ATTITUDES AND SOCIAL COGNITION Explaining the Evidence: Tests of the Story Model for Juror Decision Making Nancy Pennington and Reid Hastie University of Colorado This research investigates the Story Model, Pennington and Hastie's (1986, 1988) explanationbased theory of decision making for juror decisions. In Experiment 1, varying the ease with which stories could be constructed affected verdict judgments and the impact of credibility evidence. Memory for evidence in all conditions was equivalent, implying that the story structure was a mediator of decisions and of the impact of credibility evidence. In Experiments 2 and 3, Ss evaluated the evidence in 3 ways. When Ss made a global judgment at the end of the case, their judgment processes followed the prescriptions of the Story Model, not of Bayesian or linear updating models. When Ss made item-by-item judgments after each evidence block, linear anchor and adjust models described their judgments. In conditions in which story construction strategies were more likely to be used, story completeness had greater effects on decisions. Social psychologists have been interested in processes of causal reasoning in judgment and decision making for decades (Fischhoff, 1976; Kelley & Michela, 1980; Ross & Fletcher, 1983). The most common role assigned to causal reasoning is as a direct cognitive mediator between evidence and judgments. Causal calculi in the form of algebraic computations (e.g., Anderson, 1974; Einhorn & Hogarth, 1985) or inductive rules (e.g., Kelley, 1973) describe how stimulus information is translated into explanations, predictions, and assignments of responsibility. Causal reasoning is also hypothesized to play an auxiliary, indirect role in prescribing the types of evidence that will be entered into mental computations that are not themselves explicitly causal. For example, event base-rate information is especially likely to be used when it is deemed causally relevant to a judgment (e.g., Ajzen, 1977; Bar-Hillel, 1980; Nisbett & Ross, 1980; Tversky & Kahneman, 1980). We believe that causal reasoning often plays a third role in judgment and decision making, in which it is applied to create a summary of evidence in the form of a causal model or explanation of the relevant situation. Our proposal is that when the body of evidence relevant to a decision is large, complex, and the implications of its constituents are interdependent, the decision process is explanationbased (Pennington, 1991). This research was supported by a grant from the National Science Foundation Law and Social Sciences Program (SES-80-12002), by University of Chicago Graduate School of Business Faculty Research Support awarded to Nancy Pennington, and by the Alfred P. Sloan Foundation in support of Reid Hastie at the Center for Advanced Study in the Behavioral Sciences. Correspondence concerning this article should be addressed to Nancy Pennington, Department of Psychology, Campus Box 345, University of Colorado, Boulder, Colorado 80309. Electronic mail may be sent to firstname.lastname@example.org. In explanation-based decisions, decision makers begin by constructing a causal model to explain the available facts and then base subsequent decisions on the causal explanation they have imposed on the evidence (Pennington, 1991; Pennington & Hastie, 1986,1988). The structure of the causal model will be domain specific. For example, we have proposed that a juror uses narrative story structures to organize and interpret evidence in criminal trials (Pennington & Hastie, 1981, 1986, 1988), but we expect that different causal rules and structures would underlie an internist's causal model of a patient's condition and its precedents (Pople, 1982), an engineer's mental model of an electrical circuit (de Kleer & Brown, 1983), a merchant's image of the economic factors in a resort town (Hogarth, Michaud, & Mery, 1980), or a diplomat's cognitive map of the political forces in an international conflict (Axelrod, 1976). In this article, we review and extend our application of an explanation-based theory of decision making, the Story Model, to criminal trial verdict decisions. In the first section of this article, we present a summary of the theory (see Pennington, 1991; Pennington & Hastie, 1991 for extensive descriptions). We then report three experiments that support the Story Model and delimit conditions under which explanation-based decision making will occur. The Story Model for Judicial Decisions The Story Model is based on the hypothesis that jurors impose a narrative story organization on trial information, in which causal and intentional relations between events are central (Bennett & Feldman, 1981; Pennington & Hastie, 1981, 1986,1988). Meaning is assigned to trial evidence through the incorporation of that evidence into one or more plausible accounts or stories describing "what happened" during events Journal of Personality and Social Psychology, 1992, Vol. 62, No. 2,189-206 Copyright 1992 by the American Psychological Association, Inc. 0022-3514/92/S3.00 189 190 NANCY PENNINGTON AND REID HASTIE testified to at the trial. The story organization facilitates evidence comprehension and enables jurors to reach a predeliberation verdict decision. In overview, the Story Model includes the following three components: (a) evidence evaluation through story construction, (b) representation of the decision alternatives by learning verdict category attributes, and (c) reaching a decision through the classification of the story into the best-fitting verdict category (see Figure 1). In addition to descriptions of processing stages, a claim that the story the juror constructs determines the juror's decision is central to the Story Model. As part of the theory, we also propose four certainty principles—coverage, coherence, uniqueness, and goodness-of-fit—that govern which story will be accepted, which decision will be selected, and the confidence or degree of certainty with which a particular decision will be made (Pennington, 1991; Pennington, Messamer, & Nicolich, 1991). In the next sections of the article, we describe the processing stages proposed in the Story Model and the certainty principles that govern them. Story Construction During the course of the trial, the jurors are engaged in an active, constructive comprehension process in which they make sense of trial information by attempting to organize it into a coherent mental representation. This mental activity occurs in part because comprehension is inherently a constructive process, even for the simplest discourse (Collins, Brown, & Larkin, 1980; Crothers, 1979; Kintsch, 1974,1988; Schank & Abelson, 1977). This is especially true in the context of legal trials in which characteristics of the trial evidence make it unwieldy. First, there is a lot of evidence, often presented over a duration of several days. Second, evidence presentation typically appears in a disconnected question-and-answer format; different witnesses testify to different pieces of the chain of events, usually not in temporal or causal order; and witnesses are typically not allowed to speculate on necessary connecting events such as why certain actions were carried out, or what emotional reaction a person had to a certain event.' Third, subparts of the evidence (e.g., individual sentences or statements) are interdependent in their probative implications for the verdict. The meaning of one statement cannot be assessed in isolation because it depends on the meanings of several related statements. Story structure. According to the theory, the mental representation that is constructed will coordinate and combine the following three types of knowledge into a story form (see Figure 1): (a) case-specific information acquired during the trial (e.g., statements made by witnesses about past events relevant to the decision); (b) knowledge about events similar in content to those that are the topic of dispute (e.g., knowledge about a similar crime in the juror's community); and (c) generic expectations about what makes a complete story (eg, knowledge that human actions are usually motivated by goals). This constructive mental activity results in one or more interpretations of the evidence that have a narrative story form (Figure 1, top right). Stories involve human action sequences in which relationships of physical causality and intentional causality between events are central. A story could be described as a causal chain of events in which events are connected by causal relationships of necessity and sufficiency (Trabasso & van den Broek, 1985). However, psychological research on discourse comprehension suggests that story causal chains have additional higher order structure both when considering the discourse itself and when considering the listener's or reader's mental representations of the discourse. Stories appear to be organized into units that are often called episodes (Mandler, 1984; Pennington & Hastie, 1986; Rumelhart, 1977; Schank, 1975; Stein & Glenn, 1979; Trabasso & van den Broek, 1985; see also a review by Read, 1987; see Figure 2, left side, for an example of an event sequence in episode form). The structure of stories, according to our analysis, plays an important role in the juror's comprehension and decision-making processes. The story constructed by the juror will consist of some subset of the events and causal relationships referred to in the presentation of evidence and additional events and causal relationships inferred by the juror. Some of these inferences may be suggested by the attorney and some may be constructed solely by the juror. Whatever their source, the inferences will serve to fill out the episode structure of the story. Thus, expectations about the kinds of information necessary to make a story tell the juror when important pieces of the explanation structure are missing and when inferences must be made. Knowledge about the structure of stories allows the juror to form an opinion concerning the completeness of the evidence, the extent to which a story has all its parts. Second, the structure of episodes in a story corresponds to the structure of our knowledge about human action sequences in the world; that is, story construction is a general comprehension strategy for understanding human action. Thus, the structure that is imposed on the evidence can be easily compared by the juror with already encoded prior knowledge. Finally, the hierarchical episode and causal structure of the story provides an automatic index of the importance of different pieces of evidence (Trabasso & Sperry, 1985). Acceptability and confidence. More than one story may be constructed by the juror; however, one story will usually be viewed as more acceptable than the others. The principles that determine acceptability of a story, and the resulting level of confidence in that story, we call certainty principles. According to our theory, two certainty principles govern acceptance: coverage and coherence. An additional certainty principle, uniqueness, will contribute to confidence. A story's coverage of the evidence refers to the extent to which the story accounts for evidence presented at trial. Our principle states that the greater the story's coverage, the more acceptable is the story as an explanation of the evidence, and the greater confidence the juror will have in the story as an explanation, if accepted. Although we have not systematically collected data from actual trials, our observations suggest that trial lawyers sometimes, but not often, present opening or closing summary statements in story form. A more frequent format that we have observed is to provide a witness-bywitness summary or to focus on particular evidentiary issues. Trial tactics texts recognize the difference between organizing testimony in a narrative versus an argument form and recommend that attorneys make a deliberate choice between the two forms before going to trial (Mauet, 1981). 1 STORY MODEL story 1 191 TRIAL EVIDENCE WORLD KNOWLDEGE ABOUT SIMILAR EVENTS KNOWLEDGE ABOUT STORY STRUCTURES CONSTRUCT STORIES MATCH ACCEPTED 5TORY TO VERDICT CATEGORIES CONCLUDE WITH VERDICT B IF FIT IS GOOD INSTRUCTIONS ON THE LAW PRIOR IDEAS ABOUT CRIME CATEGORIES LEARN VERDICT CATEGORIES Figure 1. The Story Model for juror decision making. A story's coherence also enters into its acceptability and the level of confidence (given that the story is accepted). However, coherence is a concept in our theory with three components: consistency, completeness, and plausibility. Consistency concerns the extent to which the story does not contain internal contradictions. Plausibility concerns the extent to which the story is consistent with knowledge of real or imagined events in the real world. Completeness refers to the extent to which a story has all of its parts. These three components combine to yield the coherence of a story. Finally, if more than one story is judged to be coherent, then the stories will lack uniqueness, and great uncertainty will result (Einhorn & Hogarth, 1986). If there is one coherent story, this story will be accepted as the explanation of the evidence and will be instrumental in reaching a decision. (These principles are elaborated and formalized in Pennington et al., 1991.) jurors' prior knowledge of concepts such as first-degree murder, manslaughter, armed robbery, and so on. In the juror's decision task for criminal cases, the verdict representation stage involves the specification of each verdict alternative with certain defining features and a decision rule specifying their appropriate combination. We have hypothesized that the conceptual unit is a category defined by a list of criterial features referring to the identity, mental state, circumstances, and actions linked conjunctively or disjunctively to the verdict alternative (see Figure 2, and Kaplan, 1978). Story Classification According to the Story Model, the final stage in the juror's decision takes the form of a classification process in which the best match between the accepted story's features and verdict category features is determined (see Figure 1). The classification process is aided by relatively direct relations between attributes of a verdict category (crime elements) and components of story episodes (see Figure 2). The law has evolved so that the main attributes of the decision categories suggested by legal experts (Kaplan, 1978)—identity, mental state, circumstances, and actions—correspond closely to the central features of human action sequences represented as episodes: initiating events, goals, actions, and accompanying states. The story classification stage also involves the application of the judge's procedural instructions on the presumption of innocence and the standard of proof (see Figure 1). That is, if not Verdict Representation This phase of juror decision making includes the comprehension and learning of the decision alternatives. Most of the information for this processing stage is given to jurors at the end of the trial in the judge's instructions on the law, although jurors may also have prior ideas concerning the meaning of the verdict categories (see Figure 1). The process of learning the verdict categories is a one-trial learning task in which the material to be learned is very abstract. Interference may occur from 192 NITIATING EVENTS: J & Ca In bar Ca threatened J J has no weapon J leaves NANCY PENNINGTON AND REID HASTIE Initiates GOALS: Initiates reason J Intends to find Ca J Intends to kill Ca ACTIONS: J goes home J gets knife J goes back to bar Ca hits J J stabs Ca result HA1T©!K! g > K ® © I i i ' EPISODE SCHEUA COMPONENT VERDICT ATTRIBUTES Actions CONSEQUENCES: Ca wounded Ca dies Actlom Consequences Psychological State* Goals Initiating Events Physical States Implicit In Actions <— —> > Mental State Circumstances Actions (A) Unlawful killing (B) Killing In pursuance of a resolution Mentsl State (A) Intent to kill (B) Resolution formed Clrcumstsnces (A) Insufficient provocation (B) Interval between resolution and killing Identity (A) Right person <— —> Identity Figure 2. The main elements of a story (episode schema) map onto the denning attributes of a verdict definition (verdict category attributes). (J and Ca = characters in the analysis.) all of the verdict attributes for a given verdict category are satisfied "beyond a reasonable doubt" by the events in the accepted story, then the juror must presume innocence and return a default verdict of not guilty. We represent the application of these standards by our final certainty principle: goodness of fit between the accepted story and the best-match verdict category. If the match is not sufficient, a default verdict (not guilty) will result. If a match is above threshold, then confidence will be related to the goodness of the match. In sum, the basic claim of the Story Model is that story construction enables comprehension and organization of the evidence so that evidence can be meaningfully evaluated against multiple verdict judgment dimensions. The Story Model provides a psychological account for the assignment of relevance to presented and inferred information, precise claims are made concerning the representational form of the evidence, and a mediating role is claimed for stories in subsequent decisions and confidence in those decisions (see Pennington, 1991; Pennington & Hastie, 1981,1986,1988; Pennington et al., 1991, for further details). Previous Research Our initial research on the Story Model provided descriptions of mental representations of evidence and verdict infor- mation at one point in time during the decision process, on the basis of an analysis of subjects' think-aloud protocols (Pennington & Hastie, 1986). Two key results were established that were necessary conditions for pursuit of the Story Model as a viable theory of juror decision making. First, jurors' mental representations of evidence had story structure (not other plausible structures), and verdict information was structured as feature lists. Second, jurors who chose different verdicts had constructed different stories; decisions covaried with story structures. This research provided detailed support for assertions concerning representations and inferences summarized earlier in a way that only extensive verbal report data can do. However, as a trade-off for the richness of the method, there are problems concerning the demand characteristics of the interview methodology. Therefore, additional experimental studies were necessary to demonstrate that stories were constructed spontaneously in the course of decision making and that stories mediate and determine juror decisions. A second empirical study was conducted to test the Story Model by using subjects' responses to sentences presented in a recognition memory task (Pennington & Hastie, 1988). Subjects "recognized," as having been presented as trial evidence, sentences from the story associated with their verdict with a higher probability than sentences from stories associated with STORY MODEL 193 opposing (rejected) verdicts. Subjects also rated the importance of trial evidence items; these ratings were strongly related to the causal role of the item in the story associated with a subject's verdict. These results corroborated the conclusions about story structure and story-verdict relationships from the initial study because the predictions about memory performance were derived from specific results of the initial research. Furthermore, these results implied that story representations were constructed spontaneously, as part of the natural decision process, and not artificially elicited by the interview task used in the first study. A third experiment was conducted in which the order of presentation ofevidence was varied to manipulate the ease with which one story (favoring the prosecution side of the case) or another (favoring the defense) could be constructed. The order manipulation had clear effects on verdicts; easier-to-construct stories dominated the decisions. We interpreted this result as strong evidence for the causal role of stories in juror decision making (Pennington & Hastie, 1988). Results from the second and third studies also provided support for the role of story coherence and uniqueness in confidence in decisions. Thus, previous research has established that (a) narrative story structures are spontaneously created as explanatory evidence summaries, (b) story structures covary with verdict decisions, and (c) story-like evidence summaries mediate the decisions. In the three experiments we report in this article, we seek further evidence for these conclusions and investigate additional hypotheses derived from the Story Model. In Experiment 1, we examine the relationship among memory organization, recall memory, and judgments, strengthening the case for the causal role of stories in legal decisions. Then, we consider whether story coherence mediates perceptions of evidence strength, credibility, and confidence in verdicts. In Experiments 2 and 3, we further demonstrate the effects of story completeness on decisions and we identify some of the conditions under which subjects follow the explanation-based, global, memory-dependent decision model as contrasted with alternate piecemeal, on-line decision models (Hastie & Park, 1986; Hastie & Pennington, 1989; Pennington & Hastie, 1981). Experiment 1 Experiment 1 was designed to evaluate our claim (Pennington & Hastie, 1988) that verdict decisions are affected by the manipulation of the difficulty of story construction and to explore the mediating role of stories in determining the effects of credibility information (Devine & Ostrom, 1985). In previous research (Pennington & Hastie, 1988), we demonstrated that when presentation order made a story easier to construct, we obtained more verdicts in the direction of the easier-to-construct story. We regarded this as strong support for the mediating role of stories in decisions. Our interpretation of this result, however, could be questioned on the basis that the easier-toconstruct story could have resulted in better memory for that body of evidence, making it more available at the time of decision. Although this explanation of the result could not account for other results we have reported, one motivation for Experiment 1 was to replicate the result under conditions in which memory availability differences did not exist. Therefore, we again manipulated the ease of story construction by varying the order of evidence presentation, but we used simpler materials (compared with Pennington & Hastie, 1988), which had been shown in previous research to be equally memorable for different organizations of the evidence (Devine & Ostrom, 1985). We also varied the credibility of one of the witnesses, with the expectation that the effects of credibility information would be greater under conditions in which stories were easy to construct. This prediction was based on the hypothesis that when an integrated representation of the evidence (a story) can be formed, then credibility information can be applied to the "evidence as a whole." In contrast, when stories are difficult to construct, the credibility information may be associated in a haphazard manner with items of evidence considered separately. Therefore, we predicted that credibility information would have a greater impact when the witness's story is easy to assemble. This prediction was partially supported in research by Devine and Ostrom (1985) in which they demonstrated that greater discounting of an inconsistent witness occurred when evidence was organized in story order. However, they varied only evidence order and not credibility. Because we have found more decisions in the direction of easier-to-construct stories, it is not clear whether their results were due to story effects alone or to the interaction of story with credibility information. Thus, we had the following two goals in Experiment 1: (a) to test whether a story organization of evidence influences decisions in the absence of differences in memory for the evidence, and (b) to test whether or not the story organization of evidence increases the impact ofcredibility information on decisions. To accomplish this, we varied both the order of evidence and the credibility of an inconsistent witness. We included conditions in which a single inconsistent witness had low credibility or high credibility and a condition in which minimal credibility information was provided for all witnesses. If story organization matters, then there should be more verdicts in the direction of the preponderance of evidence when evidence is presented in story order even if there is virtually no credibility information. This would be a pure effect of stories. Thus, the condition in which no credibility information was provided is critical in demonstrating that story organization is the cause of the decision and that credibility and memory differences are not. If, in the high and low credibility conditions, the effect of evidence order interacts with the credibility manipulation, then one can conclude that the effect of credibility is mediated by the story organization of evidence. Method Overview. Each subject read an abbreviated courtroom transcript of a criminal trial that included a case summary and the testimony of four witnesses concerning each of four separate evidence issues. Three witnesses were in agreement and established the preponderance of the evidence toward guilt in one case and toward innocence in another. A fourth witness provided testimony that was inconsistent with the other three. The subjects were asked to make a verdict decision and to rate the probability that the defendant was guilty. The independent variables of experimental interest were evidence order (by story or by issue) and credibility of the inconsistent witness's story (low credibility, no credibility information, or high credibility). Two additional independent variables were case materials (two cases) and order (two orders). 194 NANCY PENNINGTON AND REID HASTIE Beth's testimony will be biased (distorted) because of her personal feelings about the defendant?"), and (c) opportunity to know ("How likely is it that Beth will have an opportunity to know about facts or behaviors relevant to this accident?"). Subjects could respond with a rating on the negative end of the scale (-10= very likely that testimony will not be accurate, biased, or knowledgeable), on the positive end of the scale (+10 = very likely that testimony will be accurate, biased, or knowledgeable), or at the middle point of the scale (0 = no basis on which to answer this question). For all three questions, nearly twice as many subjects in the nocredibility condition responded that they had "no basis on which to answer," compared with the high- and low-credibility conditions (see Table 1). Furthermore, subjects in the credibility conditions, who did respond with a rating, rated the low-credibility witness as less likely to be accurate and more likely to be biased (see Table 2). No difference was found for opportunity to know relevant information, which is in keeping with our intention to vary perceptions of witness bias for the inconsistent witness. It can be noted from Table 2 that our "high-credibility" condition is, on average, better described as a "moderate-credibility" condition. Each case began with a general summary of the case, outlining the charge against the defendant and information concerning times and locations of the events in question. The 16 testimony items were presented as part of a trial transcript, in a question-and-answer format. Each block of evidence was presented on a separate page, creating a five-page booklet plus aresponsesheet. The itemrelevantto the credibility of the contradictory witness was presented in exactly the same location (position 8 or 12) for both evidence order conditions, so that the effects of the credibility manipulation were not confounded with the placement of this item. In addition, one of the two order conditions for story organization balanced a slight primacy advantage for the inconsistent information with a comparable primacy disadvantage in the other order condition. Procedure. Experiment 1 was administered to groups of 5 to 10 subjects who worked independently on the materials in the same room. Subjects were informed that they would read portions of a criminal trial transcript and the testimony of witnesses. Subjects read the material presented in the booklet at their own pace but were not allowed to turn back once they had studied an evidence block. At the end of the booklet, subjects were asked to indicate how likely they thought it was that the defendant was guilty, on a scale of -10 (defendant is definitely innocent) to +10 (defendant is definitely guilty). They also provided ratings of their confidence in this assessment and of ratings of the strength of the evidence for guilt and the strength of the evidence for innocence. After performing a distractor task (rating social descriptions for typicality), half of the subjects were asked torecallas much of the evidence as they could and to write it down in whatever order it occurred to them. Subjects. Subjects were 414 University of Colorado undergraduates enrolled in general psychology, who volunteered for the Experiment 1 to fulfill a research participation requirement. Sixteen subjects who did not speak English as a first language were dropped from the sample. This resulted in approximately 17 subjects randomly assigned to each of the 24 conditions. All independent variables were varied between subjects, with an approximately equal number of subjects in each of the 24 conditions. Materials. Materials were adaptations of stimulus materials reported in Devine and Ostrom (1985). Two stimulus cases were used: a murder case in which the preponderance of evidence favored guilt (the guilty case), and a hit-and-run accident case in which the preponderance of evidence favored innocence (the innocent case). Preponderance was determined by the larger number (3) of witnesses testifying for one side of the case compared with the other side (1 inconsistent witness). Four categories of testimony (issues) were included in the case; each witness was questioned about the defendant's motive, opportunity, character, and relationship to the defendant. Six versions of each of the case materials were constructed by varying the order of the evidence and the credibility of the inconsistent witness. When evidence was organized by story, the testimony of each witness, containing information about motive, opportunity, defendant character, and credibility (as indicated by the relationship between the witness and the defendant) was presented as a block. Thus, in the story order condition, each witness testified about a relatively complete account of the crime. When evidence was organized by issue, testimony concerning motive was blocked together, as was evidence for opportunity, character, and credibility. Thus, in the issue order condition, "innocent evidence" regarding motive would be closely followed or preceded by "guilty evidence" concerning motive and in a similar manner for the other issue categories. In the low-credibility version of the cases, the single inconsistent witness was described as having a special relationship with the defendant. In the murder case, the inconsistent witness was the sister of the defendant and was the only witness to provide "innocent evidence." In a similar vein, in the hit-and-run case, the inconsistent witness was the ex-wife of the defendant and was the only witness to provide "guilty evidence." In the high-credibility versions, the single inconsistent witness was described as a person who would have opportunity to know about behaviors related to the crime but without the special biasing relationship of the low-credibility versions. For example, in the murder case, the inconsistent witness was a person who lived on the same floor in the defendant's apartment building. In the hit-and-run case, the inconsistent witness was a neighbor who rode to the market with the defendant from time to time. For both the low- and highcredibility conditions, the three witnesses providing the preponderance of the evidence were described in high-credibility terms, that is, as people who would have an opportunity to know about the defendant or the crime but who lacked any vested interest in the outcome. In the no-credibility-information versions, the witness's occupation was stated in place of information relevant to credibility for all four witnesses. Thus, no relationship was established between the witness and the defendant either in terms of vested interest or in terms of opportunity to know about the relevant events. Manipulation check data, reported later, support this characterization of the credibility conditions. To ensure that our credibility manipulations were effective, we asked an independent sample of 432 subjects to rate witness credibility given a brief description of the charge against the defendant and the high- or low-credibility "relationship" or no-credibility "occupation" information about the witness.2 We sought to verify two important parts of our credibility manipulation: First, that subjects in the nocredibility condition were more likely to not have an opinion about witness credibility; and second, for those subjects willing to rate credibility on the information given, that the high-credibility conditions would elicit higher credibility ratings than the low-credibility conditions. We asked each of the subjects the following three questions about one of eight different witnesses: (a) the overall accuracy expected from the witness ("How likely is it that Beth will give accurate testimony at the trial of Robert Evans?"), (b) any potential bias ("How likely is it that Results and Discussion Memory for the evidence. The evidence order manipulation was successful; measures of organization in memory suggested 2 Subjects were paid 25 cents to fill out a two-page questionnaire, taking about 2-4 min at a walk-up table in the student union. Eighteen observations were collected for each of the six preponderance witnesses for two credibility conditions and 36 observations were collected for each of the two inconsistent witnesses in three credibility conditions. STORY MODEL 195 that subjects' memory organization for evidence was influenced by presentation order. Subjects who heard the evidence ordered by story showed more story organization in their free recall, whereas subjects who heard the evidence ordered by issue showed more issue organization in their free recall. We measured organization in free recall by computing an adjusted ratio of clustering (ARC; Devine & Ostrom, 1985; Ostrom, Pryor, & Simpson, 1981) for organization by story groups of items and for organization by issue groups of items. Subjects who heard the evidence organized by story had a mean story ARC of .304 and those who heard the evidence organized by issue had a mean story ARC of-.023, F(l, 188) = 48.44, p < .001. Conversely, subjects who heard the evidence organized by issue had a mean issue ARC of .438 and those who heard the evidence organized by story had a mean issue ARC of .095, F(l, 188) = 39.54, p < .001. However, total amount of recall did not differ for the groups who heard different evidence orders (story order= 9.6, issue order = 9.8, F < 1), nor did it differ by credibility conditions (F < 1). Judgments of guilt. When rating how likely it was that the defendant was guilty, subjects responded to the cases, on average, in the direction of the preponderance of evidence (mean rating for guilty case = +3.08; mean rating for innocent case = -3.58); the difference between the two cases was highly reliable, F(l, 374) = 270.98, p < .001. This is supported by the ratings of evidence strength (scaled 1 to 10), with the guilty case receiving an average rating for the strength of the guilty evidence of 5.69 and the innocent case receiving an average rating of 2.89. For ratings of the strength of the not-guilty evidence, the guilty case received an average rating of 3.40 and the innocent case received 6.44. Both differences were highly reliable (Fs > 200). For all subsequent analyses, the ratings of likelihood of guilt for the innocent case were multiplied by — 1 so that the rating reflected the strength of decision in the direction of the preponderance of the evidence. We expected to find that story organization of the evidence resulted in stronger and more confident decisions in the direction of the preponderance of the evidence. Across credibility conditions, by using the rating of likelihood of guilt or innocence, we obtained a mean rating of 3.85 for those hearing the evidence in story order compared with a mean rating of 2.80 for those hearing the evidence in issue order, F(l, 374) = 6.33, p < .02. The story order subjects also rated their confidence in Table 2 Mean Rating for Subjects Responding With a Positive or Negative Rating for Each of Three Credibility Questions About the Inconsistent Witness Question Accuracy* Bias* Opportunity 0 Low-credibility condition -4.5 5.5 2.2 No-credibility condition -0.6 1.9 1.5 Statistical test of difference F(l, 100) = 19.10 p<.001 F(l, 115) = 20.74 p<.001 F< \,ns Note. See text for exact questions. *10 = very likely to be accurate. b10 = very likely to be biased. c 10 = very likely to be knowledgeable. their decisions as stronger (6.74 vs. 6.26), F(l, 374) = 5.27, p<.03. In order to discuss the effects of evidence order and credibility, we need to examine separately the no-credibility conditions and the high/low-credibility conditions.3 We have said that it is important to demonstrate that the effect of evidence order is maintained in the absence of credibility information. When we analyzed the no-credibility-information condition separately, we obtained results identical to those reported earlier. Story order resulted in stronger decision ratings in the direction of the preponderance of evidence (3.56 vs. 1.80), F(l, 131) = 7.20, p < .008. Organization of information in memory, as reflected in story and issue ARCs, differed for the two evidence order conditions as before, F(l, 62) = 21.59, p < .001, but total recall was the same for the two groups (F < 1). When credibility and evidence order are varied simultaneously (high- and low-credibility conditions), one sees the predicted effects of credibility and the interaction between credibility and evidence order (see Figure 3). Subjects in the lowcredibility condition, in which the witness who differed from the other three was discredited, gave mean decision ratings of 4.45 in the direction of the evidence, compared with a mean of 2.91 for subjects in the high-credibility condition, F(l, 243) = 8.30, p < .005. In addition, the effect of credibility information was greater when evidence was organized by story compared with when evidence was organized by issue (Credibility X Evidence Order interaction), F(l, 243) = 4.56, p < .04, as shown in Figure 3. These results support and extend our own previous results (Pennington & Hastie, 1988) and those of Devine and Ostrom Table 1 (1985) by providing further evidence that story organization of Percentage of Subjects Responding "No Basis on Which to Answer This Question" for Each of Three Credibility Questions evidence mediates jurors' decisions, confidence in decisions, No-credibility condition (n = 180) 57 64 59 Credibility conditions (n = 252) 33 25 31 Statistical test of difference* Question Accuracy Bias Opportunity p<.00l /X.001 Note. See text for exact questions. * x2(l, A = 432) computed for 2 X 2 table of frequencies for each quesf tion. 3 The high- and low-credibility conditions and the no-credibility conditions cannot be compared directly because in the high and low conditions, preponderance witnesses all had high-credibility relationships to the defendant, and only the relationship for the inconsistent witness varied. In the no-credibility condition, all four witness relationships were replaced with occupation information so that no specific credibility information was available from the stimuli for any witness. 196 NANCY PENNINGTON AND REID HASTIE Low Credibility High Credibility c o £8 £3 5- O CO 4- o o £ | d) a> " 5 o> co DC Issue Order Story Order Evidence Organization Figure 3. Mean strength of decision in the direction of the preponderance of the evidence when an inconsistent witness has low or high credibility (Experiment 1). and the effects of credibility evaluation. First, in the absence of specific credibility information, varying the organization of the evidence alone results in stronger decisions in the direction of the preponderance of the evidence. Second, this effect was obtained in the absence of differential memory for the evidence, suggesting that simple availability of the evidence at the time of decision making cannot explain this result. Also of interest is the fact that this effect was obtained when relatively barren stimulus trial materials were used, suggesting that story construction may occur even in evidence evaluation tasks in which sequential updating strategies4 could also be used. Third, we demonstrated that when credibility information can be associated with the story as a whole, the impact of the credibility information will be greater than when the testimony induces a non-story organization. This result, along with the no-credibility condition showing the effect of story organization, and with the converging evidence for stories provided by verbal protocols collected by Devine and Ostrom (1985), provides strong support for the claim that stories mediate the impact ofcredibility information relevant to witness bias. Experiment 2 We have proposed that the perceived strength of the evidence for or against a particular verdict decision is a function of the completeness of the story constructed by the juror. In Experiment 1 and in previous research (Pennington & Hastie, 1988), we indirectly varied completeness by manipulating the order of the evidence, hence varying the ease of constructing particular stories, with some orders more directly suggesting a particular interpretation. This manipulation had a large effect, shifting 4 A sequential updating strategy is one in which an initial judgment is made and then is updated or adjusted after each piece of evidence. Such a strategy is typically heavily influenced by the most recent piece of evidence, as in the case in which the old judgment (usually summarizing several previous items of evidence) and the new piece of evidence are equally weighted. This kind of strategy is not consistent with an evaluation based on story construction, in which pieces of evidence would be weighted according to their role in the story. STORY MODEL 197 decisions in the direction of the easier-to-construct stories. In Experiment 2 we examined more closely the impact of story completeness on subjects' beliefs in the guilt of the defendant. We directly varied the ease of constructing particular stories by providing subjects with frequently inferred story information as evidence, thereby explicitly increasing the completeness of a particular story interpretation. We expected that more complete stories would produce stronger judgments in the direction of the completed story. The main purpose of the story supplements was to strengthen causal links between certain pieces of evidence and weaken others, that is, to alter the interpretation of the evidence. Of course, the Story Model predicts that the interpretation of evidence is a major determinant of the decision. Therefore, explicitly stating story supplements (inferences or elaborations frequently made in interpreting the evidence) should change verdicts in the direction of the story supplements. However, simply influencing subjects' verdicts by adding supplementary information to the evidence would not provide strong support specifically for the Story Model; almost any model of juror decision making would make the same prediction. We also varied the level of aggregation at which we asked subjects to make judgments, under the hypothesis that judgments rendered at different levels of aggregation would be more or less likely to evoke story construction. At a high level of aggregation, we asked subjects to make a single global assessment of the evidence strength after reading the entire body of evidence. We hypothesized that stories are the critical mediator of the verdict decision in global evaluations of evidence because subjects can integrate evidence into a unitary summary before evaluation. At an intermediate level of aggregation, we asked subjects to make a series of cumulative item-by-item judgments, in which they rendered an evaluation after each item of evidence of all evidence presented up to that point. This method of eliciting evidence evaluations is less likely to be mediated by stories than the global assessment because the subject is focused on the adjustment or change in evaluation as each new block of evidence is presented. The item-by-item response mode is likely to evoke an on-line strategy whereby subjects anchor on the current opinion and adjust for the new evidence confronting them (Einhorn & Hogarth, 1985; Hastie & Park, 1986; Hogarth & Einhorn, 1989; Lopes, 1982; Robinson & Hastie, 1985). In this case, subjects are unlikely to integrate the evidence into a summary structure in memory because they have already incorporated prior evidence into their current (anchor) opinion. In sum, we proposed that stories would be constructed when the evidence is evaluated once globally at the end but that a sequential updating or on-line strategy would be used when subjects evaluate the evidence sequentially, item by item.5 By varying the likelihood that a story construction strategy could be used to make a judgment, we expected to produce differential effects of story completeness. Such a result would strengthen our case for the role ofstories in decisions and simultaneously delineate conditions under which story construction strategies are likely to be used. With respect to the effects of story completeness, we predicted that (a) manipulations of story completeness will shift decisions in the direction of the more complete story, and (b) manipulations of completeness will affect the global impact of the evidence (as measured in the global judgments) more than the local impact of the'same evidence considered item by item (as measured in the cumulative judgments). We also included a no-aggregation condition in which subjects were asked to make local evidence evaluation judgments for each independent block of evidence. This allowed us to compare different models of the judgment process with subjects' actual judgments. We did this by applying Bayesian, sequential updating and story construction combination rules to the local assessments of the probative impact of each evidence item, and comparing predictions of final judgments, based on these combination rules, with subjects' global and cumulative item-by-itemfinaljudgments. On the basis ofsubstantial empirical literature demonstrating that the Bayesian updating rule usually does not match human judgments, we predicted that subjects' final evaluations of the evidence would not correspond to a Bayesian aggregate of item-by-item evidence assessments (e.g., Robinson & Hastie, 1985; Schum & Martin, 1982). On the basis of our reasoning earlier, we also predicted that a combination rule reflecting story construction would better predict global assessments, and a sequential updating rule would better predict cumulative item-by-item judgments. To summarize, how will story construction affect these alternate methods of evidence evaluation? First, we expect all of the evidence evaluation measures to diverge according to the particular story supplements included in the evidence. Second, we expect the manipulation of response modes to result in different decision strategies, supporting our predictions that (a) itemby-item evaluations encourage a sequential updating strategy, (b) global evaluations encourage story construction, and (c) neither of the final evaluations will correspond to a Bayesian aggregation. Third, we expect the divergence to be greater (the preponderant evidence will be evaluated as stronger) in the global judgment response mode compared with the cumulative item-by-item method, showing the mediation of stories in the global judgments but not in the sequential adjustment process of the item-by-item judgments. We fashioned much of Experiment 2 after an extensive series of studies conducted by Schum and Martin (1980, 1982), in which they investigated how human aggregation of evidence corresponded to Bayesian aggregation for various formally defined varieties of evidence (Schum & Martin, 1982) and the consistency of belief updating with Baconian and Pascalian probability calculi (Schum & Martin, 1980). Our materials and our procedures were based on theirs, but the goals of our study as outlined earlier were substantially different. The one point of overlap was our comparison of subjects' evidence evaluations with Bayesian rules. Method Materials. Subjects evaluated testimonial evidence in a felony case (embezzlement) developed by Schum & Martin (1980,1982; see ApWe do not intend to suggest that all judgments (across judgment tasks) made at the end of evidence presentation will involve story construction rather than sequential updating strategies; there are many examples to the contrary (see Hastie & Park, 1986). We make the claim only for this task because we have shown it to be an explanation-based task under normal decision circumstances. See the General Discussion for more on this point. 5 198 NANCY PENNINGTON AND REID HASTIE then a factor of one was assigned, indicating that the probabilities under both conditions were equivalent. This resulted in a letternumberresponsepair such as G-5, indicating that the evidence favored guilt and was considered to befivetimes more likely under conditions of guilt than under conditions of innocence. (We refer to G as the direction, and to 5 as the force of this response.) For the item-by-item assessments, subjects indicated a strength of belief in guilt relative to innocence by marking two vertical lines on a graph. (This method allows for ordinal tests of the consistency of judgments with principles of Bayesian updating processes, and it also allows the construction of likelihood odds ratios similar to those used as dependent variables in the other response mode conditions.) These evaluations were made after reading the initial case description and after reading each evidence block. Graphic frames for each opinion were placed side by side on an answer sheet. Subjects were instructed that placing a longer G line on the graph as they moved to a subsequent frame meant that the evidence they had just read resulted in a stronger belief in guilt than they had prior to the evidence, and examples were given for increasing, decreasing, and no change progressions for both G and I ratings. For the local assessments, subjects read each block of evidence and provided a likelihood ratio for each block separately, indicating direction (G, I, or N) and force (a number greater than or equal to 1). After practicing each of the response modes on a sample case, subjects read and responded to the stimulus case three times, once for each response measure. Subjects responded by using item-by-item, global, and local assessments, in that order. This design confounds order and rating scale type with response mode, but it allowed us to collect within-subject responses in a way that was sensible to subjects and to compare some aspects of our data with Schum and Martin's results (1980,1982). In Experiment 3 wereplicateExperiment 2, using a between-subjects design (in which response order is not a problem), and keep the rating scale constant. Dependent variables. All three response measures were converted to likelihood ratios. For the global and local assessments, this consisted of using the force number for responses in the guilty direction, for example, G-10 is a likelihood ratio of 10. We used thereciprocalof the force number for responses in the innocent direction; for example, I—10 converts to a likelihood ratio of. 10. For the item-by-item ratings, the ratio of the guilty rating to the innocent rating constituted the corresponding likelihood ratio. Likelihood ratios cannot be meaningfully averaged because they range from 0 to 1 for innocent judgments and from 1 to infinity for guilty judgments. Transformation to log likelihood ratios solves this problem; a likelihood ratio of 10 (10 times more likely that the person is guilty, given the evidence) converts to a log likelihood of 1, and a likelihood ratio of. 10 (10 times more likely that the person is innocent given the evidence) converts to a log likelihood of-1. All analyses were performed on the log likelihood ratios. The Bayesian aggregate was computed by multiplying the local assessments of evidence blocks (adding the log likelihood ratios) according to analyses of the stimulus materials reported by Schum and Martin (1982). pendix). These stimulus materials were chosen because the evidence blocks composing the case had been formally analyzed according to their underlying inference structure and the mathematics for combining evidence block evaluations according to Bayes's rule had been developed (Schum & Martin, 1982). Evidence for the case was prepared as written transcripts containing an initial description of the defendant and the charges, followed by six blocks of evidence. Each block of evidence contained assertions by a witness relevant to a major case issue such as motive or opportunity and related evidence bearing on the credibility of the witness or rebuttal of the assertions. We constructed three versions of the case. The basic version was identical to the Schum and Martin (1980,1982) materials. We developed, in addition, a conviction version and an acquittal version in which story inferences were added to each of the basic version evidence blocks. The story inference was intended to complete a story connection under a guilty or innocent interpretation of the evidence. For example, the defendant accused of embezzlement claimed that he had been in a barber shop at the time of the alleged crime. In the basic version of the evidence, "Graves testified that he left work early on the day in question in order to get a haircut." In the conviction version of the evidence, "Graves testified that he left work early on the day in question in order to get a haircut. Graves's supervisor testified that Graves had gotten a haircut one week before the crime." In the acquittal version of the evidence, "Graves testified that he left work early on the day in question in order to get a haircut. Graves's supervisor testified that he had instructed Graves to get a haircut." The story supplements were developed on the basis of pilot subjects' common evidence interpretations. For the example given earlier, the information provided by the supplement either supports or undermines a causal link (getting a haircut because you need one) that is critical to the defendant's story. (See the Appendix for other examples of story supplements.) The convict version had a guilty story inference added to each evidence block, and the acquit version had an innocent story inference added to each evidence block. The three stimulus versions defined the three experimental conditions in the study. Subjects. Subjects were 53 Northwestern University undergraduates and members of the university community who were paid $10 for their participation. Eighteen subjects were randomly assigned to each of the experimental conditions (one subject was dropped from the analysis because of failure to follow instructions). Subjects participated in groups of one to four persons but worked individually on the task in three-hour experimental sessions. Procedure. Subjects first read general instructions informing them that the purpose of theresearchwas to study the various ways in which individuals evaluate and combine evidence in jury trials, followed by a description of the format of the case materials. Subjects then read extensive instructions for each of three response measures and practiced using the response modes on a sample case. The global assessment involved reading the case materials completely through and then estimating a single likelihood ratio for the entire collection of evidence. For this estimate the subject was asked to assess the likelihood of the case evidence assuming the defendant's guilt relative to the likelihood of the same evidence assuming innocence. The actualresponseconsisted of two parts. First, subjects indicated direction: whether the evidence favored guilt (G), or innocence (I), or was neutral (N). If the subject responded that the evidence favored guilt, he or she was asked to specify a number (force) indicating how many times more likely the evidence would be under conditions of guilt than it would be under conditions of innocence (i.e, an odds ratio was used). If the subject responded that the evidence favored innocence, then he or she was asked to specify a number indicating how many times more likely the evidence would be under conditions of innocence than it would be under conditions of guilt. If the subject responded that the evidence favored neither guilt nor innocence (N), Results Results were based on analyses of variance in which version (acquit, basic, or convict) was a between-subjects factor, and response mode (item-by-item, global, or aggregate of local) was a within-subject repeated measure. In analyses in which data after each evidence block are used, evidence block becomes another repeated measure. Evidence supplements. Our first prediction was that the addition of story supplements would cause subjects to render eval- STORY MODEL uations of evidence in the direction implied by the supplements. Averaging over response modes, subjects who saw the convict version of the case gave 3.4:1 posterior odds in favor of guilt compared with subjects' 1:1.5 odds in favor of guilt for the basic version (without supplements) and 1:4.6 odds (favoring innocence) for the acquit version, F(2,50) = 9.66, p < .0001. Judgment strategies. Next, we tested our predictions about the strategies subjects were using for responses at different levels of aggregation. We proposed, first, that subjects' global and item-by-item assessments could not be well modeled as a Bayesian aggregate of their local assessments. We examined this by looking at (a) differences in the size (force) of the final judgments, (b) differences between the item-by-item assessments and the Bayesian aggregate after each evidence block, and (c) patterns of opinion change in the item-by-item assessments. To compare the force of the global and item-by-item assessments with the magnitude predicted by a Bayesian aggregate of the local evidence assessments, we looked for variability accounted for by response mode (item-by-item, global, and Bayesian). Remember that the Bayesian response mode is a calculation performed by the experimenters that aggregates subjects' local evidence assessments according to Bayes's rule. Our data show a strong Response Mode X Treatment interaction, F(4,100) = 6.36, p < .001 (see Figure 4). The Bayesian aggregates are about 5 times stronger in force than the global evaluation and about 7 times stronger than the item-by-item assessment for all subjects. (For directionally consistent subjects, these ratios were even larger; the Bayesian aggregate was 15 times more extreme than the global judgment and 23 times more extreme than the item-by-item assessment.) Thus, the clear pattern is that item-by-item evaluations are the least extreme, global evaluations are intermediate, and Bayesian aggregates are the strongest in the preponderant verdict direction. In terms of the size of the final evaluation, subjects' global and item-by-item evaluations were nearly an order of magnitude weaker than the Bayesian prescription. The fact that Bayesian aggregates are much larger than subjects' global assessments replicates Schum and Martin's (1982) results (see also Edwards, 1968). Their explanation for this conservativism was that when people make global judgments, they forget to include some of the evidence. This "forgetting" explanation, however, does not account for the fact that the Bayesian aggregate is much larger than the item-by-item aggregates, in which subjects were forced to include each item of evidence. Comparisons between subjects' local assessments combined according to Bayes's rule to yield a cumulative aggregate after each evidence block, and subjects' item-by-item assessments that also yielded a cumulative aggregate after each evidence block are shown for each version of the stimulus case in Figure 5. It can easily be seen that the Bayesian aggregate is greater in magnitude than the item-by-item subject aggregate beginning after two or three blocks of evidence have been considered and, the more evidence that has been considered, the greater the divergence. This is supported statistically by analyzing the difference between logs of Bayesian aggregates and item-by-item assessments after each evidence block (the difference between logs is equivalent to the ratio of the estimated likelihood ratios). The mean difference over blocks is reliably different from zero, Convict version Basic version Acquit version 199 1.6- 1.2 • 0.8- f is 0.4" T» 0.0 i o O) O .0.4 -0.8 -1.2 Item-by-ltem Global Bayesian aggregate Judgment Response Mode Figure 4. Mean posterior log odds favoring guilt by case version and response mode (Experiment 2). F(l, 19) = 60.0, p< .001 (M= -1.09), and this difference becomes larger over evidence blocks, F(2,34) = 31.84, p < .001. Moreover, the Bayesian model accounts for only 7% of the variance in the final item-by-item judgments (not significantly different from zero). This comparison suggests that the Bayesian aggregate is bigger, not because subjects overlook evidence but because subjects use non-Bayesian aggregation rules when forced to make item-by-item judgments. One can also look at the pattern of opinion changes from evidence block to evidence block in the item-by-item assessment. In this assessment, subjects indicated a strength of belief in guilt and a strength of belief in innocence after each block. When opinions after each of the two consecutive evidence blocks are observed, there are three ways an opinion can change. A complementary pattern involves an increase in one of the ratings (guilt or innocence) and a decrease in the other, or no change in either rating. This pattern of opinion change is consistent with Bayesian probability schemes. A second pattern involves an increase or decrease in both the guilt and innocence ratings; a third involves the increase or decrease of one of the ratings, and the other does not change. The both and the one patterns of opinion change are inconsistent with a Bayesian model of opinion revision. Our subjects changed their opinions in a complementary fashion 52% of the time, changed both in the same direction 11 % of the time, and changed only one rating 37% of the time. Thus, almost one half (48%) of the opinion changes are inconsistent with Bayesian adjustment. This pattern of opinion change has also been found in other evidence evaluation research (Schum & Martin, 1980; Robinson & Has- 200 1.5-1 NANCY PENNINGTON AND REID HASTIE 1.51 Cumulative item-by-item judgment Bayesian model aggregation 1.51 1.03 O Anchor-and-Adjust model aggregation 1 . o - 1.0- a 0.5- 0.5- 0.5- o 5 o.o -0.5CJ O 0.0- 0.0- -0.5- -0.5- -1.0- -1.0- -1.0- -1.5 -1.5 -1.5 B0 B1 B2 B3 B4 B5 B6 B0 B1 B2 B3 B4 B5 B6 B0 B1 B2 B3 B4 B5 B6 Evidence Block A. ACQUIT VERSION Evidence Block B. BASIC VERSION C. Evidence Block CONVICT VERSION Figure 5. Mean posterior log odds favoring guilt over evidence blocks by response mode for each version of the stimulus case (Experiment 2). tie, 1985) and provides further support for the assertion that subjects' aggregation is not Bayesian. Next, we tested our assertions that subjects would use different strategies when making global and item-by-item judgments. Specifically, we proposed that item-by-item judgments could be best described as the result of a sequential updating strategy. If this is the case, then item-by-item judgments could be modeled better by an additive combination of the local evaluations, specifically by an anchor-and-adjust model in which the new evidence block is averaged with the previous opinion to yield a new judgment (see Einhorn & Hogarth, 1985; Hogarth & Einhorn, 1989; Lopes, 1982). We tested this hypothesis byfittinga multiple linear regression model to the item-by-item judgments as a function of the local evidence evaluations (weights were constrained to be positive). The best-fitting models over the six item-by-item judgments (a summary of 18 models, 3 versions of the case X 6 blocks of evidence per version) can be expressed generally as the following: J, = .45J,_, + .55E,, where J, is the current judgment, J, _, is the previous judgment, and E, is the evaluation of the current piece of evidence. As shown in Figure 5, this model provides a much closer fit to the item-by-item assessments than does the Bayesian aggregation. This is supported statistically by analyzing the absolute difference between logs of the item-by-item and the anchor-and-adjust model aggregates after each evidence block for each case. The mean difference over evidence blocks is not reliably different from zero (F < 1, M= .03) and this is constant over evidence blocks (F < 2). Furthermore, the anchor-and-adjust model accounts for 40% of the variance in individuals' item-by-item judgments. Thus, the item-by-item judgments show a consistent recency effect of the value of later evidence, consistent with the anchor-and-adjust updating strategy. We also fitted a constrained (weights positive) linear regression model of the local evidence block evaluations to the global evaluation (three models, one per version). We hypothesized that the weights would not show the extreme recency effect obtained with the item-by-item judgments because story structure (not serial position at presentation) would be the major determinant of the importance of a particular piece of evidence in the global evaluations. For the global evaluations, the bestfitting model (averaged over the three conditions) can be expressed generally as: J = 1/n 2 E,, /-1 where J is the final global evaluation, n is the number of evidence blocks, l/n is the (equal) weight accorded each evidence item, and E,- is the evaluation of the rth piece of evidence. Over case versions, the weights are approximately constant over the evidence blocks, although modelsfittedseparately to each case version show that different evidence blocks receive more or less weight, depending on the story impact of the evidence block for the version. Thus, the model-fitting exercise suggests that idiosyncratic weights across serial positions implied by the Story Model (not recency as predicted from the anchor-and-adjust model) describe the judgment process in the global response mode. Furthermore, analyzing the absolute difference between logs of global judgments and the final judgment predicted by the anchor-and-adjust model, the mean difference (M= .210) is reliably different from zero, F(l, 39) = 28.88, p < .001. This is in STORY MODEL 201 Experiment 3 contrast with the close fit reported between the cumulative item-by-item judgments and the anchor-and-adjust model. Thus, the results support our assertion that subjects used different evidence evaluation strategies for the item-by-item and global assessments. Our final hypothesis was that the global assessments would be stronger than item-by-item assessments in the direction of the preponderant verdict. This is supported by the fact that subjects' global assessments are stronger in force than the itemby-item final evaluation by a factor of about 1.5 and is supported statistically by a reliable interaction between response mode (global or item-by-item) and case version (acquit, basic, or convict), F(2,50) = 3.35, p < .05, as shown in Figure 4. As can be seen, the global acquit rating was more extreme than the item-by-item judgment in the acquit direction, and the global convict rating was more extreme in the convict direction than the corresponding item-by-item rating. A second evaluation of the prediction that story supplements affect the global evaluation more than the item-by-item evaluations is provided by examining differences between global and item-by-item judgments for each subject. In all conditions of this experiment, the global assessment was larger than was the final item-by-item assessment, F(\, 42) = 12.41, p < .001 (analysis of variance on difference between logs of two response modes, using only directionally consistent subjects). Discussion In Experiment 2, we demonstrated that explicitly adding causal story connections to the case materials that strengthen one story shifts evidence evaluations in the story direction (Figure 4). The role ofstories is most convincingly shown by the fact that global assessments based on stories consistently result in more extreme judgments than item-by-item assessments based on considering evidence items separately, even though item-byitem judgments were based on exactly the same information. We consistently supported our fundamental prediction that story supplements would have a greater impact on global assessments, when evidence is considered as a whole, than on item-by-item judgments, when evidence is considered piece by piece. In the item-by-item judgment task, the process was best described by an averaging model with substantial recency effects that corresponds to an anchor-and-adjust strategy. In the global judgment task, the process was best described by an equal-serial-position weight model that is consistent with the Story Model. Furthermore, the predictions of the best-fitting anchorand-adjust models deviated significantly from the subjects' global ratings as well as fitting more poorly than the equalweight model. Finally, we have demonstrated, as have others before us, that subjects' aggregations of evidence items, even in the item-byitem cumulative updating task, are not Bayesian. Moreover, they do not fail to be Bayesian because people forget to include some of the evidence at global aggregation levels (Schum & Martin, 1982). They fail to be Bayesian because people use different aggregation processes altogether, as demonstrated in previous updating studies (Schum & Martin, 1980; Robinson & Hastie, 1985) and by the model-fitting in this report. In Experiment 2, the fixed order in which we presented the response mode conditions corresponded to the increasing magnitude of the responses. Moreover, different response modes used different response scales. Both of these factors create an ambiguity of interpretation both for our inferences about the meaning of differences in response magnitudes and for our findings that subjects in the different response mode conditions responded using different strategies. The goal of Experiment 3 was to replicate selected parts of Experiment 2 with new case materials, by using comparable response scales across judgment types and by using a between-subjects design that would effectively counterbalance for order effects. We were most interested in whether the global assessment is more extreme than the item-by-item assessment and whether the story supplements affect the global assessment more than the itemby-item assessments. Therefore, we did not include the local assessment response mode in the design and did not repeat the modeling from Experiment 2. Our success in Experiment 3 in repeating the response magnitude effects from Experiment 2, however, lends support to the interpretation we assigned to the modeling results. Method Materials. Materials for a burglary case were added to the embezzlement case materials used in Experiment 2. For Experiment 3 we had only two versions of each case: convict and acquit (data were not collected for the basic version). For this experiment, we used a single, simple response scale rather than using the relatively complex response scales developed by Schum and Martin (1982) and used in our Experiment 2. Subjects were asked, for either the global or the item-by-item judgments, to indicate the weight of the evidence (0 to 10) in the direction of their judgment (guilty or innocent), producing a response ranging from +10 (strong evidence for guilt) to -10 (strong evidence for innocence). The case materials were assembled into booklets so that each subject would see the two cases (embezzlement or burglary), one of which would be the convict version and the other an acquit version. Order in which the cases occurred and the combination of version and case were completely counterbalanced so that equal numbers of subjects were exposed to each of the two orders and equal numbers of subjects responded to each of the four possible combinations of case and version. Each subject performed in only one response mode (global assessment or item-by-item assessment) for both cases. Subjects. Subjects were 80 Northwestern University undergraduates who were paid $5 for their participation. Twenty subjects were randomly assigned to each of the two experimental conditions (convict version or acquit version) for each case (embezzlement or burglary). Subjects participated in groups of one to four persons but worked individually on the task in a one-hour experimental session. Procedure. Subjects first read general instructions informing them that the purpose of the research was to study the various ways in which individuals evaluate and combine evidence in jury trials, followed by a description of the format of the case materials. Subjects then read instructions for using the (-10 to +10) response scale and used it on a practice case. Subjects then read and responded to each of the two stimulus cases, performing either global assessments or item-by-item assessments for both cases. 202 Results NANCY PENNINOTON AND REID HASTIE As in Experiment 2, story supplements caused subjects to render evaluations of evidence in the story direction. On average over both cases and for each case considered separately, subjects rated the convict versions as stronger evidence toward guilt (+3.8) and the acquit versions as stronger evidence toward innocence (-2.8), F(l, 151) = 135.32, p < .001. Our central interest was in the interaction between response mode (global or item-by-item) and case version (acquit or convict). Our prediction was that the story supplements would affect global ratings more than they affected item-by-item ratings. As shown in Figure 6, this prediction is strongly supported by the data; global ratings were consistently more extreme than item-by-item ratings in the story direction, F(l, 151) = 9.68, p < .003. There were no differences for the two cases. Discussion In Experiment 2, we showed that global assessments were stronger than corresponding item-by-item cumulative judgments. However, global assessments were collected after the item-by-item assessments and on a different response scale. In Experiment 3, we demonstrated that neither of these factors accounts for the result that global assessments are more extreme. Second, we showed that the impact of story supplements on global assessments is greater than it is on item-by-item assessments for both stimulus cases. We interpret this result as support for our hypothesis that the greater impact is caused by the construction of stories in the global assessment response mode, compared with the use of an anchor-and-adjust strategy in the item-by-item response mode. General Discussion This research supports our hypothesis that explanations, semantic structures that summarize the causal relationships among events the decision maker believes occurred, are key mediators of jurors' decisions and their confidence in decisions. Ease of story construction mediates perceptions of evidence strength, judgments of confidence, and the impact of information about witness credibility. In previous research, we demonstrated that when evidence is organized by stories, subjects make more decisions in the story direction compared with when the evidence is organized by witness. In Experiment 1, we extended this result by finding that subjects made stronger decisions in the direction of the preponderance of evidence when evidence is organized by story than when organized by legal issue; they express more confidence in those decisions, and credibility information has more impact in those decisions. Furthermore, memory data in Experiment 1 revealed that differential memorability of the evidence could not account for these results. In Experiments 2 and 3, we showed that providing explicit story inferences moved decisions in the direction of the more complete story, and the use of a story construction strategy increased the impact of the information "completing" the story. These results, combined with our previous research (Pennington & Hastie, 1988) support the claim that stories are the mediating mental structures that cause decisions in the juror's judgment task. Our research also delimits the conditions under which judgments will be based on memory representations rather than updated on-line (Hastie & Park, 1986; Hastie & Pennington, 1989). In Experiments 2 and 3, when subjects are not required to make item-by-item judgments as evidence is presented, their judgment process follows the prescriptions of the Story Model, not of Bayesian or linear updating models. However, when subjects are required to make item-by-item judgments, linear Anchor-and-Adjust models describe their behavior. Hastie and Park have suggested that a principal determinant of whether the on-line or the memory-based strategy will be used is whether or not a person knows that a judgment is to be made at the time of exposure to the evidence. If a person knows what judgment is to be made, then the judgment can be made online as information is presented. Several theorists have treated juror decision making as an on-line belief-updating process of this type fag, Anderson, 1959; Weld & Danzig, 1940; Weld & Roff, 1938). Our results show that on-line updating sometimes occurs but only (in our research tasks) when subjects have been introduced to the judgment dimension prior to the presentation of evidence and are explicitly asked to make judgments throughout the course of evidence presentation. In contrast, the memory representation takes over as the mediating determi- Convict veraion Aqultvaralon 3 at z o a 2 o I lum-by-IUm Judgment Response Mode Figure 6. Mean strength of evidence favoring guilt by case version and response mode for burglary and embezzlement cases combined (Experiment 3). STORY MODEL 203 nant of decisions when item-by-item judgments are not required. We expect that this is likeliest to occur when decision criteria are not clear at the outset and the complexity of the evidence demands full comprehension before action. Of course, these are exactly the conditions that occur in actual jury trials. Elsewhere we have proposed a framework for the analysis of memory-judgment relationships that is relevant to the experimental tasks in our studies (Hastie & Park, 1986; Hastie & Pennington, 1989). We distinguished among the following three types of judgment processes: on-line, memory-based, and inference-memory-based. The hypothesized relationship between memory and judgment is the simplest in the memorybased condition: The recalled evidence directly predicts the judgment. In the other two conditions, on-line and inferencememory-based, the situation is more complex, and a simple direct memory-judgment relationship would not be expected to obtain. In our research, all of the experimental conditions are of the more complex types, that is, inference-memorybased for Experiment 1, and the "global" conditions of Experiments 2 and 3; and on-line for the "item-by-item" conditions of Experiments 2 and 3. We have shown in Experiment 1 and in previous research (Pennington & Hastie, 1988) that, for explanation-based tasks (inference-memory-based in the Hastie-ParkPennington framework), the memory organization of the evidence is related to the final judgment. However, these predictions about organization of memory do not necessarily (and most often will not) yield the simple quantitative relationships found by Hastie and Park (1986) between recall and judgment for simple memory-based tasks. Although the primary goal of our research on juror decision making is to develop a general theory of complex decision making, the research also has implications for jurisprudential and policy issues concerning the Anglo-American jury trial (Pennington & Hastie, 1990). The empirical findings are most relevant to the effects of presentation order and judgment strategy on the jurors' decisions and confidence. Once again, we concluded that a narrative story sequence is the most effective "order of proof" at trial (see also Pennington & Hastie, 1988; cf. Mauet, 1981). We also found that jurors instructed to make a final global judgment were more likely to adhere to an explanation-based judgment strategy and that the "wait until the end" global judgment strategy will lead to higher confidence in verdicts than a cumulative, item-by-item updating judgment strategy. Trial judges usually instruct jurors to defer their judgments until all the evidence has been heard, thus, to adopt an explanation-based strategy. We also concluded that Bayes's theorem does not provide a valid description of jurors' typical judgment processes. However, this does not necessarily imply that statistical evidence or expert instruction on reasoning about probabilistic evidence will interfere with or degrade jurors' judgments (cf. Koehler & Shaviro, 1990; Tribe, 1971). Most discussions of juror decision making are reactive, driven by the need to make quick, definite responses to specific policy questions: What is the minimum acceptable number of jurors on a jury? Does the "death qualification" procedure of jury impanelment select or create jurors who are biased against the defendant? Is a highly technical software copyright infringement case too complex to be decided by a typical jury? This has produced a disorganized, occasionally contradictory collection of experts' intuitions about how jurors think and decide that is scattered throughout a vast literature of appellate decisions, scholarly treatises, and personal recollections. The explanation-based Story Model that we have presented in this article is a psychologically plausible, empirically supported image of the juror decision process that can serve as the basis for a unified, coherent discussion of the behavior of jurors in practical and scientific analyses. References Ajzen, I. (1977). Intuitive theories of events and the effects of base-rate information on prediction. Journal of Personality and Social Psychology, 35, 303-314. Anderson, N. H. (1959). Test of a model for opinion change. Journal of Abnormal and Social Psychology, 59, 371-381. Anderson, N. H. (1974). Cognitive algebra: Integration theory applied to social attribution. In L. Berkowitz (Ed.), Advances in experimental social psychology (Vol. 7, pp. 1-102). San Diego, CA: Academic. Axelrod, R. (Ed.). (1976). Structure of decision: The cognitive maps of political elites. Princeton, NJ: Princeton University Press. Bar-Hillel, M. (1980). The base-rate fallacy in probability judgments. Ada Psychologica, 44, 211-233. Bennett, W L., & Feldman, M. (1981). Reconstructing reality in the courtroom. New Brunswick, NJ: Rutgers University Press. Collins, A. M., Brown, J. S., & Larkin, K. (1980). Inference in text understanding. In R. J. Spiro, B. C. Bruce, & W F. Brewer (Eds.), Theoretical issues in reading comprehension (pp. 385-407). Hillsdale, NJ: Erlbaum. Crothers, E. J. (1979). Paragraph structure inference. Norwood, NJ: Ablex. de Kleer, J., & Brown, J. S. (1983). Assumptions and ambiguities in mechanistic mental models. In D. Gentner & A. L. Stevens (Eds.), Mental models (pp. 155-190). Hillsdale, NJ: Erlbaum. Devine, P. G., & Ostrom, T. M. (1985). Cognitive mediation of inconsistency discounting. Journal ofPersonality and Social Psychology, 49, 5-21. Edwards, W (1968). Conservativism in human information processing. In B. Kleinmuntz (Ed.), Formal representations of human judgment. New \fork: Wiley. Einhorn, H. J., & Hogarth, R. M. (1985). Ambiguity and uncertainty in probabilistic inference. Psychological Review, 92, 433-461. Einhorn, H. X, & Hogarth, R. M. (1986). Judging probable cause. Psychological Bulletin, 99, 3-19. Fischhoff, B. (1976). Attribution theory and judgment under uncertainty. In J. Harvey, W J. Ickes, & R. F. Kidd (Eds.), New directions in attribution research (Vol. 1, pp. 421-451). Hillsdale, NJ: Erlbaum. Hastie, R., & Park, B. (1986). The relationship between memory and judgment depends on whether the judgment task is memory-based or on-line. Psychological Review, 93, 258-268. Hastie, R., & Pennington, N. (1989). Notes on the distinction between memory-based versus on-line judgments. In J. N. Bassili (Ed.), Online cognition in person perception (pp. 1-17). Hillsdale, NJ: Erlbaum. Hogarth, R. M., & Einhorn, H. J. (1989). Order effects in beliefupdating: The belief-adjustment model. Chicago: University of Chicago, Center for Decision Research. Hogarth, R. M., Michaud, C, & Mery, J. L. (1980). Decision behavior in urban development: A methodological approach and substantive considerations. Acta Psychologica, 45, 95-117. Kaplan, J. (1978). Criminal justice: Introductory cases and materials (2nd ed.). Mineola, NY: Foundation Press. 204 NANCY PENNINGTON AND REID HASTIE Kelley, H. H. (1973). The processes of causal attribution. American P. Szolovits (Ed.), Artificial intelligence in medicine (pp. 119-190). Psychologist, 28,107-128. Boulder, CO: Westview Press. Kelley, H. H., & Michela, J. L. (1980). Attribution theory and research. Read, S. J. (1987). Constructing causal scenarios: A knowledge strucAnnual Review of Psychology, 31, 457-501. ture approach to causal reasoning. Journal ofPersonality and Social Psychology, 52, 288-302. Kintsch,W(1974). The representation ofmeaningin memory. Hillsdale, NJ: Erlbaum. Robinson, L. B., & Hastie, R. (1985). Revisions of beliefs when a hypothesis is eliminated from consideration. Journal of Experimental Kintsch, W (1988). The role of knowledge in discourse comprehenPsychology: Human Perception and Performance, 11, 443-456. sion: A construction-integration model. Psychological Review, 95, 163-182. Ross, M., & Fletcher, G. J. O. (1983). Attribution and social perception. In G. Lindzey & E. Aronson (Eds.), Handbook of social psychology Koehler, J. J., & Shaviro, D. N. (1990). Veridical verdicts: Increasing (3rd ed., Vol. 2, pp. 73-122). New York: Random House. verdict accuracy through the use of overtly probabilistic evidence Rumelhart, D. E. (1977). Understanding and summarizing brief stoand methods. Cornell Law Review, 75, 247-279. Lopes, L. L. (1982). Toward a procedural theory of judgment (Tech. Rep. ries. In D. LaBerge & S. J. Samuels (Eds.), Basic processes in reading: Perception and comprehension. Hillsdale, NJ: Erlbaum. 17). Madison: Wisconsin Human Information Processing Program, Schank, R. (1975). The structure of episodes in memory. In D. B. BoUniversity of Wisconsin. brow & A. M. Collins (Eds.), Representation and understanding: StudMandler, J. M. (1984). Stories, scripts, and scenes: Aspects of schema ies in cognitive science (pp. 237-272). San Diego, CA: Academic theory. Hillsdale, NJ: Erlbaum. Press. Mauet, T. A. (1981). Fundamentals of trial techniques. Boston: Little, Schank, R., & Abelson, R. P. (1977). Scripts, plans, goals, and underBrown. Nisbett, R. E., & Ross, L. (1980). Human inference: Strategies and short- standing. Hillsdale, NJ: Erlbaum. Schum, D. A., & Martin, A. W (1980). Probabilistic opinion revision on comings of human judgment. Englewood Cliffs, NJ: Prentice-Hall. the basis ofevidence at trial: A Baconian or a Pascalian process?(Rep. Ostrom, T. M., Pryor, J. B., & Simpson, D. D. (1981). The organization No. 80-02). Houston, TX: Rice University. of social information. In E. T. Higgins, C. P. Herman, & M. P. Zanna (Eds.), Social cognition: The Ontario Symposium (Vol. 1, pp. 1-38). Schum, D. A., & Martin, A. W (1982). Formal and empirical research on cascaded inference in jurisprudence. Law and Society Review, 17, Hillsdale, NJ: Erlbaum. 105-151. Pennington, N. (1991). A cognitive model of explanation-based deciStein, N. L., & Glenn, C. G. (1979). An analysis of story comprehension sion making. Manuscript submitted for publication. in elementary school children. In R. O. Freedle (Ed.), New directions Pennington, N., & Hastie, R. (1981). Juror decision making models: in discourse processing, (Vol. 2, pp. 53-120). Norwood, NJ: Ablex. The generalization gap. Psychological Bulletin, 89, 246-287. Trabasso, T, & Sperry, L. L. (1985). Causal relatedness and importance Pennington, N, & Hastie, R. (1986). Evidence evaluation in complex of story events. Journal of Memory and Language, 24, 595-611. decision making. Journal of Personality and Social Psychology, 51, Trabasso, T, & van den Broek, P. (1985). Causal thinking and the 242-258. representation of narrative events. Journal of Memory and LanPennington, N., & Hastie, R. (1988). Explanation-based decision makguage, 24, 612-630. ing: Effects of memory structure on judgment. Journal of ExperiTribe, L. H. (1971). Trial by mathematics: Precision and ritual in the mental Psychology: Learning, Memory, and Cognition, 14, 521-533. legal process. Harvard Law Review, 84,1329-1393. Pennington, N, & Hastie, R. (1990). Practical implications of psychoTversky, A., & Kahneman, D. (1980). Causal schemas in judgments logical research on juror and jury decision making. Personality and under uncertainty. In M. Fishbein (Ed.), Progress in social psycholSocial Psychology Bulletin, 16, 90-105. ogy (m>- 49-72). Hillsdale, NJ: Erlbaum. Pennington, N., & Hastie, R. (1991). A cognitive theory of juror deciWeld, H. P., & Danzig, E. R. (1940). A study of the way in which a sion making: The Story Model. Cardozo Law Review, 13,5001 -5039. verdict is reached by a jury. American Journal of Psychology, 53, Pennington, N., Messamer, P. J., Nicolich, R. (1991). Explanatory co518-536. herence in legal decision making. Unpublished manuscript. Weld, H. P., & Roff, M. (1938). A study in the formation of opinion Pople, H. E., Jr. (1982). Heuristic methods for imposing structure on based on legal evidence. American Journal of Psychology, 51, 609ill-structured problems: The structuring of medical diagnostics. In 628. STORY MODEL 205 Appendix Synopsis of Stimulus Materials for Experiments 2 and 3 Experiments 2 and 3: Embezzlement Case Leroy C. Graves is charged with the embezzlement of $6,500, taken from the vault of a large downtown bank. Graves was employed in the bank's vault at the time. ^___ Evidence block (basic version) 1. The janitor at the bank testified that he saw Graves place money in a bank money bag at 5:00 pm of the day in question. He did not report the incident right away. The personnel manager testified that the janitor had complained about Graves' preferential treatment prior to the incident. 2. The police found an empty bank money bag in Graves's apartment. Graves claimed that he used the money bag to carry shotgun shells while hunting. 3. The police found $4000 in small bills in a shoe box beneath the floor boards of Graves's apartment. Graves claimed that this money was a reserve for medical emergencies because he had once been refused treatment because of lack of a cash advance. 4. Graves was served with a repossession notice 4 days before the crime. However, receipts from the loan company dated 2 days before the crime were produced in evidence. 5. Graves testified that he left work early on the day in question in order to get a haircut. 6. A friend of Graves testified that Graves had been in his barber shop at 5:00 pm on the day in question. Guilty story supplement The janitor had a reason that he did not report what he had seen right away. The personnel manager did not testify. Innocent story supplement Elaboration of the janitor's complaints about Graves revealed a racial motive. Graves's use of the bag was not specified. The bag wasfilledwith shotgun shells when found. The shoebox with the money contained medical records and insurance policy information. Graves was a diabetic. Graves's use of the money was not specified. Receipts for payment of the loan were not brought in. Graves revealed the source of the money used to pay the loans. Graves's supervisor testified that Graves had gotten a haircut one week before the crime. None Graves's supervisor had instructed Graves to get a haircut. The friend supplied details supporting the time. Experiment 3: Burglary Case William A. Payne is charged with the burglary of the apartment of Keith MacMillan, an airline pilot who was out of town at the time. The articles stolen included a TV set, a stereo set, a camera, and a shotgun. The burglary occurred at about 3:00 a.m., according to neighbors who were awakened by the burglar alarm. Evidence block (basic version) 1. The stolen stereo set was found in the trunk of Payne's car the day after the robbery. Payne claimed that he had purchased the stereo set from a stranger in the parking lot of a mall. No other stereo equipment was found in Payne's apartment. 2. The stolen TV set was found in Payne's apartment. No other TV set was found in the apartment. Guilty story supplement The stranger approached Payne at the mall as he was coming out of a supermarket. Another stereo set was found in Payne's apartment. Innocent story supplement The stranger approached Payne at the mall as he was coming out of a stereo equipment store. Payne had previously talked about his intention to buy a stereo. A clerk from the stereo equipment store testified that he had been in that day shopping for a stereo. He bought the TV from the same stranger. Payne had previously talked about buying a TV. Another TV set was found in Payne's apartment. 206 Evidence block (basic version) 3. Payne visited his former fiance at 2:00 a.m. the night of the burglary. She lived in the same apartment building complex as MacMillan. 4. The widow who owned Payne's garage apartment testified that Payne arrived home somewhere between 3:00 a.m. and 4:30 a.m. that night. NANCY PENNINGTON AND REID HASTIE Guilty story supplement Payne was not on good terms with his exfiance and she refused to admit him to visit. His fiance knew MacMillan socially and Payne had expressed jealousy. None Innocent story supplement Payne frequently visited his former fiance with whom he was on friendly terms. He stopped by briefly after work the night of the burglary. The widow is certain that the time Payne arrived home was somewhere between 2:00 a.m. and 2:30 a.m. Received January 4, 1991 Revision received June 6, 1991 Accepted July 9, 1991 mm AMERICAN PSYCHOLOGICAL ASSOCIATION F SUBSCRIPTION CLAIMS INFORMATION Today's Date:_ We provide this form to assist members, institutions, and nonmember individuals with any subscription problems. With the appropriate information we can begin a resolution. If you use the services of an agent, please do NOT duplicate claims through them and directly to us. PLEASE PRINT CLEARLY AND IN INK IF POSSIBLE. PRINT FULL NAME OR KEY NAME OF LNSTmniON MEMBER OR CUSTOMER NUMBER (MAYBE POUND ON ANYPAST ISSUE LABEL) DATE YOUR ORDER WAS MAILED (OR PHONED): ADDRESS P.O. NUMBER: __PREPAID . CITY STATE/COUNTRY _CHECK ___CHARGB CHECK/CARD CLEARED DATE:_ YOUR NAME AND PHONE NUMBER (If possible, send a copy, front and hack, of jour cancelled check to help us In our research of jour claim.) ISSUES: MISSING DAMAGED TITLE VOLUME OR YEAR NUMBER OR MONTH Thank you. Once a clm'm is received and resolved, delivery of replacement issues routinely takes 4-6 weeks. DATE RECEIVED: ACTION TAKEN: STAFF NAME: DATE OF ACTION: INV. NO. & DATE: LABEL NO. & DATE: SEND THIS FORM TO: IFrt rilr • riig HTW HlitiM. TfftriiTi fmrt. fT T. ~~Tirurtni. T"'"""" PLEASE DO NOT REMOVE. A PHOTOCOPY MAY BE USED.
Pages to are hidden for
"Explaining the Evidence Tests of"Please download to view full document