AIAA 2010-8782
AIAA SPACE 2010 Conference & Exposition
30 August - 2 September 2010, Anaheim, California
A Novel System of Governance for Remote Communities
Peter J. Schubert, Ph.D., P.E.
Packer Engineering, Inc., Naperville, IL 60563
Advancing beyond the military style of command common on spacecraft, submarines and
outposts in remote, harsh environments requires new thinking in self-governance and
human relations. Without a strict system of command and control, the heterogeneous
character of human nature tends to generate societal imbalances. Greed, self-interest,
opportunism and power lust are present to some extent in every person, yet people vary
widely in how they express and manage these traits. Therefore, a non-military system of
governance must provide for balance and corruption-proofing, while still allowing individual
freedom of expression and synchronization with outside authority. Further desirable
attributes of a governance system for remote communities are the ability to adapt to
changing environments and changing community objectives, and the ability to scale up or
down as the population changes over time. A new system, tentatively called stochasticism,
aims to address these needs. Stochasticism establishes a scalable framework of governance
based upon the nominations of the community, but with selection determined by a random
lottery. A recursive hierarchy of authority is formed, and filled with community members
for fixed time periods. Higher levels of authority are drawn from lower levels, again by
nomination and lottery. Removing undesirable individuals is accomplished by a vote among
peers or a popular vote of no confidence. A mathematical model of a stochastic society is
developed which has been parameterized to allow optimization of the system operation for
the particular demands of a given community, their habitat, their environment, and their
purpose or purposes. This built-in flexibility allows communities to adapt stochasticism to
more closely reflect their collective values and to meet their particular needs. Figurehead
positions, determined by popular vote, provide communities with vision, ceremony and a
single point of contact for outside visitors. Past electees of the figurehead position serve on
an oversight board to the stochastically-selected members of the governing body, whose size
is fixed at 12 for small populations, and scales asymptotically to 122 with increasing
populations, regardless of the level in the hierarchy. Majority-rule votes which are tied will
be settled by the oversight board. With this novel system of governance, all citizens have an
equal opportunity for representation, all communities are included, all groups of subcommunities have a chance to be represented at higher levels of authority, and the entire
system can scale up or down as needs require. It is hoped this new proposed system will lead
to a system of community governance which will serve equitably and well for space
settlements.
H
I. Introduction
umans are greedy and inconsiderate. Not everyone is this way, but enough of us are that this is a reasonable
assumption on the average. Greed implies desire for wealth, but also for power, prestige, influence, or control.
Everybody has some level of greed, even if only simple self-interest, and even the nicest people will occasionally act
in an offensive way to exercise their self-interest. This is natural, otherwise we would not have survived as
individuals or as a species until 2010. Therefore, any government system which can be corrupted will be, at least to
some extent. One path to reduce corruption in government is to use a stochastically-selected hierarchy. A lottery
determines who serves. A government where the (prescreened) members are selected at random greatly reduces the
motivation for greedy people in control to accumulate power (Lord Acton: “Power corrupts, and absolute power
corrupts absolutely”) through manipulating the political system and mass perception.
The government begins with a “by-twelve” representation, selected at random from normal community dwellers
who pass basic pre-screening tests like: no felony convictions; no personal bankruptcy; and a college degree or
equivalent. Some people (lots of them) would not wish to participate. But others would, and some of those are the
type of people we would all want to run our government. In this paper, a computer simulation of people and of
governments is created and applied to a community completely isolated for 10 years. Some people die. Some
prosper. Four different governments are studied and compared, assessing the welfare of the community as time
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Copyright © 2010 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.
progresses. The government types studied are: pure communism, pure capitalism, elitism (a model of corruption),
and stochasticism – the novel government introduced here for the first time.
II. Methods
X-by Representation
A. Representation
Stochasticism is a representative government. The ratio of government servants to their immediate local
representation is an by-X schedule based on population size. One method of determining the by-X is an asymptotic
increase from populations of 1000 with by-12 representation up to a by-144 ratio for populations of 1 trillion and
above.
At the local levels, public servants are town elders to run and administer a small community or subsection of the
community. Physical demarcations for geographically-distributed communities should be based around groupings
of populations using the method of k-nearest neighbor (KNN) least-squares minimum population deviation with a
small value of k. This objective method will find natural breaks by using support vector machines (SVM) immune
to gerrymandering. Further study of the mathematics to accomplish this will be the topic of a future study applied to
land-based populations.
Terms of office at each level of a stochastic government
140
are determined by the average human lifespan (which may
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increase significantly in the future), balanced with the need to
limit the time during which corrupting influence can be
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established and become more powerful. One such method is to
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set the term of office to be 5% of the average lifespan if the
number of levels of government is less than or equal to 10. For
60
larger systems of government, the term length would be
40
1/(2*L) where L is the number of levels of hierarchy. Each
20
person already at a given level is automatically eligible for
selection at the next level after 2 years of service. Thus for a
0
3
6
9
12
very large government of 10 levels, one could conceivably rise
Log-10 of Population
to the top level after a minimum of 20 years, but more typically
Figure 1. “by-X” representation.
40 years.
Representative government, based upon random selection of pre-screened candidates continues to scale up
through village, city, region, state, nation, continent, hemisphere, planet, planetary system, solar system, or beyond.
For the purposes of this simulation, it tacitly assumed that corruption can be virtually eliminated by a stochastic
selection process of successively-higher orders of representation mediated by years to ensure smooth transitions
(e.g. to recover from decimation, the government simply scales back down). There will always be greedy
individuals, and some will get into government; but the less-greedy individuals will also have an equal opportunity
to serve the government. No great assumptions are made as to efficiency of a stochastic government, yet the
hypothesis is that there will be less loss or imbalance compared to other forms of government. Long-term runs of
the simulation show general trends and the quasi steady-state condition of growth, parity, or decline. In these
simulations, during a ten year stay or voyage, some people prosper, some people die. Different government types
prosper more than others, and have different number of deaths from either too-low productivity (sickness,
misfortune, low community assets) or too-low happiness (low personal wealth, lower community wealth). In these
simulations three other types of governments are compared to stochasticism, and their impact on the community and
the individuals is evaluated.
B. Simulation
The simulation described below was run from day 1 to the end of 10 years for a population of 151 with no
reproduction. No new immigrants are included, implying an assumption that the community is completely isolated,
such as a long-duration space voyage, or a remote outpost for which resupply launch windows are few and far
between. Upon day 1 the population initializes. From day 2 to the end of the simulation people and governments
interact through a daily sequence of the following steps: (1) people produce; (2) the government collects and then
disburses; (3) the people consume, age and update their happiness metric; and (4) the people are screened to see who
leaves (probably not to their benefit) or dies.
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C. People
People are modeled as a six dimensional vector. Individuals are evaluated on the basis of the following
characteristics: productivity; greed; age; happiness (to be defined later); consumption; and, wealth. Each have a
starting point for all six, affecting them throughout their “life” in the remote community. As time progresses one’s
productivity, happiness and wealth develop depending on each other; and also upon the community wealth, which is
in turn affected by the government types (discussed below). This section shows the mathematics of the person
model, illustrating the simplifying assumptions that must be made. This crude model does not encompass all of
human nature. Yet the interactions with the government do make for an interesting, non-linear study, and allows
comparisons between them. At the end of each simulation, any given individual can be examined, or composite
statistics gathered, to gain insight into their behavior.
1. Productivity
An individual’s productivity is measured in sustain units, and is evaluated in step (1) above. The fruit of one’s
labors equivalent to support one averagized person in a holistic, sustainable way, is defined as 1.0 sustain units.
Most motivated adults produce more than is sufficient to survive, or, in a harsh environment, they would not.
Therefore, the initial productivity of each person is selected at random from a range of 1.0 to 1.5, using a uniform
random distribution. This structured application of a random process is termed stochastic. The new style of
government presented here derives from this same sense of structured randomness. Use of stochastic variables in
the simulation in no way favors stochasticism as a government.
Productivity over time is computed as a function of these six variables: inherent productivity (the day 1 value as
described above); inherent greed (immediately below); age; happiness (explained below), personal wealth
(accumulation of sustain units), and the overall wealth of the government. Each variable has a piecewise linear
schedule relating the variable to productivity, each factor is capped at 2.0, and the average of all six determines
one’s daily productivity. Values fall linearly to 1.0, but below that, when one can’t produce enough to survive,
productivity goes down quickly. Once productivity drops below 0.25 that individual is declared dead, and step (4)
of the daily simulation removes them from the population.
2. Greed
Individuals must want enough to survive, or they will waste away and die (no family support or 1-on-1 altruism
is included in this simple model). The lower limit of selfGreed Distribution in the Population
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interest is defined as greed of 1.0. Greed is modeled as the
sum of two probability distribution functions. The first
40
component of greed is a uniform distribution over [1.0 1.2],
and represents a “normal” range. However, there is a
smaller fraction of very greedy people, who may be as
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much as 2 or 3 times greedier than the normal range, though
increasingly rarely at higher multiples. Therefore a high
20
order power of a random number over [0 1] is added to
normal greed, producing a smattering of variously highly10
greedy people with which to populate this isolated
community.
0
3. Age
1
1.5
2
2 .5
Age is measured in days, and incremented by 1 in step
(3) of the daily simulation. Initial age is a uniform random Figure 2. Greed distribution.
selection across [25 55]. When one reaches 75, death
Productivity as a function of Age
ensues immediately, and productivity goes immediately to
2
zero. Below 25 productivity is assumed to be zero. No
reproduction was included in the simulations (assume
1.5
babies are deferred to achieving a destination, to avoid a
drain on the fragile community). Productivity is presumed
1
to peak at age 50 (at a value of 2.0) where experience and
personal energy are optimally balanced. With physical
decline productivity drops, until at age 75 productivity is
0.5
equivalent to a 25 year old. The value is 1.0 at these
endpoints [25 75], and the schedule scales linearly
0
20
30
40
50
60
70
80
between, as shown in Fig. 3. This value changes by a small
amount each day, and is used to update individual Figure 3. Initial age distribution.
productivity.
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4. Happiness
Everyone has an intrinsic happiness. But happiness also depends on the circumstances of one’s life. Neutral is
defined as 1.0, rather arbitrarily. A happiness of 2.0 is considered to be the upper limit, and all happiness values are
capped at this value. Intrinsic happiness, determined at day 1, is a uniform selection across [0.75 1.25], and remains
fixed for each person.
An individual’s happiness changes over time in step (3) of the daily simulation is based on these three factors:
intrinsic happiness, personal wealth, and community wealth. Each is given a schedule shown graphically below.
In general, the happiness one feels towards personal wealth is 1.0 at a 90 day supply of sustain units. At or
above 365 days supply, this portion of one’s happiness is maximized. Below 90 days supply, one’s happiness due to
personal wealth drops from unity towards zero with a slope of -1/90.
The happiness felt towards the community is a function of community wealth, as gathered from taxes (described
in the next subsection). The government is assumed to spend its tax money on upgrades to the general well being or
necessary infrastructure and general maintenance on common property. If the government has a 90 day supply for
each person in the community, happiness is 1.0 for this component. It climbs to 2.0 when the government has a 365
day supply for all. For governments larger than this, there is a gradually decreasing, but still positive, schedule of
happiness, until at a 5 year surplus the benefits of further increases in government size exactly balance the negative
consequences (services and infrastructure are offset by loss of personal freedom, aggression towards other
communities, stifling bureaucracy, etc.) and this component of personal happiness is fixed thereafter at 1.0.
Personal happiness is calculated as an average of these three components. At individual values of 0.25 or below,
one is assumed to have died or left somehow. This composite personal happiness is used as a component of
productivity under the assumption that happier people produce more.
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INTRINSIC
20
10
0
0.8
1
1.2
PERSONAL
COMMUNITY
2
2
1.5
1.5
1
1
0.5
0.5
0
0
200
400
0
0
1
2
3
5
Figure 4. Components of personal happiness.
x 10
5. Consumption
Consumption is that portion of personal wealth which one turns into loss or waste in the course of sustaining
one’s self during a given day. Intrinsically, people are all different sizes, so a consumption variation of +/- 25% is
assumed, centered on a value of 1.0 sustain units. Therefore the largest individual in the isolated community
(assuming a selection criteria prohibiting excessive-consumption individuals) will generally eat/use/discard about
two-thirds more than the smallest individual. This value is fixed over time, but is used every time step to subtract
from the individual’s inventory.
6. Wealth
Personal wealth is the number of sustain units possessed. Everyone starts on day 1 with a 90 day supply. As
time progresses, wealth is affected daily by three factors: personal productivity, government tax on productivity
(this should also depend on consumption, but such was not included in this version for simplicity); and government
disbursements. A running tally is kept, and it changes every day of the simulation from the first day to the 3650th.
Therefore, each day’s wealth is a sum of: yesterday’s wealth, the fraction of individual productivity that is not taxed
(to be determined by government type), and the amount disbursed to individuals from the government (by type).
Wealth greater than a 365 day supply fails to provide any further gains in happiness or productivity, but an
individual’s natural productivity may still increase their wealth. Especially if one is very greedy, and even more
particularly if one is a member of the corrupt elite sharing a portion of the government’s tax receipts, one may end
up accumulating a small fortune in this simulation.
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D. Governments
The government is a 6-vector, similar to an individual. First is the community productivity – the sum of living
individuals’ productivity. The second element is a composite of community wealth plus individual wealth, and is an
overall measure of the affluence of the community. Third is age of the habitat, starting at 1. Fourth is the sum total
happiness of the group (dead people have zero happiness) and can be seen as a general measure of the quality of life
for those living there. Next is the amount the government consumes, which is the gross loss to the entire community
in the form of waste, lost resources and inefficiency. Productivity gains are needed to offset this continual drain,
considered as the cost of keeping a community alive. Sixth is the total government wealth, the Treasury, which is
the sum of taxes collected from individuals on the basis of their daily productivity (only income tax is simulated, no
tax is placed on consumption or value-added).
Treasury holdings are updated daily as a sum of yesterday’s holdings plus the sum of all tax receipts, minus the
disbursements to individuals and the disbursement to privileged individuals in the elitism government. Community
wealth is good for the individuals, being a component of their individual happiness and thereby the individual’s
productivity, thus providing a feedback path in the model. Now each type of government will be described.
1. Communism
Pure communism taxes 100% of each person’s daily productivity. They pay back 70 percent, evenly distributed
across each living individual, and the remainder goes to the Treasury. Note that the simulation results shown below
are little changed by increasing the disbursements from 70 to 75 percent, indicating that government efficiency is
not a predominant factor in the operation of pure communism.
2. Capitalism
Pure capitalism takes a tithe, just 10% of each person’s daily productivity. They return nothing to individuals
directly.
3. Elitism
One out of every 15 people is selected (at random) to represent the “elite”. How they got that way, or what they
call themselves is irrelevant. Elite is the generic term given to whatever cabal gathers power and serves selfish aims.
In the government simulation, the elite take a disproportionate share of the take, but not so much as to be completely
onerous. Six percent of the population is now entitled to a share of half of government tax receipts. This makes
their own personal happiness increase greatly, and they become more productive (perhaps they invest their earnings,
or spend it lavishly), contributing to the community total, and thereby to everyone else’s happiness indirectly.
History is rife with examples of small cabals gathering power to create an elite, and by some measures, these
societies survive for a time.
In the Elitism run of 10 years, that government taxes the people at a 25% rate. Half of their take was returned to
the people (including the elite). But the elite also received equal shares of the other half of the government’s net
take. For a habitat of 151, the elite cabal numbers 10.
4. Stochasticism
A stochastic government does what the Elitist government tries to do, but without the corruption or unbalanced
influence implied there. They take a fifth part of each individual’s daily productivity (twice that of capitalism).
From their receipts, they return to everyone a four-fifths part. All the rest goes into the government Treasury. One
might interpret this form of government as altruistic socialism. Designing a system that cannot be gamed is
probably impossible. Therefore, one should despair of ever designing a fair and sustainable method of government.
Yet, if the goal is to design a government in which it is difficult for any one person or party to influence statistically
separations and allocations to their benefit (using only very basic, objective, linear relations) then maybe fewer
people will try, fewer will be successful, so on the whole, society will still be better off. That is the hope, and the
one fundamental assumption, of this present body of work.
III. Results
The initial population is shown in Figure 5. It starts the same for each government type simulated. For each
form of government, a composite plot is shown, giving the daily progression of habitat age, plus the final
distribution of individual metrics at the end of the simulation. The final number of people still living after 10 years
is shown in the table in Figure 6.
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AGE
HAPPINESS
20
20
15
15
10
10
5
5
0
20
30
40
50
60
0
PRODUCTIVITY
200
15
150
10
100
5
50
1
1.2
1.4
1
1.2
1.4
INVENTORY
20
0
0.8
1.6
1.8
0
87 88 89 90 91 92
Figure 5. Initial distributions for each government type.
Government Type
Pure Communism
Pure Capitalism
Elitism (model of corruption)
Stochasticism (new)
Population still alive after 10 years
48
120
118
139
Fig 6. Population remaining of the original 151 inhabitants after 10 years, as a function of government.
The simulation results over the 3650 day run, using the initial values in Fig.5 are shown in Figures 7 and 8 for
communism, in Figures 9 and 10 for capitalism, in Figures 11 and 12 for elitism, and in Figures 13 and 14 for
stochasticism. Captions below each figure illustrate key findings. Simulations were run using MATLAB™, by The
MathWorks, Inc. (Natick, MA).
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AGE
HAPPY
4000
200
3000
150
2000
100
1000
0
0
1000
2000
3000
50
4000
15
150
10
100
5
50
0
1000
2000
3000
1000
4
PRODUCTIVITY
200
0
0
4000
x 10
0
2000
3000
4000
INVENTORY Gov=b Tot =r
1000
2000
3000
4000
Figure 7. Simulation values for pure communism showing community age, sum totals for the happiness and
productivity metrics, and inventory overplots for the government alone and the total community wealth.
AGE
HAPPINESS
150
150
100
100
50
50
0
0
20
40
60
80
0
0
PRODUCTIVITY
150
100
100
50
50
0
0.5
1
1
1.5
INVENTORY
150
0
0.5
1.5
0
0
200
400
600
Figure 8. Final values for pure communism at day 3650. Zero values are those people who have died
during the simulation, 103 in this run.
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AGE
HAPPY
4000
200
3000
180
2000
160
1000
0
0
1000
2000
3000
4000
0
1000
5
PRODUCTIVITY
190
140
2
x 10
2000
3000
4000
INVENTORY Gov=b Tot =r
180
1
170
160
0
1000
2000
3000
4000
0
0
1000
2000
3000
4000
Figure 9. Simulation values for pure capitalism showing age, total happiness and productivity, and
inventory overplots. Note the peak value of happiness about 6 years into the simulation run, and the
gradual decrease thereafter.
AGE
HAPPINESS
40
150
100
20
50
0
0
20
40
60
80
0
0
PRODUCTIVITY
40
50
20
0
0.5
1
1
1.5
2
1500
2000
INVENTORY
100
0
0.5
1.5
0
0
500
1000
Figure 10. Final values for pure capitalism at day 3650. Zero values are those people who have died
during the simulation, 31 in this run. Note that most of those left alive are pretty happy.
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AGE
4000
HAPPY
200
3000
180
2000
160
1000
0
0
1000
2000
3000
4000
0
1000
5
PRODUCTIVITY
200
140
2
x 10
2000
3000
4000
INVENTORY Gov=b Tot =r
180
1
160
140
0
1000
2000
3000
4000
0
0
1000
2000
3000
4000
Figure11. Simulation values for elitism showing community age, sum happiness and productivity, and
inventory. Note the large number of deaths in years 2 and 3 as indicated by the drop in productivity.
AGE
HAPPINESS
40
150
100
20
50
0
0
20
40
60
80
PRODUCTIVITY
100
0
0
0.5
1
1.5
2
INVENTORY
60
40
50
20
0
0
0.5
1
1.5
0
0
1000
2000
3000
4000
Figure 12. Final values for elitism at day 3650. Zero values are those people who have died during the
simulation, 33 in this run. Note that the number of people with zero (or very low) inventory exceeds those
dead, indicating abject poverty in some of the individuals. Also, note there are several individuals with
disproportionately high personal wealth, well above 2000.
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AGE
HAPPY
4000
220
3000
200
2000
180
1000
160
0
0
1000
2000
3000
4000
2
185
180
0
1000
5
PRODUCTIVITY
190
140
x 10
2000
3000
4000
INVENTORY Gov=b Tot =r
1
0
1000
2000
3000
4000
0
0
1000
2000
3000
4000
Figure13. Simulation values for stochasticism showing community age, sum happiness and productivity,
and inventory overplots. Note the upward trend in total community happiness, and an approximate steady
state in productivity despite loss of 11 individuals over 10 years.
AGE
HAPPINESS
40
150
30
100
20
50
10
0
0
20
40
60
80
0
0
0.5
PRODUCTIVITY
1
1.5
2
INVENTORY
80
30
60
20
40
10
20
0
0
0.5
1
1.5
0
0
500
1000 1500 2000 2500
Figure 14. Final values for stochasticism at day 3650. Zero values are those people who have died during
the simulation, just 11 in this run. People are generally happy, productive and still alive.
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IV. Discussion
All forms of government survived the 10 year experiment. If there were four such habitats launched with
independent governing systems as a parallel test, there are a number of ways to measure success. Certainly from the
sanctity of life, stochasticism excels in the retention of living, productive inhabitants. Pure communism fades away
because of the net drain on the economy due to inefficiency of transferring value back to the community.
Capitalism is good, up to a point. If practiced in its pure form, unfortunate individuals are not supported by the
government and can suffer, die, or leave. Given the assumption of no new additions, capitalism advances
community happiness, wealth and productivity, but this eventually tapers out with diminishing return. Elitism
matches capitalism in survivability, but has a society polarized between haves and have-nots, the latter of which
includes many on the brink of death. Stochasticism performs better, due in part to “unfortunate” individuals being
carried through statistically-harder periods which might otherwise lead to a spiral of low productivity, low happiness
(health) and eventual death. Stochasticism assumes a balance between communism and capitalism, but without the
deleterious effects of an elite. Given these simplistic assumptions about how a government operates, and a crude
model of human expression, the hypothesis was proved true to the extent that the models represent reality.
V. Conclusion
If people tend to be greedy and inconsiderate, governments should be designed which are cognizant of this
tendency, and use statistics to level opportunities for abuse of power.
If this can be accomplished in a secure and universally-acceptable way, then a low- or no-corruption zone would
have been created. In a stochastic government, personal greed may not benefit a given individual as much as in
capitalism, but one still profits by the fruit of one’s labors and the lesser among us can still earn a living. It should
be noted that the operation of this system, including individuals and the community, was not evident from the rules
programmed in. Emergent behavior was exhibited and shown here graphically. The insight gained upon study of
these results suggests a measurable benefit to a society’s well-being and the individuals’ quality of life, using a
stochastically-selected hierarchical government.
This paper has introduced a simple model of a utopian society where dutiful citizens are selected stochastically
in a hierarchy of governmental bureaucracy but without the temptations and distractions of the popular vote. By
avoiding this glaring means of corruption, stochastically, a more just society can be formed; one which increases the
happiness, the personal wealth, and most important, the most people, in the long run, so they survive to their
destination, or until the next resupply – the ultimate goal for any remote community.
Acknowledgement
The author is grateful to Emily A. Schubert, who provided valuable debugging of the simulation model.
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