Symbolically speaking: a connectionist model of sentence production

The ability to combine words into novel sentences has been used to argue that humans have symbolic language production abilities. Critiques of connectionist models of language often center on the inability of these models to generalize symbolically (Fodor & Pylyshyn, 1988; Marcus, 1998). To address these issues, a connectionist model of sentence production was developed. The model had variables (role‐concept bindings) that were inspired by spatial representations (Landau & Jackendoff, 1993). In order to take advantage of these variables, a novel dual‐pathway architecture with event semantics is proposed and shown to be better at symbolic generalization than several variants. This architecture has one pathway for mapping message content to words and a separate pathway that enforces sequencing constraints. Analysis of the model's hidden units demonstrated that the model learned different types of information in each pathway, and that the model's compositional behavior arose from the combination of these two pathways. The model's ability to balance symbolic and statistical behavior in syntax acquisition and to model aphasic double dissociations provided independent support for the dual‐pathway architecture.     

Labels as features (not names) for infant categorization: a neurocomputational approach

A substantial body of experimental evidence has demonstrated that labels have an impact on infant categorization processes. Yet little is known regarding the nature of the mechanisms by which this effect is achieved. We distinguish between two competing accounts: supervised name-based categorization and unsupervised feature-based categorization. We describe a neurocomputational model of infant visual categorization, based on self-organizing maps, that implements the unsupervised feature-based approach. The model successfully reproduces experiments demonstrating the impact of labeling on infant visual categorization reported in Plunkett, Hu, and Cohen (2008) . It mimics infant behavior in both the familiarization and testing phases of the procedure, using a training regime that involves only single presentations of each stimulus and using just 24 participant networks per experiment. The model predicts that the observed behavior in infants is due to a transient form of learning that might lead to the emergence of hierarchically organized categorical structure and that the impact of labels on categorization is influenced by the perceived similarity and the sequence in which the objects are presented. The results suggest that early in development, say before 12 months old, labels need not act as invitations to form categories nor highlight the commonalities between objects, but they may play a more mundane but nevertheless powerful role as additional features that are processed in the same fashion as other features that characterize objects and object categories.     

Combining versus analyzing multiple causes: how domain assumptions and task context affect integration rules

In everyday life, people typically observe fragments of causal networks. From this knowledge, people infer how novel combinations of causes they may never have observed together might behave. I report on 4 experiments that address the question of how people intuitively integrate multiple causes to predict a continuously varying effect. Most theories of causal induction in psychology and statistics assume a bias toward linearity and additivity. In contrast, these experiments show that people are sensitive to cues biasing various integration rules. Causes that refer to intensive quantities (e.g., taste) or to preferences (e.g., liking) bias people toward averaging the causal influences, whereas extensive quantities (e.g., strength of a drug) lead to a tendency to add. However, the knowledge underlying these processes is fallible and unstable. Therefore, people are easily influenced by additional task-related context factors. These additional factors include the way data are presented, the difficulty of the inference task, and transfer from previous tasks. The results of the experiments provide evidence for causal model and related theories, which postulate that domain-general representations of causal knowledge are influenced by abstract domain knowledge, data-driven task factors, and processing difficulty.     

Words Get in the Way: Linguistic Effects on Talker Discrimination

A speech perception experiment provides evidence that the linguistic relationship between words affects the discrimination of their talkers. Listeners discriminated two talkers' voices with various linguistic relationships between their spoken words. Listeners were asked whether two words were spoken by the same person or not. Word pairs varied with respect to the linguistic relationship between the component words, forming either: phonological rhymes, lexical compounds, reversed compounds, or unrelated pairs. The degree of linguistic relationship between the words affected talker discrimination in a graded fashion, revealing biases listeners have regarding the nature of words and the talkers that speak them. These results indicate that listeners expect a talker's words to be linguistically related, and more generally, indexical processing is affected by linguistic information in a top‐down fashion even when listeners are not told to attend to it.     

The role of the ‘other’ in national identity: exploring the context‐dependence of the national ingroup stereotype

Analysts from a range of disciplines (especially sociology and social anthropology) highlight the role of the ‘other’ in the construction and definition of national identity. Recently some social psychologists have come to emphasize the inherently relational nature of identity. Drawing upon these recent investigations, the present paper reports a field study investigating the context‐dependent nature of group identity. Using a modified version of the Katz–Braly task, British subjects (n=240) stereotyped two national groups: Americans and British. They did so in two conditions. In the ‘one‐group’ conditions, subjects rated either of the two groups. In the ‘two‐group’ conditions, they rated one whilst also considering the other. Following Oakes, Haslam and Turner (1994) we predicted that whereas subjects' stereotypes of the national outgroup (the Americans) would be unaffected by this manipulation, their stereotype of the national ingroup (the British) would be affected. This prediction was confirmed. We also predicted that the national ingroup stereotype obtained in the ‘two‐group’ condition would be one which was defined in contrast to the American ‘other’ which constituted the comparative context. Using a measure which takes into account the applicability of ingroup‐defining terms to both the ingroup and the outgroup (the diagnosticity measure of stereotyping proposed by McCauley and Stitt, 1978) we show that the ingroup identity definition produced in this condition did indeed differentiate the British from the Americans. The significance of these data for those concerned with the application of social psychological theory to real‐life social problems is discussed. Copyright © 1999 John Wiley & Sons, Ltd.     

Religion and self-efficacy: a multilevel approach

Can the religious values of an entire geographic area affect the self-efficacy of emerging adults living in that area? Although prior research has demonstrated that individual religious characteristics are associated with self-efficacy, less is known about how the overall religious context influences self-efficacy. Using multilevel analyses on two waves of the National Study of Youth and Religion (NSYR) merged with county-level variables, this study finds that a county’s higher conservative Protestant population share is associated with lower self-efficacy even after controlling for various variables. Surprisingly, this conservative Protestant contextual effect also applies to residents who are not conservative Protestants but live in a conservative Protestant county. In contrast, county-level Catholic population share is linked with higher self-efficacy. However, this Catholic contextual effect is explained when controlling for county-level variables.     

公共组织学习的心理学透视：经验习得与信息加工

本文从心理学关于学习的概念,关于行为、认知与信息加工的行为学习理论、社会学习理论和信息加工理论,以及行为绩效的心理学原理角度,阐述了我们所提出的公共组织学习的概念框架的心理学理论基础。认为从心理学角度透视公共组织学习,其实质是经验习得与信息加工的过程。这充分体现了心理学基本理论原理在公共组织学习理论建构中所具有的重要应用价值。     

Linguistic and Perceptual Mapping in Spatial Representations: An Attentional Account

Building on evidence for embodied representations, we investigated whether Spanish spatial terms map onto the NEAR/FAR perceptual division of space. Using a long horizontal display, we measured congruency effects during the processing of spatial terms presented in NEAR or FAR space. Across three experiments, we manipulated the task demands in order to investigate the role of endogenous attention in linguistic and perceptual space mapping. We predicted congruency effects only when spatial properties were relevant for the task (reaching estimation task, Experiment 1) but not when attention was allocated to other features (lexical decision, Experiment 2; and color, Experiment 3). Results showed faster responses for words presented in Near‐space in all experiments. Consistent with our hypothesis, congruency effects were observed only when a reaching estimate was requested. Our results add important evidence for the role of top‐down processing in congruency effects from embodied representations of spatial terms.     

What you are confident of determines your choices in context: Confidence in yourself versus in your ability

The notion that consumers' preference is constructed by decision context is well established. Two of such salient manifestations are compromise effect and attraction effect. Although literature has explored the moderators of these effects from the perspective of a decision maker, little is known about whether a significant difference exists between the effects of individual differences as a situational state and as a stable personality. This article approaches this question by examining how specific self‐confidence and general self‐confidence shape consumer's preference for context options. Four studies find that compromise effect is greater for consumer with high specific self‐confidence, whereas attraction effect is greater for consumer with low specific self‐confidence. The two context effects are greater for consumers with low general self‐confidence only in the presence of social influence. In addition, low (vs. high) general self‐confidence strengthens (vs. weakens) the impact of specific self‐confidence on context effects under this condition. This article concludes by discussing the theoretical and practical implications of the findings.     

One or two dimensions in spontaneous classification: a simplicity approach

When participants are asked to spontaneously categorize a set of items, they typically produce unidimensional classifications, i.e., categorize the items on the basis of only one of their dimensions of variation. We examine whether it is possible to predict unidimensional vs. two-dimensional classification on the basis of the abstract stimulus structure, by employing Pothos and Chater's simplicity model of spontaneous categorization [Pothos, E. M., & Chater, N. (2002). A simplicity principle in unsupervised human categorization. Cognitive Science, 26, 303-343]. The simplicity model provides a quantitative measure of how intuitive a particular classification is. With objects represented in two dimensions, we propose that a unidimensional classification will be preferred if it is more intuitive than all possible two-dimensional ones, and vice versa. Empirical results supporting this proposal are reported. Implications for Goodman's paradox are discussed.     

Religion and youth educational aspirations: a multilevel approach

Previous research has demonstrated that individual religious beliefs and practices are associated with educational outcomes. However, less is known about the manner in which the overall religious cultural influence of a religion can affect an individual’s educational aspirations. Using multilevel analyses on two waves of the National Study of Youth and Religion (NSYR) merged with county-level variables from the US Census, and the Religious Congregations and Membership Study (RCMS), the study shows that a county’s higher Jewish population share is associated with a higher level of educational aspirations for the youth, regardless of being Jewish or not. This Jewish contextual effect remains robust even after controlling a wide range of individual and county-level variables, such as individual academic achievement and religious identity. Consistent with the relevant theory and literature, the negative main effect of county-level conservative Protestant population share on educational aspirations is explained by county-level socioeconomic characteristics. The same mechanism is used in part to explain the initially positive relationship between Catholic population share and educational aspirations. Finally, the study highlights the importance of using a multilevel approach to examine and provide understanding of the relationship between religious influence and educational outcomes.     

The Baltimore Mural Project: An approach to threshold concepts in religious studies

The Baltimore Mural Project (BMP) seeks to connect religious studies education to the growing literature on threshold concepts in order to address bottleneck areas in student learning. The project is designed for undergraduate service courses comprised of mostly non‐majors: for example, world religions. Students in these courses often struggle to understand and apply the discipline's unique approaches to the study of religion (i.e. its threshold concepts). Rather than merely memorize certain facts about a religious tradition's myths [or world forming stories], rituals [or embodied disclosures], materials, and so on... students are asked to apply threshold concepts related to religion, art, and the social good to the study of murals in Baltimore. Through a series of project elements (including: field work, photography, digital geomapping, and quantitative, qualitative, and archival research) the BMP helps students who struggle with threshold concepts in religious studies by creatively connecting the more conventional aspects of world religions courses to social justice issues related to mural art in Baltimore. By experientially helping students to make these connections, they are able to find creative routes through otherwise hindering barriers to their learning in religious studies.     

Acquiring and processing verb argument structure: distributional learning in a miniature language

Adult knowledge of a language involves correctly balancing lexically-based and more language-general patterns. For example, verb argument structures may sometimes readily generalize to new verbs, yet with particular verbs may resist generalization. From the perspective of acquisition, this creates significant learnability problems, with some researchers claiming a crucial role for verb semantics in the determination of when generalization may and may not occur. Similarly, there has been debate regarding how verb-specific and more generalized constraints interact in sentence processing and on the role of semantics in this process. The current work explores these issues using artificial language learning. In three experiments using languages without semantic cues to verb distribution, we demonstrate that learners can acquire both verb-specific and verb-general patterns, based on distributional information in the linguistic input regarding each of the verbs as well as across the language as a whole. As with natural languages, these factors are shown to affect production, judgments and real-time processing. We demonstrate that learners apply a rational procedure in determining their usage of these different input statistics and conclude by suggesting that a Bayesian perspective on statistical learning may be an appropriate framework for capturing our findings.     

A small look at the ear recognition process using a hybrid approach

The purpose of this document is to offer a combined approach in biometric analysis field, integrating some of the most known techniques using ears to recognize people. This study uses Hausdorff distance as a pre-processing stage adding sturdiness to increase the performance filtering for the subjects to use it in the testing process. Also includes the Image Ray Transform (IRT) and the Haar based classifier for the detection step. Then, the system computes Speeded Up Robust Features (SURF) and Linear Discriminant Analysis (LDA) as an input of two neural networks to recognize a person by the patterns of its ear. To show the applied theory experimental results, the above algorithms have been implemented using Microsoft C#. The investigation results showed robustness improving the ear recognition process.     

A nonsequential approach to the study of operant renewal: a reverse translation

ABA renewal is a model of treatment relapse that describes the recurrence of severe problem behavior when behavior learned in one context (e.g., home; A) and treated in a separate context (e.g., clinic; B) reemerges when the original context is reintroduced (A). However, in the typical environment and during the usual course of treatment for severe problem behavior, the target behavior is exposed to the baseline context periodically (e.g., the child returns home after several hours in a clinic setting). Due to the difficulty of studying what effect this may have on treatment relapse during ABA renewal in a strictly applied investigation, we developed a human‐laboratory translation to study renewal in a nonsequential manner. Using undergraduate students as subjects, we directly compared levels of recurrence using the standard ABA renewal procedure and a modified nonsequential ACA procedure, one modeled from the typical course of treatment for problem behavior. Both methods produced renewal at comparable levels, and patterns during nonsequential ACA renewal were similar to those during sequential ABA renewal. We discuss the implications of these findings in the framework of treatment for severe problem behavior.     

Judgments in a hurry: Time pressure affects how judges assess unfairly shared losses and unfairly shared gains

Human society has evolved to allow third parties—the court system, parents or other societal arbitrators—to punish norm violators and compensate victims. Few studies explore the effect of stress or time pressure on a third‐party judge. Under time pressure, people will likely show a more instinctual reaction or judgment style. We investigated third‐party punishment and compensation within the context of unfairly shared losses and gains in a dictator game under time pressure. Our results show that under no time pressure, participants were inclined to punish dictators who unfairly split windfall gains; however, participants chose to compensate victims more than punish the norm‐violating dictators in the context of unfairly shared losses. With added time pressure, third‐parties were disposed to inflict punishment upon the dictator in both the gain and loss contexts—punishment became the action of choice. Our results shed light on the way observed behavior and stress affect social cognition and decision making in the context of altruistic social interventions and the enforcement of social norms.     

Probability judgment in hierarchical learning: a conflict between predictiveness and coherence

Why are people's judgments incoherent under probability formats? Research in an associative learning paradigm suggests that after structured learning participants give judgments based on predictiveness rather than normative probability. This is because people's learning mechanisms attune to statistical contingencies in the environment, and they use these learned associations as a basis for subsequent probability judgments. We introduced a hierarchical structure into a simulated medical diagnosis task, setting up a conflict between predictiveness and coherence. Thus, a target symptom was more predictive of a subordinate disease than of its superordinate category, even though the latter included the former. Under a probability format participants tended to violate coherence and make ratings in line with predictiveness; under a frequency format they were more normative. These results are difficult to explain within a unitary model of inference, whether associative or frequency-based. In the light of this, and other findings in the judgment and learning literature, a dual-component model is proposed.