Beliefs and environmental behavior: The moderating effect of emotional intelligence

Recent decades have seen a proliferation of studies aiming to explain how pro‐environmental behavior is shaped by attitudes, values and beliefs. In this study, we have included an aspect in our analysis that has been rarely touched upon until now, that is, the intelligent use of emotions as a possible component of pro‐environmental behavior. We applied the Trait Meta Mood Scale‐24 (TMMS‐24) and the New Environmental Paradigm scale to a sample of 184 male and female undergraduate students. We also carried out correlation and hierarchical regression analyses of blocks. The results show the interaction effects of the system of environmental beliefs and the dimensions of emotional intelligence on glass recycling attitudes, intentions and behavior. The results are discussed from the perspective of research on how the management of emotions guides thought and behavior.     

The Goal Circuit Model: A Hierarchical Multi‐Route Model of the Acquisition and Control of Routine Sequential Action in Humans

Human control of action in routine situations involves a flexible interplay between (a) task‐dependent serial ordering constraints; (b) top‐down, or intentional, control processes; and (c) bottom‐up, or environmentally triggered, affordances. In addition, the interaction between these influences is modulated by learning mechanisms that, over time, appear to reduce the need for top‐down control processes while still allowing those processes to intervene at any point if necessary or if desired. We present a model of the acquisition and control of goal‐directed action that goes beyond existing models by operationalizing an interface between two putative systems—a routine and a non‐routine system—thereby demonstrating how explicitly represented goals can interact with the emergent task representations that develop through learning in the routine system. The gradual emergence of task representations offers an explanation for the transfer of control with experience from the non‐routine goal‐based system to the routine system. At the same time it allows action selection to be sensitive both to environmental triggers and to biasing from multiple levels within the goal system.     

Quantitative Standards for Absolute Linguistic Universals

Absolute linguistic universals are often justified by cross‐linguistic analysis: If all observed languages exhibit a property, the property is taken to be a likely universal, perhaps specified in the cognitive or linguistic systems of language learners and users. In many cases, these patterns are then taken to motivate linguistic theory. Here, we show that cross‐linguistic analysis will very rarely be able to statistically justify absolute, inviolable patterns in language. We formalize two statistical methods—frequentist and Bayesian—and show that in both it is possible to find strict linguistic universals, but that the numbers of independent languages necessary to do so is generally unachievable. This suggests that methods other than typological statistics are necessary to establish absolute properties of human language, and thus that many of the purported universals in linguistics have not received sufficient empirical justification.