Some New Infinity Puzzles

Philosophia - Salmon (1970) was the first to speak explicitly of paradoxes of kinematics. In this short note I introduce a new class of infinity puzzles. Following natural terminology, they should...     

More Royalist Than the King? Immigration Policy Attitudes Among Naturalized Citizens

Social psychological research has analyzed immigration attitudes mostly from the perspective of natives without an immigrant background. Nevertheless, an increasing number of migrants obtain national citizenship and take a stance towards immigration policies. By studying immigration policy attitudes reported by naturalized citizens, this article develops a dual-pathway model of immigrant political incorporation featuring pathways of either absorption or transformation. Based on a unique sample of immigrants who just accomplished the naturalization procedure (N = 566), we investigate participants' preferences for permissive or restrictive immigration policies as a function of their naturalization motives and expectations about how immigrants should acculturate in the receiving society (i.e., acculturation orientations). Our findings provide evidence for both processes of political absorption and transformation. On the one hand, belongingness motives underlying naturalization were connected to orientations towards host culture adoption, which in turn predicted support for restrictive immigration policies. On the other hand, instrumental motives were connected to orientations towards heritage culture maintenance, which in turn predicted support for permissive immigration policies. To conclude, we discuss the social psychological dynamics involved in the transition from national outsiders to national insiders and highlight the effects of naturalization on power relations between national majority and immigrant minority groups.     

Does Partisan Bias Modulate Neural Processing of Political Information? An Analysis of the Neural Correlates of Corruption and Positive Messages

Daily worldwide newspapers print articles exposing government corruption. Yet these messages do not lead to a loss of votes for the corrupt parties. Sympathizers’ partisan bias, which respectively minimizes and maximizes corruption and positive messages of their own parties respectively, is widely considered the main cause of the loss of effectiveness of political communications. Despite the well-established existence of such bias when processing political information, little is known as to its psychological origin. Through the use of neuroscience (fMRI), this study explores the underlying brain mechanisms of negative (corruption) and positive political messages related to a conservative and a socialist Spanish political party, as well as the differences between their sympathizers. The findings reveal that negative (vs. positive) political messages exert the greatest neuroimaging impact on the electorate, as shown in aversive, risk, and disappointment-related brain regions. Interestingly, we show that there exists a main partisan bias against opposite parties (and not a positive bias toward one’s own party) that stems from a higher risk, ambiguity, and disbelief provoked by both positive and negative information about rival parties. Furthermore, this bias was more pronounced among conservative supporters. The current findings provide valuable insights for political parties to improve their communication campaigns.     

Truth Without Reference: The Use of Fictional Names

Topoi - Singular terms without referents are called empty or vacuous terms. But not all of them are equally empty. In particular, not all proper names that fail to name an existing object fail in...     

Speaking like a Man: Women’s Pitch as a Cue for Gender Stereotyping

Sex Roles - Women’s average voice pitch has decreased in recent years, reducing the gap between men on this vocal dimension. The present study examined whether a woman speaking at a lower...     

EARSHOT: A Minimal Neural Network Model of Incremental Human Speech Recognition

Despite the lack of invariance problem (the many-to-many mapping between acoustics and percepts), human listeners experience phonetic constancy and typically perceive what a speaker intends. Most models of human speech recognition (HSR) have side-stepped this problem, working with abstract, idealized inputs and deferring the challenge of working with real speech. In contrast, carefully engineered deep learning networks allow robust, real-world automatic speech recognition (ASR). However, the complexities of deep learning architectures and training regimens make it difficult to use them to provide direct insights into mechanisms that may support HSR. In this brief article, we report preliminary results from a two-layer network that borrows one element from ASR, long short-term memory nodes, which provide dynamic memory for a range of temporal spans. This allows the model to learn to map real speech from multiple talkers to semantic targets with high accuracy, with human-like timecourse of lexical access and phonological competition. Internal representations emerge that resemble phonetically organized responses in human superior temporal gyrus, suggesting that the model develops a distributed phonological code despite no explicit training on phonetic or phonemic targets. The ability to work with real speech is a major advance for cognitive models of HSR.     

Four Dimensions of Criticism Against Gender-Fair Language

Sex Roles - The gender-neutral third-person pronoun singular hen was recently introduced in Swedish as a complement to she (hon) and he (han). The initiative to add hen initially received strong...     

Decision-makers use social information to update their preferences but choose for others as they do for themselves

People's risky decisions are susceptible to the social context in which they take place. Across three experiments using different paradigms, we investigated the influence of three social factors upon participants' decisions: the recipient of the decision-making outcome (self, other, or joint), the nature of the relationship with the other agent (friend, stranger, or teammate), and the type of information that participants received about others' preferences: none at all, general information about how previous participants had decided, or information about a specific partner's preference. We found that participants' decisions about risk did not differ according to whether the outcome at stake was their own, another agent's, or a joint outcome, nor according to the type of information available. Participants did, however, adjust their preferences for risky options in light of social information.     

Ethical Decision Making in Autonomous Vehicles: The AV Ethics Project

Science and Engineering Ethics - The ethics of autonomous vehicles (AV) has received a great amount of attention in recent years, specifically in regard to their decisional policies in accident...