Problem‐Solving Phase Transitions During Team Collaboration

Multiple theories of problem‐solving hypothesize that there are distinct qualitative phases exhibited during effective problem‐solving. However, limited research has attempted to identify when transitions between phases occur. We integrate theory on collaborative problem‐solving (CPS) with dynamical systems theory suggesting that when a system is undergoing a phase transition it should exhibit a peak in entropy and that entropy levels should also relate to team performance. Communications from 40 teams that collaborated on a complex problem were coded for occurrence of problem‐solving processes. We applied a sliding window entropy technique to each team's communications and specified criteria for (a) identifying data points that qualify as peaks and (b) determining which peaks were robust. We used multilevel modeling, and provide a qualitative example, to evaluate whether phases exhibit distinct distributions of communication processes. We also tested whether there was a relationship between entropy values at transition points and CPS performance. We found that a proportion of entropy peaks was robust and that the relative occurrence of communication codes varied significantly across phases. Peaks in entropy thus corresponded to qualitative shifts in teams’ CPS communications, providing empirical evidence that teams exhibit phase transitions during CPS. Also, lower average levels of entropy at the phase transition points predicted better CPS performance. We specify future directions to improve understanding of phase transitions during CPS, and collaborative cognition, more broadly.     

Naïve and Robust: Class‐Conditional Independence in Human Classification Learning

Humans excel in categorization. Yet from a computational standpoint, learning a novel probabilistic classification task involves severe computational challenges. The present paper investigates one way to address these challenges: assuming class‐conditional independence of features. This feature independence assumption simplifies the inference problem, allows for informed inferences about novel feature combinations, and performs robustly across different statistical environments. We designed a new Bayesian classification learning model (the dependence‐independence structure and category learning model, DISC‐LM) that incorporates varying degrees of prior belief in class‐conditional independence, learns whether or not independence holds, and adapts its behavior accordingly. Theoretical results from two simulation studies demonstrate that classification behavior can appear to start simple, yet adapt effectively to unexpected task structures. Two experiments—designed using optimal experimental design principles—were conducted with human learners. Classification decisions of the majority of participants were best accounted for by a version of the model with very high initial prior belief in class‐conditional independence, before adapting to the true environmental structure. Class‐conditional independence may be a strong and useful default assumption in category learning tasks.     

Intuitive Probabilities and the Limitation of Moral Imagination

There is a vast literature that seeks to uncover features underlying moral judgment by eliciting reactions to hypothetical scenarios such as trolley problems. These thought experiments assume that participants accept the outcomes stipulated in the scenarios. Across seven studies (N = 968), we demonstrate that intuition overrides stipulated outcomes even when participants are explicitly told that an action will result in a particular outcome. Participants instead substitute their own estimates of the probability of outcomes for stipulated outcomes, and these probability estimates in turn influence moral judgments. Our findings demonstrate that intuitive likelihoods are one critical factor in moral judgment, one that is not suspended even in moral dilemmas that explicitly stipulate outcomes. Features thought to underlie moral reasoning, such as intention, may operate, in part, by affecting the intuitive likelihood of outcomes, and, problematically, moral differences between scenarios may be confounded with non‐moral intuitive probabilities.     

Generalized Information Theory Meets Human Cognition: Introducing a Unified Framework to Model Uncertainty and Information Search

Searching for information is critical in many situations. In medicine, for instance, careful choice of a diagnostic test can help narrow down the range of plausible diseases that the patient might have. In a probabilistic framework, test selection is often modeled by assuming that people's goal is to reduce uncertainty about possible states of the world. In cognitive science, psychology, and medical decision making, Shannon entropy is the most prominent and most widely used model to formalize probabilistic uncertainty and the reduction thereof. However, a variety of alternative entropy metrics (Hartley, Quadratic, Tsallis, Rényi, and more) are popular in the social and the natural sciences, computer science, and philosophy of science. Particular entropy measures have been predominant in particular research areas, and it is often an open issue whether these divergences emerge from different theoretical and practical goals or are merely due to historical accident. Cutting across disciplinary boundaries, we show that several entropy and entropy reduction measures arise as special cases in a unified formalism, the Sharma–Mittal framework. Using mathematical results, computer simulations, and analyses of published behavioral data, we discuss four key questions: How do various entropy models relate to each other? What insights can be obtained by considering diverse entropy models within a unified framework? What is the psychological plausibility of different entropy models? What new questions and insights for research on human information acquisition follow? Our work provides several new pathways for theoretical and empirical research, reconciling apparently conflicting approaches and empirical findings within a comprehensive and unified information‐theoretic formalism.     

Heidegger on Expression: Formal Indication and Destruction in the Early Freiburg Lectures

Of all the methodological terms used by Heidegger in the early Freiburg period, few have attracted less consensus than Formal Indication. With its relation to the earliest lecture series, critical debate has tended to focus on the extent to which this concept defines the difference between Husserlian and Heideggerian phenomenology. The argument of this paper is that Formal Indication is best understood in its relation to Heidegger’s other key methodological term from this period, Phenomenological Destruction. Not only do (i) both concepts grow out of the same problem set, but (ii) they act in a limited sense as counter-movements to one another. Considered together, I argue, they make up Heidegger’s response to the problem of language as expressed by Paul Natorp, and first dealt with in the Kriegsnotsemester in 1919.     

Further evidence of renewal in automatically maintained behavior

Renewal is a relapse phenomenon that refers to the recurrence of a previously reduced behavior following a change in stimulus conditions. Muething et al. (2022) examined the phenomenology of renewal among individuals with automatically maintained challenging behavior treated at an outpatient clinic. We replicated their findings by retrospectively examining renewal across various topographies of automatically maintained behavior treated at an inpatient hospital, and we extended their work by also examining differences across subtypes of automatically maintained self-injurious behavior. The prevalence of renewal was comparable to that observed by Muething et al., supporting the notion that automatically maintained challenging behavior is susceptible to relapse phenomena. Furthermore, renewal was twice as likely to occur for individuals with Subtype 2 versus Subtype 1 self-injurious behavior, providing additional evidence of behavioral differentiation between subtypes. Our findings suggest that even after apparent stability in treatment, practitioners should remain vigilant for the recurrence of automatically maintained behavior during generalization.     

Entrapment,temptation and virtue testing

Philosophical Studies - We address the ethics of scenarios in which one party (the ‘agent’) entraps, intentionally tempts or intentionally tests the virtue of another (the...     

Development and psychometric evaluation of the Male Body Attitudes Scale (MBAS)

A measure of men's attitudes toward their body (MBAS) was developed and evaluated via three independent samples of college men. In Studies 1 and 2, factor analyses determined and cross-validated the MBAS's underlying structure. Three factors emerged from the items: muscularity, low body fat, and height. Studies 1 and 2 provided construct (i.e., convergent, concurrent, and discriminant) validity evidence for the MBAS total scale and subscales; they were related or not related as expected to drive for muscularity, body esteem, internalization of the muscular ideal, pressures for muscularity, pressures for thinness, self-esteem, body comparison, eating disorder symptomatology, and impression management. Study 3 revealed that the MBAS total score and subscale scores were stable over a 2-week period. The internal consistency reliabilities for the total score and subscale scores were high across all three studies. The MBAS should prove useful for researchers and clinicians interested in men's body image assessment.