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)
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 many learning or inference tasks human behavior approximates that of a Bayesian ideal observer, suggesting that, at some level, cognition can be described as Bayesian inference. However, a number of findings have highlighted an intriguing mismatch between human behavior and standard assumptions about optimality: People often appear to make decisions based on just one or a few samples from the appropriate posterior probability distribution, rather than using the full distribution. Although sampling-based approximations are a common way to implement Bayesian (...) inference, the very limited numbers of samples often used by humans seem insufficient to approximate the required probability distributions very accurately. Here, we consider this discrepancy in the broader framework of statistical decision theory, and ask: If people are making decisions based on samples—but as samples are costly—how many samples should people use to optimize their total expected or worst-case reward over a large number of decisions? We find that under reasonable assumptions about the time costs of sampling, making many quick but locally suboptimal decisions based on very few samples may be the globally optimal strategy over long periods. These results help to reconcile a large body of work showing sampling-based or probability matching behavior with the hypothesis that human cognition can be understood in Bayesian terms, and they suggest promising future directions for studies of resource-constrained cognition. (shrink)
We provide experimental evidence that subjects blame others based on events they are not responsible for. In our experiment an agent chooses between a lottery and a safe asset; payment from the chosen option goes to a principal who then decides how much to allocate between the agent and a third party. We observe widespread blame: regardless of their choice, agents are blamed by principals for the outcome of the lottery, an event they are not responsible for. We provide an (...) explanation of this apparently irrational behavior with a delegated-expertise principal-agent model, the subjects’ salient perturbation of the environment. (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.
Hierarchical Bayesian models (HBMs) provide an account of Bayesian inference in a hierarchically structured hypothesis space. Scientific theories are plausibly regarded as organized into hierarchies in many cases, with higher levels sometimes called ‘paradigms’ and lower levels encoding more specific or concrete hypotheses. Therefore, HBMs provide a useful model for scientific theory change, showing how higher‐level theory change may be driven by the impact of evidence on lower levels. HBMs capture features described in the Kuhnian tradition, particularly the idea that (...) higher‐level theories guide learning at lower levels. In addition, they help resolve certain issues for Bayesians, such as scientific preference for simplicity and the problem of new theories. *Received July 2009; revised October 2009. †To contact the authors, please write to: Leah Henderson, Massachusetts Institute of Technology, 77 Massachusetts Avenue, 32D‐808, Cambridge, MA 02139; e‐mail: [email protected] (shrink)
Rogers & McClelland (R&M) criticize models that rely on structured representations such as categories, taxonomic hierarchies, and schemata, but we suggest that structured models can account for many of the phenomena that they describe. Structured approaches and parallel distributed processing (PDP) approaches operate at different levels of analysis, and may ultimately be compatible, but structured models seem more likely to offer immediate insight into many of the issues that R&M discuss.