How to Develop Reliable Instruments to Measure the Cultural Evolution of Preferences and Feelings in History?

Reproductive Strategies and Romantic Love in Early Modern Europe

In Western Europe, the Early Modern Period is characterized by the rise of tenderness in romantic relationships and the emergence of companionate marriage. Despite a long research tradition, the origins of these social changes remain elusive. In this paper, we build on recent advances in behavioral sciences, showing that romantic emotional investment, which is more culturally variable than sexual attraction, enhances the cohesion of long-term relationships and increases investment in children. Importantly, this long-term strategy is considered especially advantageous when living standards are high. Here, we investigate the relationship between living standards, the emotional components of love expressed in fiction work, and behavioral outcomes related to pair bonding, such as nuptial and fertility rates. We developed natural language processing measures of "emotional investment" (tenderness) and "attraction" (passion) and computed romantic love in English plays (N = 847) as a ratio between the two. We found that living standards generally predicted and temporally preceded variations of romantic love in the Early Modern Period. Furthermore, romantic love preceded an increase in nuptial rates and a decrease in births per marriage. This suggests that increasing living standards in the Early Modern Period may have contributed to the emergence of modern romantic culture.

Intelligence across humans and machines: a joint perspective

This paper aims to address the divergences and contradictions in the definition of intelligence across different areas of knowledge, particularly in computational intelligence and psychology, where the concept is of significant interest. Despite the differences in motivation and approach, both fields have contributed to the rise of cognitive science. However, the lack of a standardized definition, empirical evidence, or measurement strategy for intelligence is a hindrance to cross-fertilization between these areas, particularly for semantic-based applications. This paper seeks to equalize the definitions of intelligence from the perspectives of computational intelligence and psychology, and offer an overview of the methods used to measure intelligence. We argue that there is no consensus for intelligence, and the term is interchangeably used with similar, opposed, or even contradictory definitions in many fields. This paper concludes with a summary of its central considerations and contributions, where we state intelligence is an agent's ability to process external and internal information to find an optimum adaptation (decision-making) to the environment according to its ontology and then decode this information as an output action.