Shame and the virtual gaze: Supporting children's encounters in online worlds

As the virtual gaze of another becomes an increasingly prevalent feature in children's lives, this paper aims to explore some of the emotional complexities of the emerging physical/virtual landscape of children's experience. Based on an analysis of the emotion of shame, the paper explores the new challenges that children face both now and in the future in their virtual encounters and relations with others. It is argued that virtual spaces bring new dimensions to emotional experience, at times making it more difficult to realise the productive potential of shame. This is because the gaze or imagined gaze of another, as invoked through the experience of shame, occurs in conditions of uncertainty, has no boundaries and may arise at any time in the future. These insights are significant if we are to support children in building a capacity to restore the self and be resilient in these new spaces of social encounter.     

A general model for the analysis of multilevel data

A general model is developed for the analysis of multivariate multilevel data structures. Special cases of the model include repeated measures designs, multiple matrix samples, multilevel latent variable models, multiple time series, and variance and covariance component models.We would like to acknowledge the helpful comments of Ruth Silver. We also wish to thank the referees for helping to clarify the paper. This work was partly carried out with research funds provided by the Economic and Social Research Council (U.K.).     

Multilevel models in developmental psychological research: Rationales and applications

The armoury of statistical techniques has recently been enhanced with the multilevel model for longitudinal data. The present article explains the multilevel model for longitudinal data to the statistically non-sophisticated reader. It shows how the model relates to the five rationales of longitudinal research, as they were put forward by Baltes and Nesselroade (1979). In addition, it shows how the model matches Wohlwill's methodology of developmental functions. To elucidate the model further, three applications are given. The applications pertain to the development of children's sleeping duration during the first 18 months of life, the effects of early hospitalization on the daily frequency of crying, and the developmental relationship between social and solitary play.     

Connectionist models of conditioning: A tutorial

Models containing networks of neuron-like units have become increasingly prominent in the study of both cognitive psychology and artificial intelligence. This article describes the basic features of connectionist models and provides an illustrative application to compound-stimulus effects in respondent conditioning. Connectionist models designed specifically for operant conditioning are not yet widely available, but some current learning algorithms for machine learning indicate that such models are feasible. Conversely, designers for machine learning appear to have recognized the value of behavioral principles in producing adaptive behavior in their creations.     

A structural model for postpartum responses to the somatic and cognitive items on the Beck Depression Inventory

A distinction can be drawn between those items on the Beck Depression Inventory (BDI) that reflect mainly cognitive and emotional symptoms and those that reflect somatic symptoms. Responses to the BDI were obtained from women at 3, 6, 9, and 24 weeks postpartum. The covariances of cognitive and somatic symptom scores across the four time points were closely fit by a structural equations model referred to as the simplex. The modeling indicates that earlier cognitive scores directly predict later somatic scores but that early somatic scores do not directly predict later cognitive scores. Other data confirm the results.Much of this research was supported while the first author was an NIMH Fellow at the University of Iowa (MH15168).     

A taxonomy of item response models

A number of models for categorical item response data have been proposed in recent years. The models appear to be quite different. However, they may usefully be organized as members of only three distinct classes, within which the models are distinguished only by assumptions and constraints on their parameters. “Difference models” are appropriate for ordered responses, “divide-by-total” models may be used for either ordered or nominal responses, and “left-side added” models are used for multiple-choice responses with guessing. The details of the taxonomy and the models are described in this paper. The present study was supported in part by two postdoctoral fellowships awarded to Lynne Steinberg: an Educational Testing Service Postdoctoral Fellowship at ETS, Princeton, NJ and an NIMH Individual National Research Service Award at Stanford University, Stanford, CA. Helpful comments by the editor and three anonymous reviewers are gratefully acknowledged.     

Does Analytic Thinking Insulate Against Pro-Kremlin Disinformation? Evidence From Ukraine

Pro-Kremlin disinformation campaigns have long targeted Ukraine. We investigate susceptibility to this pro-Kremlin disinformation from a cognitive-science perspective. Is greater analytic thinking associated with less belief in disinformation, as per classical theories of reasoning? Or does analytic thinking amplify motivated system 2 reasoning (or “cultural cognition”), such that analytic thinking is associated with more polarized beliefs (and thus more belief in pro-Kremlin disinformation among pro-Russia Ukrainians)? In online (N = 1,974) and face-to-face representative (N = 9,474) samples of Ukrainians, we find support for the classical reasoning account. Analytic thinking, as measured using the Cognitive Reflection Test, was associated with greater ability to discern truth from disinformation—even for Ukrainians who are strongly oriented towards Russia. We find similar, albeit weaker, results when operationalizing analytic thinking using the self-report Actively Open-Minded Thinking scale. These results demonstrate a similar pattern to prior work using American participants. Thus, the positive association between analytic thinking and the ability to discern truth versus falsehood generalizes to the qualitatively different information environment of postcommunist Ukraine. Despite low trust in government and media, weak journalistic standards, and years of exposure to Russian disinformation, Ukrainians who engage in more analytic thinking are better able to tell truth from falsehood.     

Job seekers' attitudes toward cybervetting in China: Platform comparisons and relationships with social media posting habits and individual differences

Cybervetting, or reviewing applicants' social media profiles, has become a central part of the hiring process for many organizations. Yet, extant cybervetting research is largely limited to Western platforms and samples. The present study examines the three core elements of attitudes toward cybervetting (ATC—perceived justice, privacy invasion, and face validity) using a sample of 200 Chinese job seekers providing their views on three popular platforms in China (WeChat, QQ, and Weibo). Attitudes were negative across all platforms, although slightly more positive for WeChat. ATC were associated with job seekers' social media posting habits (e.g., posting positive content more frequently) and individual differences (i.e., gender and extraversion). Organizations should be mindful that cybervetting might impede the recruitment of talents.