Public discourse is often caustic and conflict-filled. This trend seems to be particularly evident when the content of such discourse is around moral issues (broadly defined) and when the discourse occurs on social media. Several explanatory mechanisms for such conflict have been explored in recent psychological and social-science literatures. The present work sought to examine a potentially novel explanatory mechanism defined in philosophical literature: Moral Grandstanding. According to philosophical accounts, Moral Grandstanding is the use of moral talk to seek social (...) status. For the present work, we conducted six studies, using two undergraduate samples (Study 1, N = 361; Study 2, N = 356); a sample matched to U.S. norms for age, gender, race, income, Census region (Study 3, N = 1,063); a YouGov sample matched to U.S. demographic norms (Study 4, N = 2,000); and a brief, one-month longitudinal study of Mechanical Turk workers in the U.S. (Study 5, Baseline N = 499, follow-up n = 296), and a large, one-week YouGov sample matched to U.S. demographic norms (Baseline N = 2,519, follow-up n = 1,776). Across studies, we found initial support for the validity of Moral Grandstanding as a construct. Specifically, moral grandstanding motivation was associated with status-seeking personality traits, as well as greater political and moral conflict in daily life. (shrink)

The present work posits that social motives, particularly status seeking in the form of moral grandstanding, are likely at least partially to blame for elevated levels of affective polarization and ideological extremism in the U.S. In Study 1, results from both undergraduates (N = 981; Mean age = 19.4; SD = 2.1; 69.7% women) and a cross-section of U.S. adults matched to 2010 census norms (N = 1,063; Mean age = 48.20, SD = 16.38; 49.8% women) indicated that prestige-motived grandstanding (...) was consistently and robustly related to more extreme ideological views on a variety of issues. In Study 2, results from a weighted, nationally-representative cross-section of U.S. adults (N = 2,519; Mean age = 47.5, SD = 17.8; 51.4% women) found that prestige motivated grandstanding was reliably related to both ideological extremism and affective polarization. (shrink)

Yarkoni has argued that psychology is facing a generalizability crisis, but the real cost of this crisis is obscured by a focus on topics from psychology's most academic subfields. Psychology is also filled with applied subfields, and it is within those subfields – especially clinical science – where the cost of a generalizability crisis will be most severe.

The present study aimed to understand how status-oriented individual differences such as narcissistic antagonism, narcissistic extraversion, and moral grandstanding motivations may have longitudinally predicted both behavioral and social media responses during the early stages of the COVID-19 pandemic. Via YouGov, a nationally representative sample of U.S. adults was recruited in August of 2019 (N = 2,519; Mage = 47.5, SD = 17.8; 51.4% women) and resampled in May of 2020, (N = 1,533). Results indicated that baseline levels of narcissistic antagonism (...) were associated with lower levels of social distancing and lower compliance with public health recommended behaviors. Similarly, dominance oriented moral grandstanding motivations predicted greater conflict with others over COVID-19, greater engagement in status-oriented social media behaviors about COVID-19, and lower levels of social distancing. (shrink)

Shepard has argued that a universal law should govern generalization across different domains of perception and cognition, as well as across organisms from different species or even different planets. Starting with some basic assumptions about natural kinds, he derived an exponential decay function as the form of the universal generalization gradient, which accords strikingly well with a wide range of empirical data. However, his original formulation applied only to the ideal case of generalization from a single encountered stimulus to a (...) single novel stimulus, and for stimuli that can be represented as points in a continuous metric psychological space. Here we recast Shepard's theory in a more general Bayesian framework and show how this naturally extends his approach to the more realistic situation of generalizing from multiple consequential stimuli with arbitrary representational structure. Our framework also subsumes a version of Tversky's set-theoretic model of similarity, which is conventionally thought of as the primary alternative to Shepard's continuous metric space model of similarity and generalization. This unification allows us not only to draw deep parallels between the set-theoretic and spatial approaches, but also to significantly advance the explanatory power of set-theoretic models. Key Words: additive clustering; Bayesian inference; categorization; concept learning; contrast model; features; generalization; psychological space; similarity. (shrink)

In order to receive controlled pain medications for chronic non-oncologic pain, patients often must sign a “narcotic contract” or “opioid treatment agreement” in which they promise not to give pills to others, use illegal drugs, or seek controlled medications from health care providers. In addition, they must agree to use the medication as prescribed and to come to the clinic for drug testing and pill counts. Patients acknowledge that if they violate the opioid treatment agreement, they may no longer receive (...) controlled medications. OTAs have been widely implemented since they were recommended by multiple national bodies to decrease misuse and diversion of narcotic medications. But critics argue that OTAs are ethically suspect, if not unethical, and should be used with extreme care if at all. We agree that OTAs pose real dangers and must be implemented carefully. But we also believe that the most serious criticisms stem from a mistaken understanding of OTAs’ purpose and ethical basis. (shrink)

In this note we develop a method for constructing finite totally-ordered m-zeroids and prove that there exists a categorical equivalence between the category of finite, totally-ordered m-zeroids and the category of pseudo Łukasiewicz-like implicators.

This collection brings together prominent thinkers from numerous disciplines to address the legacy of Gillian Rose for political theology today. Rose’s work is notorious for its eclectic range, difficult style, and iconoclastic defiance of the conventions of postmodern critical theory. The theologians, religious scholars, ethicists, and theorists in this collection discuss Rose’s relationship to such topics as the Frankfurt School, social theory, feminism, literature, law, Hegel, Kant, and psychoanalysis. They situate her work within the wider context of political theology, as (...) it is understood in religious studies and continental philosophy. Though attentive to the theoretical issues raised by Rose’s work, these essays are also engage the role that work may play in political action today, examining issues such as refugee immigration in Europe, the rise of nationalism, and anticapitalist political organizing. The collection is a vital contribution to the rising body of literature on Rose and her importance to political philosophy, ethics, and theology, but it will also serve as an important orienting guide for readers new to Rose’s work and its demanding style. (shrink)

Disruptive societal changes following from emerging science and technology have recently led to a growing interest in developing ethical frameworks. Responsible Research and Innovation (RRI) is such a framework that aims to improve the relationship between science and society. Now a decade after its conceptualization, it still seems to suffer from conceptual unclarity and lack of implementation. Since responsibility in research and innovation practice remains as important as ever, we propose to revive the normative potential of RRI by approaching it (...) as a matter of collective democratic experimentation. To further develop this approach, we propose a pragmatist conceptualization inspired by John Dewey, his work on democracy as an ethical way of life and his attention to the contextual nature of responsibility. Furthermore, we show how his interest in social inquiring publics provides a particularly apt foothold from which to operationalize collective democratic experimentation with RRI. We will illustrate the utility of this approach, with specific attention to the social, experimental and public character of social inquiry, by connecting it to the recent call to use social labs methodology to experiment with RRI. From this we draw lessons for future collective democratic experimentation with responsibility in research and innovation practice. (shrink)

We present statistical analyses of the large‐scale structure of 3 types of semantic networks: word associations, WordNet, and Roget's Thesaurus. We show that they have a small‐world structure, characterized by sparse connectivity, short average path lengths between words, and strong local clustering. In addition, the distributions of the number of connections follow power laws that indicate a scale‐free pattern of connectivity, with most nodes having relatively few connections joined together through a small number of hubs with many connections. These regularities (...) have also been found in certain other complex natural networks, such as the World Wide Web, but they are not consistent with many conventional models of semantic organization, based on inheritance hierarchies, arbitrarily structured networks, or high‐dimensional vector spaces. We propose that these structures reflect the mechanisms by which semantic networks grow. We describe a simple model for semantic growth, in which each new word or concept is connected to an existing network by differentiating the connectivity pattern of an existing node. This model generates appropriate small‐world statistics and power‐law connectivity distributions, and it also suggests one possible mechanistic basis for the effects of learning history variables (age of acquisition, usage frequency) on behavioral performance in semantic processing tasks. (shrink)

People are adept at inferring novel causal relations, even from only a few observations. Prior knowledge about the probability of encountering causal relations of various types and the nature of the mechanisms relating causes and effects plays a crucial role in these inferences. We test a formal account of how this knowledge can be used and acquired, based on analyzing causal induction as Bayesian inference. Five studies explored the predictions of this account with adults and 4-year-olds, using tasks in which (...) participants learned about the causal properties of a set of objects. The studies varied the two factors that our Bayesian approach predicted should be relevant to causal induction: the prior probability with which causal relations exist, and the assumption of a deterministic or a probabilistic relation between cause and effect. Adults’ judgments (Experiments 1, 2, and 4) were in close correspondence with the quantitative predictions of the model, and children’s judgments (Experiments 3 and 5) agreed qualitatively with this account. (shrink)

Good communication is critical to the practice of medicine. This is particularly true when outcomes are unpredictable and/or patients lack the capacity to participate in medical decision making. Disputes may develop that cannot be addressed using basic communication skills. Conflict of this nature can burden patients, families, and medical staff and may result in increased suffering for all parties. Many physicians lack the necessary communication tools to handle difficult conversations. Training in bioethics mediation provides physicians with skills that can promote (...) healing by empowering participants to engage in effective discourse and break down barriers to find common ground. Mediation training for physicians can expand their capacity to connect with patients and enhance their ability to identify potential conflict early on, in order to collaborate more effectively. Competency in the processes of negotiation and conflict resolution should therefore be seen as essential elements of medical training. (shrink)

We present statistical analyses of the large‐scale structure of 3 types of semantic networks: word associations, WordNet, and Roget's Thesaurus. We show that they have a small‐world structure, characterized by sparse connectivity, short average path lengths between words, and strong local clustering. In addition, the distributions of the number of connections follow power laws that indicate a scale‐free pattern of connectivity, with most nodes having relatively few connections joined together through a small number of hubs with many connections. These regularities (...) have also been found in certain other complex natural networks, such as the World Wide Web, but they are not consistent with many conventional models of semantic organization, based on inheritance hierarchies, arbitrarily structured networks, or high‐dimensional vector spaces. We propose that these structures reflect the mechanisms by which semantic networks grow. We describe a simple model for semantic growth, in which each new word or concept is connected to an existing network by differentiating the connectivity pattern of an existing node. This model generates appropriate small‐world statistics and power‐law connectivity distributions, and it also suggests one possible mechanistic basis for the effects of learning history variables (age of acquisition, usage frequency) on behavioral performance in semantic processing tasks. (shrink)

Background:Ethical conflict and subsequent nurse moral distress and burnout are common in the intensive care unit (ICU). There is a gap in our understanding of nurses’ perceptions of how organizational resources support them in addressing ethical conflict in the intensive care unit.Research question/objectives/methods:The aim of this qualitative, descriptive study was to explore how nurses experience ethical conflict and use organizational resources to support them as they address ethical conflict in their practice.Participants and research context:Responses to two open-ended questions were collected (...) from critical care nurses working in five intensive care units at a large, academic medical center in the Midwestern region of the United States.Ethical considerations:This study was approved by the Institutional Review Board at the organization where the study took place.Findings:Three main interwoven themes emerged: nurses perceive (1) intensive care unit culture, practices, and organizational priorities contribute to patient suffering; (2) nurses are marginalized during ethical conflict in the intensive care unit; and (3) organizational resources have the potential to reduce nurse moral distress. Nurses identified ethics education, interprofessional dialogue, and greater involvement of nurses as important strategies to improve the management of ethical conflict.Discussion:Ethical conflict related to healthcare system challenges is intrinsic in the daily practice of critical care nurses. Nurses want to be engaged in discussions about their perspectives on ethical conflict and play an active role in addressing ethical conflict in their practice. Organizational resources that support nurses are vital to the resolution of ethical conflict.Conclusion:These findings can inform the development of interventions that aim to proactively and comprehensively address ethical conflict in the intensive care unit to reduce nurse moral distress and improve the delivery of patient and family care. (shrink)

We applaud Millikan's psychologically plausible version of the causal theory of reference. Her proposal offers a significant clarification of the much-debated relation between concepts and beliefs, and suggests positive directions for future empirical studies of conceptual development. However, Millikan's revision of the causal theory may leave us with no generally satisfying account of concept individuation in the mind.

In order to account for how children can generalize words beyond a very limited set of labeled examples, Bloom's proposal of word learning requires two extensions: a better understanding of the “general learning and memory abilities” involved, and a principled framework for integrating multiple conflicting constraints on word meaning. We propose a framework based on Bayesian statistical inference that meets both of those needs.

We present statistical analyses of the large‐scale structure of 3 types of semantic networks: word associations, WordNet, and Roget's Thesaurus. We show that they have a small‐world structure, characterized by sparse connectivity, short average path lengths between words, and strong local clustering. In addition, the distributions of the number of connections follow power laws that indicate a scale‐free pattern of connectivity, with most nodes having relatively few connections joined together through a small number of hubs with many connections. These regularities (...) have also been found in certain other complex natural networks, such as the World Wide Web, but they are not consistent with many conventional models of semantic organization, based on inheritance hierarchies, arbitrarily structured networks, or high‐dimensional vector spaces. We propose that these structures reflect the mechanisms by which semantic networks grow. We describe a simple model for semantic growth, in which each new word or concept is connected to an existing network by differentiating the connectivity pattern of an existing node. This model generates appropriate small‐world statistics and power‐law connectivity distributions, and it also suggests one possible mechanistic basis for the effects of learning history variables (age of acquisition, usage frequency) on behavioral performance in semantic processing tasks. (shrink)

Over half a century ago, George Zipf observed that more frequent words tend to be older. Corpus studies since then have confirmed this pattern, with more frequent words being replaced and regularized less often than less frequent words. Two main hypotheses have been proposed to explain this: that frequent words change less because selection against innovation is stronger at higher frequencies, or that they change less because stochastic drift is stronger at lower frequencies. Here, we report the first experimental test (...) of these hypotheses. Participants were tasked with learning a miniature language consisting of two nouns and two plural markers. Nouns occurred at different frequencies and were subjected to treatments that varied drift and selection. Using a model that accounts for participant heterogeneity, we measured the rate of noun regularization, the strength of selection, and the strength of drift in participant responses. Results suggest that drift alone is sufficient to generate the elevated rate of regularization we observed in low‐frequency nouns, adding to a growing body of evidence that drift may be a major driver of language change. (shrink)

A long history of research has revealed many neurophysiological changes and concomitant behavioral impacts of sleep deprivation, sleep restriction, and circadian rhythms. Little research, however, has been conducted in the area of computational cognitive modeling to understand the information processing mechanisms through which neurobehavioral factors operate to produce degradations in human performance. Our approach to understanding this relationship is to link predictions of overall cognitive functioning, or alertness, from existing biomathematical models to information processing parameters in a cognitive architecture, leveraging (...) the strengths from each to develop a more comprehensive explanation. The integration of these methodologies is used to account for changes in human performance on a sustained attention task across 88 h of total sleep deprivation. The integrated model captures changes due to time awake and circadian rhythms, and it also provides an account for underlying changes in the cognitive processes that give rise to those effects. The results show the potential for developing mechanistic accounts of how fatigue impacts cognition, and they illustrate the increased explanatory power that is possible by combining theoretical insights from multiple methodologies. (shrink)