Open Access
The Evolved Nest: A Partnership System that Fosters Child and Societal Wellbeing
Author(s) -
Mary S. Tarsha,
Darcia Narváez
Publication year - 2019
Publication title -
interdisciplinary journal of partnership studies
Language(s) - English
Resource type - Journals
ISSN - 2380-8969
DOI - 10.24926/ijps.v6i3.2244
Subject(s) - thriving , humanity , environmental ethics , psychological resilience , empathy , psychology , general partnership , social psychology , sociology , developmental psychology , political science , social science , law , philosophy
Although most people want children to thrive, many adults in industrialized nations have forgotten what that means and how to foster thriving. We review the nature and effects of the evolved developmental system for human offspring, a partnership system that fosters every kind of wellbeing. The environment and the type of care received, particularly in early life, shape neurobiological process that give rise to social and moral capacities. A deep view of history sheds light on converging evidence from the fields of neuroscience, developmental psychology, epigenetics, and ethnographic research that depicts how sociomoral capacities are not hardwired but are biosocially constructed. The Evolved Nest is the ecological system of care that potentiates both physical and psychological thriving, the foundations of cooperative and egalitarian societies. Deprivation of the evolved nest thwarts human development, resulting in sub-optimal, species-atypical outcomes of illbeing, high stress reactivity, dysregulation, and limited sociomoral capabilities. Utilizing a wider lens that incorporates humanity’s deep ancestral history, it becomes clear that deprivation of the evolved nest cuts against the development of human nature and humanity’s cultural heritage. Returning to providing the evolved nest to families and communities holds the potential to revise contemporary understandings of wellbeing and human nature. It can expand current metrics of wellness, beyond resilience to optimization.