Effect of autonomy support and dialogic learning on school children’s physical activity and sport

This study applies an intervention based on autonomy support through dialogic learning to examine effects on motivation and the promotion of physical activity and sport involvement during schoolchildren’s leisure time. One hundred and two primary school students, aged 11–13 years, participated (M = 10.93, SD = 0.75). The sample was divided into two groups: an experimental group (49 students) and a control group (53 students). A quasi-experimental study was conducted in physical education classes over the course of 9 months. Assessments of autonomy support from teachers, family, and peers; basic psychological needs; self-determined motivation in physical education and during leisure time; planned behavior variables; physical activity intention; and estimated and actual physical exercise behavior time were included in the model. Following the intervention, the results revealed that greater autonomy support by the teacher, the family and peers, satisfaction of the basic psychological needs, self-determined motivation during physical education class and during free time, greater perceived control, favorable attitude and intention to engage in physical activity contributed to the explanation of student physical activity involvement. These results suggest that when students receive extensive social support from diverse social agents that essential precursors to physical activity are strengthened and contribute to increased motivation and actual physical activity involvement. Efforts to promote effective communications with students and other pedagogical efforts, such as providing dialogic learning opportunities, should be considered in order to strengthen physical activity motivation and involvement in students.     

Gender Attitudes and Public Opinion Towards Electoral Gender Quotas in Brazil

Research on public opinion towards affirmative action shows that citizens often support the principle of equality while simultaneously rejecting policies that promote it in a pattern described as the “principle-policy puzzle.” The scholarship also shows that ideology and prejudice towards the targeted group explain the puzzle with respect to racial affirmative action. In this article, we use unique survey questions included in the 2014 round of the AmericasBarometer in Brazil to show that citizens tend to support electoral gender quotas while rejecting gender-based egalitarianism in a reversed version of the “principle-policy puzzle.” We argue that a different type of gender attitudes, namely benevolent sexism, shapes support for gender quotas as well as for the principle of equality. While benevolent sexists tend to reject gender equality based on views about gender complementarity and stereotypes about women's purity, they also support quotas as policies to foster such values. Our findings suggest that even though the political and scholarly debates can provide sound normative reasons for the adoption of quotas across different contexts, public support for them often relies on paternalistic views and expectations about the role of women in politics.     

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...     

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...     

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...