Let's Not Do Responsibility Skepticism

I argue for three conclusions. First, responsibility skeptics are committed to the position that the criminal justice system should adopt a universal nonresponsibility excuse. Second, a universal nonresponsibility excuse would diminish some of our most deeply held values, further dehumanize criminals, exacerbate mass incarceration, and cause an even greater number of innocent people (nonwrongdoers) to be punished. Third, while Saul Smilansky's ‘illusionist’ response to responsibility skeptics – that even if responsibility skepticism is correct, society should maintain a responsibility-realist/retributivist criminal justice system – is generally compelling, it would not work if a majority of society were to convert, theoretically and psychologically, to responsibility skepticism. In this (highly improbable) scenario, and only in this (highly improbable) scenario, the criminal justice system would need to be reformed in such a way that it aligned with the majority's responsibility-skeptical beliefs and attitudes.     

Effects of processing speed on cerebral asymmetry for left- and right-oriented faces

A free-vision chimeric facial emotion judgment task and a tachistoscopic face-recognition reaction time task were administered to 20 male right-handed subjects. The tachistoscopic task involved judgments of whether a poser in the centrally presented full-face photograph was the same or different poser than in a profile photograph presented in the left or right visual field (LVF, RVF). The free-vision task was that used by J. Levy, W. Heller, M. Banich, and L. Burton (1983, Brain and Cognition, 2, 404-419) and involved judging which of two chimeric faces appeared happier, in which the two chimeras were mirror images of each other and each chimera consisted of a smiling half-face joined at the midline to a neutral half-face of the same poser. For the tachistoscopic task, subjects were divided into groups of Fast and Slow responders by a median split of the mean reaction times. For the Fast subjects, judgments were faster in the LVF than in the RVF, and there was a significant interaction between visual field and profile direction, such that responses were faster for medially oriented profiles; i.e., LVF responses were faster for right-facing than for left-facing profiles, with the reverse relationship in the RVF. The Slow responders did not show these effects. Only the Fast group showed the bias for choosing the chimera with the smile on the left as happier, and mean response speed and the LVF advantage on the tachistoscopic test correlated with the leftward bias on the free-vision task for all subjects combined. It was suggested that overall response speed on the face-matching task reflected the extent to which specialized and more efficient right hemisphere functions were activated.     

Can Happiness Apps Generate Nationally Representative Datasets? - a Case Study Collecting Data on People’s Happiness Using the German Socio-Economic Panel

In the last few years, apps have become an important tool to collect data. Especially in the case of data on people’s happiness, two projects have received substantial attention from both the media and the scientific world: “Track your happiness” from Killingsworth and Gilbert (Science, 330, 932-932, 2010), and “Mappiness,” from MacKerron (2012). Both happiness apps used the experience sampling method to ask people a few times per day how they feel, what they do, with whom, and where. The collected data are then displayed for the participants in simple graphs to help them understand what makes them happy and what does not. Both studies have collected considerable data without giving participants any financial rewards. But quantity is not everything that matters with respect to data collection, and thus, understanding whether nationally representative datasets can be collected using such happiness apps is crucial. To address this question, we built a new happiness app and ran a case-study with over 4000 participants of the innovation sample of the German Socio-Economic Panel (Richter and Schupp in Schmollers Jahrbuch, 135(3), 389–399, 2015). Participants were informed that the app collects data on everyday happiness after a household interview and asked whether they would like to use the app. In the first year (2015), participants did not receive any reward, and in the second year (2016), a different group of participants received a 50 Euro Amazon voucher for their participation. The results showed that our happiness app cannot generate nationally representative datasets if it is not controlled that all demographic sub-groups have access to a smartphone, are highly motivated with a sufficient reward and data is collected with quota sampling.