Predicting recidivism with the Psychopathy Checklist: are factor score composites really necessary?

In two previous studies on general and violent recidivism (Walters & Heilbrun, 2010; Walters, Knight, Grann, & Dahle, 2008), the summed composite antisocial facet of the Psychopathy Checklist displayed incremental validity relative to the other 3 facets (interpersonal, affective, lifestyle), whereas the other 3 facets generally failed to demonstrate incremental validity relative to the antisocial facet. Because summed composite scores do not account for ordinal item distributions, the 6 Walters et al. (2008) samples were reanalyzed with factor score composites derived from a 4-factor confirmatory factor analysis. The results, however, showed little change from what had been obtained earlier with summed composite scores. Two additional samples not previously included in any incremental validity analyses of the Psychopathy Checklist evidenced a 3-factor structure, with the lifestyle and antisocial facets merged into a single factor. This single factor displayed incremental validity relative to the interpersonal and affective facets, but the reverse was not true regardless of whether summed composite scores or factor score composites were used. A comparison of zero-order correlations from all 8 samples revealed that the antisocial summed composite score predicted significantly better than the summed composite scores for the other 3 facets and that a superordinate factor failed to improve on the performance of either the antisocial summed composite score or the antisocial factor score composite.     

The mental representation of causal conditional reasoning: mental models or causal models

In this paper, two experiments are reported investigating the nature of the cognitive representations underlying causal conditional reasoning performance. The predictions of causal and logical interpretations of the conditional diverge sharply when inferences involving pairs of conditionals—such as if P₁then Q and if P₂then Q—are considered. From a causal perspective, the causal direction of these conditionals is critical: are the P_icauses of Q; or symptoms caused byQ. The rich variety of inference patterns can naturally be modelled by Bayesian networks. A pair of causal conditionals where Q is an effect corresponds to a “collider” structure where the two causes (P_i) converge on a common effect. In contrast, a pair of causal conditionals where Q is a cause corresponds to a network where two effects (P_i) diverge from a common cause. Very different predictions are made by fully explicit or initial mental models interpretations. These predictions were tested in two experiments, each of which yielded data most consistent with causal model theory, rather than with mental models.     

Language acquisition meets language evolution

Recent research suggests that language evolution is a process of cultural change, in which linguistic structures are shaped through repeated cycles of learning and use by domain-general mechanisms. This paper draws out the implications of this viewpoint for understanding the problem of language acquisition, which is cast in a new, and much more tractable, form. In essence, the child faces a problem of induction, where the objective is to coordinate with others (C-induction), rather than to model the structure of the natural world (N-induction). We argue that, of the two, C-induction is dramatically easier. More broadly, we argue that understanding the acquisition of any cultural form, whether linguistic or otherwise, during development, requires considering the corresponding question of how that cultural form arose through processes of cultural evolution. This perspective helps resolve the "logical" problem of language acquisition and has far-reaching implications for evolutionary psychology.     

A Clinical Model in Action in Intensive Residential Treatment: Meeting the Needs of Adolescent Boys who have Experienced Domestic Violence

The Habitat Program at Wood’s Homes, Calgary, Alberta, is an eight bed residential treatment program for conduct-disordered youth who have been exposed or subjected to high levels of violence in their family home. The program was based on the assumption that working effectively with such youth requires consideration of the background experiences of family violence, yet traditional treatment models often ignore or minimize the importance of these experiences. We present a clinical model which incorporates aspects of milieu treatment, relationship-based daily interventions and elements of Jenkins’ invitational approach to working with men and boys who use violence as well as Wade’s response-based approach to counseling with victims and perpetrators of violence. The model also incorporates ideas based on Maruna’s research into recidivism and excuse-making. The purpose of the model is twofold: to be broad enough to structure an overall treatment strategy based on the assumption that successful treatment results from the cumulative effect of many interactions over time, and to be specific enough to guide staff in developing strategies for specific situations that typically arise in daily interaction with the youth. We use a case example format to illustrate how staff has utilized the model to engage youth in exploring both their experiences of violence in the family home and in developing new ways of thinking and talking about behavioural choices.     

A new consequence of Simpson's paradox: stable cooperation in one-shot prisoner's dilemma from populations of individualistic learners

Theories of choice in economics typically assume that interacting agents act individualistically and maximize their own utility. Specifically, game theory proposes that rational players should defect in one-shot prisoners' dilemmas (PD). Defection also appears to be the inevitable outcome for agents who learn by reinforcement of past choices, because whatever the other player does, defection leads to greater reinforcement on each trial. In a computer simulation and 4 experiments, the authors show that, apparently paradoxically, when players' choices are correlated by an exogenous factor (here, the cooperativeness of the specific PD chosen), people obtain greater average reinforcement for cooperating, which can sustain cooperation. This effect arises from a well-known statistical paradox, Simpson's paradox. The authors speculate that this effect may be relevant to aspects of real-world human cooperative behavior.     

From universal laws of cognition to specific cognitive models

The remarkable successes of the physical sciences have been built on highly general quantitative laws, which serve as the basis for understanding an enormous variety of specific physical systems. How far is it possible to construct universal principles in the cognitive sciences, in terms of which specific aspects of perception, memory, or decision making might be modelled? Following Shepard (e.g., 1987 ), it is argued that some universal principles may be attainable in cognitive science. Here, 2 examples are proposed: the simplicity principle (which states that the cognitive system prefers patterns that provide simpler explanations of available data); and the scale‐invariance principle, which states that many cognitive phenomena are independent of the scale of relevant underlying physical variables, such as time, space, luminance, or sound pressure. This article illustrates how principles may be combined to explain specific cognitive processes by using these principles to derive SIMPLE, a formal model of memory for serial order ( Brown, Neath, & Chater, 2007 ), and briefly mentions some extensions to models of identification and categorization. This article also considers the scope and limitations of universal laws in cognitive science.     

Using statistical smoothing to estimate the psycholinguistic acceptability of novel phrases

Native speakers of languages perceive differences in the acceptability of phrases even when those phrases are both grammatical and novel (previously unseen). We suggest that smoothing, a statistical technique used by natural language processing engineers, provides several candidate mechanisms for investigating this phenomenon. We describe the creation of a large data set of predictions from several smoothing algorithms about the acceptability of unseen grammatical phrases and a novel experimental method for the pairwise comparison of these models. We use this method to compare three smoothing methods and consider the results in light of the differences among the models. We argue that the data support the idea that similarity in this domain is best thought of as a form of asymmetric representational distortion and that the informational basis over which such estimates are made is broad, rather than narrow, as has been previously suggested.