New Reflections on the Mirror: the Interests Proximity Bias Solution

Philosophia - We worry about becoming non-existent, but not about coming into being. But both events are similarly bad according to Deprivationism; hence, it seems that we should display symmetric...     

Testosterone and cortisol responses to competitive fighting in human males: A pilot study

Serum testosterone and cortisol levels were measured by radioimmunoassay in 14 young male judo competitors, in samples taken 10 minutes before and 45 minutes after two different procedures. The first involved physical exercise and the second competitive fighting. Both procedures were of 5 minutes duration and sessions took place at the same time (between 10:00 A.M. and 12:00 P.M. local time) but on different days. Comparing the two situations over all subjects revealed that testosterone increased after exercise and decreased slightly after Competition. Between subject comparisons suggested that contrary to previous claims, winning or losing did not significantly change the testosterone and cortisol levels. Comparisons of subjects who were members of the Regional Team with individuals who were not part of that group confirmed that members increased their testosterone levels after competition, whereas the nonmembers showed a significant decrease. Moreover, success of the individuals, in their sporting record, correlated positively and significantly with the changes of testosterone observed during the competition. These preliminary results suggest that previous personal experience of success can influence the pattern of the psychoendocrine response to a contest situation.     

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...     

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...     

For-Me-Ness,For-Us-Ness,and the We-Relationship

Topoi - This article investigates the relationship between for-me-ness and sociality. I start by pointing out some ambiguities in claims pursued by critics that have recently pressed on the...     

Corporate Social Responsibility Practices of Colombian Companies as Perceived by Industrial Engineering Students

Science and Engineering Ethics - This work describes the perceptions that Industrial Engineering students have regarding Colombian firms’ corporate social responsibility (CSR) practices. It...     

Does cognitive reflection mediate the math gender gap at university admission in Chile?

Social Psychology of Education - In Chile, a vast and persistent gender gap in math performance at university admission has negative consequences for women’s opportunities. International...