Shaping Global Cooperation with Ecological Governance
Bibliographic record
Abstract
We propose a new shape for global governance based on bottom-up self-regulating and self-governing processes proven by evolution. Scientist and engineers have extracted the essential features of these processes and used them to design self-regulating, and self-governing space probes and automobiles. Now the same can be done with social systems. Wiener coined the word “cybernetics” to describe this knowledge that has now become the science of governance. Cybernetic pioneers Ashby and Shannon identified why is impossible for simple centralised command and control hierarchies to directly govern complexity reliably. Humans are able to thrive in novel, complex environments with unknowable dynamic risks and opportunities, and yet the brain has “no chief executive officer neuron”. Human brains resemble a massively parallel computer with distributed intelligence and distributed decision-making. Different areas of the brain make decisions in competition with other areas according to multidimensional conflicting priorities as Figure 1 suggests. The “Global Governance Models in History” offer little guidance on achieving the Global Challenges objectives because execution is depend upon hierarchies that cannot reliably work. Ecological governance, as found in our brains, has no central command centre with excessive powers to create toxic governance. Nominating “key individuals” could be counterproductive. Hierarchies manage complexity incompletely by filtering out information through each level. Networks can manage complexity as comprehensively as desired by increasing their number. Hierarchies cannot directly control complexity because by their nature they lack requisite variety of independent feedback channels to communicate or control the complexity of variables they may encounter. The amplification of control of complex variables can however be achieved indirectly through a process described as “Supplementation”. This creates networks and explains our strategy describe below for establishing a “New Shape” for global cooperation and governance. Ecological governance may appear to be counter-intuitive to many social scientists that may implicitly assume that the natural order of control is top-down as accepted by monotheists and inferred by the word “management”. However, Nobel Laureate Ostrom has extensive case studies providing compelling evidence that the natural order in traditional societies is from the bottom-up creating self-governing networks with top down influences to avoid “the tragedy of the commons”. This is the new shape of global cooperation we are proposing. The Ostrom’s also refer to higher order networks as “polycentric compound republics”. This also describes how our brains operate and stakeholder governed firms like the Mondragon Cooperatives in Spain. Quantum physicist Bohm described the arrangement that involved both bottom up and top down influences as “the architecture of the universe”. Simon identified why this is the most efficient way to create or reliably govern complexity. Yet academic researchers have no agreed definition of “sound governance” with practitioners ignoring how centralised control can corrupt absolutely. We propose that the DNA for building polycentric compound republic networks be undertaken by seeding the world with Pioneer Global Transformative Networks (PGTNs). The life of PGTNs would be limited to five years to create urgency and the opportunity to improve the process in successor Global Transformative Networks (GTNs). These are recreated every 20 years to establish “creative destruction” to discover adaptive improvements without coercion. Evaluation would be with OECD “individual wellbeing” metrics. The objective of the PGTNs would be to establish frameworks for: (i) Seeding the creation of more effective and comprehensive GTNs; (ii) Establishing research, education and testing of designs for more effective GTNs; (iii) Accelerating the spread of nations with declining populations; (iv) Introducing currencies whose value is defined by an eternal service of nature in each bioregion so market forces can further the wellbeing of nature's bioregions and of humanity [14]; (v) Explaining how to create an Universal Living Income (ULI) with less taxation to increase equality and remove the need for children to provide old age support; (vi) Establishing bottom-up early warning processes for identifying and taking counter measures to any existential threats, costs and risks to the eternal wellbeing of the planet or humanity. If we became finalists in March 2018 we would activate plans with existing associated global networks to become sponsors of PGTNs. Practical initiatives could to be identified with the winners in May 2018. Implementation initiatives would require the production of a handbook on how PGTNs could carry out their transformative role. This would require collating existing literature on the transformation strategies such as: (a) Identifying, how “the biggest market failure the world has even known” that produced Climate Change can be corrected by tethering the value of money to an index. The index would be automatically established by the Internet of Things so as to increase the relative purchasing power of regional currencies that most efficiently maximised reliance on benign renewable energy sources. Monetary values would stabilise and encourage humanity to become distributed to the most sustainable locations on the planet. Contagion of crises eliminated with possibly also the need for carbon taxes or trading. Banking would become decentralised with money better fit for purpose as a medium of exchange without asset bubbles. (b) Introducing on a political vote winning manner ecological forms of owning realty, enterprises and money to significantly reduce inequality. Ecological “use or lose it ownership rules provides a way for democratising the wealth of nations while reducing: taxes, public welfare, and the size of government. This is achieved by equity sharing without the use money to represent a policy option neglected by economists while providing a way to fund a ULI without taxes neglected by Utopians. Our proposals offers unique insights into sources of inequality from investors being overpaid in ways not reported by accountants and so not noticed by policy makers. This is matched with politically attractive non-cash ways to reduce inequality to fund an ULI. In addition, we have life experience as business, social and policy entrepreneurs to bring authority for implementing our ideas.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".