Adding a Conditional to Kripke’s Theory of Truth

Kripke’s theory of truth (Kripke, The Journal of Philosophy72(19), 690–716; 1975) has been very successful but shows well-known expressive difficulties; recently, Field has proposed to overcome them by adding a new conditional connective to it. In Field’s theories, desirable conditional and truth-theoretic principles are validated that Kripke’s theory does not yield. Some authors, however, are dissatisfied with certain aspects of Field’s theories, in particular the high complexity. I analyze Field’s models and pin down some reasons for discontent with them, focusing on the meaning of the new conditional and on the status of the principles so successfully recovered. Subsequently, I develop a semantics that improves on Kripke’s theory following Field’s program of adding a conditional to it, using some inductive constructions that include Kripke’s one and feature a strong evaluation for conditionals. The new theory overcomes several problems of Kripke’s one and, although weaker than Field’s proposals, it avoids the difficulties that affect them; at the same time, the new theory turns out to be quite simple. Moreover, the new construction can be used to model various conceptions of what a conditional connective is, in ways that are precluded to both Kripke’s and Field’s theories.     

Improving Psychological Measurement: Does It Make a Difference? A Comment on Nesselroade and Molenaar (2016)

Nesselroade and Molenaar advocate the use of an idiographic filter approach. This is a fixed-effects approach, which may limit the number of individuals that can be simultaneously modeled, and it is not clear how to model the presence of subpopulations. Most important, Nesselroade and Molenaar's proposal appears to be best suited for modeling long time series on a few variables for a few individuals. Long time series are not common in psychological applications. Can it be applied to the usual longitudinal data we face? These are characterized by short time series (four to five points in time), hundreds of individuals, and dozens of variables. If so, what do we gain? Applied settings most often involve between-individual decisions. I conjecture that their approach will not outperform common, simpler, methods. However, when intraindividual decisions are involved, their approach may have an edge.     

Factor analysis models via I-divergence optimization

Given a positive definite covariance matrix \(\widehat{\Sigma }\) of dimension n, we approximate it with a covariance of the form \(HH^\top +D\), where H has a prescribed number \(k<n\) of columns and \(D>0\) is diagonal. The quality of the approximation is gauged by the I-divergence between the zero mean normal laws with covariances \(\widehat{\Sigma }\) and \(HH^\top +D\), respectively. To determine a pair (H, D) that minimizes the I-divergence we construct, by lifting the minimization into a larger space, an iterative alternating minimization algorithm (AML) à la Csiszár–Tusnády. As it turns out, the proper choice of the enlarged space is crucial for optimization. The convergence of the algorithm is studied, with special attention given to the case where D is singular. The theoretical properties of the AML are compared to those of the popular EM algorithm for exploratory factor analysis. Inspired by the ECME (a Newton–Raphson variation on EM), we develop a similar variant of AML, called ACML, and in a few numerical experiments, we compare the performances of the four algorithms.     

Perceptual and affective mechanisms in facial expression recognition: An integrative review

Facial expressions of emotion involve a physical component of morphological changes in a face and an affective component conveying information about the expresser’s internal feelings. It remains unresolved how much recognition and discrimination of expressions rely on the perception of morphological patterns or the processing of affective content. This review of research on the role of visual and emotional factors in expression recognition reached three major conclusions. First, behavioral, neurophysiological, and computational measures indicate that basic expressions are reliably recognized and discriminated from one another, albeit the effect may be inflated by the use of prototypical expression stimuli and forced-choice responses. Second, affective content along the dimensions of valence and arousal is extracted early from facial expressions, although this coarse affective representation contributes minimally to categorical recognition of specific expressions. Third, the physical configuration and visual saliency of facial features contribute significantly to expression recognition, with “emotionless” computational models being able to reproduce some of the basic phenomena demonstrated in human observers. We conclude that facial expression recognition, as it has been investigated in conventional laboratory tasks, depends to a greater extent on perceptual than affective information and mechanisms.     

There’s More Than Catastrophizing in Chronic Pain: Low Frustration Tolerance and Self-Downing Also Predict Mental Health in Chronic Pain Patients

Among the potential range of irrational beliefs that could be used as predictors of physical and mental health, catastrophizing is the process that has received most attention in chronic pain research. Other irrational processes such as demandingness, low frustration tolerance, and self-downing have rarely been studied. The goal of this study was to explore whether this wider range of beliefs is associated with health in chronic pain patients beyond catastrophizing. A total of 492 chronic pain patients completed a measure of irrational beliefs, a measure of physical and mental health, and a numerical rating scale designed to assess pain intensity and interference. Irrational processes were more strongly associated with mental than with physical health. Low frustration tolerance and self-downing were found to be significantly related to mental health even after controlling for the effect of catastrophizing. Processes other than catastrophizing appear to have potentially important relationships with the mental health of people with chronic pain. These results may offer new intervention targets for practitioners.     

Not All Alike: The Distinctive Impact of Voluntary and Involuntary Effort on Stress and Fatigue

Nowadays, little evidence exists on how variations in effort affect worker health, such as stress and fatigue, two important and undesirable outcomes for workers. Then, this paper analyses the impact of different dimensions of effort on stress and fatigue. To do so we use past literature to links the different effort dimensions on employee health. Concretely, the frameworks used in the paper are the one developed by Karasek and Theorell (1990), according to which the different combinations of work demands, competences in decision making and social support determine the stress employees suffer; and the effort-reward imbalance model (ERI Model) of Siegrist (Psychology 1:27–41, 1996). This provides a more sensitive model of stress, as it uses a combination of extrinsic effort and intrinsic effort as predictors of stress. Building on these theoretical models of job stress we argue that one main source of employee stress and fatigue is employee effort. Using a representative Spanish data set, our study reveals that different dimensions of effort have different consequences for workers. Whereas involuntary effort increases both stress and fatigue, voluntary effort entails a decrease in both.     

Orders to Shoot (a Camera): Effects of Ostracism on Obedience

Research suggests that ostracism increases susceptibility to indirect forms of social influence (e.g., conformity). Yet, no study to date has explored whether the effects of ostracism extend to the most direct form of social influence—obedience. We investigated whether ostracized individuals would be more likely to obey a direct command to do something effortful in uncomfortable conditions. Participants (N = 62) were randomly assigned to be included or ostracized in Cyberball, or assigned to a control condition. They were then approached by the experimenter and commanded to go outside when temperatures were below 30°F and take 39 unique and creative photographs in the cold of winter. Ostracized participants were more likely to obey the experimenter’s command to be creative when taking photographs. No differences in obedience emerged between the inclusion and the control condition. We provided evidence completing the social influence “trifecta”: ostracism increases susceptibility to conformity, compliance, and now, obedience.     

Facial expression recognition in peripheral versus central vision: role of the eyes and the mouth

This study investigated facial expression recognition in peripheral relative to central vision, and the factors accounting for the recognition advantage of some expressions in the visual periphery. Whole faces or only the eyes or the mouth regions were presented for 150 ms, either at fixation or extrafoveally (2.5° or 6°), followed by a backward mask and a probe word. Results indicated that (a) all the basic expressions were recognized above chance level, although performance in peripheral vision was less impaired for happy than for non-happy expressions, (b) the happy face advantage remained when only the mouth region was presented, and (c) the smiling mouth was the most visually salient and most distinctive facial feature of all expressions. This suggests that the saliency and the diagnostic value of the smile account for the advantage in happy face recognition in peripheral vision. Because of saliency, the smiling mouth accrues sensory gain and becomes resistant to visual degradation due to stimulus eccentricity, thus remaining accessible extrafoveally. Because of diagnostic value, the smile provides a distinctive single cue of facial happiness, thus bypassing integration of face parts and reducing susceptibility to breakdown of configural processing in peripheral vision.     

Uncovering unknown unknowns: Towards a Baconian approach to management decision-making

Bayesian decision theory and inference have left a deep and indelible mark on the literature on management decision-making. There is however an important issue that the machinery of classical Bayesianism is ill equipped to deal with, that of “unknown unknowns” or, in the cases in which they are actualised, what are sometimes called “Black Swans”. This issue is closely related to the problems of constructing an appropriate state space under conditions of deficient foresight about what the future might hold, and our aim is to develop a theory and some of the practicalities of state space elaboration that addresses these problems. Building on ideas originally put forward by Bacon (1620), we show how our approach can be used to build and explore the state space, how it may reduce the extent to which organisations are blindsided by Black Swans, and how it ameliorates various well-known cognitive biases.