The position of authenticity within extant models of personality

The aim of the current study was to explore where authenticity, derived from the humanistic tradition of psychology, was positioned within a number of extant models of personality. Exploratory and Confirmatory Factor Analysis of data from four samples (total N = 1286) suggested that authenticity can be considered as loading on the Honesty-Humility factor of personality. These findings are discussed in terms of the wider theoretical overlaps between Honesty-Humility and psychological functioning as emphasised by the humanistic tradition of psychology.     

Selective impairment of living things and musical instruments on a verbal 'Semantic Knowledge Questionnaire' in a case of apperceptive visual agnosia

Semantic memory was investigated in a patient (MR) affected by a severe apperceptive visual agnosia, due to an ischemic cerebral lesion, bilaterally affecting the infero-mesial parts of the temporo-occipital cortices. The study was made by means of a Semantic Knowledge Questionnaire (Laiacona, Barbarotto, Trivelli, & Capitani, 1993), which takes separately into account four categories of living beings (animals, fruits, vegetables and body parts) and of artefacts (furniture, tools, vehicles and musical instruments), does not require a visual analysis and allows to distinguish errors concerning super-ordinate categorization, perceptual features and functional/encyclopedic knowledge. When the total number of errors obtained on all the categories of living and non-living beings was considered, a non-significant trend toward a higher number of errors in living stimuli was observed. This difference, however, became significant when body parts and musical instruments were excluded from the analysis. Furthermore, the number of errors obtained on the musical instruments was similar to that obtained on the living categories of animals, fruits and vegetables and significantly higher of that obtained in the other artefact categories. This difference was still significant when familiarity, frequency of use and prototypicality of each stimulus entered into a logistic regression analysis. On the other hand, a separate analysis of errors obtained on questions exploring super-ordinate categorization, perceptual features and functional/encyclopedic attributes showed that the differences between living and non-living stimuli and between musical instruments and other artefact categories were mainly due to errors obtained on questions exploring perceptual features. All these data are at variance with the 'domains of knowledge' hypothesis', which assumes that the breakdown of different categories of living and non-living things respects the distinction between biological entities and artefacts and support the models assuming that 'category-specific semantic disorders' are the by-product of the differential weighting that visual-perceptual and functional (or action-related) attributes have in the construction of different biological and artefacts categories.     

Testing the limits of long-distance learning: learning beyond a three-segment window

Traditional flat-structured bigram and trigram models of phonotactics are useful because they capture a large number of facts about phonological processes. Additionally, these models predict that local interactions should be easier to learn than long-distance ones because long-distance dependencies are difficult to capture with these models. Long-distance phonotactic patterns have been observed by linguists in many languages, who have proposed different kinds of models, including feature-based bigram and trigram models, as well as precedence models. Contrary to flat-structured bigram and trigram models, these alternatives capture unbounded dependencies because at an abstract level of representation, the relevant elements are locally dependent, even if they are not adjacent at the observable level. Using an artificial grammar learning paradigm, we provide additional support for these alternative models of phonotactics. Participants in two experiments were exposed to a long-distance consonant-harmony pattern in which the first consonant of a five-syllable word was [s] or [∫] ("sh") and triggered a suffix that was either [-su] or [-∫u] depending on the sibilant quality of this first consonant. Participants learned this pattern, despite the large distance between the trigger and the target, suggesting that when participants learn long-distance phonological patterns, that pattern is learned without specific reference to distance.     

Theory learning as stochastic search in the language of thought

We present an algorithmic model for the development of children's intuitive theories within a hierarchical Bayesian framework, where theories are described as sets of logical laws generated by a probabilistic context-free grammar. We contrast our approach with connectionist and other emergentist approaches to modeling cognitive development. While their subsymbolic representations provide a smooth error surface that supports efficient gradient-based learning, our symbolic representations are better suited to capturing children's intuitive theories but give rise to a harder learning problem, which can only be solved by exploratory search. Our algorithm attempts to discover the theory that best explains a set of observed data by performing stochastic search at two levels of abstraction: an outer loop in the space of theories and an inner loop in the space of explanations or models generated by each theory given a particular dataset. We show that this stochastic search is capable of learning appropriate theories in several everyday domains and discuss its dynamics in the context of empirical studies of children's learning.     

Dealing with Dynamic Decision Problems when Knowledge of the Environment Is Limited: An Approach Based on Goal Systems

We experimentally analyzed decision procedures for dealing with a dynamic decision‐making problem in which only qualitative information about the deterministic dynamics of the environment was available to participants. A participant's task was to maximize long‐term profit in a computer‐simulated monopoly market featuring delays and inertia. The design enabled a goal‐system‐based procedure, whereby a participant could select one or several short‐term variables to be controlled (goal variables) and chose target values (aspiration levels) for each of them over a total of 50 periods. We report results based on a sample of 63 participants on the formation of goal systems and the process of aspiration adaptation. Our main findings are, first, that more frequently selecting goal systems that adequately reflect the causal structure of the underlying model is positively correlated with long‐term profit; second, that goal persistence, a measure of a participant's tendency to stick to the current goal system, is positively correlated with long‐term profit; and third, that aspiration levels tend to be adapted in strong agreement with certain basic principles of a benchmark model of aspiration adaptation. Our study thus suggests and provides empirical foundation for an approach to dealing with complex dynamic decision problems based on neither optimization nor learning. Copyright © 2011 John Wiley & Sons, Ltd.     

More important and surprising actions of a moral exemplar trigger stronger admiration and inspiration

ABSTRACT

Admiring a moral role model has been found to inspire people to become better persons themselves. But what are the antecedents that trigger admiration and thus make inspiration more likely? In three studies, we tested the effect of perceived importance and perceived surprisingness of the moral action on resulting admiration and inspiration. Study 1 finds that perceived importance, and to a lesser extent, the perceived surprisingness of a moral action, are related to stronger admiration. Manipulating the perceived importance of the same moral action by only providing a little more detail about the moral action, could increase the admiration and inspiration the role models elicit (Studies 2 and 3). Our findings help the understanding of how moral exemplars trigger inspiration and provide valuable insights into further investigation toward the causes of admiration.     

Association Learning with Own‐ and Other‐race Faces in three‐ and six‐month old infants – A longitudinal study

This longitudinal study assessed 133 Caucasian German infants at 3 and 6 months of age to investigate the influence of own‐race and other‐race faces as visual stimuli on association learning in the visual expectation paradigm (VExP). The study is related to the findings on the other‐race‐effect (ORE) which is said to emerge at 6 months of age. Caucasian faces were used as stimuli of a familiar ethnic category, whereas African faces were used as stimuli of an unfamiliar ethnic category. There was no significant difference between the two stimulus classes in infants' reaction time (RT) to stimulus shifts at 3 months. At 6 months of age, infants' RT decreased significantly in the Caucasian faces condition but not in the African faces condition. These results indicate that the processing of other‐race versus own‐race faces by the age of 6 months, which is also the relevant age for the onset of the ORE, has an important influence on the performance on the VExP. Copyright © 2011 John Wiley & Sons, Ltd.     

Performance evaluation of recent information criteria for selecting multilevel models in Behavioral and Social Sciences

This study was designed to find the best strategy for selecting the correct multilevel model among several alternatives taking into account variables such as intraclass correlation, number of groups (m), group size (n), or others as parameter values and intercept-slope covariance. First, we examine this question in a simulation study and second, to illustrate the behavior of the criteria and to explore the generalizability of the findings, a previously published educational dataset is analyzed. The results showed that none of the selection criteria behaved correctly under all the conditions or was consistently better than the others. The intraclass correlation somewhat affects the performance of all selection criteria, but the extent of this influence is relatively minor compared to sample size, parameter values, and correlation between random effects. A large number of groups appears more important than a large number of individuals per group in selecting the best model (m ≥ 50 and n ≥ 20 is suggested). Finally, model selection tools such as Akaike's Information Criterion (AIC) or the conditional AIC are recommend when it is assumed that random effects are correlated, whereas use of the Schwarz's Bayesian Information Criterion or the consistent AIC are advantageous for uncorrelated random effects.     

Probabilistic single function dual process theory and logic programming as approaches to non-monotonicity in human vs. artificial reasoning

In this paper, it is argued that single function dual process theory is a more credible psychological account of non-monotonicity in human conditional reasoning than recent attempts to apply logic programming (LP) approaches in artificial intelligence to these data. LP is introduced and among other critiques, it is argued that it is psychologically unrealistic in a similar way to hash coding in the classicism vs. connectionism debate. Second, it is argued that causal Bayes nets provide a framework for modelling probabilistic conditional inference in System 2 that can deal with patterns of inference LP cannot. Third, we offer some speculations on how the cognitive system may avoid problems for System 1 identified by Fodor in 1983. We conclude that while many problems remain, the probabilistic single function dual processing theory is to be preferred over LP as an account of the non-monotonicity of human reasoning.     

Are People Naïve Probability Theorists? A Further Examination of the Probability Theory + Variation Model

Two experiments tested predictions derived from the Probability Theory + Variation (PTV) model. PTV model assumes that judgments follow probability theory, but systematic errors arise from noise in the judgments. Experiment 1 compared the PTV model to a configural weighted averaging model in joint probability judgment and found more support for the PTV model in diagnostic cases. Specifically, noise was negatively correlated with semantic coherence and conjunction and disjunction fallacies increased when order effects produced more noise in conjunctions and disjunctions. Consistent with both models, judgments adhered stochastically to the addition law. Contrary to the integration rules of the PTV model, we failed to find increased noise in disjunctions compared to conjunctions. Experiment 2 tested predictions of the PTV model for conditional probability judgment. Consistent with the PTV model, noise was negatively correlated with semantic coherence in conditional probabilities and judgments adhered stochastically to Bayes' theorem. Conversion errors were generally more prevalent than conditional reversals, a finding that is not fully consistent with the PTV model. In general, the quantitative fit of the PTV model was relatively better for overlapping and subset problems compared to identical, independent and mutually exclusive problems, especially for semantic coherence. Copyright © 2014 John Wiley & Sons, Ltd.