“This way!”, “No! That way!”—3-year olds know that two people can have mutually incompatible desires

In theory of mind research, there is a long standing dispute about whether children come to understand the subjectivity of both desires and beliefs at the same time (around age 4), or whether there is an asymmetry such that desires are understood earlier. To address this issue, 3-year olds’ understanding of situations in which two persons have mutually incompatible desires was tested in two studies. Results revealed that (i) children were quite proficient at ascribing incompatible desires to two persons, and in simpler scenarios even incompatible desire-dependent emotions; (ii) children showed this proficiency even though they mostly failed the false belief task. Overall, these results suggest that there is an asymmetry such that young children come to understand the subjective nature of desires before they understand the corresponding subjectivity of beliefs. Possible explanations for this asymmetry are discussed in light of conceptual change and information-processing accounts of theory of mind development.     

Visual and haptic feedback contribute to tuning and online control during object manipulation

The authors employed a virtual environment to investigate how humans use haptic and visual feedback in a simple, rhythmic object-manipulation task. The authors hypothesized that feedback would help participants identify the appropriate resonant frequency and perform online control adjustments. The 1st test was whether sensory feedback is needed at all; the 2nd was whether the motor system combines visual and haptic feedback to improve performance. Task performance was quantified in terms of work performed on the virtual inertia, ability to identify the correct rhythm, and variability of movement. Strict feedforward control was found to be ineffective for this task, even when participants had previous knowledge of the rhythm. Participants (N = 11) performed far better when feedback was available (11 times more work, 2.2 times more precise frequency, 30% less variability; p < .05 for all 3 performance measures). Using sensory feedback, participants were able to rapidly identify 4 different spring-inertia systems without foreknowledge of the corresponding resonant frequencies. They performed over 20% more work with 24% less variability when provided with both visual and haptic feedback than they did with either feedback channel alone (p < .05), providing evidence that they integrated online sensory channels. Whereas feedforward control alone led to poor performance, feedback control led to fast tuning or calibration of control according to the resonant frequency of the object, and to better control of the rhythmic movement itself.     

Beyond the Conflict: Religion in the Public Sphere and Deliberative Democracy

Traditionally, liberals have confined religion to the sphere of the ‘private’ or ‘non-political’. However, recent debates over the place of religious symbols in public spaces, state financing of faith schools, and tax relief for religious organisations suggest that this distinction is not particularly useful in easing the tension between liberal commitments to equality on the one hand, and freedom of religion on the other. This article deals with one aspect of this debate, which concerns whether members of religious communities should receive exemptions from regulations that place a distinctively heavy burden on them. Drawing on Habermas’ understanding of churches as ‘communities of interpretation’, we explore possible alternatives to both the ‘rule-and-exemption’ approach and the ‘neutralist’ approach. Our proposal rests on the idea of mutual learning between secular and religious perspectives. On this interpretation, what is required is (i) the generation and maintenance of public spaces in which there could be discussion and dialogue about particular cases, and (ii) evaluation of whether the basic conditions of moral discourse are present in these spaces. Thus deliberation becomes a touchstone for the building of a shared democratic ethos.     

Latent state–trait theory: An application in sport psychology

ObjectiveQuestionnaires are often applied in sports psychology to measure a person's trait or state. However, the extent to which the questionnaire captures differences because of trait or state influences is often unclear. The latent state–trait (LST) theory offers the opportunity to separate both variance sources. This separation allows estimating specific reliability coefficients.DesignThe present paper gives a theoretical introduction to LST and its basic ideas. Using a real data set with N = 156 athletes we exemplify the steps necessary to derive the LST coefficients. All athletes filled out a comprehensive inventory assessing competitive anxiety on two occasions.MethodThe data are analysed with structural equation models based on LST principles.ResultsThe results confirm the questionnaire's trait saturation.ConclusionFinally, results are discussed in light of practical and theoretical implications.     

Coping with loneliness in old age: a cross-cultural comparison

The present study is an examination of the influence of cultural background on the ways in which the aged cope with loneliness. Thirty-six participants from Canada and 105 from Portugal (60-83 years old) answered an 86-item questionnaire which examined thebeneficial strategies which they used to cope with loneliness. The strategies which were examined included Acceptance and Reflection, Self-Development and Understanding, Social Support Network, Distancing and Denial, Religion and Faith, and Increased Activity. Results indicated that the elderly of the two cultures differ on three subscales. Gender differences between and within cultures were also examined.     

The psychometric function: I. Fitting, sampling, and goodness of fit

The psychometric function relates an observer’s performance to an independent variable, usually some physical quantity of a stimulus in a psychophysical task. This paper, together with its companion paper (Wichmann & Hill, 2001), describes an integrated approach to (1) fitting psychometric functions, (2) assessing the goodness of fit, and (3) providing confidence intervals for the function’s parameters and other estimates derived from them, for the purposes of hypothesis testing. The present paper deals with the first two topics, describing a constrained maximum-likelihood method of parameter estimation and developing several goodness-of-fit tests. Using Monte Carlo simulations, we deal with two specific difficulties that arise when fitting functions to psychophysical data. First, we note that human observers are prone to stimulus-independent errors (orlapses). We show that failure to account for this can lead to serious biases in estimates of the psychometric function’s parameters and illustrate how the problem may be overcome. Second, we note that psychophysical data sets are usually rather small by the standards required by most of the commonly applied statistical tests. We demonstrate the potential errors of applying traditionalX ² methods to psychophysical data and advocate use of Monte Carlo resampling techniques that do not rely on asymptotic theory. We have made available the software to implement our methods.     

Statistical Learning of Unfamiliar Sounds as Trajectories Through a Perceptual Similarity Space

In typical statistical learning studies, researchers define sequences in terms of the probability of the next item in the sequence given the current item (or items), and they show that high probability sequences are treated as more familiar than low probability sequences. Existing accounts of these phenomena all assume that participants represent statistical regularities more or less as they are defined by the experimenters—as sequential probabilities of symbols in a string. Here we offer an alternative, or possibly supplementary, hypothesis. Specifically, rather than identifying or labeling individual stimuli discretely in order to predict the next item in a sequence, we need only assume that the participant is able to represent the stimuli as evincing particular similarity relations to one another, with sequences represented as trajectories through this similarity space. We present experiments in which this hypothesis makes sharply different predictions from hypotheses based on the assumption that sequences are learned over discrete, labeled stimuli. We also present a series of simulation models that encode stimuli as positions in a continuous two‐dimensional space, and predict the next location from the current location. Although no model captures all of the data presented here, the results of three critical experiments are more consistent with the view that participants represent trajectories through similarity space rather than sequences of discrete labels under particular conditions.