Kant on the bounds of promise making: A Mendelssohnian account

In this essay, I argue that Kant holds one of the following two theses: A promise to do something that violates the moral law (a) is impossible or (b) can be conscientiously broken. On this issue, I put Kant in dialogue with Moses Mendelssohn in order to show, against recent suggestions, that Kant's account is distinctly Mendelssohnian.     

Crime location choices: A geographical analysis of German serial killers

The present study examined whether there are different processes operating in the crime location choices between body‐disposing and non‐body‐disposing serial killers and between sexual serial killers and acquisitive serial killers. A sample of 49 series of solved German serial killings is used to examine the differences in travelled distances between these groups of killers. Nonparametric tests revealed that body‐disposing and non‐body‐disposing serial killers and sexual and acquisitive serial killers did not constitute subgroups of serial killers regarding their spatial behaviour. The results suggest that the compared groups are subjected to the same factors that influence their travelled distances. Furthermore, the possible role of planning and anticipated emotions in crime location choices of serial killers is discussed, as well as the limitations of the study and recommendations for future research.     

The Performance Appraisal Milieu: A Multilevel Analysis of Context Effects in Performance Ratings

Purpose

The purpose of this study was to take an inductive approach in examining the extent to which organizational contexts represent significant sources of variance in supervisor performance ratings, and to explore various factors that may explain contextual rating variability.

Design/Methodology/Approach

Using archival field performance rating data from a large state law enforcement organization, we used a multilevel modeling approach to partition the variance in ratings due to ratees, raters, as well as rating contexts.

Findings

Results suggest that much of what may often be interpreted as idiosyncratic rater variance, may actually reflect systematic rating variability across contexts. In addition, performance-related and non-performance factors including contextual rating tendencies accounted for significant rating variability.

Implications

Supervisor ratings represent the most common approach for measuring job performance, and understanding the nature and sources of rating variability is important for research and practice. Given the many uses of performance rating data, our findings suggest that continuing to identify contextual sources of variability is particularly important for addressing criterion problems, and improving ratings as a form of performance measurement.

Originality/Value

Numerous performance appraisal models suggest the importance of context; however, previous research had not partitioned the variance in supervisor ratings due to omnibus context effects in organizational settings. The use of a multilevel modeling approach allowed the examination of contextual influences, while controlling for ratee and rater characteristics.

     

A probabilistic model of cross-categorization

Most natural domains can be represented in multiple ways: we can categorize foods in terms of their nutritional content or social role, animals in terms of their taxonomic groupings or their ecological niches, and musical instruments in terms of their taxonomic categories or social uses. Previous approaches to modeling human categorization have largely ignored the problem of cross-categorization, focusing on learning just a single system of categories that explains all of the features. Cross-categorization presents a difficult problem: how can we infer categories without first knowing which features the categories are meant to explain? We present a novel model that suggests that human cross-categorization is a result of joint inference about multiple systems of categories and the features that they explain. We also formalize two commonly proposed alternative explanations for cross-categorization behavior: a features-first and an objects-first approach. The features-first approach suggests that cross-categorization is a consequence of attentional processes, where features are selected by an attentional mechanism first and categories are derived second. The objects-first approach suggests that cross-categorization is a consequence of repeated, sequential attempts to explain features, where categories are derived first, then features that are poorly explained are recategorized. We present two sets of simulations and experiments testing the models’ predictions about human categorization. We find that an approach based on joint inference provides the best fit to human categorization behavior, and we suggest that a full account of human category learning will need to incorporate something akin to these capabilities.     

Learning to learn causal models

Learning to understand a single causal system can be an achievement, but humans must learn about multiple causal systems over the course of a lifetime. We present a hierarchical Bayesian framework that helps to explain how learning about several causal systems can accelerate learning about systems that are subsequently encountered. Given experience with a set of objects, our framework learns a causal model for each object and a causal schema that captures commonalities among these causal models. The schema organizes the objects into categories and specifies the causal powers and characteristic features of these categories and the characteristic causal interactions between categories. A schema of this kind allows causal models for subsequent objects to be rapidly learned, and we explore this accelerated learning in four experiments. Our results confirm that humans learn rapidly about the causal powers of novel objects, and we show that our framework accounts better for our data than alternative models of causal learning.     

Physician and patient communication training in primary care: effects on participation and satisfaction

OBJECTIVE: To assess the effects of a communication skills training program for physicians and patients. DESIGN: A randomized experiment to improve physician communication skills was assessed 1 and 6 months after a training intervention; patient training to be active participants was assessed after 1 month. Across three primary medical care settings, 156 physicians treating 2,196 patients were randomly assigned to control group or one of three conditions (physician, patient, or both trained). MAIN OUTCOME MEASURES: Patient satisfaction and perceptions of choice, decision-making, information, and lifestyle counseling; physicians' satisfaction and stress; and global ratings of the communication process. RESULTS: The following significant (p < .05) effects emerged: physician training improved patients' satisfaction with information and overall care; increased willingness to recommend the physician; increased physicians' counseling (as reported by patients) about weight loss, exercise, and quitting smoking and alcohol; increased physician satisfaction with physical exam detail; increased independent ratings of physicians' sensitive, connected communication with their patients, and decreased physician satisfaction with interpersonal aspects of professional life. Patient training improved physicians' satisfaction with data collection; if only physician or patient was trained, physician stress increased and physician satisfaction decreased. CONCLUSION: Implications for improving physician-patient relationship outcomes through communication skills training are discussed.     

A test of the peak-end rule with extended autobiographical events

Forty-nine students went on vacation for an average of 7 days and sent daily text messages about the happiness they had experienced over the previous 24 h. After their vacation, they were questioned on the overall happiness they had experienced and were asked to recall the daily record of their happiness. The duration of the vacation had no effect on the subsequent evaluations, and participants were not able to recall the detail of their day-to-day changes in happiness. A number of summary measures provided reasonable prediction of the recalled overall happiness of the vacation. The peak-end rule was not an outstandingly good predictor. Overall, the results indicate much reconstruction of the affective states.