Birth Spacing, Aggression and Chiefly Cycling: The Evolution

of Social Complexity

Professor Dwight Read

Department of Anthropology

UCLA

Introduction• Three paradigms that have been used by archaeologists to

account for the evolution of complex societies• Model 1: Decision Making Mediated by Culture• Model 2: Competition Between Groups

– Implications of Patch Size and Seasonality for Group Competition• Cyclical pattern of coalescence, replacement of local groups through

aggression, and fission (Yanamamo, Highland New Guinea)

• Stable coalescence/new form of social organization and eventual global replacement through competition between groups (Hunter-gatherer social organization)

• Chiefly Recycling and State systems

Sequence of Societies

(1) Solitary society: I = <{single individual}>

(2) Group consisting of several individuals: G = <{Ii: 1 < i < m}, SG>

(3) Band society/community composed of several groups: B = <{Gi: 1 < i < n}, SB>

(4) Tribal society/simple chiefdoms composed of several B's: T = <{Bi: 1 < i < p}, ST>

and

(5) Complex chieftains composed of several T's: C = <{Ti: 1 < i < q},SC>,

where SG, SB, ST, SC, stand for the internal organization of the units making up a society

at a particular level in the sequence.

Three Paradigms for Modeling Evolution of Complex Societies

(1) Evolution of a Society as a Totality

Band Level Societies Tribal Level Societies

Chieftain Level Societies State Level Societies

White (1949), Steward (1955), Fried (1967), Service (1962)

Three Paradigms for Modeling Evolution of Complex Societies (cont’d)

(2) Evolution of the Internal Structure of a Society

Viewed as a Hierarchical Control/Information

Processing System

"… the most striking differences between states and

simpler societies lie in the realm of decision-making

and its hierarchical organization …" (Flannery 1972, p. 412 )

Three Paradigms for Modeling Evolution of Complex Societies (cont’d)

(3) Agent and Agency in the Evolution of Societies

“… the formal, functional, and dynamic properties of the state are outcomes of the

often conflictive interaction of social actors with separate agendas, both

within and outside the official structure of the decision-making institution”

(Blanton 1998, p. 140, emphasis added)

“The organizational forms of Mesopotamian complex societies emerged through

the dynamic interaction of partly competing, partly cooperating groups or

institutional spheres and different levels of social inclusiveness”

(Stein 1994, p.12 )

Model 1: Decision Making Mediated by Culture

Observation: Among the !Kung san, a hunter-gatherer group in southern Africa, women space their children about every four years.

Analytic Goal: (1) Construct an ethnographically based decision rule for child

spacing decisions by !Kung San women based on individual circumstances.

(2) Implement the decision rule in an agent-based demographic simulation and determine its demographic consequences.

Ethnographic Basis for Constructing a Decision Rule

"to carry a third child and the food she gathers would be practically impossible for those small women" (time/energy conflict between parenting and gathering) (Marshall 1976: 166, 168)

"They want children, all the children they can possibly have" "They want children, all the children they can possibly have" ((decrease decrease spacingspacing))

"they explained that they cannot feed babies that are born too close "they explained that they cannot feed babies that are born too close together. . . . A mother had not enough milk to sustain completely two together. . . . A mother had not enough milk to sustain completely two infants at the same time" infants at the same time" ((increase spacingincrease spacing))

””they believe a child must have strong legs, and it is mother's milk that they believe a child must have strong legs, and it is mother's milk that makes them strong . . . a child needs milk till he is three or four years old at makes them strong . . . a child needs milk till he is three or four years old at least" least" ((duration of nursing = mechanism for spacingduration of nursing = mechanism for spacing))

(1) Concern for spacing of births

(2) Means for birth spacing

(3) Time/energy conflict between parenting and gathering

Characterization of Female Activities

• Set {A1, A2, …, An} of activities– Subset S = {S1, S2 …, Sm} of subsistence activities– Subset P = {P1, P2…, Pk} of parenting activities– Subset O = {O1, O2 …, Oj} of other tasks

• Total (perceived) Cost TC = iAi,

where i is a conversion factor relating time/energy per unit of time (e.g., day, week, year,

etc.) to perceived cost

Criterion for Decisions

• Tmax, maximum acceptable value for TC

• If TC > Tmax then for at least one activity, Aj, the coefficient j will be set to (or close to) 0

Implication: Modify spacing of births since parenting costs are directly related to spacing of births and parenting costs are high and have more elasticity than subsistence costs and other costs.

Decision Rule

• If TC < Tmax at time t then set f(t) = r0 , (Desire for as many children as possible)

• If TC Tmax at time t then set f(t) = 0 (Desire for well-being of a family, Tmax a cultural parameter)

where: r0 is the intrinsic fertility rate (~ 10 births per female per reproductive period)

andf(t) is her fertility rate at time t

Simulation: Implementation of the Decision Rule

TC = (parenting cost) + (foraging cost) =

= nWt + P/K

where:• Wt is the parenting cost/infant

• n = number of infants (age IA)

• K is a weighting factor that converts P into a foraging cost per female

IA = I0 * P/K, I0 maximum age for weaning

Multi-agent Simulation: Simulation events for each simulation year

Female and Male Agents Female Agent only Male Agent only

Age = Age + 1 If Married = True and Age Menopause and Alive = True, use Decision Rule to set Defer Pregnancy to True or False

If Age Puberty and Married = False, search for Spouse agent among Female Agents with Married = False and appropriate age range

Set Alive to True or False based on probability of death computed from age specific mortality rates; if Age = 75 set Alive = False

If Defer Pregnancy = False, set Birth = True or False based on probability of birth computed from a total fertility rate of 15 births over a completed reproductive cycle.

If Age > Infant Age set Infant = False If Birth = True, construct a new agent, set Mother = Female Agent, set Father = Spouse of Female Agent, assign Sex = M or Sex = F randomly, set Age = 0, set Alive = True, set Infant = True, set Married = null, set Defer Pregnancy = null.

If Age = Puberty, set Married = False

If Spouse found, set Married = True, set Spouse agent for both agents

If Alive = False for Spouse, set Married = False

Demographic Event

Cultural Context

Decision Rule

Decision Rule for Birth Spacing

Change in Parameters

(1) Cultural --Wt (Value Placed on Parenting) Effect on:• Stabilized Population Size

• Demographic Trajectory Through Time

(2) Material-- Resource DensityEffect on Relationship of Stabilized Population Size to Carrying Capacity

Stabilized Population Size

DemographicTrajectory: Three Simulations

1) Wt = Tmax = 16 (arbitrary units) -- Women respond only to cost of children

2) Wt = 8, Tmax = 16 -- Women respond to both the cost of children and the cost of foraging

3) Wt = 0, Tmax = 16 -- Women respond only to the cost of foraging

1) through 3) represent decreasing cultural value placed on the well-being of a family

Demographic Trajectory Through Time

Effect of Change in Resource Density

Resource Density

Num

ber

of F

orag

ers

n1

n2

Catchment Area = A

cost/foragerhigh resource density ~ A/n1 < A/n2 ~ cost/foragerlow resource density

Carrying Capacity versus Stabilized Population Size

Australian Data

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16

Net Above Ground Productivity (~K)

1/Ar

ea (~

K*)

Model 2: Competition Between Groups

dP1/dt = P1(a1 – b11 P1– b12P2)

dP2/dt = P2(a2 – b21P1 – b22P2)

Equation 1 states: “Growth of population 1 increases according to its intrinsic growth rate (a1), less the extent to which the size of population 1 inhibits its own further growth (b11), less the extent to which the size of population two inhibits the further growth of population 1 (b12).”

Competition Between Two Groups

Phase State, Equilibrium Between Two Populations

Three Groups, Small Resource Patches

Change in Competition, Coalescence of Groups 1 and 2

Change in population size of group 1

Fission (No Change in Population Density)

• Fission of Groups 1 and 2 is likely due to cost of maintaining larger group and ability to revert back to smaller groups without major demographic consequences.

• Expect cycling pattern between coalescence/growth and fissioning when growth in size occurs without change in population density.

Yanomamo Cycling• A group (teri) of around 30-40 close kin-related persons is a

stable social and subsistence unit (Chagnon 1983)

• However, resource scarcity leads to warfare (Johnson and Earle 2000)

• Warfare often leads to displacement of one teri by another (Bioca 1971, Smole 1976)

• Coalescence: A teri needs to have around 80 - 100 persons to defend itself against raids; a large teri is more likely to be able to mount successful raids (Chagnon 1983)

• Coalescence does not appear to increase population density--territory, rather than density, increases

• Fission: A teri is increasingly likely to break up when the teri exceeds 100 persons (Chagnon 1983)

Highland New Guinea Cycling

• Local groups around Mount Hagen may expand their territorial base through warfare but in time fission takes place and new local groups are formed (Strathern 1971)

• Similar pattern occurs among the Kuma (Reay 1959)

• “a single regional Big Man has not emerged… and transformed [Central Enga] into a chiefdom….the conditions for economic control are absent in the Highlands …” (Johnson and Earle 2000, p. 232-33)

Seasonal Variation in Resources, Large Patch Size

Seasonal Resource Abundance, Implications for Coalescence

Coalescence Leads to Increase in Population Density: Combined Group 1

+ Group 2 Wins Out

Change in population size/density of group 1

Transition from Troop to Hunter-Gatherer Form of Social

Organization

Groups of Individuals

Band society

Implications for Chiefly Cycling

Chiefdom (Simple)

Chiefdom (Complex)

Implications for State Society

State Structure(top down structure)

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