unhappy/sad). Part of the explanation offered by Sherman concerns the inherent ambiguity of the explicit negative (e.g., not happy) which allows a wide range of interpretations from “neutral” to “sad”. Ambiguity seems less of a problem with IF NOT and UNLESS because, in certain contexts, they yield comparable interpretations (e.g., “The tourists intend to walk if it is not raining” has the same import as “The tourists intend to walk unless it is

691 0749-596X’86 $3.00 Copyright Q 1986 by Academic Press. Inc. All rights of reproduction in any form reserved.

692

WRIGHT

raining”). This equivalence does not always hold. There is no equivalence when the negative element qualifies only part of the following clause, especially the noun phrase rather than the verb phrase. Compare sentence la, lb, and lc where the meaning of 1b is quite different from the meaning of la and lc. la. All noises will be ignored unless one of them has special significance. lb. All noises will be ignored if one of them does not have special significance. lc. All noises will be ignored if not one of them has special significance. The present studies will be confined to materials where the two conditional terms are interchangeable, but because they differ in the way the negative is signified, it is an open question as to whether readers will represent both conditionals in similar ways. In a well-written text, the clause orders within a sentence will be chosen by the author not only to maintain cohesion but also to facilitate the cognitive and linguistic processing which readers have to carry out. Bock (1982) has suggested that information requiring more difficult cognitive processing will be placed later in the sentence, and easier information will be given at the beginning. This is consistent with evidence that presupposed information is usually given before new information, since it is the new information which will require more processing (Clark & Haviland, 1977; Haviland & Clark, 1974). Negative conditionals might well afford an instance of the kind of complexity that is more easily dealt with when it occurs late in the sentence. If Bock’s suggestion applies to readers’ representation of negative conditionals, then we would expect that sentences in which positive action information precedes negative conditional information will be easier for readers to understand than sentences where the condition is mentioned before the action. It should be noted that this is the reverse of the temporal con-

AND

HULL

tingency where an event, denoted by the conditional information, must precede the action to be performed. Performance with IF NOT has been examined in studies where procedural information has been given. Wright and Wilcox (1979) used procedural instructions in tasks where the action information (e.g., Do action A) always preceded the condition information (if condition C does not arise), and the prevailing contingency determined whether a response was either made or withheld. They found more errors occurred when there was a negative element in the first clause than when the negative element occurred in the second clause. That is to say the written instruction, “Do not do action A if condition C” was more error prone than “Do action A if condition C does not happen.” This appears fully consistent with Bock’s theory that it is easier for people to deal with complexity (here negativity) when it occurs later in the sentence. However, in related studies where one of two alternative responses had to be made on each trial, Wright and Wilcox found that this pattern of difficulty changed. Instructions having negative information relating to the condition (Do action A if condition C does not happen) were more error prone than those having negative information relating to the action (Do not do action A if condition C happens). Neither order of mention nor syntax was systematically varied by Wright and Wilcox; nevertheless the performance variation across these two tasks implies that there are multiple determinants of performance, presumably mediated by the different representations which people can adopt. The data from both these studies suggest that no matter what the representation chosen, negative actions and negative conditions differ in their effect on the ease of processing imperative sentences. Readers’ representation of other conditionals has been examined for procedural information (e.g., Dixon, 1985). Several

REPRESENTINGNEGATIVECONDITIONALS

studies have shown that instructions are easier to follow, or are executed more rapidly, if the action to be performed is mentioned before giving the relevant contingency under which the action should be carried out (Dixon, 1982, 1984). Action and condition information are likely to be accorded different status in readers’ creation of action plans because action sequences are generally represented as hierarchies of schemas, where the superordinate schema corresponds to intention and the subordinate schemas are triggered by appropriate conditions (Norman, 1981). In contrast to what is done when reading for the purpose of creating an action plan, readers’ representation of declarative information may not differentiate between action and condition information as such. Instead, the priorities assigned within the reader’s representation may be determined by the writer’s syntax. One reason for such assignment is that in a well-written text the author’s expression will maintain thematic cohesion. So the reader of declarative information may adopt a propositional representation in which the ordering of the propositions reflects the order of mention in the text. In this case the author’s sequencing of information may influence the relative ease with which the represented constituents of the sentence can be accessed. The present studies will focus on declarative rather than imperative sentences. Dixon (1984, 198.5) also showed that task parameters, such as the recoding options available, could influence readers’ representation. He found that when people were following instructions their pattern of performance changed as a function of their prior knowledge. This implies that there can be no simple metric of “difficulty” for linguistic structures. Difficulty will be a function of the processing undertaken; this in turn will be influenced by task characteristics. The task chosen for the present studies involves the successive presentation of two sentences, followed by a question which requires readers to integrate the

693

information from both sentences (see 2a-c). 2a. Sentence 1. The team would lodge an objection if the referee did not start the game. 2b. Sentence 2. The referee did start the game. 2c. Question. Did the team lodge the objection? In order to develop a model of how this task is done, let us suppose that readers first represent the information as given by the writer, and then they optionally apply certain recoding strategies to this representation. As we mentioned earlier, one recoding option might be to reflect the syntactic priorities of main and subordinate clause relations. This might be expected to yield differential ease of access to information about the action (main clause) and condition (subordinate clause) information. It also gives rise to the expectation that forming this representation will be easier if the writer mentions the action before the condition (cf. Jarvella and Herman, 1972). The need to have negative elements late in the sentence gives rise to the same expectation for these conditional sentences. If readers seek to represent the condition-action contingency, this could be done in several ways. The representation might specify only the contingency for the condition mentioned by the writer, or readers might infer the missing contingency and represent that as well, or they might have a bias toward representing positive contingencies (i.e., what happens if condition C occurs, rather than if condition C does not occur). If readers represent only the contingency they have read about, then for IF NOT and UNLESS, we would expect performance to be better (faster or more accurate) when sentence 2 also refers to negative (rather than positive) information about the condition. If this advantage for negative, rather than positive, information in sentence 2 is not found, then other possible representations of the contingency information will need to be considered.

694

WRIGHT AND HULL

Table 1 outlines a processing model in which the representation of sentence 1 is assumed to undergo processing operations reflecting the writer’s word order, an assignment of syntactic priorities which is overwritten by the pragmatic need to maintain the contingent sequence of conditionaction. Table 1 suggests the ordering of these operations is critical to determining ease of processing. As outlined in Table 1, readers must manipulate their representations more often when writers mention the condition before the action. If the data do not support this suggestion then the operations can be reordered (interchanging 1.2 and 1.3 would yield the expectation of poorer performance when writers mention the action before the condition), or certain operations may be omitted. The general outline given in Table 1 does not specify whether the reader’s representation retains the full surface structure characteristics of the sentence or whether some more abstract propositional representation is adopted, or even some form of mental model (Mani & Johnson-Laird, 1982). For our immediate purposes this aspect of the form of the representation will not be critical. We can still consider how the subsequent representation of sentence 2 might be integrated with readers’ representation of sentence 1. While Table 1 out-

lines these processes only in general terms, Table 2 indicates the processing operations that would follow each of the four sentence 2 variants. We are assuming that both conditionals undergo similar processing. A summary of the relative ease of integrating information from sentence 2 is given via the index of “processing complexity” in the bottom row of Table 2. This index is derived from assuming an increment in complexity for each new representation the reader must create, plus an increment for answering No rather than Yes when the question fails to match any element in the current representation (Carpenter and Just. 1975). The loci of these increments are starred in the model. The need to process a double negative, when sentence 2 is negative and refers to the action, is given a larger increment. Although this appears arbitrary, the data will indicate whether such an assumption is warranted. In summary, model 1 makes four predictions: (I) Ward order. The order in which the writer mentions action and condition information will influence the ease of representing the information from sentence 1 but will not effect the ease of processing sentence 2, because a common representation will have been formed before reading sentence 2.

TABLE 1 MODEL 1 Writer’s order AC Reader’s representation of sentence 1 +A -C 1.1 Representation from word order +A -C 1.2 Syntactic priority -C +A 1.3 Sequence contingency Operations on sentence 2 2.1 Represent information 2.2 Check if match exists with any element of previous representation: If yes -+ question: if no change to action, then + question Operations following question 3.1 Represent question 3.2 -Check match with current representation: If match, respond Yes; if no match. respond NO

CA -C +A +A -C -C +A + infer

695

REPRESENTING NEGATIVE CONDITIONALS

EXAMPLE

OF How

FWXESSING

OPERATIONS

TABLE 2 1 VARY

IN MODEL

WITH

THE INFORMATION

IN SENTENCE

2

Representation of sentence 1

-C +A

-C +A

-C +A

-C +A

Sentence2 either 2.1 Representation of sentence2 2.2 Inferred new representation 3.1 Representation of question 3.2 Answer

Positive condition +c -A* +A No*

Negative condition -C

Positive action +A

i-A Yes

+c No*

Negative action -A -* ( -C) = +c** +c Yes

Processingcomplexity:

2

0

I

3

(2) Conditionals. Readers will form com- The design was repeated with another parable representations for IF NOT and UN- group of 16 subjects. LESS. Performance was self-paced and the (3) Positive/negative. Performance will measures taken were the reading times on be better if further information about the sentences 1 and 2 and the time to read and condition is negative rather than positive, respond to the question. or if further information about the action is Subjects. The data analyzed come from positive rather than negative. 32 adult volunteers from the subject panel (4) Condition/action. Performance will be of the Applied Psychology Unit. They were better when sentence 2 refers to the condi- paid for taking part in the experiment. tion rather than the action, if sentence 2 is Their ages ranged from 19 to 61 years, negative. This trend will reverse when sen- mean age 43 years. Because the main analtence 2 is positive. ysis focused on time data, people who wrongly answered all four questions in any EXPERIMENT 1 treatment combination were replaced, as were people who had more than 30% errors Method with either conditional term. There were Design. A 2 x 2 x 2 x 2 mixed design six “high error” replacements, among was used. The within-subject factors were whom there were no evident error patterns related to sentences 1 and 2 as shown although more errors were made with UNbelow: LESS (48% items incorrect) than with IF Sentence 1: Clause order either AC or NOT (22% wrong). Four of the subjects who CA; conditional either UNLESS or IF NOT; were retained had more than 20% errors, Sentence 2: Mentioned either the action but none more than 25% overall. or condition, either positively or negaMaterials. A list of 86 sets of triplets tively; (sentence 1, sentence 2, question) was deQuestion: A positive, yes/no question re- vised. All 86 sentence contents were diflating to the information not given in sen- ferent. This list was made up of 6 practice tence 2. items, 16 filler items which did not involve Across subjects it was possible to coun- either UNLESS or IF NOT, and 4 occurrences terbalance for clause order and conditional. of each of the 16 treatments. That is to say, for each specific content Care was taken when designing the mateused for sentence 1 there were four rials, to be certain that the question could variants and these were paired with each of not be answered solely from the pragmatics the four variants of sentence 2. It therefore of sentence 2 without semantically protook 16 subjects to complete the design. cessing sentence 1. For example, if sen-

696

WRIGHTANDHULL

tence 2 said “It was raining” and the question asked “Did the family have a picnic?” the answer has a high probability of being “No” independently of the information given in sentence 1. To avoid this, an operational criterion was applied to sentence 1, which stipulated that it should also be an acceptable English sentence when a positive conditional (such as IF) replaced the negative conditionals being used in this experiment. This criterion eliminated sentences such as “The French yachtsman would win the race unless his mast broke” but permitted sentences such as “The French yachtsman would win the race unless the wind changed.” Care was also taken to ensure that the conditional information in sentence 1 could be easily expressed with both UNLESS and IF NOT. The order of the sentence contents was maintained throughout the experiment, but 16 different presentation lists were used to cover all combinations of the four sentence 1 treatments and the four sentence 2 treatments. It is inevitable, given that the two conditionals being studied are UNLESS and IF NOT, that the phrasing of the verb in sentence 2 when giving further information about the condition will vary in its correspondence to the verb phrase within sentence 1. The conditional clause in sentence 1 could have been either “unless the wind changed” or “if the wind did not change.” The main difference between these two verb phrases is the presence of DID. It was decided to include DID in sentence 2 because this made the verb form fairly similar for the positive and negative versions of sentence 2 (i.e., DID could be included in both a positive sentence 2, “The wind did change,” and in a negative sentence 2, “The wind did not change”). But it should be noted that this verb phrasing chosen for sentence 2 corresponds more closely to the verb phrase in sentence 1 when the conditional was IF NOT rather than UNLESS. Procedure. Subjects sat in front of a 12-in. video display screen on which the written information appeared in white capital letters on a black screen. The display

had 40 characters per line. Subjects had a three-key response box. One key would change the display and two other keys were used for giving Yes and No answers. There were no facilities for backtracking through the display. This was pointed out to subjects who were instructed to read each sentence carefully and then respond to the question as quickly as possible. The response box was interfaced with an Apple II computer which controlled the stimulus presentation and, via an internal clock, recorded to the nearest millisecond the time at which all keys were pressed. Results Errors

It was pointed out when describing the subject population that in order to have adequate time data, the overall error rate was held to an artificially low level (10.2%) by replacing people who had high error rates. As a consequence the distribution of errors across the 16 treatments is thin. Nevertheless, errors were made by all subjects and, as was true of the subjects replaced, more errors were made with UNLESS (16.5%) than with IF NOT (11.9%). All statistical comparisons within the error data were done by means of two-tailed Wilcoxon signed ranks tests. The different error rates for the two conditionals was statistically significant (T = 50, Z = 2.86, p < .Ol). However, our primary concern is in the error patterns as a function of sentence 2 factors (see Figure 1). Positive vs negative. For IF NOT, when sentence 2 concerned the action, negative information was significantly more error prone than positive information (by subjects, ?‘ = 59.5, Z = 2.39, p < .05; by sentences, T = 87.0, Z = 1.80, p < .05). But when sentence 2 referred to the condition there was no significant difference between positive and negative information. When the conditional was UNLESS there were no significant differences between positive and negative information either for action or condition information.

REPRESENTINGNEGATIVECONDITIONALS

m ,..’ &..’

,..’

,..’

condition

,,.,..A

co”d,+io”

,.” ,..’

,.:

,..’

..’

.. ./CA

,:’

*.’

. ..” AC mtion CA ortlo”

:::::-

01 p Par

w

I

POS

w

I

FIG. 1. Experiment 1: Effect of positive/negative sentence 2 on the mean % errors.

Action vs condition. For IF NOT, reference to the action was more error prone than reference to the condition when sentence 2 was negative (by subjects, T = 45.5, Z = 2.99, p < .Ol; by sentences, T = 29, Z = 2.02, p < .05), but there was no difference when sentence 2 was positive. For UNLESS there was no significant difference between the errors made with action and condition information. AC vs CA. Changing the order in which the clauses are mentioned from AC to CA produced slightly more errors in almost all subconditions. Pooling across subconditions, this difference was not significant for either conditional. However, within UNLESS there were significantly more errors following CA sentences than AC sentences, when sentence 2 was positive and referred to the action (T = 17, Z = 1.99, p < .05).

Time Data The individual data points on which the following analyses are based are the median times of each subject (S) from the four replications of each of the 16 treatment combinations. The times for questions not correctly answered were excluded from the computation of these medians. So too were values which seemed exceptionally long (i.e., more than 20 s to read sentence 1).

697

Empty cells were replaced by the mean of the row (S’s overall performance) and column (treatment) means. This replacement was done for 13 of the 512 cells in the analysis of sentence 1. The statistical analyses were done both by subjects and by “sentences.” However, across a group of 16 subjects each sentence content occurred only once in each of the treatment conditions. Therefore if an error were made, the cell was empty. To compensate for this, data for the “sentences” factor were pooled for each subject across the four sentence contents which contributed to a specific treatment combination, and the medians of these sets of four sentences were used in the analysis. Thus the sentence analysis had some comparability with the subject analysis which was carried out on the median of four values. However, it must be remembered that the factor being called “sentences” was in fact a composite of several sources of variance including sentence content and serial position in the list. It has been conventional to analyze time data by means of analyses of variance. The power of applying such statistical tools to data which do not meet the criteria concerning the underlying distribution has recently been challenged (Blair & Higgins, 1985). Although extremely long latencies were removed from the present data, there remained wide individual differences. So it was decided to follow the recommendation of Blair and Higgins to use the nonparametric Wilcoxon test for analyzing these data. All comparisons are two-tailed unless it is stated otherwise. Sentence 1. The mean time spent reading sentence 1 is shown in Figure 2. These times refer only to trials where people gave the correct answer. None of the sentence 2 factors are relevant here, since sentence 2 has not yet been presented. So the only statistical comparison of interest concerns the clause order of sentence 1. Statistical analysis confirmed that for sentences containing UNLESS the clause order AC was read faster than the clause

698

WRIGHTANDHULL

AC

CA.

AC

CA

FIG. 2. Experiment 1: Effect of writer’s order on the mean time to read sentence 1.

clause

order CA (analysis by subjects, T = 115, Z = 2.79, p < .Ol; analysis by sentences, T = 145, Z = 2.23, p < .03). In contrast, for sentences containing IF NOT, reading times were not affected by clause order (this comparison was not significant either by subjects or by sentences). Although Figure 2 suggests that the main difference between the conditionals occurred with the clause order AC, only 18 of the 32 subjects spent less time reading UNLESS than IF NOT AC sentences, with 14 people showing the reverse trend. Sentence 2 + Question. During testing it was observed that some people paused on sentence 2 and worked out what the question was going to be before they read it. In contrast, other people read sentence 2 rapidly and spent considerably longer working out their answer while the question was on the screen. The ratio of time spent reading sentence 2 to the time spent answering the question ranged from 0.49, on occasions when people hurried through to the question, to 3.94, on occasions when people paused on sentence 2 and anticipated the question. For 17 people this mean ratio fell within the range 1.2 I- 1.6 1, indicating that they spent about half as long again on reading sentence 2 as they did on reading and answering the question. For 9 people

the ratio fell between I.2 and 0.95, indicating that they spent roughly equal time on sentence 2 and the question. For 6 people the ratio fell between 1.61 and 2.22, indicating that they spent roughly twice as long on sentence 2 as on the question. As the simplest way of handling this variation in where people chose to pause and manipulate the information they were reading, the analysis was undertaken on the combined time spent reading sentence 2 and answering the question. It will be remembered that the question had been included on each trial simply to give an orienting task for reading the sentences. The data for the analysis were generated by taking medians, in the same way as for the analysis of time to read sentence 1. Times relating to errors were excluded as were unduly long times (over 10 s to read sentence 2 and answer the question). In line with the previous analysis procedure, 1 I of the 512 cells were replaced by the mean of the row and column means. The pattern of mean times across all treatment conditions is shown in Figure 3. The same three statistical comparisons were made as for the error data. Positive vs negative. For IF NOT the difference between positive and negative information was significant only for condition information, where performance was

FIG. 3. Experiment 1: Effect of positive/negative sentence 2 on the mean time to read sentence 2 and answer the question.

REPRESENTINGNEGATIVECONDITIONALS

faster if sentence 2 was negative rather than positive (by subjects, T = 130, 2 = 2.51, p < .02; by sentences, T = 150, 2 = 2.13, p < .05). This implies that the condition information in IF NOT is represented as - C. The corresponding advantage in processing positive sentences referring to the action has already been reported for errors. There were no significant time differences for action information. For UNLESS, when sentence 2 gave information about the action, performance appeared faster when this information was negative, but this was significant only following CA sentences (by subjects, T = 139, Z = 2.34, p < .02; by sentences, T = 169, Z = 1.78, p < .06). This implies that CA sentences encourage people to represent UNLESS as -A+C. However, there was no significant difference between positive and negative information when sentence 2 referred to the condition. Action vs condition. Response times were shorter when sentence 2 referred to the condition rather than to the action. This difference was significant for IF NOT in an overall analysis (by subjects, T = 26, Z = 4.45, p < .OOl; by sentences, T = 91, Z = 3.24, p < .Ol) and in separate comparisons within positive and negative second sentences (for both, p < .OOl). We have already seen that for IF NOT more errors were made when sentence 2 referred to the action rather than the condition 0, < .Ol). For UNLESS, pooling across clause orders, the overall comparison of action and condition information was equivocal (by subjects, T = 131, Z = 2.49, p < -02; by sentences, T = 192, ns). Separate comparisons of the time to deal with action and condition information in sentence 2, as a function of whether sentence 2 was positive or negative, suggested a significant difference only for positive sentences (by subjects: positive, T = 143, Z = 2.26, p < .03; negative, T = 225, Z = 0.7, ns). Pooling across clause orders may not be appropriate if UNLESS is represented differently in AC and CA sentences.

699

AC vs CA. There were no statistically significant differences in overall time to respond to sentence 2 and the question as a function of the order in which the clauses were mentioned in sentence 1, for either UNLESS or IF NOT. This implies that before reading sentence 2, people had completed whatever recoding operations they wished to apply to sentence 1. For UNLESS, Figure 3 suggests that people were slower responding to positive information after a CA sentence, which implies that further operations occurred when sentence 2 was presented. However, the reliability of this time difference is insecure (by sentences, p < .02; by subjects, p < .I). Discussion How Is IF NOT Represented?

When sentence 2 referred to the action, performance was worse if this information was negative rather than positive (errors, p < .05). When sentence 2 referred to the condition, performance was worse if this information was positive rather than negative (time to read sentence 2 and answer question, p < .OS). These two findings are consistent with IF NOT being represented as -C +A, as suggested in model 1. That no clause order effects are evident in the time to read sentence 2 and respond to the question suggests not only that readers have completed their recoding prior to sentence 2, but that such recoding has produced a common representation no matter which clause order the writer chose. The absence of significant word order effects on the time to read sentence 1 requires revision of this section of the model. Assuming that readers’ initial representation reflects syntactic priority (i.e., deleting process 1.1) would be sufficient to make these reading times equivalent. The finding that further information about the action influences errors, whereas further information about the condition influences only response latency, suggests

700

WRIGHTANDHULL

that it is harder for people to integrate new information about the action with the representation they have formed for sentence 1 than to integrate further information about the condition. For IF NOT the action condition difference was much greater when sentence 2 was negative. Model 1 attributes this to the difficulty associated with processing a double negative representation, processing only required when sentence 2 is negative and refers to the action. 1s UNLESS Represented

in u Similar Way

to IFNOT?

The data show several differences between the performance patterns for UNLESS and IF NOT. Only for UNLESS was reading time on sentence 1 affected by the order in which the action and condition information was presented @ < .Ol). Unlike IF NOT, with UNLESS there were no coherent effects on performance of having positive/negative information in sentence 2. However, when sentence 1 had the clause order CA, people were faster responding to sentence 2 referring to the action if it was negative rather than positive (p < .02). This suggests people had created a representational form + C -A, quite different from that created for IF NOT. Since the motivation for this change appears to be lexical it

requires that model 1 be modified by the inclusion of a recoding option which causes the negative element to be reassigned from the condition to the action. This alternative model is outlined in Table 3, and the specific predictions following from this alternative representation are given in Table 4. It is possible that the absence of any significant positive/negative differences following an AC sentence 1 is due to a mixture of representational strategies being used, either between or within people. Mixed strategies have been found in other studies of conditionals. Jones (1966) reported that when instructed to “respond to all except four items,” 44% of the subjects recoded this into a fully affirmative form (i.e., they specified the subset to be responded to), while 56% chose not to undertake such recoding and made many more false positive errors. Is There Differential Ease ofAccess Representation of Action and Condition Information?

to the

For IF NOT, analysis of the times to read sentence 2 and answer the question indicates that performance is better when sentence 2 refers to the condition rather than to the action (times, p < .OOl; errors, p < .Ol). For UNLESS this pattern was present only when sentence 2 was positive, and

TABLE3 MODEL?

Writer’s order AC Reader’s representation of sentence 1 -C +A -C 1.1 Representation from word order -A +C tC 1. la Representation lexis of conditional -A tC -A 1.2 Syntactic priority tC +C -A 1.3 Sequence contingency Operations on sentence 2 2.1 Represent information 2.2 Check if match exists with any element of previous representation: If yes 4 question; if no change to action, then + question Operations following question 3.1 Represent question 3.2 Check match with current representation: If match, respond Yes; If no match. respond No

CA +A

-A +C -A

+ infer

701

REPRESENTINGNEGATIVECONDITIONALS TABLE4 EXAMPLE

OF How

Representation

PROCESSING

of sentence 1

Sentence 2 either 2.1 2.2 3.1 3.2

Representation of sentence 2 Inferred new representation Representation of question Answer

Processing complexity

OPERATIONS

IN MODEL

2 VARY

WITH

THE INFORMATION

IN SENTENCE

2

+C -A

+C -A

+C -A

+C -A

Positive condition +c

Positive action i-A -c* +c No*

Negative action -A

-+A No*

Negative condition -C -*(-A) = +A** +A Yes

I

3

2

0

only on the response times (p < .03), not the error data. The absence of any clear pattern for UNLESS can be accounted for by assuming that readers varied their representational strategies. Pooling models 1 and 2 would give the same numerical index of complexity for all variants of sentence 2. Differences in the ease of dealing with further information about the action and condition must be interpreted with caution. There are both syntactic and content differences between action and condition clauses. We might expect, other things being equal, that the information in the main clause would be more readily available than that in the subordinate clause (Clark & Clark, 1968). In our sentences the main clause contained the action information, but for IF NOT performance was poorer with action than with condition information in sentence 2. Content differences may be the explanation, but these would apply equally to IF NOT and UNLESS. So, although the data are not compelling, it seems plausible that the ease of access to action and condition information is a function of the reader’s chosen representation which is itself a function of both the lexical item used for the conditional and the writer’s order of mentioning action and condition information. Does the Clause Order of Sentence I Injluence the Representation Chosen? In discussing the representation of UNLESS we suggested that UNLESS was more

+c Yes

likely to be recoded into -A + C following CA rather than AC sentences. There has been no indication that any such differential encoding occurred for IF NOT. The reason for readers showing greater unanimity in their selection of recoding options for UNLESS following CA sentences is far from obvious. Possible reasons why the representation for UNLESS may differ from IF NOT will be considered later, under General Discussion. Postscript One of the differences between UNLESS and IF NOT concerned the materials used in the verb phrase of sentence 2 when it gave information referring to the condition (see Materials, above). By always using the same verb phrase in sentence 2, no matter which conditional had been used in sentence 1, there was a closer match with the verb phrase present in a preceding IF NOT sentence 1 (e.g., “X would happen if the referee did not start the game”) than with the verb phrase in a preceding UNLESS sentence 1 (e.g., “X would happen unless the referee started the game”). This similarity in phrasing could account for the observation that although the data in Figure 3 show an overall advantage for sentence 2 containing condition information rather than action information, this advantage was twice as great for IF NOT (690 ms) than for UNLESS (340 ms). Masson (1984) has pointed out that indirect measures show that readers do remember and are in-

702

WRIGHTANDHULL

fluenced by the surface structure of sentences. One way of examining whether the verb phrase has biased the representations people chose is to repeat the study, using a verb phrasing for sentence 2 that is similar to that in the conditional clause following UNLESS (e.g., “the wind changed”). This potential advantage for UNLESS will only occur for positive information in sentence 2, because negative information will still involve a phrase such as “did not.” The effect of making this change to the verb phrase is explored in Experiment 2. Comparison of performance across Experiments 1 and 2 may indicate whether readers represented the surface structure characteristics or some more abstract (e.g., propositional) form of sentence 1. The suggestion that performance may be better when sentence 2 refers to the condition rather than the action is further explored in Experiment 2 by controlling for content differences between the action and condition clauses. It was found possible to create a subset of materials such that the action and condition information could be interchanged (see sentences 4a, b). 4a. The referee would start the match unless the team objected. 4b. The team would object unless the referee started the match. These materials were incorporated into Experiment 2 in order to give a clearer answer to the question about the ease of accessing action and condition information. Experiment 2 therefore essentially repeats Experiment 1 with modifications to the materials. One advantage of such a replication is that it may shed further light on the representation of UNLESS.

signment to action and condition clauses in sentence 1. Thus the experiment had three factors relating to sentence 1 (conditional, clause order, content assignment to action/ condition) and two factors relating to sentence 2 (positive/negative, information referring to action/condition). Materials. The same 86 triplets were used as had been used in Experiment 2, with the following changes. The verb phrase in sentence 2 when it referred to conditional information was changed from “The wind did change” to “The wind changed.” The purpose of this modification was to examine whether the verbatim similarity of the verb phrase in sentences 1 and 2 was important. Indirectly this addresses the issue relating to question 4, namely the importance or otherwise of the precise form of expression for determining the representation chosen by readers. Therefore the comparison of interest will be with the pattern of performance in Experiment 1. A second change in materials concerned the allocation of specific content to the action or condition clause in sentence 1. Difficulties in generating sentences which allowed interchanging the condition and action information (e.g., sentences 4a and b above) meant that this could only be done for half the sentence contents. Therefore half the subjects had these sentences with the original content allocations and for half the subjects this allocation was reversed, so that within Experiment 2 a comparison of the relative difficulty of integrating condition and action information could be made which was unconfounded by sentence content at the lexical level. The remaining sentences, for which the content could not be reversed, afford an indication of the comEXPERIMENTS parability of the people taking part in Experiment 2 with those who participated in Method Experiment 1. Subjects. Another 32 adult subjects from Design. Building on the 2 x 2 x 2 x 2 experimental design used in Experiment I, the Applied Psychology Unit’s volunteer a further between-subjects factor was intropanel, who had not participated in the preduced, namely a reversal of the content as- vious experiment, were paid for taking part

REPRESENTING

NEGATIVE

in Experiment 2. Their ages ranged from 22 to 64, with a mean of 43 years. An additional 6 people were tested but replaced for high errors (more than 30% on any conditional). Within this 6, the mean error rate on UNLESS was 39% and on IF NOT was 24%. Two other people were replaced for having exceedingly slow times. Procedure. All aspects of the experimental procedure (apart from the changes to materials noted above) were identical to the procedure used in Experiment 1. Results Errors The pattern of errors on all sentences is shown in Figure 4. Comparison across Experiments 1 and 2 of the error patterns when a positive sentence 2 referred to the condition suggests that changing the surface form of the verb phrase has had little effect. In Experiment 1 the verb form chosen for sentence 2 included did (e.g., the wind did change) whereas in Experiment 2 the regular past tense was used (e.g., the wind changed). In Experiment 1 the use of did appeared to give a closer surface structure match for positive information about the condition following IF NOT ‘8

14t

703

[I8 (7%) errors] than UNLESS [29 (11.5%) errors]. Comparison with performance in Experiment 2, where this correspondence with IF NOT is reduced, suggests that this may not have been a critical factor [IF NOT had 12 (4.5%) errors; UNLESS had 29 (1 I .5%) errors]. Positive vs Negative. The pattern of errors across all materials is very similar to that obtained in Experiment 1. For IF NOT significantly more errors were made when the action information was negative (13.5%) than when it was positive (7%) (by subjects, T = 234, Z = 3.2, p < .Ol; by sentences, T = 304, Z = 2.9, p < .Ol). This is consistent with the representation of IF NOT being + A - C. For UNLESS, as in Experiment 1, there were no signficant effects on errors of sentence 2 being positive or negative. Action vs condition. This analysis is appropriately confined to the subset of materials in which the action and condition information were interchanged. The pattern of errors with this subset of materials is shown in Figure 5. The only significant dif-

ruNLE35]

/lF AC action

16 t

CONDITIONALS

P


...’

,...” AC ariion

. /p- .,...” ,.....” .5c cOnd,tion

l ..”

1

FIG. 4. Experiment 2. Effect of positive/negative sentence 2 on the mean % errors across all materials.

POS. PCS Neg. NW FIG. 5. Experiment 2: Effect of positive/negative sentence 2 on the mean % errors with the reversible materials.

704

WRIGHT AND HULL

ference was found with IF NOT, where more errors were made on Action information than on Condition information when sentence 2 was negative (by subjects, T = 40, Z = 2.21, p < .03; by sentences, T = 29, Z = 2.02, p < .05). Reference to Figure 4 shows that there was the same general pattern of actioncondition differences with the full set of materials as for the reversible subset. Analysis of the full set showed that the only significant difference in errors occurred with IF NOT, and then only when sentence 2 was negative (by subjects, T = 21. Z = 2.98, p < .Ol; by sentences, T = 128, Z = 2.54, p < .02). AC vs CA. For UNLESS, the tendency shown in Figure 4 for more errors to be made with CA (19%) than with AC (14%) sentences was significant (by subjects, N = 22, X = 6, p < .05). For IF NOT, error rate was not significantly affected by clause order (AC = 11%, CA = 9%). Time Data Sentence 1. Figure 6 shows the pattern of reading times for sentence 1. Following the earlier procedure of excluding times relating to errors and times greater than 20 s, the values in 2 of the 512 cells were re-

7.

a

7. 6z z 1. ::

.d

?

2

7

0

placed by the mean of the row and column means, because these cells were otherwise empty. A significant effect of changing clause order was found for the conditional UNLESS, with AC sentences being read faster than CA sentences, but no effect of clause order was found for IF NOT (Wilcoxon test on ah materials: for UNLESS, T = 141, Z = 2.30, p = .02; for IF NOT, T = 193, Z = 1.33. ns). This pattern of significant differences replicates that found in Experiment 1. Sentence 2 + Question. Seven of the 512 cell entries were over 10 s and were replaced by the mean of the row and column means, as was done in Experiment 1. Figure 7 shows the effect of the various treatment combinations on the time to read sentence 2 and answer the question. Changing the verb form seemed to have little effect on the response times to further conditional information. Because these subjects are much faster than those who took part in Experiment 1, it is helpful to make the comparisons across experiments with reference to a data point in both groups which should not have been affected by the verb change. Sentence 2 giving negative information about the condition can serve as such a reference point. Comparison of the positive-negative difference for conditional information showed no significant increase in the speed with which people could process the positive

-L

POI AC

CA

AC

CA

FIG. 6. Experiment 2. Effect of writer’s order on the mean time to read sentence 1.

clause

Neg.

POI

Nag

FIG. 7. Experiment 2: Effect of positive/negative sentence 2 on the mean time to read sentence 2 and answer question; data from all materials.

REPRESENTING

NEGATIVE

condition information from UNLESS, nor was there a significant decrease in the speed of handling positive condition information from IF NOT. These nonsignificant findings suggest that operations involving the matching of particular word strings were not important in accounting for the present pattern of data. Positive vs Negarive. For IF NOT there were no significant differences between positive and negative information, but Figure 7 suggests that underlying trends tended to be in the reverse direction to those found for UNLESS, particularly for condition information and responses after CA sentences. For UNLESS the action information from sentence 2 was processed faster when it was negative than when it was positive. (Pooling across the clause orders and analyzing the data from all sentences, Wilcoxon T = 164, Z = 1.87, p < .05, one-tailed; by sentences, T = 158, Z = 1.98, p < .05). In contrast, for condition information responses were faster for positive than negative information, although significant only for the analysis by subjects (by subjects, Wilcoxon T = 150, Z = 2.13, p < .05, two-tailed: by sentences, T = 310, Z = 0.9, ns). This pattern of positive-negative differences is consistent with the earlier suggestions that UNLESS is represented as + C -A. Figure 7 shows that the magnitude of the effect appears greater following CA sentences than AC sentences. Action vs Condition. For the reversible materials, significant error differences have already been reported for IF NOT, showing that people were more accurate when sentence 2 gave further information about the condition rather than the action. The times taken to read sentence 2 and correctly answer the question are shown in Figure 8. With only two values per cell instead of four, the criterion of dropping any value over 10 s was applied before a cell median was determined. The error rate was such that the number of cells which were replaced by row and column means was 27

CONDITIONALS

705

FIG. 8. Experiment 2: Effect of positive/negative sentence 2 on the mean time to read sentence 2 and answer question; data from reversible materials only.

(i.e., 10.5%), which is considerably higher than in any of the previous analyses (Experiment 1 = 2.5%; Experiment 2 full materials = 1.4%). Because the data for reversible sentences were much thinner than for the full materials the analysis by sentences was not carried out. For IF NOT, responses were faster when sentence 2 referred to the condition than when it referred to the action. This difference was significant both for AC (T = 150, Z = 2.18, p < .05) and for CA sentences (T = 147, Z = 2.13, p c.05). For UNLESS, there was no reliable difference in the response time to action and condition information in AC sentences. But when CA sentences were followed by a positive sentence 2, there was a significant increase in response time for action information (T = 131, Z = 2.49, p < .02). The pattern of response times noted with the reversible materials is echoed when all the data are considered. For IF NOT, responses were significantly faster to condition than to action information (T = 152, Z = 2.09, p < .05). For UNLESS the advantage for condition information was only found when sentence 2 was positive (T = 133, Z = 2.45, p < .Ol). AC vs CA. As in Experiment 1, neither IF NOT nor UNLESS showed overall effects of the writer’s clause order in the times taken to read sentence 2 and answer the ques-

706

WRIGHTANDHULL

tion. In discussing Experiment 1 we suggested that the writer’s clause order influenced the likelihood of readers choosing a particular representation for UNLESS. Although it seems that in this study most readers represented UNLESS as +C -A, the magnitude of the positive-negative difference is greater following a CA sentence (action, 490 ms; condition, 490 ms) than following an AC sentence (action, 100 ms; condition, 250 ms). This is consistent with the possibility that strategies were more variable following AC sentences than following CA sentences. Discussion How Is IF NOT Represented? As in Experiment 1, when sentence 2 referred to the action, performance was significantly worse if this information was negative rather than positive (errors, p < .Ol). Although the time differences in Experiment 2 were not significant, Figure 7 shows that when sentence 2 referred to the condition, the mean trend was in the same direction as the significant difference found in Experiment 1, with negative information leading to faster responses than positive information. These findings support the suggestion that the representation for IF NOT is + A -C, the model outlined in Table 1. Is UNLESS Processed in the Same Way as IF NOT?

As in Experiment 1, the pattern of performance with UNLESS showed several differences from that found with IF NOT. For UNLESS the error data showed no differences between having positive and negative information in sentence 2. The removal of high error subjects may have contributed to this. However, response times did show differences between positive and negative sentences. People were significantly faster responding to negative than to positive information if this referred to the action (p < .05). In contrast, when sentence 2 referred to the condition, people were significantly faster with positive than with negative in-

formation (p < .05). These findings support the earlier suggestion that readers represent sentences containing UNLESS as -A+C, model 2. In both experiments, the positive-negative difference for UNLESS was much greater following CA sentences than AC sentences. This interaction with clause order may reflect some optionality in readers’ choice of representation; the representation of UNLESS sentences as -A + C appears more likely following CA sentences. Another difference between IF NOT and UNLESS occurred in the time to read sentence 1 (Figure 6). As in Experiment I, clause order influenced the reading time for UNLESS but not for IF NOT. This is consistent with recoding operations being applied to UNLESS when in a CA sentence, which are not applied to IF NOT when in the comparable sentence structure. Model 2 attributes these extra operations to lexically motivated recoding but particular combinations of lexis and syntax can have strong presuppositional implications (e.g., Clark and Lucy, 1975) and these may determine the representations readers choose. Is There Differential Ease of Access to the Representation of Action and Condition Information? The use of reversible materials means that this question can be answered without confounding with lexical differences between the action and condition information. For IF NOT, readers were more accurate when sentence 2 referred to the condition rather than to the action 0, < .05) if sentence 2 was negative. They also responded faster when sentence 2 referred to the condition following both AC @J< .05) and CA sentences 07 < .05). Model 1 attributes this pattern of performance with negative sentences to the difficulty of the double negative when sentence 2 refers to the action. The model fails to account for the faster performance with condition information when sentence 2 is positive. One

REPRESENTINGNEGATIVECONDITIONALS

way of meeting this difficulty is to assume that readers have only serial access to the elements within their representations. The contingency sequencing operations (1.3 in Table 1) would be responsible for the easier access to the condition information. Such an explanation has two drawbacks. On the one hand it tends to invoke strong assumptions about the nature of the representation, and on the other it predicts similar patterns for IF NOT and UNLESS. Since the response times are a composite of the time to read the sentence and answer the question, it is logically possible that the advantage does not, as we have been suggesting, arise from the integration of the information from sentence 2 with that from sentence 1 but might instead be solely attributable to the question-answering component, in which case the advantage is not for condition information which was presented in sentence 2, but for action information which is what the subsequent question concerned. Again this could be handled within model 1 by assuming serial access to the elements of the presentation, and by assuming that the final representation reflects syntactic priority (operation 1.2). Both explanations predict similar performance patterns on action and condition information for IF NOT and UNLESS, but this prediction receives little support from the data. For UNLESS there were no significant error differences between action and condition information. Response times were only slower to action information when sentence 2 was positive and followed a CA sentence. Model 2 predicts a difference in this direction. However, the failure to find a difference in the reverse direction when sentence 2 was negative could lend indirect support to the notion of serial access to the elements of the representation, with performance as measured being a composite of these two factors. Does the Clause Order of Sentence 1 InJluence the Representation Chosen?

We have seen that for IF NOT, in both ex-

707

periments, the writer’s clause order had no effect on the pattern of errors with positive and negative information in sentence 2, nor on the time to read sentence 1, nor on the time to read and respond to sentence 2. In Experiment 2, the mean difference between responding to positive and negative information was 175 ms following both AC and CA sentence 1. This is consistent with the suggestion that the representation of IF NOT as -C + A was made irrespective of the writer’s chosen order. For UNLESS, performance was more error prone (p < .05) when sentence 1 was CA rather than AC. Similarly, people took significantly longer reading sentence 1 when the clause order was CA than when it was AC (p < .02). Model 2 suggests that this extra time was needed for additional recoding operations (to give the representation +C-A) applied to UNLESS sentences in the CA clause order. It is a deficiency of model 2 that it gives no indication why different representations should be chosen after AC and CA sentences. Moreover, this effect of writer’s word order on the representation readers choose for declarative sentences containing UNLESS can be contrasted with evidence that when reading imperative sentences readers will always adopt the + C -A representation for UNLESS, no matter which clause order the writer uses (Wright & Hull, 1987). Another aspect of the effect of the surface structure characteristics of sentence 1 was explored in Experiment 2. The materials had been modified from Experiment 1, so that the wording of the verb phrase in sentence 2, when the information about the condition was positive, corresponded more closely to the verb phrase in sentence 1 when the conditional was UNLESS rather than IF NOT. The analysis of the times to read sentence 2 and answer the question showed that this modification had no direct effect on performance. It is possible that there may have been an indirect effect on the strategy selected for representing UNLESS, since Experiment 2 has shown a

708

WRIGHTANDHLJLL

more consistent use of the +C-A representation than was obtained in Experiment I. However, this representation does not require the retention of specific elements from the original surface structure. The models simply assert that recoding processes are applied to UNLESS, so that the negative element migrates from the condition to the action. Performance in Experiment 2 was somewhat better than in Experiment 1, Perhaps readers with more facility at cognitive gymnastics are more likely to undertake the recoding necessary for certain representations.

were in AC sentences), it was found that across 129 occurrences in seven written domains (press, magazine, fiction, literary, literary “official,” technical “official,” and technical) UNLESS occurred in AC sentences 96 times (74%), but in CA sentences only 33 times (26%). This bias was present in all seven categories of textual materials. Only in the sample taken from magazines were the proportion of CA sentences broadly similar to the proportion of AC sentences. In the other six categories the proportion of AC sentences containing UNLESS ranged from 68 to 100% with a mean of 86%. Whether the low frequency of parGENERALDISCUSSION ticular clause orders arises because of the In the Introduction, the existence of al- difficulty of processing these constructernative strategies for representing the in- tions, or whether the performance diffiformation from sentences was recognized. culty results from their being relatively unThe present experiments have suggested common is a chicken and egg question. But that the representations of IF NOT and UN- if UNLESS seldom occurs in every day LESS are the outcome of different recoding usage in sentences having the clause order operations. Although models of these re- CA, people may not have well-established coding operations have been proposed, it is strategies for dealing with UNLESS in this realized that these models have more de- form. grees of freedom than can be pinned down This suggestion about the possible imby the present data. For example, it is pos- pact of everyday usage, if correct, has sible that the differences between IF NOT some important implications for the level of and UNLESS attributed to “lexis” (a) may abstraction at which readers are applying be a function of readers’ differential re- general rules as the means of generating the sponses to explicit (IF NOT) and implicit representations they form. It suggests that (UNLESS) negation, (bj may arise from dif- such rules may be far more lexically speferences in the relative ease of lexical pro- cific than is often assumed. Whether the cessing (accuracy was always higher with causal factor is lexis per se or some aspect IF NOT than with UNLESS), or (c) may be of cognitive complexity it is not yet posdue to something idiosyncratic about UN- sible to say. When mixed strategies are LESS, such as common linguistic usage. found for representing information (e.g., Data from other conditionals would be Springston & Clark, 1973) then cognitive needed to discriminate among these alter- complexity might seem the more likely natives. Some tentative support for the ex- causal factor than lexis. Again it would be istence of usage factors being potentially helpful to have data from other condiimportant for UNLESS comes from the fre- tionals to assist in deciding among these alquency of the two clause orders in a re- ternative interpretations. cently collected linguistic corpus (G. The suggestions made here concerning possible reasons for the differences beLeech, personal communication*). Considering only those instances where the sub- tween IF NOT and UNLESS highlight only a stitution of IF NOT for UNLESS did not few of the factors which will influence the change the meaning of the sentence (i.e., representations people adopt. We have 19 instances were excluded, of which 13 data from other experiments showing that

REPRESENTING

NEGATIVE

task factors and presentation variables will also influence how negative conditionals are represented. The present models do not account for the selection of particular representations by readers. But explanations of why of certain representations are chosen can benefit from knowing when particular representations are formed. The data reported here are seen as a preliminary contribution to the much more important second step. The present studies can do no more than emphasize that people draw from a repertoire of representational strategies. Some of the factors influencing strategy selection have been demonstrated [e.g., the specific conditional term used (UNLESS/IF NOT); the linguistic structure (AC/CA) of the original sentence]. Undoubtedly many other factors remain to be discovered. REFERENCES

AARONSON, D. (1976). Performance theories for sentence coding: Some qualitative observations. Journal

of Experimental

Psychology,

2, 42-55.

AARONSON, D., & SCARBOROUGH, H. S. (1976). Performance theories for sentence coding: Some quantitative evidence. Journal of Experimental Psychology,

2, 36-70.

BLAIR, R. C., & HIGGINS J. J. (1985). Comparison of the power of the paired samples t test to that of Wilcoxon’s signed-ranks test under various population shapes. Psychological Bulletin, 97, 119- 128. BOCK, J. K. (1982). Towards a cognitive psychology of syntax: Information processing contributions to sentence formulation. Psychological Review, 89, l-47. CARPENTER, P. A., & JUST, M. A. (1975). Sentence comprehension: A psycholinguistic processing model. Psyrhoiogical Review, 82, 45-73. CLARK, H. H., & CLARK, E. V. (1968). Semantic distinctions and memory for complex sentences. Quarterly

Journal

of Experimental

CONDITIONALS

709

hension and the given-new contract. In R. 0. Freedle (Ed.), Discourse production and comprehension (pp l-40). Norwood, NJ: Ablex. CLARK, H. H., AND LUCY, P (1975). Understanding what is meant from what is said: A study of conversationally conveyed requests. Journal of Verbal

Learning

and

Verbal

Behavior,

DIXON, P. (1982). Plans and written complex tasks. Journal of Verbal Verbal

Behavior,

Learning

for and

21, 70-84.

DIXON, P. (1984). The structure of mental plans for following directions. Unpublished manuscript. DIXON, P. (1985). Actions and procedural directions. In R. Tomlin (Ed.) Coherence and grounding in discourse. Amsterdam: John Benjamin. HAVILAND S. E., & CLARK, H. H. (1974). What’s new? Acquiring new information as a process in comprehension. Journal of Verbal Learning and Verbal

Behavior,

13, 512-521.

JARVELLA, R. J., & HERMAN, S. J. (1972). Clause structure of sentences and speech processing. Perception

and Psychophysics,

11, 381-383.

JONES, S. (1966). Decoding a deceptive instruction. Journal

of Verbal

Learning

and

Verbal

Behavior,

5,405-411. MANI, K., & JOHNSON-LAIRD, P. N. (1982). The mental representation of spatial descriptions. Memory & Cognition, 10, 181-187. MASSON, M. E. J. (1984). Memory for the surface structure of sentences: Remembering with and without awareness. Journal of Verbal Learning and

Verbal

Behavior,

23, 579-592.

NORMAN, D. A. (1981). Categorisation of action slips. Psychological Review, 88, l- 15. SHERMAN. M. A. (1973). Bound to be easier? The negative prefix and sentence comprehension. Journal of Verbal 12, 76-84.

Learning

and Verbal

Behavior,

SPRINGSTON, E J., & CLARK, H. H. (1973). And and or, or the comprehension of pseudo imperatives. Journal of Verbal 12, 258-272.

Learning

and

Verbal

Behavior.

WRIGHT, P., & HULL, A. J. (1987). Reading to do: Creating contingent action plans. Submitted for publication. WRIGHT, P. & WILCOX, P. (1979) When two No’s nearly make a Yes: A study of conditional imperatives. In P. A. Kolers, M. E. Wrolstad, and H. Bouma (Eds.), Processing of visible language 1 (pp. 413-430). New York: Plenum.

Psychology,

20, 129- 138. CLARK, H. H., & HAVILAND S. E. (1977). Compre-

14,56-72.

directions

(Received January 13, 1986) (Revision received July 22. 1986)