THE COLLAPSE OF OLIGARCHIC CAPITALISM AND THE RISE OF REGENERATIVE LEARNING: HOW THE SCIENCE OF ENERGY SYSTEMS CLARIFIES WHAT’S HAPPENING TODAY AND WHAT COMES NEXT | Sally J. GOERNER

We live in a head-spinning, gut-wrenching time of multiplying crises. At home we face outsourced jobs, crumbling cities, underpaid teachers, unaffordable healthcare, endless wars, political corruption, a co-opted corporate media, skyrocketing inequality, and public “austerity” measures whose main purpose is to make tax-breaks for the rich more affordable. Working-class stagnation is producing widespread anxiety, mounting debt, and “despair deaths” from opioid abuse. Fear is fueling populist outrage, along with extremism, authoritarianism, and the conditions for a fascist takeover. Meanwhile, climate change poses an existential threat to humanity itself. All of these calamities spring from the same root cause: an oligarchic capitalism that puts short-term profit for owners over people and planet. While this system seems immutable, upheavals from Occupy Wall Street to the rise of right-wing populism signal a backlash to a political–economic establishment that treats people and planet as resources to be pillaged and expenses to be minimized. Its failures have also been driving the development of new possibilities in the form of more systemic approaches. Still, while systems thinking has improved approaches in fields from agriculture to medicine, so far none of these reforms have been able to channel public frustration into true transformation because none addresses the root problem: oligarchy. The science of systemic vitality we need is also being born, but so far, its findings are diffuse. This article shows how the science of energy systems can galvanize today’s economic reformation by articulating the common sense rules and rigorous measures of systemic vitality, while anchoring them in an evidence-based vision of humanity as a collaborative learning species. The result is a practical path to building systemic socioeconomic vitality by revitalizing human networks, energizing collective learning, and clarifying why oligarchic capitalism is a distortion of our original democratic free-enterprise dream, which is now careening toward collapse.

KEYWORDS: Big history, energy networks, economic development, great change, paradigm shift, regenerative economics, societal learning.

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Measuring regenerative economics: 10 principles and measures undergirding systemic economic health

 Abstract

Applying network science concepts and methods to economic systems is not a new idea. In the last few decades, however, advances in non-equilibrium thermodynamics (i.e., self-organizing, open, dissipative, far-from-equilibrium systems), and nonlinear dynamics, network science, information theory, and other mathematical approaches to complex systems have produced a new set of concepts and methods, which are powerful for understanding and predicting behavior in socio-economic systems. In several previous papers, for example, we used research from the new Energy Network Science (ENS) to show how and why systemic ecological and economic health requires a balance of efficiency and resilience be maintained within a particular a “window of vitality”. The current paper outlines the logic behind 10 principles of systemic, socio-economic health and the quantitative measures that go with them. Our particular focus is on “regenerative aspects”, i.e., the self-feeding, self-renewal, and adaptive learning processes that natural systems use to nourish their capacity to thrive for long periods of time. In socio-economic systems, we demonstrate how regenerative economics requires regular investment in human, social, natural, and physical capital. Taken as a whole, we propose these 10 metrics represent a new capacity to understand, and set better policy for solving, the entangled systemic suite of social, environmental, and economic problems now faced in industrial cultures.

Keywords

Regenerative economics | Resilience | Economic networks | Self-organization | Autocatalysis | Socio-ecological systems | Network analysis

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