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Why inferences might berestrictedCharles A. Perfetti aa University of Pittsburgh , 644 LRDC, 3939O'Hara Street, Pittsburgh, PA, 15260Published online: 11 Nov 2009.

To cite this article: Charles A. Perfetti (1993) Why inferencesmight be restricted, Discourse Processes, 16:1-2, 181-192, DOI:10.1080/01638539309544836

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DISCOURSE PROCESSES 16, 181-192 (1993)

Why Inferences Might Be Restricted

CHARLES A. PERFETTI

University of Pittsburgh

Inferences are both commonplace and elusive in reading. The key question is: Whatprinciples separate the commonplace from the elusive? Although those who argue for on-line goal-directed inferences may be correct, the evidence in favor of such inferences isyet not substantial and is open to other interpretations. Higher level inferences may berestricted in part because, unlike syntactic processes, they do not operate in response tosimple memory symbols, but depend on complex compositional representations thatmight not always be available.

Sherlock Holmes was a veritable inference machine. But psychologists have hada devil of a time demonstrating that ordinary people make any real inferences atall, at least when they read. To be sure, ordinary readers make mundane "in-ferences"—those that bind a pronoun to its antecedent, and those that allow thereader to conclude that the noun phrase he or she has just read, say "the man,"refers to the very man the reader has just read about in the last sentence! Maybefor Doctor Watson, such inferences would be impressive. But if this is the typicallevel of human inferential achievement, then we surely stand humiliated in theshadow of the legendary Holmes.

I am undecided at this point whether to think there is more to human inferenc-ing talent than we have discovered or to conclude that inference making is not agood candidate for scientific study. I will argue that there is a bit of insight inboth of these possibilities, but that the outlook is something intermediate to theoptimism of the first and the pessimism of the second.

First, I have to briefly defend the possibility that the situation is pessimisticwith respect to human inference making, at least during reading. Reading thecollection of articles in this special issue will not at all convey this impression.Most of the authors report studies that they take to support the occurrence ofsome kind of inferences during reading (see Zwaan & van Oostendorp, 1993, forthe clearest exception to this trend). There is, outside the covers of this specialissue, however, considerable evidence consistent with the view that readers aresomething less than inference machines, making only those inferences requiredfor local text coherence. For the strongest argument on behalf of this "mini-malist" view of inference making, see McKoon and Ratcliff (1992). Indeed, tounderstand the potential contribution of the present collection of articles, alongwith other recent research supporting inferences during reading (Murray, Klin, &

Correspondence and requests for reprints should be sent to Charles A. Perfetti, 644 LRDC, 3939O'Hara Street, Pittsburgh, PA 15260.

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Myers, in press), an appreciation of the minimalist view, which is more consis-tent with the bulk of data on inferences during reading than any specific alter-native, is essential.

It would be nice if someone could weave an insightful argument through thosestudies supporting the minimalist position and those supporting the collection ofalternative models (collectively constituting what I will term the "maximalist"position for the sake of contrast) and then point to the grand reconciliation, forexample, something along the lines of "All studies with good textual materialsand proper on-line measures support . . ." Someone might be able to do that, butit is too daunting a task for me.

Besides, we already have some claims of this kind of insight in the literature.McKoon and Ratcliff (1992) conclude that the vast research on "constructionist"comprehension has produced "almost no unassailable support" for its assump-tion that inferences are an automatic part of comprehension (p. 2). The newresearch in their article adds critical evidence against global goal-basedinferences.

Then there is the insight of Trabasso and Suh (1993), who claim that positiveresults for global goal-based inferences are obtained "on-line" when there isindependent evidence that subjects make these inferences at the point the textintends. The "three-pronged" approach of Magliano and Graesser (1991; seealso the article by Magliano, Baggett, Johnson, & Graesser, 1993) provides thebasis for this potentially clarifying perspective on the contradictory research.Perhaps studies failing to find inferences have used texts that have not promotedsuch inferences at the critical points. This is certainly possible, but it remains tobe demonstrated. I am skeptical that this is all there is to it.

Careful readings of the literature may provide some coherence to the patternof existing results. And methodological progress may provide for more con-vergence in the future. Unfortunately, there is another perspective on the issue:Inferences represent an unprincipled collection of higher level thinking processesfor which chaos, rather than clarity, ought to be expected. Before exploring thispessimistic alternative, let us consider the narrower issue of what is at stake inthe debate about inferences.

ON LINES AND OFF

It turns out that one can make at least one general claim to which all participantswill agree. During ordinary reading, inferences of all kinds are often made.Furthermore, it is beyond dispute that some very restricted inferences are oblig-atorily made on-line. Those inferences necessary for local coherence, spe-cifically processes that establish coreferentiality, are made on-line. Nearlyeverything else is in dispute, although the story seems more clear in some casesthan in others. Thus, elaborative predictive inferences seem not to be made on-line, as a number of studies have shown (including Fincher-Kiefer, 1993). Goal-directed causal inferences are another matter, with some evidence that locally

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required causal inferences are on-line, although the evidence might be open toother interpretations (McKoon & Ratcliff, 1992).

It is worth considering what is meant by on-line, given its importance in theinference question. On-line is an apt offspring of the computer metaphor that hasguided the development of cognitive science: A user can interact with computerdata, on-line as the data are initially made available; or a user can wait andinteract with a data file at his or her leisure, off-line. Each option has advantagesand disadvantages. An on-line use can get the data immediately into a usableform, and can influence the user's understanding of the world immediately; inaddition, useless data can be deleted immediately. But it is time consuming todeal with each piece of data that might be available. The off-line alternativeallows a more efficient use of processing time, doing what has to be done now,putting off other things to a later checking of data. Off-line even allows moreselectivity. By the time the user accesses data off-line, a decision about what isworth looking at can further save time. The downside of off-line is that eithereverything has to be saved or else some loss of information has to be tolerated.

Minimalist and Maximalist Data ManagementApplied to the inference issue, the metaphor takes on this tone, according to theminimalist position: The reader does what is minimally necessary on-line, mak-ing sure that all pronouns are immediately attached to antecedents and makingsure that each sentence can connect to some preceding sentence stored in memo-ry. Everything else is postponed until later, examined off-line as the readerprepares to paraphrase, summarize, or answer some question about what wasread. Of course it turns out that some things were lost. But the efficient operationof a passive text-processing machinery is sufficient to ensure that causal in-ferences are available as a by-product of processing that does not explicitly try toproduce them (Kintsch, 1991).

The maximalist position says that the reader does everything on-line, postpon-ing nothing to off-line. Of course, there is no maximalist position per se, al-though the class of models that Magliano et al. (1993) refer to as "predictionsubstantiation" is close to maximal. Expectation-driven reading is the core ideahere, with texts substantiating what the reader expects. The middle ground,represented by the "bridging model" described by Magliano et al. basically saysthat the minimal coherence inferences plus causal antecedent inferences are madeon line; the rest, including predictive inferences, are not. The causal inferencemodel of Trabasso and Suh (1993) is similar, although it more clearly includesglobal causal inferences, whereas the bridging model is not clear on whethercausal inferences are more than local phenomena.

The on-line metaphor is only partly apt, however. It misses the question ofhow the user makes a decision to do things on-line or off. One might imagine thatthis is a basic constraint on a limited system, as in earlier days of computer use,when all data had to be entered and read off-line in "batch." Or it might be adecision guided by user intelligence, as when one decides whether or not to

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interrupt a current computer task to read an incoming message. But if inferencemaking is like this, a matter of choice, then it slips beyond the boundaries ofnormal science, either as indeterminant as "free will" or as uninteresting as"data management." No doubt, the standard a reader sets for comprehension iscritical in controlling some inferences, but the debate is not about setting stan-dards. So the key question becomes whether inferences are automatic—madewithout option by the reader.l

It may seem to misstate things to say that the question is whether inferencesare made automatically. Isn't the question which ones are made automatically?Maybe—if there is a theory that divides inferences into those that should beautomatic and those that should not be. A theory of inferences based on Kintsch's(1988) text-processing model, which explicitly requires a local coherence, doesthis, selecting the minimalist inferences from all others for automatic on-lineprocessing. A theory of causal coherence (Trabasso & van den Broek, 1985) alsoprovides a clear candidate for automatic inferences, as both Trabasso and Suh(1993) and van den Broek and Lorch (1993) demonstrate. Both the text-basedtheory and the causal inference theory, despite their differences in levels, areexplicit on the critical question of what goes on when a reader reads a sentence.In both cases, something the reader is assumed to do provides the basis for aprediction about inferences. Maximalist theories, that is, prediction-substitutionmodels, seem less well motivated by a clear idea of what a reader does when hereads a sentence. Prediction, in particular, seems a cumbersome and unlikelyprocess for a skilled reader to engage in routinely. There will be conditions whichstimulate predictive inferences, but there will be little that is both principled andautomatic about them.

If this is correct, then the issues narrow considerably. The question becomesincreasingly focused on causal inferences, which are not part of one theory butare central to another theory. At this point, the conclusion remains unclear. Aminimalist can cite the experiments of McKoon and Ratcliff (1992), which ap-pear to show that higher level goals that are causally antecedent to an event in astory are not invoked by the reader on line. On the other hand, a maximalist cancite Trabasso and Suh (1993) as showing just the opposite.2

1 Magliano et al. (1993) suggest that the "inevitability" of an inference, rather than its automat-icity, is a useful standard to apply. Some inferences might be too slow to qualify as automatic but stillcertain enough to qualify as on-line. This is an interesting possibility, but to take it seriously we mayhave to turn to a more probabilistic computational mechanism, which amounts to abandoning theinevitability. Otherwise, to suppose that an inference is both always made and only made after 400 msseems to burden the scheduling of other reading processes. A glacier is slow and inevitable; on theother hand, it has nothing else to do except be a glacier.

2 Other articles also address goal-driven inferences—Magliano et al. (1993), Long and Golding(1993), and van den Broek and Lorch (1993). I focus on Trabasso and Suh (1993), because it is theclearest in spelling out its challenge to the minimalist theory, and because it is based on a theoreticalanalysis of what readers do with sentences in stories. Van den Broek and Lorch can be said to have

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The Birthday RevisitedTo engage the issue, we have to get reacquainted with Betty. Betty, as readers ofTrabasso and Sun (1993) already know, wanted to give her mother a birthdaypresent. Then, the story continues, "[She] went to the department store. [She]found that everything was too expensive. . . . Betty decided to knit a sweater."The key inference occurs at the final sentence: Betty is knitting a sweater becausethis will satisfy her goal of getting a present for her mother, this goal having beentemporarily blocked by financial limitations. I find this inference quite compel-ling, and I am sure that most readers, like Trabasso and Suh's subjects, agree.This intuition is reinforced by reading the comparison story in which the initialgoal is not frustrated at the department store: In this version, "Betty went to thedepartment store. [She] bought [her mother] a purse. . . . Betty decided to knit asweater." Here it is difficult to make any sense out of what the last sentence hasto do with anything that has gone on before. Surely, Trabasso and Suh are right inclaiming that understanding this final sentence in the first story is guided by aglobal causal inference. It is the goal of getting a present, stated at the beginningof the story, that controls the inference.

Note, however, that the subjects in Trabasso and Suh's (1993) study did notreadjust these few sentences. There were several additional sentences before weread that Betty decided to knit a sweater. The inference is actually somewhat lesscompelling in this case. This is what makes the global causal inference hypoth-esis interesting. The goal is textually remote from the sentence whose com-prehension it is supposed to control.

Are these intuitions about a goal-based inference confirmed by on-line mea-sures? Trabasso and Suh (1993) argue that their data do provide this confirma-tion: There are differences between the two texts in reaction times to a goal-related memory probe at critical points. In the example, probing after the sen-tence about knitting a sweater with some phrase about Betty's goal of getting hermother a birthday present produces faster decisions in the hierarchical story(where the sweater knitting is inferentially related to the goal) than in the sequen-tial story (where the present goal has already been satisfied).

There are reasons not to accept these conclusions on the basis of the data aspresented in the Trabasso and Suh (1993) article, even though the authors mightbe right about what ought to happen. For one thing, we see only difference scoresin their data. An argument about on-line measures is better made by showing thatthe absolute recognition times (RTs) are rapid, consistent with what one mightexpect for recent memory items. The difference scores tell us only that the twostories produced different probe times at a key point—a very important result,but an incomplete one.3

demonstrated that reader's representations of texts include goal information, but not whether in-ferences are made on-line.

3 This problem also applies to the data reported in the Magliano et al. (1993) study.

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Absolute scores would also help answer the question of whether there wereactually memory effects in the data, that is, increasing RTs as a function of textdistance. On one reading of how causal inferences work, it should not muchmatter whether a probe related to the goal—for example, present in the Bettycase—had just occurred in the text or had occurred several sentences back.(Although Trabasso & Suh, 1993, did not display their probes, present wouldseem to represent the idea.) In both cases, the goal is actively represented inworking memory as long as it has been unsatisfied and, thus, is controllingprocessing. On another reading of the hypothesis, the goal is not actually repre-sented in working memory, but is quickly reaccessed in order to interpret anotherwise incoherent sentence. Comparisons based on reasonable memory as-sumptions (such as text distance) are needed to help decide this.

A specific comparison that would help is between two versions of the sen-tence assumed to trigger the inference: "Betty decided to knit a sweater" and"Betty decided to knit a sweater for her mother." The second sentence makesclear that the reader should invoke the present goal in order to understand "forher mother." If the status of an inferred goal is the same when it is clearlyrequired and when it is not, then probe times should be the same in the twosituations.

This leads to a related problem of interpretation. Trabasso and Suh (1993)dismiss context checking as an explanation, because a goal probe would have fitthe two story contexts (hierarchical and sequential) equally well. Context check-ing is not a very well defined concept but, when applied to a memory probesituation, it roughly refers to the reader's deciding that a word plausibly mighthave been in the story, even though he or she does not actually remember itsoccurrence. Making a plausibility check for a goal word such as present actuallyshould be easier for the hierarchical story for the same reason that Trabasso andSuh postulated for a faster memory retrieval. Present is more plausible where itmight help interpret the sentence about knitting: "Present? Oh, yeh that's whyshe was knitting the sweater." This leads to a quick response to the probe word inthe context of the sentence. In effect, the probe word may trigger the inferencerather than measure its previous occurrence. In the control case, in which thegoal has been satisfied, the subject is, as Trabasso and Suh predict, trying toestablish a new event chain about sweater knitting, when the present probeoccurs. Here there is more genuine memory search, because present is notsolving any comprehension problem the subject is having. In fact, the greatercomprehension effort in this case might be enough by itself to slow a memorycheck for any probe, goal or otherwise.

If this alternative seems a lot like something that Trabasso and Suh (1993)would agree with—it is using causal inference as an explanation of the subject'sresponse—it should be. But it is a question of whether a fast response means thesubject has already made the inference in understanding the sentence, which iswhat the interesting reading of the causal hypothesis is, or that the subject now

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sees the probe word as a plausible solution to a comprehension problem, agree-ing with its plausibility.4

There is yet another alternative to consider, one theoretically more interesting.Suppose that the faster RT to a goal probe when Betty has failed to buy a present,compared with when she has bought a present, reflects the accessibility of theepisode and not the control of the goal. When Betty buys a purse and makes hermother happy, as happens in the control story, that episode ends. Or actually, itends only with the next sentence, which "opens" a new episode: "Several dayslater, Betty saw her friend knitting. Betty was good at knitting. Betty decided toknit a sweater." Probing with something from the first episode should takelonger, goal or no goal, because the reader is working on a new episode aboutknitting. In the experimental condition, the episode about buying a present hasnot ended, and so any probe from that episode is more available during thecritical knitting sentence.

Well, one might ask, isn't that the point of the causal analysis? The firstepisode is closed when its goal is satisfied and kept open when its goal is notsatisfied? This may depend on how one thinks episodes get opened and closed.The reader knows "Her mother was very happy" ends the first episode, becausethe next sentence is about Betty seeing her friend knitting several days later.There is no local coherence tie between this sentence and the preceding sentenceabout Betty's mother, so this signals a new episode. The first episode is now lessavailable. In the experimental condition, however, there is no local coherencebreak. Instead of a sentence about Betty's mother, there is a sentence aboutBetty: "Betty felt sorry." The next sentence, "Several days later, Betty saw herfriend knitting" has at least a superficial coherence tie to this sentence, so thereader is not forced to start a new episode.5 This alternative analysis focuses onthe importance of episode-guided processing, but without giving any specialstatus to a goal inference. (See Gernsbacher, 1990, for an account of comprehen-sion that gives a major role to episode boundaries.)

These questions are addressable in the long run, requiring applications of theresearch paradigms commonly used—with more attention to issues of timecourse (the location of probes can occur within as well as after sentences), foils

4 Relevant for this issue is the nature of the memory foils used in an experiment. Plausibilitychecking is something that will turn up some false alarms to words that were plausible in the contextbut did not occur. Trabasso and Suh (1993) say nothing about these foils in their article.

5 My treatment of this and other issues in this article benefited from some insightful observationsof Anne Britt. Britt points out that an interesting comparison would be between two possible ways ofending the sequential birthday present episode: "Her mother was very happy" and "Betty was veryhappy." The second establishes a coherence relation for the next sentence, and thus does not force aclosing of the episode. Whether it satisfies the goal is less clear. Is it being happy (either Betty or hermother) that satisfies the goal or is it having bought the purse? Probably it is the inference that thepurse is the birthday present. In any case, the contribution of these different factors, episode bound-aries, and goal inferences, can be tested.

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(important if plausibility arguments are to be ruled out), more- and less-explicittexts, and episode boundaries. And it would be a good idea to be alert to newresearch possibilities as well. The use of memory probe RTs has paid off inproducing interesting results in discourse, especially showing sensitivity to thereader's representation of the text. But, if an inference is not like a textualproposition, then memory probes might not be the best indicator of inferenceactivity. We need evidence that an inference has left a trace on processing, notnecessarily that a particular word has been stored in memory. The memory probeprocedure works often, because this trace often affects the activation level ofwords related to it. But this is no guarantee that it should work under allconditions.6

One suggestion for other measures draws on research on syntax, which hasexploited garden path phenomena (e.g., Britt, Perfetti, Garrod, & Rayner, 1992;Rayner, Carlson, & Frazier, 1983). Garden path data are increased reading timeson a later part of a sentence that result from an incorrect analysis of an earlier partof a sentence. In the inference case, there is an analogy: If the reader has made apostulated inference at a certain place, then a following sentence can be arrangedto betray that inference. For example, in Betty's story, if the reader has made thekey inference that Betty is knitting the sweater for her mother's birthday, agarden path can be arranged in the following sentence: ". . . Betty decided toknit a sweater. But before she started to knit, she remembered that she still hadnot bought a birthday present for her mother. So she returned to the departmentstore." If the reader made the critical inference in the first sentence, there shouldbe an inference-induced garden path in the second sentence, that is, longerreading times.7 The garden path strategy has the advantage that it does not relyon the dubious assumption that all inferences are represented by words from thetext, although it would leave doubt about the inferential mechanism and itsspecific timing.

I now turn to what I see as a more fundamental issue of interpretation: Areinferences principled?

LIFE OUTSIDE THE MODULEComprehension is the name we give to a complex, interrelated set of processes.Some of these processes appear to be principled and well behaved, but others do

6 Measurement questions are present in all the tasks used in inference research. The lexicaldecision task, often used to indicate priming, is very susceptible to backward association effects,another form of context checking. These measures were used in the Magliano et al. (1993) study andin the Long and Golding (1993) study. The authors of both studies acknowledge the problem of theseeffects, but they do not demonstrate that their data are free of the problem. In particular, is eat a fasterlexical decision following a sentence about a dragon kidnapping three daughters because the readerimmediately inferred that eat was the goal? Or does the faster time reflect the quick checking of eatagainst a plausible context, something that increases the confidence of the subject in a positivedecision? This problem is only reduced, not eliminated, in naming tasks.

7 I am indebted to Shelley Ross for suggesting this kind of experiment.

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not. Syntactic processes are the best example of well-behaved comprehension.Although there are plenty of controversies about the details of syntactic process-ing, it seems a fair assessment to say that syntactic principles of some kindcontrol a reader's initial parsing of sentence constituents. Indeed, the bulk of theevidence favors the proposition that a reader makes a predictable syntacticallybased decision on how to attach each word to an ongoing constituent representa-tion (see Mitchell, in press, for a thorough review of this literature). There isnothing hit or miss about these syntactic procedures, as near as we can tell. Theyare embedded in a language-processing mechanism in such a way as to do theirwork automatically and rapidly, with minimum interference from nonlinguisticknowledge sources (Clifton & Ferriera, 1989; Ferreira & Clifton, 1986; Perfetti,1990). Information from outside a sentence is critical in finally understanding thesentence, but use of this information is typically slightly delayed relative tosyntactic information in the sentence (e.g., Rayner, Garrod, & Perfetti, 1992; seealsoBrittetal., 1992).

It is relevant in this context to consider the well-behavedness of inferences.They contrast on just this point with syntactic processes. They are hit or miss,they are not automatic, and they are delayed. That is, except for the inferencesof local coherence, which behave rather like syntactic principles. Why thedifference?

There are at least two kinds of answers to this question. One is that certainlanguage processes, especially syntax, are modular, that is, specialized pro-cesses, encapsulated cognitively, rapidly executed, and shielded from interactionwith central processes critical for thinking. Local coherence inferences are sort oflike that, and in fact, referential binding is a process with syntactic components.Elaborative inferencing is not like that. It is critically dependent on specificknowledge and can operate only with substantial involvement of central process-ing. Whatever else such processes are, they are not specialized, and they are notshielded. The inference research question can be seen as asking whether they arerapidly executing, which would give them at least one characteristic of modularprocesses.

This approach to the problem can lead to the conclusion that inferences arechaotic central processes and, like thinking generally, are not something weshould expect to learn very much about. Fodor (1983), arguing that little progressin cognitive science has occurred in the study of central processes, whereas muchhas occurred in the study of modular systems, put it this way: "If central pro-cesses have the sorts of properties I have ascribed to them, then they are badcandidates for scientific study" (p. 127).

A second approach to the problem, less pessimistic, is to ask about mecha-nisms. Even without modularity, there are differences between syntactic andlocal coherence processes and general inference processes. The former can bemodeled by postulating simple memory symbols that control specific procedures.The latter, in general, cannot. These symbols are activated as part of elementaryprocessing and, in turn, trigger some other process. A syntactic trigger produces

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a syntactic procedure, as when an article triggers the opening of a noun phrase(Kimball, 1973; Perfetti, 1990). A coherence trigger produces a rapid memorysearch to produce a matching symbol, as when a pronoun triggers a search for amatching antecedent. There is more to syntactic procedures than triggers, ofcourse, because the triggers have to be embedded in a processing mechanism thatknows what to do with them. (Modules are handy for this purpose.) But the pointis that these procedures rely heavily on specific symbols that have just beenactivated during processing.

Inferences, by contrast, depend on complex computations rather than sym-bols. There is no trigger for an inference that a fall from 14 stories producesdeath, to use a well-known example from McKoon and Ratcliff (1986). Nor isthere a trigger for drilling in Fincher-Kiefer's (1993) story about going to adentist. The inference is plausible, of course. The dentist has found some cav-ities. The reader knows the patient hates going to the dentist. But these sentencesresult not in simple memory symbols that can serve as triggers, but in complexcomputations that produce (arguably) complex memory products, that is, memo-ries that include relationships and are thus compositional. There is no memorysymbol to trigger drill. In fact, part of the research strategy is to make sure thereare no triggers. This is what controlling for semantic associates does.

This analysis appears to apply to causal inferences as well. In Betty's story,there is no symbol in short-term memory to trigger some process when the readerencounters the critical knitting sentence. There is a possible retrieval operation,but what will trigger it? It is plausible that a comprehension problem will triggerthis search, and this is more or less what the minimalist position (and also thebridging hypothesis) would predict. The causal inference theory, however, seemsto assume that an inference is generated (not triggered) by the reader's need tolink actions to goals. In the framework of a memory symbol mechanism, there isno surefire way to cause the inference unless the goal is permanently kept activeas a simple memory symbol.

Consistent with this analysis is the variability observed in the extent to whichcausal inferences are generated even off-line. Trabasso and Suh (1993) reportthat their stories, which were designed to differentially elicit goal inferences,were highly variable in how differential they actually were. If stories made tospecifically control inference processes cannot uniformly do so, then the worldof ordinary text must be even more hit or miss. Not only are there no triggers,there sometimes isn't even a gun.8

8 The individual differences in goal inferences reported by Long and Golding (1993) might also betaken to reflect this problem of variability. Some do it, some do not. Of course, it is more interestingthan this, if those that do it are the skilled comprehenders and those that do not are the unskilledcomprehenders. If inference making is characteristic only of high reading skill, as some havesuggested (Oakhill & Garnham, 1988), this would suggest some leads for where to search for aninference mechanism. I do think that individuals differ widely in their inference abilities as in otherthings, but that, once one accounts for both knowledge and skill in basic processes, one might alsoaccount for whatever is systematic in such differences. For discussion on these issues, see Perfetti(1989). For suggestive data, see Haenggi and Perfetti (in press).

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It is important to emphasize that this analysis does not predict that certainkinds of inferences will not be made. It rather predicts that certain ones will bemade. Other inferences can be made on other grounds, but they will indeed be hitor miss. They have to compete with the demands of a processing schedule thatwill force certain syntactic, semantic, and inferential processes to be made in atimely manner. In such competition, they just might not be made, at least not inthe explicit way that is typically implied.

CONCLUSION

The question of when what kinds of inferences occur remains open. Despite thesamples of research claiming to show goal-related and predictive inferences,skepticism is warranted. Maybe the case for global causal inferences will bestrengthened in the next round of experimental fine-tuning. It is important tokeep in mind that the ultimate story on the application of human intelligence tothe comprehension of texts is not an issue. We can all agree that inferences areoften made at the earliest opportunity. Getting the story right about which onesare made automatically is what is contested at the moment. The case for a set ofpassively triggered inferences is good. Furthermore, there are principles andcomprehension mechanisms that predict these inferences. The case for predictiveand elaborative inferences seems less good, and the variability in results can beunderstood in terms of the absence of a simple mechanism to bring about suchinferences. The case for a restricted set of goal inferences is intermediate. Thereare some theoretically grounded principles to separate these inferences fromother ones, although a mechanism more complex than what is needed for otherautomatic processes, including local coherence inferences and syntactic com-prehension, will be required. Finally, as I have implied in a couple places, theremay be some parallels with syntax to consider, both in research paradigms(garden paths) and in conceptualizing the reader's task in terms of opening andclosing constituents.

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