An interesting perspective on how arguments might actually be the extremes against the middle ground:
To continue their analogy, my theory of responding in a reasonable fashion if you have the perspective to do it could be compared to people who have a strong immune system or have been immunised providing help to those at risk of infection.
Of course, no amount of help from others will beat each of us making sure our mental vaccinations are up to date.
However, what interested me more than the opportunity to extend a metaphor was the potential expansion of the concept beyond anger.
Whether through existing temperament, long exposure to legal thinking, or a combination thereof, I love nuances and boundary cases: looking at those situations that break an either-or classification. But, in daily life I consider nuance a lot less.
If faced with a choice between ethical and not ethical, I will choose ethical. If faced with a choice between two different ethical grounds (for example, coffee grown to high environmental standards with no information on worker wages and coffee with no statement of environmental standards but grown by a company that demonstrates it pays a fair wage) then I will probably consider the relative merits. But if faced with a choice between ethical for A-and-B or ethical for B-and-C or ethical for A-and-D, I am more likely to fall back on a guideline that B is better than A than to carry out a balancing act in the supermarket aisle.
And potentially this is a good thing. If every decision required assessment of all the consequences and factors in real-time, then I wouldn’t get anything done. Whereas, with some heuristics developed from a more general consideration I can make decisions that a still mostly good orders of magnitude faster.
Which makes me wonder if some ideas are symbiotic. Like all symbiosis, they involve a compromise but usually provide more benefit than is lost.
For example, Newtonian physics. Most of us are infected in school with the classical view of physics; a view that doesn’t fit reality as observed, but which does work as well – if not better – as a guide to most real world issues as applying a more accurate model.