Resourciv: Social Models

I’ve been procrastinating on Resourciv because I couldn’t come up with a demographic or economic framework (or perhaps meta-framework, since I really want to support different modes of production and distribution and so on) I was happy with. So I made some scripts to simulate different social dynamics in the hopes that I would land on a way to represent them without giving myself or the player a headache.

Inheritance

My least favorite of the two is an inheritance simulator. I read a couple books by historian and social scientist (stricto sensu) Peter Turchin, who’s most famous for his concept of elite overproduction, but I was struck by a point he made that inequality would emerge even in egalitarian societies if the society practices inheritance because families with less children divide the parents’ wealth amongst less recipients. I simulated a society at three sexes (for the purposes of reproduction: F, M, or X) and three age levels (young, adult, or elder) with each individual starting at 100 wealth. Every generation:

1. Elderly individuals die and give their adult children inheritance.
2. Adult individuals become elderly, and potentially gain new wealth based on that of their parents weighted by a random fortune roll.
3. Young individuals are paired according to sex to maximize their wealth (given what they are expected to receive from their parents); then they become adults and have somewhere from 1–6 children.

Then I measured what percent of the population owns each quarter percentile of wealth. Initially, these quarters are split between equal 25% portions of the population. Society A has each child receive equal inheritance from their parents, Society B gives inheritance to the oldest child; and Society C prioritizes the oldest male child if a family has any. Below are final distributions of wealth at generation 20, though they tended to hit those points as early as generations (lol) 6–7. I also included various statistics, including a wealth Gini coefficient (doesn’t wealth make more sense to measure than income?).

Statistic	Society A	Society B	Society C
Quarter 1	37%	61%	67%
Quarter 2	29%	27%	23%
Quarter 3	22%	10%	8%
Quarter 4	12%	2%	2%
Minimum	103	56	63
Median	207	112	112
Maximum	3546	212392	168101
Gini	15%	40%	44%

One generation is, what, 20–25 years? I was surprised to find then that the point around which these societies hit relative stagnancy was 150 years, about the same length of time for which Turchin proposes (following Ibn Khaldun) a political order lasts. It should also be said that the precondition for such a dynasty to last as long as this is to have a consistent source of new wealth entering the system; otherwise, inequality accelerates. Also notice the more fundamental preconditions: that property is privately held, can be accumulated, and is passed on from parent to child. It’s no wonder Marx and Engels target inheritance! They must have had this very dynamic in mind—besides the obvious need to expropriate wealth from the bourgeois and aristocratic families.

This model is not a sustainable one to plug into Resourciv as-is. I can’t simulate thousands of individuals, much less millions or billions. I’d be better off tracking the concentration of wealth within a population, and my goal here was more to see what that looks, w.r.t. how long it takes to reach certain levels of inequality and what those levels are. I will say that for the top 10% of the population to own 25–50% of wealth is nothing compared to the levels of modern capitalism, meaning this model or something similar would be improved by accounting for the capitalization of wealth besides gaining just 30–180% of what one’s parents had—but, ugh, what a fucking headache. Could maybe track how much wealth is put into a population, track the inequality rate as a separate and abstract thing under the assumption that new wealth is distributed relative to imaginary individuals’ wealth—is this even necessary? I’m basically brainstorming. I don’t have any plans yet.

Resources

This system has more semblance to what already exists in the game. My partner helped me a lot with this one because she had studied ecology as part of her biology degree, so she let me borrow her school notes to make sense of the dynamics I wanted to simulate. Thank you so much, love, I figure you’ll read this eventually :) this abstracts the economy from assigning individual peeps to dividing the population into classes which produce and consume goods at different levels. This is sort of a typical carrying capacity problem, but (as I’ve been doing) instead of using a population function with an actual formal ceiling, I’m adjusting the rate of growth based on the availability of resources (which themselves are produced at rates depending on the population). Some resources are also non-mobile meaning they aren’t actively produced but exist in a pool; these can be natural resources like water or (as in this model) housing, which we can assume is constructed as part of a settlement’s production queue or whatever—remember the game. The growth rate of a class depends on a base fertility rate and their satisfaction level, which is based on which resource (if any) they lack the most.

I tried two models, both with classes of fiefs and lords, each having a different approach (because I need to figure out which makes more sense): one where fiefs have a greater fertility rate and thus lords have too many fiefs to rule over; and another where the lords (relatively speaking) outpace the fiefs and, along the lines of Turchin, compete over petty power access. What’s neat about the framework is that the rates of production regulate relative ratios of population, e.g. the population of lords (or of non-fiefs in general) cannot exceed more than 20% of that of fiefs, and constant ‘pools’ of e.g. homes see populations taper off before hitting their limit (same effect as with a typical carrying capacity formula). The math works out well structurally and pacing-wise.

The problem is that earlier I opted to replace my early demographic system with a more discrete one treating peeps as the atomic unit of population. It still more makes sense to me because I can’t reconcile in my mind a granular population system with an abstract map and building system. How many individuals fit on a hex? How does population which grows exponentially translate into rates of production? Can one convert from population to meeps (i.e., units which move around on the map)? How do I handle not just growth of individual population blocs, but also transfers of population from one bloc into another? Not sure. Back to the whiteboard.