Psychological Review

Tversky, Amos; Koehler, Derek J.

doi: 10.1037/0033-295X.101.4.547pmid: N/A

This article presents a new theory of subjective probability according to which different descriptions of the same event can give rise to different judgments. The experimental evidence confirms the major predictions of the theory. First, judged probability increases by unpacking the focal hypothesis and decreases by unpacking the alternative hypothesis. Second, judged probabilities are complementary in the binary case and subadditive in the general case, contrary to both classical and revisionist models of belief. Third, subadditivity is more pronounced for probability judgments than for frequency judgments and is enhanced by compatible evidence. The theory provides a unified treatment of a wide range of empirical findings. It is extended to ordinal judgments and to the assessment of upper and lower probabilities.

doi: 10.1037/0033-295X.101.4.547pmid: N/A

This article presents a new theory of subjective probability according to which different descriptions of the same event can give rise to different judgments. The experimental evidence confirms the major predictions of the theory. First, judged probability increases by unpacking the focal hypothesis and decreases by unpacking the alternative hypothesis. Second, judged probabilities are complementary in the binary case and subadditive in the general case, contrary to both classical and revisionist models of belief. Third, subadditivity is more pronounced for probability judgments than for frequency judgments and is enhanced by compatible evidence. The theory provides a unified treatment of a wide range of empirical findings. It is extended to ordinal judgments and to the assessment of upper and lower probabilities.

doi: 10.1037/0033-295X.101.4.568pmid: 7984707

In response to Anastasi's (1958) long-standing challenge, the authors propose an empirically testable theoretical model that (a) goes beyond and qualifies the established behavioral genetics paradigm by allowing for nonadditive synergistic effects, direct measures of the environment, and mechanisms of organism-environment interaction, called proximal processes, through which genotypes are transformed into phenotypes; (b) hypothesizes that estimates of heritability (e.g., h2) increase markedly with the magnitude of proximal processes; (c) demonstrates that heritability measures the proportion of variation in individual differences attributable only to actualized genetic potential, with the degree of nonactualized potential remaining unknown; (d) proposes that, by enhancing proximal processes and environments, it is possible to increase the extent of actualized genetic potentials for developmental competence.

doi: 10.1037/0033-295X.101.4.587pmid: 7984708

The 1st part of this article evaluates the extent to which 2 elemental theories of conditioning, stimulus sampling theory and the Rescorla–Wagner (1972) theory, are able to account for the influence of similarity on discrimination learning. A number of findings are reviewed that are inconsistent with predictions derived from these theories, either in their present form or in various modified forms. The 2nd part of the article is concerned with developing an alternative, configural account for discrimination learning. In contrast to previous configural theories, the present version is set within the framework of a connectionist network.

Oaksford, Mike; Chater, Nick

doi: 10.1037/0033-295X.101.4.608pmid: N/A

Human reasoning in hypothesis-testing tasks like Wason's (1966, 1968) selection task has been depicted as prone to systematic biases. However, performance on this task has been assessed against a now outmoded falsificationist philosophy of science. Therefore, the experimental data is reassessed in the light of a Bayesian model of optimal data selection in inductive hypothesis testing. The model provides a rational analysis (Anderson, 1990) of the selection task that fits well with people's performance on both abstract and thematic versions of the task. The model suggests that reasoning in these tasks may be rational rather than subject to systematic bias.

doi: 10.1037/0033-295X.101.4.608pmid: N/A

Human reasoning in hypothesis-testing tasks like Wason's (1966, 1968) selection task has been depicted as prone to systematic biases. However, performance on this task has been assessed against a now outmoded falsificationist philosophy of science. Therefore, the experimental data is reassessed in the light of a Bayesian model of optimal data selection in inductive hypothesis testing. The model provides a rational analysis (Anderson, 1990) of the selection task that fits well with people's performance on both abstract and thematic versions of the task. The model suggests that reasoning in these tasks may be rational rather than subject to systematic bias.

doi: 10.1037/0033-295X.101.4.632pmid: 7984709

Responsibility acts as a psychological adhesive that connects an actor to an event and to relevant prescriptions that should govern conduct. People are held responsible to the extent that (a) a clear, well-defined set of prescriptions is applicable to an event (prescription–event link); (b) the actor is perceived to be bound by the prescriptions by virtue of his or her identity (prescription–identity link); and (c) the actor is connected to the event, especially by virtue of appearing to have personal control over it (identity–event link). Studies supported the model, showing that attributions of responsibility are a direct function of the combined strengths of the 3 linkages (Study 1) and that, when judging responsibility, people seek out information that is relevant to the linkages (Study 2). The model clarifies prior multiple meanings of responsibility and provides a coherent framework for understanding social judgment.

doi: 10.1037/0033-295X.101.4.653pmid: 7984710

Three experiments and a simulation study investigate competing featural and phonemic views of the representation of the speech input in access to the mental lexicon. Auditory lexical decision and gating tasks show that the processing consequences of subcategorical mismatches (conflicts between phonetic cues to speech segment identity) depend on the lexical status of the conflicting cues, such that conflicts that only involve nonwords do not disrupt performance. A further study, using a phonetic-decision task with the same stimuli, found the same pattern. A simulation study shows that the interactive activation model TRACE, with top-down feedback to a prelexical phonemic level, does not model these effects successfully. The authors argue instead for a direct access featural model, based on a distributed computational substrate, where featural information is mapped directly onto lexical representations.

doi: 10.1037/0033-295X.101.4.676pmid: 7984711

Ambiguity resolution is a central problem in language comprehension. Lexical and syntactic ambiguities are standardly assumed to involve different types of knowledge representations and be resolved by different mechanisms. An alternative account is provided in which both types of ambiguity derive from aspects of lexical representation and are resolved by the same processing mechanisms. Reinterpreting syntactic ambiguity resolution as a form of lexical ambiguity resolution obviates the need for special parsing principles to account for syntactic interpretation preferences, reconciles a number of apparently conflicting results concerning the roles of lexical and contextual information in sentence processing, explains differences among ambiguities in terms of ease of resolution, and provides a more unified account of language comprehension than was previously available.

doi: 10.1037/0033-295X.101.4.704pmid: 7984712

A general account of choice behavior in animals, the cumulative effects model, has been proposed by Davis, Staddon, Machado, and Palmer (1993). Its basic assumptions are that choice occurs in an all-or-none fashion for the response alternative with the highest probability of reinforcement and that the probability of reinforcement for each response alternative is calculated from the entire history of training (total number of reinforced responses/total number of reinforced and nonreinforced responses). The model's reliance on probability of reinforcement as the fundamental variable controlling choice behavior subjects the cumulative effects model to the same criticisms as have been directed toward other related models of choice, notably melioration theory. Several different data sets show that the relative value of a response alternative is not predicted by the obtained probability of reinforcement associated with that alternative. Alternative approaches to choice theory are considered.