Childhood and advances in human tool use

Human life history incorporates childhood, a lengthy post-weaning period of dependency. This species-specific period provides an opportunity for extensive learning and for sophisticated cultural behaviors to develop, including crucial tool use skills. Although I agree that no individual cognitive trait singularly differentiates humans from other animals, I suggest here that without childhood, the traits that are key to human tool use would not emerge.     

A stochastic lie detector

Surveys on sensitive issues provide distorted prevalence estimates when participants fail to respond truthfully. The randomized-response technique (RRT) encourages more honest responding by adding random noise to responses, thereby removing any direct link between a participant’s response and his or her true status with regard to a sensitive attribute. However, in spite of the increased confidentiality, some respondents still refuse to disclose sensitive attitudes or behaviors. To remedy this problem, we propose an extension of Mangat’s (Journal of the Royal Statistical Society: Series B, 56, 93–95, 1994) variant of the RRT that allows for determining whether participants respond truthfully. This method offers the genuine advantage of providing undistorted prevalence estimates for sensitive attributes even if respondents fail to respond truthfully. We show how to implement the method using both closed-form equations and easily accessible free software for multinomial processing tree models. Moreover, we report the results of two survey experiments that provide evidence for the validity of our extension of Mangat’s RRT approach.     

Come as you are? Public Reason and Climate Change

Res Publica - The likely adverse effects of climate change call for political action. In this paper, we argue that the public reason framework—with its insistence on justifiability to all...     

multiTree: A computer program for the analysis of multinomial processing tree models

Multinomial processing tree (MPT) models are a family of stochastic models for psychology and related sciences that can be used to model observed categorical frequencies as a function of a sequence of latent states. For the analysis of such models, the present article presents a platform-independent computer program called multiTree, which simplifies the creation and the analysis of MPT models. This makes them more convenient to implement and analyze. Also, multiTree offers advanced modeling features. It provides estimates of the parameters and their variability, goodness-of-fit statistics, hypothesis testing, checks for identifiability, parametric and nonparametric bootstrapping, and power analyses. In this article, the algorithms underlying multiTree are given, and a user guide is provided. The multiTree program can be downloaded from http://psycho3.uni-mannheim.de/multitree.     

The Comprehensive Alcohol Expectancy Questionnaire: Confirmatory Factor Analysis,Scale Refinement,and Further Validation

The Comprehensive Alcohol Expectancy Questionnaire (CAEQ; Demmel & Hagen, 2003a, 2003b) is a self-report measure designed to assess an individual’s alcohol expectancies. In this study, we examined the CAEQ in a student sample (N= 932) and in a clinical sample of alcohol-dependent inpatients (N= 744). The Five-factor structure was confirmed by means of confirmatory factor analysis. Convergent validity of the revised CAEQ was supported by showing significant relationships to quantity and frequency of drinking. The results of this study suggest that the revised CAEQ appears to be a psychometrically sound tool for the assessment of alcohol expectancies among both students and alcohol-dependent inpatients.     

Impaired artificial grammar learning in agrammatism

It is often assumed that language is supported by domain-specific neural mechanisms, in part based on neuropsychological data from aphasia. If, however, language relies on domain-general mechanisms, it would be expected that deficits in non-linguistic cognitive processing should co-occur with aphasia. In this paper, we report a study of sequential learning by agrammatic aphasic patients and control participants matched for age, socio-economic status and non-verbal intelligence. Participants were first exposed to strings derived from an artificial grammar after which they were asked to classify a set of new strings, some of which were generated by the same grammar whereas others were not. Although both groups of participants performed well in the training phase of the experiment, only the control participants were able to classify novel test items better than chance. The results show that breakdown of language in agrammatic aphasia is associated with an impairment in artificial grammar learning, indicating damage to domain-general neural mechanisms subserving both language and sequential learning.     

Optimizing subjective measures of consciousness

Dienes and Seth (2010) conclude that confidence ratings and post-decision wagering are two comparable and recommendable measures of conscious experience. In a recently submitted paper, we have however found that both methods are problematic and seem less suited to measure consciousness than a direct introspective measure.Here, we discuss the methodology and conclusions put forward by Dienes and Seth, and why we think the two experiments end up with so different recommendations.