Everstate is an imaginary state in our contemporary world of the beginning of the 21st century, created to identify and imagine various futures.

It will be used to represent all states and each state. Everstate is thus an ideal-type state. It is also a shorthand for the model that was constructed to represent the dynamics and processes underlying the evolution of a state, as political form. This model is a dynamic graph, map or network, as is explained in Modeling for Dynamic Risks and Uncertainties (1) : Mapping Risk and Uncertainty and Modeling for Dynamic Risks and Uncertainties (2) : Mapping a Dynamic Network

However, even if we work with an ideal-type, events do not unfold in a vacuum but are dependent upon and constrained by a host of specific factors, most notably geography, the ecological milieu and history.

Thus, to make our foresight realistic, replicable, as well as adaptable to specific, existing countries, some criteria were identified and then specified: i.e. we give them values for Everstate. Those initial characteristics will also influence what happens.

Readers and users of the Chronicles of Everstate can imagine changing those criteria to test potential futures for countries of interest. They can apply real criteria to identify plausible futures for real countries.

For example, if geography is selected as a criteria, then the value may be: land in the tropical belt in South Asia, or land in Northern America. The size of the country must will also need to be specified, etc.

To identify the criteria, we used a “revisited influence analysis“. We then explain how to attribute values for each criterion in the specific case of dynamic networks. We finally highlight the criteria selected and their values for Everstate.

Next, we explicate how the map is used to construct the narrative through use of ego networks, and apply it to articulate how the values selected set the stage for Everstate.

We then start telling the story of Everstate, while, in the meantime, showing how to do it.

Published by Dr Helene Lavoix (MSc PhD Lond)

Dr Helene Lavoix is President and Founder of The Red Team Analysis Society. She holds a doctorate in political studies and a MSc in international politics of Asia (distinction) from the School of Oriental and African Studies (SOAS), University of London, as well as a Master in finance (valedictorian, Grande École, France). An expert in strategic foresight and early warning, especially for national and international security issues, she combines more than 25 years of experience in international relations and 15 years in strategic foresight and warning. Dr. Lavoix has lived and worked in five countries, conducted missions in 15 others, and trained high-level officers around the world, for example in Singapore and as part of European programs in Tunisia. She teaches the methodology and practice of strategic foresight and early warning, working in prestigious institutions such as the RSIS in Singapore, SciencesPo-PSIA, or the ESFSI in Tunisia. She regularly publishes on geopolitical issues, uranium security, artificial intelligence, the international order, China’s rise and other international security topics. Committed to the continuous improvement of foresight and warning methodologies, Dr. Lavoix combines academic expertise and field experience to anticipate the global challenges of tomorrow.

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