Differences and Climate: the USA

Again: an ABCM pattern

I’ve been maniacally busy with an impossible assignment for the last few weeks. An hour-long lecture to young scientists dedicated to machine learning (ML), artificial intelligence (AI) and big data (BD) about complexity. I zoom in on five different forces that together form a social climate (veracity, loyalty, money, coercion and fitness) and try to show that different value configurations lead to different climates. Climates are interpretations of the conditions in which decisions are made. I distinguish individual and collective interpretations. Individual decisions are made against the background of what the decision maker as an individual can do best (in terms of veracity, loyalty, money, coercion and fitness) to survive individually. Collective decisions are made against the background of what the collective (or institution) can do best (in terms of veracity, loyalty, money, coercion, and fitness) to survive as a collective.

Fig. 1 A Framework for my ABCM approach

I enlist the help of the grid in Fig. 1 to support ABCM-based interpretations of Fig. 2 and Fig. 2a. It concerns the usual Petri net notation with circles for state of affairs and rectangles for processes or functions. The idea of Fig. 1 is that the environment (world/domain) generates situations (SITUATION) that prompt rationalizing actors to make a plan of action (plan). This process is fed by the decision-maker’s DNA (its subconscious character if it is an individual and its climate if it is a collective) and the valuations (VERACITY, LOYALTY, SECURITY, MONEY, FITNESS) that this decision-maker is using at that moment for his action plan (PLAN). This can be done, in thought (imagine), but also in practice (behave). The result (RESULT) flows back into the environment, which turns it into a situation or a story (STORY) that in turn leads to making a plan, etc., etc.

Application to the last year of COVID-19 in the USA

If these forms of climate play a role, they must be reflected in the ways in which the different forms of policy regarding COVID-19 have emerged. I choose the last year of COVID-19 in the USA (Fig. 2) as a second target for the application of the pattern from Fig. 1.

Fig. 2 One year COVID-19 in the US

331 million people live in the US. The first wave had arrived in July 2020, but the pandemic was not under control: around 1,000 COVID deaths were counted daily and around 50,000 infections, numbers that are too high to effectively control a pandemic through contact tracing. This is also apparent from the sequel: from October the second wave starts, which will reach its peak in January 2021 with daily infections in the order of 250,000, infections which are associated with 3,500 daily deaths. The declines then set in when the presidency is handed over (Trump-Biden) and when, concurrently, effective vaccines begin to become available. The US is far from being at the level of China in terms of COVID-19 containment. In the US, the pandemic has killed 602,820 (or 1,820 per million inhabitants) to date, in China it is 1,430 people killed (or 4 per million inhabitants). How did the diversity in these numbers happen?

Measures were mainly taken by state or at a lower level. The numbers indicate that there is no control over the pandemic yet. Wikipedia says today:

High levels of vaccine hesitancy in parts of the country have hampered vaccination efforts amidst the rise of the Delta variant, another more easily transmissible variant from India, in July 2021; this led to a fifth rise in infections, with the vast majority of new cases being among unvaccinated people. State and local responses to the outbreak have included mask mandates, prohibition and cancellation of large-scale gatherings (including festivals and sporting events), stay-at-home orders, and school closures. Disproportionate numbers of cases have been observed among Black and Latino populations, and there were reported incidents of xenophobia and racism against Asian Americans. Clusters of infections and deaths have occurred in many areas.

I assume the quote is a good representation of what policy has been in the US. And that it gives an indication of the (locally) applicable climates. These are the basis for collective COVID-19 decisions in the US during that period.

VERACITY then plays a role in the shared realization that COVID-19 is a contagious disease that spreads exponentially (without counter measures) and in many cases leads to unbearable suffering and life-threatening conditions. The first six months of the pandemic have shown this, first in and around Wuhan in China and a month and a half later in the US (see Fig. 2a), especially in New York. Like in China, in the US veracity is not always a decisive value. There are also situations there (I am thinking of the deliberate presidential trivialization of COVID-19) where LOYALTY to the political base is decisive in a way that invokes coercion-protected constitutional rights, whether or not hypothetical, to self-determination and expression (SECURITY COERCION) over veracity. The other local measures mentioned in Wikipedia are also considered appropriate in the US in terms of the locally prevailing value climates (with which they vary). The US has seen its society and also its economy reopen locally from August 2020 (MONEY) under a strong diversity of vigilance and effective measures against local outbreaks, depending on the political leaning of the region. Minimal obstacles to the movement of people and goods and the associated data are also necessary conditions for the US for survival in the current world (FITNESS) and require adequate infrastructures and bearable osmotic processes at the borders.

Fig. 2a COVID-19 in the US, the first 6 months

There is hardly any difference in scale between the numbers in the first and last months in the US. In the US, the pandemic is not under control. It seems to me that the cause is not only that a two-party culture has emerged in the US political world (in which LOYALTY takes precedence over VERACITY in both camps, while the two party climates have now drifted so far apart that they tend to demonize each other where possible) but also that facing the pandemic is left to disparate local regulators (who disagree on the seriousness of the threat and also on the merits of the vaccines) while the contagions care little about region or party membership.

More on climate differences within and between the US and the PRC will follow later.